struct folio *folio = page_folio(page); if (WARN_ON_ONCE(folio_ref_count(folio) <= 0)) return -ENOMEM; if (unlikely(!(flags & FOLL_PCI_P2PDMA) && is_pci_p2pdma_page(page))) return -EREMOTEIO; if (flags & FOLL_GET) folio_ref_inc(folio);
checks for code that is involved in policy but is not the actual logic
else if (flags & FOLL_PIN) { /* * Don't take a pin on the zero page - it's not going anywhere * and it is used in a *lot* of places. */ if (is_zero_page(page)) return 0; /* * Similar to try_grab_folio(): be sure to *also* * increment the normal page refcount field at least once, * so that the page really is pinned. */ if (folio_test_large(folio)) { folio_ref_add(folio, 1); atomic_add(1, &folio->_pincount); } else { folio_ref_add(folio, GUP_PIN_COUNTING_BIAS); } node_stat_mod_folio(folio, NR_FOLL_PIN_ACQUIRED, 1); }
Logic that actually tries to grab the folio. Also policy use code and not actual policy
if (unlikely((flags & FOLL_LONGTERM) && !folio_is_longterm_pinnable(folio))) { if (!put_devmap_managed_page_refs(&folio->page, refs)) folio_put_refs(folio, refs); return NULL;
checks for longterm folio pins.
if (WARN_ON_ONCE((flags & (FOLL_GET | FOLL_PIN)) == 0)) return NULL; if (unlikely(!(flags & FOLL_PCI_P2PDMA) && is_pci_p2pdma_page(page))) return NULL;
Time saving predictions(unlikely) and single time warning func(WARN_ON_ONCE) for flags. Not actual policy logic so low confidence.
if (unlikely(page_folio(page) != folio)) { if (!put_devmap_managed_page_refs(&folio->page, refs)) folio_put_refs(folio, refs); goto retry;
Uses prediction to check if a folio still points to the page. This is part of the function that tries to retrieve the folio to confirm that it is associated with a page.
folio = page_folio(page); if (WARN_ON_ONCE(folio_ref_count(folio) < 0)) return NULL; if (unlikely(!folio_ref_try_add(folio, refs))) return NULL;
These increment the reference count for the folio since you're returning a reference of the folio. Important function so important internal logic subsequently
if (is_zero_page(page) || !folio_test_anon(folio)) continue; if (!folio_test_large(folio) || folio_test_hugetlb(folio))
Sanity checks for pinned pages wouldn't classify as policy logic but common sense pre-checks for the actual policy. But I think it's worth tagging this to gain a sense of what is not policy code
if (flags & FOLL_PIN) { ret = arch_make_page_accessible(page); if (ret) { gup_put_folio(folio, 1, flags); goto pte_unmap; } }
part of policy code
Reviewer #1 (Public Review):
The authors investigate whether during free exploration of an environment with an internal structure of corridors and occasionally fluid-rewarded alleys, rat CA1 place cells generate multiple firing fields in repeating patterns, allowing the investigators to analyze whether firing field positional properties like alley orientation, and non-positional properties like heading, field-rate modulation and other properties are similar or different within and across single place cell place fields. They adopt a standard cognitive map analysis framework, conceiving each cell as an individual map element and characterizing each cell's individual activity independently of the activity of other cells, such that the main unit of analysis is a place field averaged across recording times of many minutes. Despite framing the work as an investigation of a fundamentally-subjective episodic memory system sensitive to hidden cognitive and attentional variables, the experiment and analyses are conceived as if the cells respond to positional and non-positional features of experience as static "inputs" that the investigators infer. These "inputs" are conceptualized as effectively stationary and steady, and they are not manipulated. The authors find that there are many "repeated" firing fields, that they tend to have similar orientation more than expected by chance, and that each field's rate is modulated distinctly by heading direction and other factors, leading them to conclude that each field's nonpositional inputs are "individually addressable." The authors do not consider alternative possibilities for which there are strong indications in the contemporary literature like 1) CA1 activity could be internally generated; 2) that there could be hidden cognitive variables that influence CA1 activity episodically and in non-stationary ways rather than consistently; 3) that CA1 cells exhibit mixed tuning to a variety of environmental and navigational variables; 4) that CA1 activity is better interpreted from the point-of-view of a neural ensemble or a neural manifold of conjoint neural activity that represents multiple information variables, or 5) that stable neural representations of information need not depend on stable stimulus-response properties of individual cells. In fact, the analyses provide evidence consistent with each of these alternatives, but they are not considered. There is a case to be made that the authors are allowed to ignore these alternatives because they properly engage the dogmatic point of view, in which case there is little to adjust in the manuscript, which is both well-conceived and well-executed in the classic (but not contemporary) norms of place cell investigations.
My comments are focused on improving the manuscript without insisting that the authors adopt alternative (contemporary) points of view, but requiring them to clarify their point of view and explain that there are alternatives.
(1) The authors define what they mean by "positional" and "non-positional" "inputs" later in the manuscript. Since the experimental apparatus and task have been designed to isolate these "inputs" the authors should in the initial description of the environment and task explain what the task does and does not allow them to analyze. Instead, they have repeatedly asserted that the environment is a hybrid of an open-field and a linear track environment. This may be the case, but so what? The authors need to better explain, up front, why that matters and what they will be able to investigate as a result. As written, this all seems to me rather vague and post hoc.
(2) The abstract states "Previous work implies a distinction between positional inputs to the hippocampus that provide information about an animal's location and non-positional inputs which provide information about the content of experience." While I understand what the authors mean, I want to point out that it is not straightforward to identify the "positional inputs" and the "non-positional inputs." What are they, how can they be measured? Is it not also possible that hippocampus generates "positional" information rather than receiving it, that is in fact the longstanding view of the cognitive map framework that the authors have adopted, and yet they frame the essential issue as one of differential receipt of positional and non-positional inputs. This seems to me imprecise and hard to defend but demonstrates the authors' opinion in framing this work. In my view a more objective and accurate statement might be "Previous work implies a distinction between hippocampal (positional) activity representing information about an animal's location and (non-positional) activity which represents information about the content of experience." This opinion about "inputs" is found throughout the manuscript over 50 times, starting with the title. While in my view this is not an objective treatment of the experimental design or data (positional and non-positional inputs are never identified or manipulated, they are merely inferred), I accept that the authors can say whatever they want so long as they make it clear to the reader that theirs is an opinion or assumption rather than a measurement. The manuscript is written as if the different inputs are identified and valid, rather than inferred.
(3) The abstract states "even though the animal's behavior was not constrained to 1-D trajectories" whereas page 13 states "but their trajectories were constrained to orthogonal directions by the city-maze architecture" and page 23 states "but their trajectories were constrained to a rectilinear grid." While I understand what the authors mean, the first statement appears to contradict the others. There are additional examples that I do not identify here. In any case, I would like to have seen examples of the animals' trajectories through the maze. A figure showing the raw trajectories and another after the unwanted behaviors have been filtered out should be given, allowing the reader to understand how much the animals tended to travel through the alleys, how much they turned and lingered within them, etc.
(4) The abstract ends with "These results demonstrate that the positional inputs that drive a cell to fire in similar locations across the maze can be behaviorally and temporally dissociated from the nonpositional inputs that alter the firing rates of the cell within its place fields, thereby increasing the flexibility of the system to encode episodic variables within a spatiotemporal framework provided by place cells." I don't see the evidence for the "thereby ..." claim. The authors are free to speculate and discuss but they should say they are speculating and/or discussing a possibility, rather than assert as if they have demonstrated a fact.
(5) The Introduction begins with "All behavior is embedded within a spatial and temporal framework." By this statement, I believe the authors mean to assert, or at least they cause a reader to understand that there is a spatial and temporal framework that is separate from the behaving subject. They will use this point of view to design their experiment around the utility of a city- maze. Since the authors appeal to cognitive map theory so much, I point out that O'Keefe and Nadel write in The Hippocampus as a Cognitive Map that "Space was a way of perceiving, not a thing to be perceived." Sentence number 2 of the book states "We shall argue that the hippocampus is the core of a neural memory system providing an objective spatial framework within which the items and events of an organism's experience are located and interrelated." Consistent with Kant and O'Keefe and Nadel, the present authors might more accurately state "All behavior is embedded within a subjective spatial and temporal framework." but then they will have to explain why they conceive of there being "positional inputs" to which they are measuring CA1 responses. This framing seems to me problematic and not logically self-consistent.
(6) On page 2 the authors assert "Neurons within the hippocampus respond to a wide array of sensory and otherwise nonspatial cues..." then they go on to list sensory features and "non-positional" features of experience to which CA1 cells respond. It seems to me they leave out a class of features of experience that might be considered "subjective spatial frames" that have been investigated by Gothard and Redish when they were in the McNaughton and Barnes lab, as well the Fenton and Muller labs, amongst others. All of these papers describe non-stationary, multi-stable place cell phenomena that are tied to subjective variables, which have the potential to undermine the premise of the present work's analyses and so they should be considered. I list a sample but certainly not all the work that might be considered.
Gothard KM, Skaggs WE, Moore KM, McNaughton BL (1996) Binding of hippocampal CA1 neural activity to multiple reference frames in a landmark-based navigation task. J Neurosci 16:823-835.
Gothard KM, Skaggs WE, McNaughton BL (1996) Dynamics of mismatch correction in the hippocampal ensemble code for space: interaction between path integration and environmental cues. J Neurosci 16:8027-8040.
Gothard KM, Hoffman KL, Battaglia FP, McNaughton BL (2001) Dentate gyrus and ca1 ensemble activity during spatial reference frame shifts in the presence and absence of visual input. J Neurosci 21:7284-7292.
Redish AD, Rosenzweig ES, Bohanick JD, McNaughton BL, Barnes CA (2000) Dynamics of hippocampal ensemble activity realignment: time versus space. J Neurosci 20:9298-9309.
Rosenzweig ES, Redish AD, McNaughton BL, Barnes CA (2003) Hippocampal map realignment and spatial learning. Nat Neurosci 6:609-615.
Jackson J, Redish AD (2007) Network dynamics of hippocampal cell-assemblies resemble multiple spatial maps within single tasks. Hippocampus 17:1209-1229
Lenck-Santini PP, Fenton AA, Muller RU (2008) Discharge properties of hippocampal neurons during performance of a jump avoidance task. J Neurosci 28:6773-6786.
Fenton AA, Lytton WW, Barry JM, Lenck-Santini PP, Zinyuk LE, Kubik S, Bures J, Poucet B, Muller RU, Olypher AV (2010) Attention-like modulation of hippocampus place cell discharge. J Neurosci 30:4613-4625.
Kelemen E, Fenton AA (2013) Key features of human episodic recollection in the cross-episode retrieval of rat hippocampus representations of space. PLoS Biol 11:e1001607.
(7) The Introduction asserts that "rate remapping" is a hypothesis. Rate remapping is a phenomenon, something that is observed. The interpretation of the observation as being the substrate of episodic memory is certainly a hypothesis that in my opinion has not been tested and is not being tested in the present work. After making the above statement, the authors go on to describe that firing rates differ across "repeated" firing fields, which seems to be a form of rate remapping, and predicted by the relevant hypothesis that different episodes of experience at the same locations are represented by different firing rates. This is very speculative and there are many other explanations.
(8) The Introduction ends with the statement "Here, we show that repeating fields of the same neuron do not always display the same nonpositional rate modulation, demonstrating that nonpositional cues are dissociable from, and more flexible than, the positional inputs onto place cells in a given environment." Apart from my concern about using the "input" terminology I which to point out that there is very little novel in this statement. It has been described many times before that on linear tracks CA1 firing fields are directionally modulated such that the field rates for traversals in one direction are different compared to field traversals in the opposite direction. Jackson and Redish (2007) cited above show this to be due to reference frame or map switching. That and other work allow one to state that "Others show that repeating fields of the same neuron do not always display the same nonpositional rate modulation, demonstrating that nonpositional cues are dissociable from, and more flexible than, the positional inputs onto place cells in a given environment." Either the present authors should acknowledge that they are demonstrating what others have already demonstrated, or they should more precisely describe what about their contribution is unique.
(9) Page 6 Methods - Data Filtering and Pre-processing. How did the authors handle theta cells and others that fired more or less everywhere but with spatial modulation?
(10) Page 9 Methods - Why was the session-wide activity used to normalize the firing rates for the activity vector input to the random forest classifier? The authors state "The normalized firing rate was computed as discussed above with the change that the session-wide activity in the alley was used." It seems to me better to have used the session-averaged firing rate map because the activity would be normalized by the expected positional firing. I imagine "The classifier used the population vector of firing rates as the input." is incorrect and the authors mean to state "The classifier used the population vector of normalized firing rates as the input."
(11) What does "spatially-gated" mean? The use of such jargon should be explained, or better avoided.
(12) Page 12: Since fields tend to have similar orientations, but not repeat at all geometrically similar locations, did they tend to be clustered? Was there a proximity feature to their distribution?
(13) Page 18 states "Thus, although there was a slight trend for repeating field ..." The authors are reporting a significant effect not a "slight trend." They do something similar in reporting Figure 5's result. Despite significant effects, they seem to think the findings are not large enough so state that repeating-field directionality is not conserved. It is fine to explain that a significant effect was small (for example give the effect size, which would have been welcome throughout) but as in these cases and others, the authors should be more objective in their reporting of the outcomes. Either a statistical test was or was not significant. It is not "a little" or "a lot" significant.
(14) Page 18: What do the authors mean by "topology?" Might they mean "topography?"
(15) Figure 6 shows field instability and multi-stability (termed temporal dynamics) as described on page 22. The recording sessions were 60 min. Is this impression simply due to long recording sessions? If 10 or 15 minutes of data were analyzed (which is more the norm), would similar instability be observed/detectable?
(16) I found the Discussion very confusing. On the one hand, there is an assertion that because the location of firing fields is stable there is a "positional code." How would that actually work? Any neural system has to signal by firing rates or firing coincidences across groups of cells (that are affected by changes in rate) so if there is firing field firing rate instability the authors should explain how position can be accurately decoded on a behaviorally-meaningful time scale. In fact, they should demonstrate such decoding explicitly. Just because there is modulation and instability, it is a rather long leap to assert that this is how episodic experience/memory is encoded (as stated at the end of the abstract and elsewhere for example on page 24: "The present data utilize repeating fields to suggest that, within an environment, the positional inputs are relatively rigid, whereas the nonpositional inputs are more flexible, allowing different repeating fields to show different directional preferences. In other words, fields are individually addressable with respect to the nonpositional inputs they receive; they do not inherit their nonpositional tuning as a global property of the cell." What does it mean that a field is "individually addressable?" How is that achieved by neurons? If the authors want to make such assertions they should explain and demonstrate how their assertions can be valid, given the data and findings. At least they should explain what they are assuming.<br /> The main findings seem related to the published finding that in large environments place cells have multiple firing fields, with distinct rates in each field, quite similar to what is here described in the city maze. In my opinion, positional representations can only plausibly work in such cases by using the conjoint population activity moment to moment, which necessarily marginalizes the value of individual firing fields, yet the present work focuses the discussion (and analyses) on interpretations of single firing fields (which they assert are individually addressable multiple times). I don't know what that means exactly and the authors should explain why maintaining the standard single-field perspective is appropriate and how position can be represented in such a system, given the data. In fact, I would have thought that the present findings would cause the authors to reject as invalid the framework they have adopted.
(17) This is a further example, on page 25 which asserts that "Directionality is affected by an animal's experience through the field (Navratilova et al., 2012), so it is possible the difference in experience between sampling fields on the same versus different corridors affects the directional tuning properties between them." I do not understand how "the difference in experience between sampling fields on the same versus different corridors affects the directional tuning properties between them." If I follow the logic then the so-called directionality would depend on experience and so only emerge after a certain time for experience, or else the firing during one traversal would need to be modulated by information about future traversals, which I suppose the authors would agree does not make sense.
(18) I found it at times confusing to follow the arguments because the terms "route" and "trajectory" and also "direction" and "heading" were used sometimes interchangeably and sometimes in ways that appear distinct.
(19) Page 25 states "One explanation for these data is that fields sampled along contiguous routes, without interruptions from heading change or reward delivery, are more likely to share their directionality." The authors should consider alternative explanations like reference frame shifts as mentioned in comment 6 above. These alternatives can be rejected based on data, but they should be considered because they seem to offer more parsimonious explanations for the observations than what the authors have offered. For example, what can explain the bimodality reported in Fig. 5G?
(20) The authors assert on page 15 that "In the present study, turns at the ends of corridors, along with reward deliveries, may be salient task boundaries at which point theta sequences are terminated. Fields active within the same theta sequence (typically same corridor fields) may be functionally coupled, while fields active on opposite sides of a theta sequence termination (different corridor fields) may be uncoupled and their tuning uncorrelated." The authors should check this. They recorded the LFPs. Why speculate when they can evaluate the speculation?
(21) The authors assert on page 26 "It is important to note that because a Pearson correlation was used, it is possible the fields are related in time with a phase shift, and we did not have the statistical power to test this possibility adequately." I either do not understand this statement or it is untrue. Please clarify.
(22) The authors continue on page 26, asserting "Thus, although it is clear that the place fields of repeating cells do not change their firing rates in synchrony, as if the cell had a global excitability change that made all its fields wax and wane together, it nonetheless remains an open question as to whether the subfields of repeating cells engage in certain types of competitive interactions or other network dynamics that couple changes in their firing rates in more complex ways." This statement implies that it might even be possible for firing fields in distinct and distant locations to be modulated together. Could the authors please explain how that is possible? A firing field is an observation that requires averaging over minutes and behavioral sampling across minutes. How might one cell be modulated to fire at a low rate during one minute and then at another minute later be modulated to fire at a high rate everywhere in the environment? Perhaps I am again not understanding the assertion - please clarify.
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Welcome to this demo lesson where you're going to get experience configuring fail-over routing as well as private hosted zones.
Now with this demo lesson you have the choice of either following along in your own environment or watching me perform the steps.
If you do wish to follow along in your own environment you will need a domain name that's registered within Route 53.
Remember that was an optional step at the start of this course so if you did register a domain of your own then you can do this demo lesson.
In my case I registered animals for life 1337.org.
If you registered a domain it will be different and so wherever you see me use animals for life.org you need to replace it with your registered domain.
If you didn't register one then you'll have to watch me perform all of these steps because you can't do this lesson without your own registered domain.
In order to get started you need to make sure that you're logged in as the I am admin user of the general AWS account which is the management account of the organization and you'll need to have the Northern Virginia region selected.
Now we're going to need to create some infrastructure in order to perform this demo lesson so attached to this lesson is a one-click deployment link and you should go ahead and click that link now.
That's going to take you to a quick create stack screen.
Everything should be pre-populated the stack name is DNS and failover demo all you'll need to do is scroll down to the bottom check this capabilities box and then click on create stack.
That's going to take a few minutes and it's going to create infrastructure that we're going to need to continue with the demo lesson so go ahead and pause the video wait for your stack to move into a create complete state and then we're good to continue.
Okay so the stacks now in a create complete state and it's created a number of resources the most important one being a public EC2 instance so we just need to test this first so if you just click in the search box and type EC2 and then right click to open that in a new tab.
Once you're there click on instances running and you should see a4l-web just select that under public IP version 4 just click on this symbol to copy the IP address into your clipboard make sure you don't click open address because that's going to try and use HTTPS which we don't want so copy this IP address into your clipboard and then open that in a new tab and you should see the animals for life super minimal homepage and if you see that it means everything's working as intended so go ahead and close down that tab.
Now we also need to give this instance an elastic IP address so that it has a static public IP version 4 address now to give it an elastic IP on the menu on the left scroll down to the bottom under network and security select elastic IPs and then we need to allocate an elastic IP make sure us - east - 1 is in this box scroll down and click on allocate once the elastic IP address is allocated to this account select it click on actions and then associate elastic IP once we're at this screen make sure instance is selected click in this search box and then select a4l-web once selected click in the private IP address box and select the private IP address of this instance and then check the box to say allow this elastic IP address to be re-associated once all that's complete click on associate and that now means that our EC2 instance has been allocated with a static IP version 4 address now we're configuring failover DNS and so the EC2 instance is going to be our primary record so we're going to assume that this is the animals for life main website and we want to configure an S3 bucket which is running as the backup in case this EC2 instance fails so the next thing we need to do is to create the S3 bucket so click in the search box type S3 and open that in a new tab and then go to the S3 console and at this point we're going to create an S3 bucket and configure it as a static website now the naming of the S3 bucket is important earlier in the course you should have registered a domain name in my case I registered animals for life 1337.org so I'm going to create a bucket with the name www.animalsforlife1337.org you need to create one which is called www.and then the domain name that you registered so I'm going to click and create bucket the bucket name is www.animalsforlife1337.org and it's going to be in the US east northern Virginia region which is US-East-1 then we're going to scroll down and we're going to need to uncheck block all public access because this bucket is going to be used to host a static website I'll need to acknowledge that I'm okay with that so I'll do that and then scroll all the way down to the bottom and then I'm going to click on create bucket then I'm going to go inside the bucket click on upload and then add files now attach to this lesson is an assets file I want you to go ahead and download that file then extract it and wave extracted it it should create a folder called R53 underscore zones underscore and underscore failover go inside that folder and there'll be two more folders one which is 01 underscore A4L website and another which is 02 underscore A4L failover we're interested in the A4L failover so go into that folder select both these files so index.html and minimal.jpeg click on open and then upload those files so we'll scroll down and click on upload once that's completed click on close then we go into enable static website hosting so click on properties and to enable this it's all the way down towards the bottom click on edit next to static website hosting and enable it make sure that host a static website is selected and then for the index document and the error document we're going to type index.html and once both of those are entered scroll down to the bottom and save changes now we've one final thing to do on this bucket we need to add a bucket policy so that this bucket is public so we need to click on permissions scroll down and then under bucket policy click on edit and this bucket currently does not have a bucket policy now also inside the assets folder that you extracted earlier in this lesson there's a file called bucket underscore policy.json this is the file so you'll need to copy the contents of that file into your clipboard and then inside this policy box paste that in and then click on the icon next to the bucket ARN to copy that into your clipboard and then we need to replace this placeholder with what you've just copied so I want you to select from just to the right of the first speech mark all the way through to before the forward slash so you should have ARN colon AWS colon S3 colon colon colon colon and then example bucket and then go ahead and paste the text from your clipboard which will overwrite that with the actual bucket ARN so it should look like this once you've got that scroll down and save the changes so now we have the failover website configured the static website running from the S3 bucket so now we need to go ahead and move to the route 53 console where we going to create a health check and configure the failover record so click in the search box type route 53 right click and open that in a new tab then click on health checks we're going to create a health check for the health check name type a4l health and it's going to be an end point health check scroll down we're going to specify the endpoint by IP address the protocols going to be HTTP and we need the IP address of the EC2 instance so if we go back to the EC2 console the EC2 instance is now using the elastic IP so if we scroll down and click on elastic IPs and copy the elastic IP into our clipboard then go back to the route 53 console and paste that in and the health check is going to be configured to health check the index.html document so in path we need to click and type index.html then we're going to expand advanced configuration and by default a health check is checking every 30 seconds so this is a standard health check we need to change this to fast because we want our health check to react as fast as possible if our primary website fails so select fast scroll down to the bottom click on next we don't want to create an alarm because we don't want to take any action if this health check fails we're just going to use it as part of our fail-over routing so go ahead and make sure no is selected and then click create health check now the health check is going to start off with an unknown status because it hasn't gathered enough information about the health of the primary website it's going to take a few minutes to move from this status to either healthy or unhealthy what we can do though is if we check this we can click on the health checkers tab and start to see the results of the globally distributed set of health check endpoints so we can see that we're already getting success HTTP status code 200 and this is telling us our primary website is already passing these individual checks and after a couple of minutes if we hit refresh we should see that the status changes from unknown to healthy so next we need to create the failover record so click on hosted zones locate the hosted zone for the domain that you registered at the start of the course and click it then click on create record now you can switch between two different modes either the quick create record mode or the wizard mode we're going to keep this demo simple so click on switch to wizard we're going to choose a failover record so select failover and click next we're going to call the record www we're going to set a TTL of one minute so click 1m and that will change the TTL seconds to 60 scroll down and we're going to define some failover records so click define failover record first we need to create the primary record so click in this first drop down and we're going to pick IP address or another value depending on record type so click that and then we need the elastic IP address so go back to the EC2 console and copy the elastic IP into your clip board and paste that into this box and then for failover record type this is the primary record so click on primary we need to associate it with a health check so click in that drop down and choose a for L health now once we do that it means that this primary record will only be returned if this health check is healthy otherwise the secondary record will be returned which we're going to define in a second under record ID just go ahead and type EC2 this needs to be unique within this set of records with the same name so going to call one EC2 and the other S3 so this one's EC2 so define that failover record and then we're going to define a new failover record so click that box again this time in this drop down we need to scroll down and we're going to select alias to an S3 website endpoint so select that choose the region and it needs to be US - East - 1 once selected you should be able to click in this box and see the S3 bucket that you just created so click on this to select that S3 bucket and we're going to set this as the secondary record so click on secondary we won't be associating this with a health check and we won't be evaluating the target health this record will only ever be used if the primary fails its health check and so we want this record to take effect whenever the health check associated with the primary fails and we're going to test that by shutting down the EC2 instance so this record should then take over so finally we need to enter S3 in the record ID and click on define failover record once we've done both of those we can go ahead and click on create records so now that we have both of those records in place the primary pointing at EC2 and the secondary at S3 if we copy down this full DNS name into our clipboard and open that in a new tab that should direct towards the animals for life.org super minimal homepage remember this is the website running on EC2 now what we need to do is to simulate a failure so go back to the EC2 console scroll to the top click on EC2 dashboard then instances running right click on this instance select stop instance and confirm that by clicking stop so now we've stopped this instance it should begin failing the health check so let's go back to the route 53 console click on health checks select this a4 health health check click on the health checkers tab and then click on refresh and over the coming seconds we should start to see some failure responses in this status column there we go we're getting connection timed out and over the next minute or so we should see that the status of the health check overall should move from healthy to unhealthy let's click on refresh it might take a minute or so for that to take effect so let's just give it a minute or so and now we can see that it's moved into an unhealthy state now this means that our failover record will detect this and then it's going to start returning the secondary record rather than the primary now DNS does have a cache remember we set the TTL value to 60 seconds so one minute but what we should find after that cache expires if we go back to this tab which we have open to the www.animalsforlife.org website and if we now hit refresh we should see that it changes to the animals for life.org super minimal failover page and this is the website that's running on s3 so the failover record has used a health check detected the failure of the EC2 instance and redirected us towards the backup s3 site so now we can go ahead and reverse that process if we go back to the EC2 console we can right click on this instance and start the instance that will take a few minutes to move from the stopped state through the pending state and then finally to running and once it's in a running state if we go back to the route 53 console and select this health check and then refresh on the health checkers initially we'll see a number of different messages if we keep hitting refresh over the next few minutes we should see this change to an okay message there we can see the first HTTP status code 200 if we keep refreshing we'll see more of those again more 200 statuses which means okay now that all of these are coming back okay let's click refresh on the health check itself it's still showing us unhealthy let's give it a few more seconds now it's reporting as healthy again if we go back to the tab that we have open to the website and click on refresh now it should change back to the original EC2 based website and it does so that means our failover record has worked in both directions it's failed over to s3 and failed back to EC2 okay so this is the end of part one of this lesson it was getting a little bit on the long side and so I wanted to add a break it's an opportunity just to take a rest or grab a coffee part 2 will be continuing immediately from the end of part one so go ahead complete the video and when you're ready join me in part 2.
This repo contains peer apps for the Over-the-Air Firmware Upgrade embedded app. Binaries and source code are included. Separate apps are supplied for: Android ...
4 Peer Apps
This repo contains peer apps for the Over-the-Air Firmware Upgrade embedded app. Binaries and source code are included. Separate apps are supplied for: Android ...
for - Peer Apps
Reviewer #2 (Public review):
The manuscript "Spatial frequency adaptation modulates population receptive field sizes" is a heroic attempt to untangle a number of visual phenomena related to spatial frequency using a combination of psychophysical experiments and functional MRI. While the paper clearly offers an interesting and clever set of measurements supporting the authors' hypothesis, my enthusiasm for its findings is somewhat dampened by the small number of subjects, high noise, and lack of transparency in the report. Despite several of the methods being somewhat heuristically and/or difficult to understand, the authors do not appear to have released the data or source code nor to have committed to doing so, and the particular figures in the paper and supplements give a view of the data that I am not confident is a complete one. If either data or source code for the analyses and figures were provided, this concern could be largely mitigated, but the explanation of the methods is not sufficient for me to be anywhere near confident that an expert could reproduce these results, even starting from the authors' data files.
Major Concerns:
I feel that the authors did a nice job with the writing overall and that their explanation of the topic of spatial frequency (SF) preferences and pRFs in the Introduction was quite nice. One relatively small critique is that there is not enough explanation as to how SF adaptation would lead to changes in pRF size theoretically. In a population RF, my assumption is that neurons with both small and large RFs are approximately uniformly distributed around the center of the population. (This distribution is obviously not uniform globally, but at least locally, within a population like a voxel, we wouldn't expect the small RFs to be on average nearer the voxel's center than the voxel's edges.) Why then would adaptation to a low SF (which the authors hypothesize results in higher relative responses from the neurons with smaller RFs) lead to a smaller pRF? The pRF size will not be a function of the mean of the neural RF sizes in the population (at least not the neural RF sizes alone). A signal driven by smaller RFs is not the same as a signal driven by RFs closer to the center of the population, which would more clearly result in a reduction of pRF size. The illustration in Figure 1A implies that this is because there won't be as many small RFs close to the edge of the population, but there is clearly space in the illustration for more small RFs further from the population center that the authors did not draw. On the other hand, if the point of the illustration is that some neurons will have large RFs that fall outside of the population center, then this ignores the fact that such RFs will have low responses when the stimulus partially overlaps them. This is not at all to say that I think the authors are wrong (I don't) - just that I think the text of the manuscript presents a bit of visual intuition in place of a clear model for one of the central motivations of the paper.
The fMRI methods are clear enough to follow, but I find it frustrating that throughout the paper, the authors report only normalized R2 values. The fMRI stimulus is a very interesting one, and it is thus interesting to know how well pRF models capture it. This is entirely invisible due to the normalization. This normalization choice likely leads to additional confusion, such as why it appears that the R2 in V1 is nearly 0 while the confidence in areas like V3A is nearly 1 (Figure S2). I deduced from the identical underlying curvature maps in Figures 4 and S2 that the subject in Figure 4 is in fact Participant 002 of Figure S2, and, assuming this deduction is correct, I'm wondering why the only high R2 in that participant's V1 (per Figure S2) seems to correspond to what looks like noise and/or signal dropout to me in Figure 4. If anything, the most surprising finding of this whole fMRI experiment is that SF adaptation seems to result in a very poor fit of the pRF model in V1 but a good fit elsewhere; this observation is the complete opposite of my expectations for a typical pRF stimulus (which, in fairness, this manuscript's stimulus is not). Given how surprising this is, it should be explained/discussed. It would be very helpful if the authors showed a map of average R2 on the fsaverage surface somewhere along with a map of average normalized R2 (or maps of each individual subject).
On page 11, the authors assert that "Figure 4c clearly shows a difference between the two conditions, which is evident in all regions." To be honest, I did not find this to be clear or evident in any of the highlighted regions in that figure, though close inspection leads me to believe it could be true. This is a very central point, though, and an unclear figure of one subject is not enough to support it. The plots in Figure 5 are better, but there are many details missing. What thresholding was used? Could the results in V1 be due to the apparently small number of data points that survive thresholding (per Figure S2)? I would very much like to see a kernel density plot of the high-adapted (x-axis) versus low-adapted (y-axis) pRF sizes for each visual area. This seems like the most natural way to evaluate the central hypothesis, but it's notably missing.
Regarding Figure 4, I was curious why the authors didn't provide a plot of the difference between the PRF size maps for the high-adapted and low-adapted conditions in order to highlight these apparent differences for readers. So I cut the image in half (top from bottom), aligned the top and bottom halves of the figure, and examined their subtraction. (This was easy to do because the boundary lines on the figure disappear in the difference figure when they are aligned correctly.) While this is hardly a scientific analysis (the difference in pixel colors is not the difference in the data) what I noticed was surprising: There are differences in the top and bottom PRF size maps, but they appear to correlate spatially with two things: (1) blobs in the PRF size maps that appear to be noise and (2) shifts in the eccentricity maps between conditions. In fact, I suspect that the difference in PRF size across voxels correlates very strongly with the difference in eccentricity across voxels. Could the results of this paper in fact be due not to shifts in PRF size but shifts in eccentricity? Without a better analysis of the changes in eccentricity and a more thorough discussion of how the data were thresholded and compared, this is hard to say.
While I don't consider myself an expert on psychophysics methods, I found the sections on both psychophysical experiments easy to follow and the figures easy to understand. The one major exception to this is the last paragraph of section 4.1.2, which I am having trouble following. I do not think I could reproduce this particular analysis based on the text, and I'm having a hard time imagining what kind of data would result in a particular PSE. This needs to be clearer, ideally by providing the data and analysis code.
Overall, I think the paper has good bones and provides interesting and possibly important data for the field to consider. However, I'm not convinced that this study will replicate in larger datasets - in part because it is a small study that appears to contain substantially noisy data but also because the methods are not clear enough. If the authors can rewrite this paper to include clearer depictions of the data, such as low- and high-adapted pRF size maps for each subject, per visual-area 2D kernel density estimates of low- versus high-adapted pRF sizes for each voxel/vertex, clear R2 and normalized-R2 maps, this could be much more convincing.
Author response:
We thank the reviewers for their valuable comments. Our revision will address their recommendations and clarify any misconceptions. The main points we plan to amend are as follows:
Direct comparison of pRF sizes
We may have misunderstood this comment in the eLife assessment. We believe our original analyses and the figures already provided a “direct comparison between pRF sizes in the high-adapted and low-adapted conditions”. Specifically, we included a figure showing the histograms of pRF sizes in both conditions, and also reported statistical tests to compare conditions both within each participant and across the group. However, we now realize these comparisons might not be as clear to readers as we intended, which would explain Reviewer #2’s interpretations. To clarify, in our revised version we will instead show 2D plots comparing pRF sizes between conditions as suggested by Reviewer #2, and also show the pRF size plotted against eccentricity (rather than only the difference) as suggested by Reviewer #3.
Data sharing
The behavioral data, fMRI data (where ethically permissible), stimulus-generation code, statistical analyses, and fMRI stimulus video are already publicly available at the link: https://osf.io/9kfgx/. However, we unfortunately failed to include the link in the preprint. We apologize for this oversight. It will be included in the revision. The repository now also contains a script for simulated adaptation effects on pRF size used in our response to Reviewer #2. Moreover, for transparency, we will include plots of all the pRF parameter maps for all participants, including pRF size, polar angle, eccentricity, normalized R2, and raw R2.
Sample size
The reviewers shared concerns about the sample size of our study. We disagree that this is a weakness of our study. It is important to note that large sample sizes are not necessary to obtain conclusive results, especially when the research aims to test whether an effect exists, rather than finding out how strong the effect is on average in a population (Schwarzkopf & Huang, 2024, currently out as preprint, but in press at Psychological Methods). Our results showed robust within-subject effects, consistent across multiple visual regions in most individual participants. A larger sample size would not necessarily improve the reliability of our findings. Treating each individual as an independent replication, our results suggest a high probability that they would replicate in each additional participant we could scan.
Reviewer #1:
We thank the reviewer for their careful evaluation and positive comments. We will include a more detailed discussion about the issues pointed out, and an additional plot showing the polar angle for both adapter conditions. In line with previous work on the reliability of pRF estimates (van Dijk, de Haas, Moutsiana, & Schwarzkopf, 2016; Senden, Reithler, Gijsen, & Goebel, 2014), both polar angle and eccentricity maps are very stable between the two adaptation conditions.
Reviewer #2:
We thank the reviewer for their comments - we will improve how we report key findings which we hope will clarify matters raised by the reviewer.
RF positions in a voxel
The reviewer’s comments suggest that they may have misunderstood the diagram (Figure 1A) illustrating the theoretical basis of the adaptation effect, likely due to us inadvertently putting the small RFs in the middle of the illustration. We will change this figure to avoid such confusion.
Theoretical explanation of adaptation effect
The reviewer’s explanation for how adaptation should affect the size of pRF averaging across individual RFs is incorrect. When selecting RFs from a fixed range of semi-uniformly distributed positions (as in an fMRI voxel), the average position of RFs (corresponding to pRF position) is naturally near the center of this range. The average size (corresponding to pRF size) reflects the visual field coverage of these individual RFs. This aggregate visual field coverage thus also reflects the individual sizes. When large RFs have been adapted out, this means the visual field coverage at the boundaries is sparser, and the aggregate pRF is therefore smaller. The opposite happens when adapting out the contribution of small RFs. We demonstrate this with a simple simulation at this OSF link: https://osf.io/ebnky/.
Figure S2
It is not actually possible to compare R2 between regions by looking at Figure S2 because it shows the pRF size change, not R2. Therefore, the arguments Reviewer #2 made based on their interpretation of the figure are not valid. Just as the reviewer expected, V1 is one of the brain regions with good pRF model fits. In our revision, we will include normalized and raw R2 maps to make this more obvious to the readers and provide additional explanations.
V1 appeared essentially empty in that plot primarily due to the sigma threshold we selected, which was unintentionally more conservative than those applied in our analyses and other figures. We apologize for this mistake and will correct it in the revised version by including a plot with the appropriate sigma threshold.
Thresholding details
Thresholding information was included in our original manuscript; however, we will include more information in the figure captions to make it more obvious.
2D plots will replace histograms
We thank the reviewer for this suggestion. The manuscript contained histograms showing the distribution of pRF size for both adaptation conditions for each participant and visual area (Figure S1). However, we agree that 2D plots better communicate the difference in pRF parameters between conditions, so we will replace this figure. We will consider 2D kernel density plots as suggested by the reviewer; however, such plots can obscure distributional anomalies so they may not be the optimal choice and we may opt to show transparent scatter plots of individual pRFs instead.
(proportional) pRF size-change map
The reviewer requests pRF size difference maps. Figure S2 in fact demonstrates the proportional difference between the pRF sizes of the two adaptation conditions. Instead of simply taking the difference, we believe showing the proportional change map is more sensible because overall pRF size varies considerably between visual regions. We will explain this more clearly in our revision.
pRF eccentricity plot
“I suspect that the difference in PRF size across voxels correlates very strongly with the difference in eccentricity across voxels.”
Our manuscript already contains a supplementary plot (Figure S4 B) comparing the eccentricity between adapter conditions, showing no notable shift in eccentricities except in V3A - but that is a small region and the results are generally more variable. We will comment more on this finding in the main text and explain this figure in more detail.
To the reviewer’s point, even if there were an appreciable shift in eccentricity between conditions (as they suggest may have happened for the example participant we showed), this does not mean that the pRF size effect is “due [...] to shifts in eccentricity.” Parameters in a complex multi-dimensional model like the pRF are not independent. There is no way of knowing whether a change in one parameter is causally linked with a change in another. We can only report the parameter estimates the model produces.
In fact, it is conceivable that adaptation causes both: changes in pRF size and eccentricity. If more central or peripheral RFs tend to have smaller or larger RFs, respectively, then adapting out one part of the distribution will shift the average accordingly. However, as we already established, we find no compelling evidence that pRF eccentricity changes dramatically due to adaptation, while pRF size does. We will illustrate this using the 2D plots in our revision.
Reviewer #3:
We thank the reviewer for their comments.
pRF model
Top-up adapters were not modelled in our analyses because they are shared events in all TRs, critically also including the “blank” periods, providing a constant source of signal. Therefore modelling them separately cannot meaningfully change the results. However, the reviewer makes a good suggestion that it would be useful to mention this in the manuscript, so we will add a discussion of this point.
pRF size vs eccentricity
We will add a plot showing pRF size in the two adaptation conditions (in addition to the pRF size difference) as a function of eccentricity.
Correlation with behavioral effect
In the original manuscript, we pointed out why the correlation between the magnitude of the behavioral effect and the pRF size change is not an appropriate test for our data. First, the reviewer is right that a larger sample size would be needed to reliably detect such a between-subject correlation. More importantly, as per our recruitment criteria for the fMRI experiment, we did not scan participants showing weak perceptual effects. This limits the variability in the perceptual effect and makes correlation inapplicable.
References
van Dijk, J. A., de Haas, B., Moutsiana, C., & Schwarzkopf, D. S. (2016). Intersession reliability of population receptive field estimates. NeuroImage, 143, 293–303. https://doi.org/10.1016/J.NEUROIMAGE.2016.09.013
Schwarzkopf, D. S., & Huang, Z. (2024). A simple statistical framework for small sample studies. BioRxiv, 2023.09.19.558509. https://doi.org/10.1101/2023.09.19.558509
Senden, M., Reithler, J., Gijsen, S., & Goebel, R. (2014). Evaluating population receptive field estimation frameworks in terms of robustness and reproducibility. PloS One, 9(12). https://doi.org/10.1371/JOURNAL.PONE.0114054
Incorrect Console Output on Enqueue (push):The push method in JavaScript returns the new length of the array, not the element that was pushed. So, let enter = que.push(input[i][1]) assigns the length of the queue to enter, not the element that was added.
The problem in your code seems to be with the way you’re handling the push operation and printing the result. Here’s a breakdown of the issues and improvements you can make:
Incorrect Console Output on Enqueue (push):
The push method in JavaScript returns the new length of the array, not the element that was pushed. So, let enter = que.push(input[i][1]) assigns the length of the queue to enter, not the element that was added. Instead, you should directly print the element that was added to the queue. Correcting the console.log for Enqueue:
Replace console.log(enter) with console.log(input[i][1]) to print the element being added to the queue instead of the length of the queue.
Experience the flawless elegance
We're missing baseline alignment across the columns. Could we also watch out for widows at the end of the paragraphs? Not sure if it is possible to ensure we never have widows in the code.
Reviewer #2 (Public review):
Summary:
In this manuscript, Pereira de Castro and coworkers are studying potential competition between a more standard splicing factor SF1, and an alternative splicing factor called QK1. This is interesting because they bind to overlapping sequence motifs and could potentially have opposing effects on promoting the splicing reaction. To test this idea, the authors KD either SF1 or QK1 in mammalian cells and uncover several exons whose splicing regulation follows the predicted pattern of being promoted for splicing by SF1 and repressed by QK1. Importantly, these have introns enriched in SF1 and QK1 motifs. The authors then focus on one exon in particular with two tandem motifs to study the mechanism of this in greater detail and their results confirm the competition model. Mass spec analysis largely agrees with their proposal; however, it is complicated by the apparently quick transition of SF1-bound complexes to later splicing intermediates. An inspired experiment in yeast shows how QK1 competition could potentially have a detrimental impact on splicing in an orthogonal system. Overall, these results show how splicing regulation can be achieved by competition between a "core" and alternative splicing factor and provide additional insight into the complex process of branch site recognition. The manuscript is exceptionally clear and the figures and data are very logically presented. The work will be valuable to those in the splicing field who are interested in both mechanism and bioinformatics approaches to deconvolve any apparent "splicing code" being used by cells to regulate gene expression. Criticisms are minor and the most important of them stem from overemphasis on parts of the manuscript on the evolutionary angle when evolution itself wasn't analyzed per se.
Strengths:
(1) The main discovery of the manuscript involving evidence for SF1/QK1 competition is quite interesting and important for this field. This evidence has been missing and may change how people think about branch site recognition.
(2) The experiments and the rationale behind them are exceptionally clearly and logically presented. This was wonderful!
(3) The experiments are carried out to a high standard and well-designed controls are included.
(4) The extrapolation of the result to yeast in order to show the potentially devastating consequences of the QK1 competition was very exciting and creative.
Weaknesses:
Overall the weaknesses are relatively minor and involve cases where clarification is necessary, some additional analysis could bolster the arguments, and suggestions for focusing the manuscript on its strengths.
(1) The title (Ancient...evolutionary outcomes), abstract, and some parts of the discussion focus heavily on the evolutionary implications of this work. However, evolutionary analysis was not performed in these studies (e.g., when did QK1 and SF1 proteins arise and/or diverge? How does this line up with branch site motifs and evolution of U2? Any insight from recent work from Scott Roy et al?). I think this aspect either needs to be bolstered with experimental work/data or this should be tamped down in the manuscript. I suggest highlighting the idea expressed in the sentence "A nuanced implication of this model is that loss-of-function...". To me, this is better supported by the data and potentially by some analysis of mutations associated with human disease.
(2) One paper that I didn't see cited was that by Tanackovic and Kramer (Mol Biol Cell 2005). This paper is relevant because they KD SF1 and found it nonessential for splicing in vivo. Do their results have implications for those here? How do the results of the KD compare? Could QK1 competition have influenced their findings (or does their work influence the "nuanced implication" model referenced above?)?
(3) Can the authors please provide a citation for the statement "degeneracy is observed to a higher degree in organisms with more alternative splicing"? Does recent evolutionary analysis support this?
(4) For the data in Figure 3, I was left wondering if NMD was confounding this analysis. Can the authors respond to this and address this concern directly?
(5) To me, the idea that an engaged U2 snRNP was pulled down in Figure 4F would be stronger if the snRNA was detected. Was that able to be observed by northern or primer extension? Would SF1 be enriched if the U2 snRNA was degraded by RNaseH in the NE?
(6) I'm wondering how additive the effects of QK1 and SF1 are... In Figure 2, if QK1 and SF1 are both knocked down, is the splicing of exon 11 restored to "wt" levels?
(7) The first discussion section has two paragraphs that begin "How does competition between SF1..." and "Relatively little is known about how...". I found the discussion and speculation about localization, paraspekles, and lncRNAs interesting but a bit detracting from the strengths of the manuscript. I would suggest shortening these two paragraphs into a single one.
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Welcome back and in this brief demonstration you'll have the opportunity to create an EC2 instance with WordPress bootstrapped in ready and waiting to be configured.
But this time you'll be using an enhanced CloudFormation template which uses CFN init and creation policies rather than the simple user data that you used in the previous demonstration.
To get started just make sure you are logged in to the general AWS account as the I am admin user and as always make sure you've got the northern Virginia region selected.
Now attached to this lesson are two one click deployment links.
Go ahead and use the first one which is the VPC link.
Everything should be pre-populated.
All you'll need to do is scroll down to the bottom, check the acknowledgement box and click on create stack.
Once it's moved into a create complete status you can resume and we'll carry on with the demo.
I'll assume that that's now in a create complete status and now we're going to apply another CloudFormation template.
This is the template that we'll be using.
It's just an enhancement of the one that you used in the previous lesson.
This time instead of using a set of procedural instructions, so a script that are passed into the user data, this uses the CFN init system and creation policies.
So let's have a look at exactly what that means.
If I scroll down and locate the EC2 instance logical resource, then here we've got this creation policy.
This means that CloudFormation is going to create a hold point.
It's not going to allow this resource to move into a create complete status until it receives a signal.
And it's going to wait 15 minutes for this signal.
So a timeout of 15 minutes.
Now scrolling down and looking at the user data, the only things we do in a procedural way, we use the CFN init command to begin the desired state configuration.
That will either succeed or not.
And based on that we use the CFN signal command to pass that success or failure state back to the CloudFormation stack.
And that's what uses this creation policy.
So the creation policy will wait for a signal and it's this command which provides that signal, either a success signal or a failure signal.
Now what we're interested in specifically for this demo lesson is this CFN init command.
So this is the thing that pulls the desired state configuration from the metadata of this logical resource.
I'll talk all about that in a second.
But it pulls that down by being given the stack ID and it uses this substitution command.
So instead of this being passed into the instance, what's actually passed instead of this variable name, so the stack ID variable name, is the actual stack ID.
And then likewise, instead of this variable name, aws colon region is passed to the actual region that this template is being applied into.
So that's what the substitution function does.
It replaces any variable or parameter names with the values of those variables or parameters.
So the CFN init process is then able to consult the CloudFormation stack and retrieve the configuration information.
That's all stored in the metadata section of this logical resource.
Now I just want to draw your attention to this double hyphen config sets wordpress underscore install.
This tells us what set of instructions we want CFN init to run.
So if I just expand the metadata section here, we've got one or more config sets defined.
In this case, we've only got the one which is wordpress underscore install.
And this config set runs five individual items, one after the other.
And these are called config keys.
So install CFN, software install, configure instance, install wordpress and configure wordpress.
Now these reference the config keys defined below.
So you'll see that the same name install CFN, software install, configure instance, install wordpress and configure wordpress.
You'll recognize a lot of the commands used because they're the same commands that install and configure wordpress.
So in the software install config key, we're using the DNF package manager to install various software packages that we need for this installation, such as WGet, MariaDB, the Apache web server and various other utilities.
Then another part is services and we're specifying that we want these services to be enabled and to be running.
So this means that the service will be set to start up on instance boot and it will make sure that it's running right now.
The next config key is configure instance.
The files component of this can create files with a certain content.
So we're creating a file called etc update-motd.d/40-cow.
This is the part that we had to do manually before and this is the thing that adds the cow say banner.
Then we're running some more procedural commands to set the database root password and to update this banner.
Then we've got install wordpress, which uses a sources option to expand whatever is specified here into this directory.
So this automatically handles the download and the unjzip and untarring of this archive into this folder and it can even do that with authentication if needed.
We're creating another file this time to perform the configuration of wordpress and another file this time to create the database for wordpress.
Then finally we've got the configure wordpress which fixes up the permissions and creates these databases.
So this is doing the same thing as the procedural example in the previous demo.
Instead of running all of these commands one by one, this is just using desired state.
Now there is one more thing that I wanted to point out right at the top.
This is the part that configures CFN init to keep watching the logical resource configuration inside the cloud formation stack.
And if it notices that the metadata for EC2 instance inside the stack changes, then it will run CFN init again.
Remember how in the theory lesson I mentioned that this process could cope with stack updates.
So it doesn't only run once like user data does.
Well, this is how it does that.
This configures this automatic update that keeps an eye on the cloud formation stack and reruns CFN init whenever any changes occur.
This is well beyond what you need for the associate exam.
I just want you to be aware of what this is and how it works.
Essentially we're setting up a process called CFN hop and making it watch the cloud formation stack for any configuration changes.
And then we're setting it up so that the CFN hop process is enabled and running so that it can watch the resource configuration constantly.
So that's it for this template.
What we'll do now is apply it.
So go ahead and click on the second one click deployment link attached to this lesson.
It should be called A4LEC2CFN init.
So click that link.
All you'll need to do is scroll down to the bottom and then click on create stack.
Now this time remember we're using a creation policy.
So cloud formation is not going to move this logical ID and to create complete when EC2 signals that the launch process is completed.
Instead it's going to wait until the instance itself signals the successful completion of the CFN init process.
So because we're using this creation policy it's going to hold until the instance operating system using CFN-signal provide a signal to cloud formation to say yep everything's okay and at that point the logical resource will move into create complete.
So that's going to take a couple of minutes.
The EC2 instance will need to actually launch itself and pass its status checks and then the CFN init process will run, perform all of the configuration required and then assuming the status code of that is okay then CFN-signal will take that status code and respond to the cloud formation stack with a successful completion and then the process will move on then cloud formation will mark the particular resources complete and the stack is complete.
Now that will take a few minutes so just keep hitting refresh and you should see the status update after two to three minutes but go ahead and pause the video and resume it once your stack moves into the create complete status.
And there we go at this point the stack has moved into the create complete status and I just want to draw your attention to this line.
You won't have seen this before.
This is the line where our EC2 instance has run the CFN init process successfully and then the CFN signal command has taken that success signal and delivered it to the cloud formation stack.
So this is the signal that cloud formation was waiting for before moving this resource into a create complete status and that's what's needed before the stack itself could move into a create complete status.
So now we explicitly know that the configuration of this instance has actually been completed.
So we're not relying on EC2 telling us that the instance status is now running with two out of two checks.
Instead the operating system itself the CFN init process that's completed successfully and the CFN signal process has explicitly indicated to cloud formation that that whole process has been completed.
So if we move across to the EC2 console we should be able to connect to the instance exactly as we've done before.
Look for the running instance and select it.
Copy the public IP version 4 IP address and open that in a new tab.
All being well you should see the familiar WordPress installation screen.
If you're right click on that instance and put connect.
Go to instance connect and hit connect that will connect you into the instance and you should be greeted by the cow themed login banner.
This time if we use curl to show us the contents of user data this time it's only a small number of lines because the only thing that runs is the CFN init process and the CFN signal process.
Notice though how all of these variable names have been replaced with their values so the stack IDs and the region.
So this is how it knows to communicate with the right stack in the right region inside cloud formation.
If we do a CD space forward slash var forward slash log and then do a listing we've still got these original two files so cloud hyphen init dot log and cloud hyphen init hyphen output dot log.
So these are primarily associated with the user data output.
But now we've also got these new log files so CFN hyphen init hyphen CMD dot log and that is an output of the CFN init process.
So if we cat that so shudu space cat space and then the name of that log file this will show us an output of the CFN init process itself.
So we can see each of the individual config keys running and what individual operations are being performed inside each of those keys.
So it's a more complex but a more powerful process.
And at this point that's everything I wanted to cover.
It was just to give you practical exposure to an alternative to raw user data and that was CFN hyphen init.
It's a much more powerful system especially when combined with cloud formation creation policies which allow us to pause the progress of a cloud formation stack waiting for the resource itself to explicitly say yes I finished off all of my bootstrapping process you're good to carry on and that's done using the CFN hyphen signal command.
Now at this point let's just clean up the account move back to cloud formation.
Once you there go ahead and delete the EC2 CFN init stack wait for that process to complete and once you've done that go ahead and delete the A4L VPC stack and that will return the AWS account into the state that you had it at the start of this demo.
At that point thanks for doing this demo I hope it was useful.
You can go ahead and complete this video now and when you're ready you can join me in the next.
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
(1) The sample size of the in-house dataset used for training the model was relatively small (34 patients), which might limit the generalizability of the findings.
(2) The authors did not perform functional experiments to directly validate the roles of the identified key genes in radiotherapy sensitivity, relying instead on associations with immune features and signaling pathways.
(3) The study did not discuss the potential limitations of using machine learning algorithms, such as the risk of overfitting and the need for larger, diverse datasets for more robust model development and validation.
(1) Currently, we are actively expanding the dataset by incorporating additional patient samples to enhance the model's robustness and generalizability. Furthermore, we implement advanced statistical techniques, including cross-validation, during model development to mitigate the potential limitations associated with the small sample size on our results. This limitation has been comprehensively addressed in the discussion section of our manuscript.
(2) Given the current resource limitations, our study predominantly employed bioinformatics analyses. We acknowledge the critical importance of experimental validation and are actively pursuing additional funding and collaborative opportunities to facilitate future experimental studies. Concurrently, we have enhanced the discussion section to comprehensively address the limitations of our approach and emphasize the necessity for future experimental validation.
(3) We appreciate the reviewers' insightful comments regarding the potential limitations of machine learning algorithms, particularly the risk of overfitting. In response, we have incorporated a comprehensive discussion of these concerns, detailing the measures implemented to mitigate such risks, including the application of regularization techniques and the adoption of more rigorous cross-validation methodologies. We further acknowledge the necessity for larger and more diverse datasets to enhance model validity and generalizability, a concern we intend to address in our future research endeavors. The revised manuscript includes an expanded discussion on these critical points.
Here is the limitation section in the revised Manuscript:
“This study primarily focuses on specific subtypes of nasopharyngeal carcinoma (NPC), potentially limiting its direct generalizability to other NPC subtypes or related head and neck malignancies. Furthermore, the limited sample size of our dataset may impact the model's generalizability and extrapolation capabilities. To mitigate the potential limitations associated with the small sample size, we employed advanced statistical methodologies, including cross-validation, to enhance the robustness and reliability of our findings. Nevertheless, we acknowledge the necessity for larger datasets and are actively collaborating with other research institutions to expand our sample size, thereby enhancing the robustness and broader applicability of our findings. Additionally, while our study utilizes bioinformatics approaches to identify and analyze key genes, we recognize that the absence of direct experimental functional validation represents a significant limitation. To address this limitation, we are actively pursuing additional funding and establishing collaborations with specialized laboratories to conduct crucial functional validation experiments, which will further elucidate the specific roles of these genes in radiotherapy response. Moreover, we acknowledge the potential risk of overfitting inherent in the application of machine learning algorithms to biomedical data analysis. To mitigate this risk, we implemented regularization techniques during model development and adopted a rigorous cross-validation strategy for model validation. These methodological approaches aim to ensure that our models maintain robust predictive performance on unseen data. Notwithstanding these limitations, our study offers novel insights into the molecular mechanisms underlying radiotherapy sensitivity in NPC and indicates promising avenues for future investigation. Future research endeavors will prioritize expanding the dataset, conducting comprehensive experimental validation, and refining our predictive model to enhance its accuracy and clinical applicability.”
Reviewer #2 (Public Review):
(1) The study focuses on a specific type of nasopharyngeal carcinoma (NPC) and may not be generalizable to other subtypes or related head and neck cancers. The applicability of NPC-RSS to a broader range of patients and tumor types remains to be determined.
(2) The study does not account for potential differences in radiotherapy protocols, doses, and techniques between the training and validation cohorts, which could influence the performance of the predictive model. Standardization of treatment parameters would be important for future validation studies.
(3) The binary classification of patients into radiotherapy-sensitive and resistant groups may oversimplify the complex spectrum of treatment responses. A more granular stratification system that captures intermediate responses could provide more nuanced predictions and better guide personalized treatment decisions.
(4) The study does not address the potential impact of other relevant factors, such as tumor stage, histological subtype, and concurrent chemotherapy, on the predictive performance of NPC-RSS. Incorporating these clinical variables into the model could enhance its accuracy and clinical utility.
(1) We appreciate the reviewers' interest in the applicability of our study. This study specifically focuses on a particular subtype of nasopharyngeal carcinoma (NPC), which may limit its direct generalizability to other NPC subtypes or related head and neck malignancies. We have incorporated a detailed discussion of this limitation in the Discussion section and intend to investigate the applicability of NPC-RSS across a broader spectrum of tumor types and subtypes in subsequent studies.
(2) We acknowledge the reviewers' emphasis on the significance of potential variations in radiotherapy regimens, doses, and techniques. In the current study, we did not sufficiently account for these factors, potentially impacting the model's generalizability and accuracy. We aim to improve data consistency and strengthen model validation by standardizing treatment parameters in future investigations.
(3) We concur with the reviewers' assessment that binary categorization may oversimplify the intricate nature of treatment responses. Indeed, radiotherapy responses likely exist on a continuous spectrum. Consequently, we intend to develop more refined stratification systems to capture intermediate responses, thereby enhancing the accuracy of treatment outcome predictions and facilitating personalized treatment decisions.
(4) We appreciate the reviewers' recommendation to incorporate clinical variables, including tumor stage, histological subtype, and concurrent chemotherapy, into the model. We acknowledge that these factors are crucial for enhancing the accuracy and clinical applicability of predictive models. We are presently compiling these additional data and intend to integrate these variables into subsequent model iterations.
Reviewer #1 (Recommendations For The Authors):
(1) The manuscript would benefit from a more comprehensive comparison of the NPC-RSS with existing prognostic models or biomarkers for nasopharyngeal carcinoma. This would help highlight the unique value and potential superiority of the NPC-RSS in predicting radiotherapy sensitivity.
2) The authors should consider expanding their discussion on the potential molecular mechanisms underlying the association between the key NPC-RSS genes and radiotherapy response. They could explore whether these genes have been previously implicated in radiotherapy resistance in other cancer types and discuss the potential functional roles of these genes in the context of nasopharyngeal carcinoma.
(1) We appreciate your thorough review and valuable suggestions concerning our study. In response to the suggestion of comparing the Nasopharyngeal Carcinoma Radiotherapy Sensitivity Score (NPC-RSS) with existing prognostic models or biomarkers, we have carefully considered this proposal and determined that such a comparison is beyond the scope of our current study. The primary focus of our research is on the development and internal validation of the NPC-RSS model's accuracy and reliability. At present, we do not have access to the necessary external data to conduct a valid comparison, and the integration of such data extends beyond the parameters of this study. We intend to incorporate this comparative analysis in future studies to further validate the efficacy and explore the clinical application potential of the NPC-RSS model. We appreciate your understanding and continued support for our research endeavors.(2) In the revised manuscript, we have incorporated a comprehensive review of the functions of these key genes in various cancer types and explored their potential mechanisms of action in nasopharyngeal carcinoma (NPC). Through the citation of pertinent studies, we have elucidated the impact of these genes on radiotherapy sensitivity and resistance. Furthermore, we have proposed future research directions to elucidate the specific roles of these genes in the radiotherapy response of NPC.
The following are new additions to the revised draft：
“Previous studies have demonstrated that SMARCA2 significantly influences the radiotherapy response in non-small cell lung cancer (NSCLC). Depletion of SMARCA2 has been shown to enhance radiosensitivity, suggesting its potential as a therapeutic target for radiosensitization [30478150]. Additionally, the DMC1 gene has been incorporated into the radiosensitivity index (RSI) to evaluate radiotherapy sensitivity and prognosis, particularly in endometrial cancers. This inclusion provides valuable insights into the DNA damage repair process [38628740]. Studies on CD9 in glioblastoma multiforme (GBM) have revealed that post-radiotherapy increases in CD9 and CD81 levels in extracellular vesicles (EVs) are strongly correlated with the cytotoxic response to treatment. This finding suggests the potential of CD9 as a novel biomarker for monitoring radiotherapy efficacy [36203458]. In contrast, the association of PSG4 and KNG1 with radiotherapy resistance remains unexplored in the current literature.
Future research should focus on analyzing the expression patterns of SMARCA2 in NPC patients and its correlation with radiotherapy efficacy using clinical samples. This analysis could elucidate its potential as a target for radiosensitization therapy. Investigating the correlation between DMC1 expression levels and radiotherapy sensitivity in NPC could potentially aid in predicting treatment efficacy and optimizing therapeutic regimens. Furthermore, analysis of extracellular vesicles, particularly those containing CD9, in post-radiotherapy NPC patients could assess their feasibility as biomarkers for monitoring treatment response. These proposed studies would not only contribute to a deeper understanding of the mechanisms underlying the role of these genes in NPC radiotherapy but could also potentially lead to the development of novel strategies for enhancing radiotherapy efficacy.”
Minor Recommendations:
(1) It is recommended that the author share the code for the article on Github or a similar open source platform.
(2) The manuscript would benefit from a thorough review of the punctuation and sentence structure to improve readability and clarity.
(1) You suggest sharing the code utilized in this study on GitHub or a comparable open-source platform to enhance the transparency and reproducibility of the research. I fully recognize the significance of this suggestion. However, due to the sensitivity of the data involved and the existing intellectual property agreement with my research team, we are unable to make the code publicly available at this time. We are actively seeking a method to safeguard the intellectual property of the project while also planning to share our tools and methodologies in the future. At this stage, we are open to collaborating with other researchers under appropriate frameworks and conditions to validate and replicate our findings by providing essential code execution snippets or assisting with data analysis.
(2) Your suggestions are vital for enhancing the quality of the manuscript. I will perform a comprehensive linguistic and structural review of the manuscript to ensure that statements flow coherently and punctuation is employed correctly. We also intend to engage a professional scientific and technical writing editor to ensure that the manuscript adheres to the high standards required for academic publishing.
Reviewer #2 (Recommendations For The Authors):
(1) The manuscript would benefit from a more in-depth discussion of the potential clinical implications of the NPC-RSS. The authors should elaborate on how this score could be integrated into clinical decision-making and patient management.
(2) The authors should consider including a section discussing the limitations of their study and potential areas for future research. This could include the need for prospective validation of the NPC-RSS in larger patient cohorts and the exploration of additional biological mechanisms.
(1) We concur that a more comprehensive discussion regarding the application of the NPC-RSS in clinical decision-making would significantly enhance the practical value of this study. In the revised draft, we will include a section that elaborates on the integration of the NPC-RSS scoring system into daily clinical practice, detailing how it can assist physicians in developing individualized treatment plans and optimize patient management by predicting treatment responses.
The following are new additions to the revised draft:
“The incorporation of the NPC-RSS scoring system into clinical decision-making and patient management involves several key steps: first, establishing genetic testing as a standard component of nasopharyngeal cancer diagnosis and ensuring that physicians have prompt access to scoring results to guide treatment planning. Second, physicians should utilize the scoring results to tailor individualized treatment plans and engage in multidisciplinary discussions to optimize decision-making. Concurrently, physicians should elucidate the clinical significance of the scores and effectively communicate with patients to facilitate shared decision-making. Furthermore, continuous monitoring of the relationship between scoring and treatment outcomes, optimizing the scoring model based on empirical data, and ensuring the integration of technological platforms along with regulatory compliance are essential for safeguarding the effective operation of the scoring system and the protection of patient information.
(2) In light of the reviewers' valuable suggestions, we acknowledge the significance of prospective validation of the NPC-RSS scoring system in a broader patient population and the necessity for thorough exploration of the underlying biological mechanisms. Accordingly, we are incorporating a new section in the revised manuscript that elaborates on the limitations of the current study and outlines potential directions for future research. This encompasses plans to increase the sample size for validation and further investigations into the biological basis of the scoring system to enhance its predictive validity and clinical applicability. We believe that these additions will significantly enrich the depth and breadth of the study, thereby serving the scientific community and clinical practice more effectively.”
Minor Recommendations:
(1) The authors should ensure that all abbreviations are defined at their first mention in the text.
(2) The figure legends should be more descriptive and self-explanatory, allowing readers to understand the main findings without referring back to the main text.
(1) You pointed out the need to define all acronyms at the first mention in the text and suggested that a comprehensive list of acronyms be included in the revised draft. We fully concur and have included a comprehensive list of acronyms in the revised text. Additionally, to enhance clarity, we have included the full name and definition of each acronym alongside its first occurrence in the text. This will assist readers in comprehending the study without the need to repeatedly refer to the glossary.
(2) You recommended enhancing the descriptive quality of the figure legends to enable readers to discern the key findings from the figures without consulting the text. We have redesigned and refined all charts and legends to ensure they provide adequate information and are more descriptive. Each legend now outlines the experimental conditions, the variables employed, and the primary conclusions, ensuring that the charts themselves sufficiently convey the key findings of the study.
Reviewer #1 (Public review):
Summary:
Intravital microscopy (IVM) is a powerful tool that facilitates live imaging of individual cells over time in vivo in their native 3D tissue environment. Extracting and analysing multi-parametric data from IVM images however is challenging, particularly for researchers with limited programming and image analysis skills. In this work, Rios-Jimenez and Zomer et al have developed a 'zero-code' accessible computational framework (BEHAV3D-Tumour Profiler) designed to facilitate unbiased analysis of IVM data to investigate tumour cell dynamics (via the tool's central 'heterogeneity module') and their interactions with the tumour microenvironment (via the 'large-scale phenotyping' and 'small-scale phenotyping' modules). It is designed as an open-source modular Jupyter Notebook with a user-friendly graphical user interface and can be implemented with Google Colab, facilitating efficient, cloud-based computational analysis at no cost.
To demonstrate the utility of BEHAV3D-TP, they apply the pipeline to timelapse IVM imaging datasets to investigate the in vivo migratory behaviour of fluorescently labelled DMG cells in tumour-bearing mice. Using the tool's 'heterogeneity module' they were able to identify distinct single-cell behavioural patterns (based on multiple parameters such as directionality, speed, displacement, and distance from tumour edge) which was used to group cells into distinct categories (e.g. retreating, invasive, static, erratic). They next applied the framework's 'large-scale phenotyping' and 'small-scale phenotyping' modules to investigate whether the tumour microenvironment (TME) may influence the distinct migratory behaviours identified. To achieve this, they combine TME visualisation in vivo during IVM (using fluorescent probes to label distinct TME components) or ex vivo after IVM (by large-scale imaging of harvested, immunostained tumours) to correlate different tumour behavioural patterns with the composition of the TME. They conclude that this tool has helped reveal links between TME composition (e.g. degree of vascularisation, presence of tumour-associated macrophages) and the invasiveness and directionality of tumour cells, which would have been challenging to identify when analysing single kinetic parameters in isolation.
A key limitation of the pipeline is that it does not overcome the main challenges and bottlenecks associated with processing and extracting quantitative cellular data from timelapse and longitudinal intravital images. This includes correcting breathing-induced movement artifacts, automated registration of longitudinal images taken over days/weeks, and accurate, automated segmentation and tracking of individual cells over time. Indeed, there are currently no standardised computational methods available for IVM data processing and analysis, with most laboratories relying on custom-built solutions or manual methods. This isn't made explicit in the manuscript early on (described below), and the researchers rely on expensive software packages such as IMARIS for image processing and data extraction to feed the required parameters into their pipeline. This limitation unfortunately reduces the likely impact of BEHAV3D-TP on the IVM field.
Nonetheless, this computational framework appears to represent a useful and comparatively user-friendly tool to analyse dynamic multi-parametric data to help identify patterns in cell migratory behaviours, and to assess whether these behaviours might be influenced by neighbouring cells and structures in their microenvironment. When combined with other methods, it, therefore, has the potential to be a valuable addition to a researcher's IVM analysis 'tool-box'.
Strengths:
(1) The figures are clearly presented, and the manuscript is easy to follow.
(2) The pipeline appears to be intuitive and user-friendly for researchers with limited computational expertise. A detailed step-by-step video is also included to support its uptake.
(3) The different computational modules have been tested using a relevant dataset.
(4) All code is open source, and the pipeline can be implemented with Google Colab.
(5) The tool combines multiple dynamic parameters extracted from time-lapse IVM images to identify single-cell behavioural patterns and to cluster cells into distinct groups sharing similar behaviours, and provides avenues to map these onto in vivo or ex vivo imaging data of the tumour microenvironment.
Weaknesses:
(1) As highlighted above, the tool does not facilitate the extraction of quantitative kinetic cellular parameters (e.g. speed, directionality, persistence, and displacement) from intravital images. Indeed, to use the tool researchers must first extract dynamic cellular parameters from their IVM datasets, requiring access to expensive software (e.g. IMARIS as used here) and/or above-average computational expertise to develop and use custom-made open-source solutions. This limitation is not made explicit or discussed in the text.
(2) The number of cells (e.g. per behavioural cluster), and the number of independent mice, represented in each result figure, is not included in the figure legends and are difficult to ascertain from the methods.
(3) The data used to test the pipeline in this manuscript is currently not available, making it difficult to assess its usability. It would be important to include this for researchers to use as a 'training dataset'.
(4) Precisely how the BEHAV3D-TP large-scale phenotyping module can map large-scale spatial phenotyping data generated using LSR-3D imaging data and Cytomap to 3D intravital imaging movies is unclear. Further details in the text and methods would be beneficial to aid understanding.
(5) The analysis provides only preliminary evidence in support of the authors' conclusions on DMG cell migratory behaviours and their relationship with components of the tumour microenvironment. Conclusions should therefore be tempered in the absence of additional experiments and controls.
Author response:
We want to thank the reviewers for their positive and constructive comments on the manuscript. We already addressed some of their concerns and are planning the following revisions to both BEHAV3D-TP and the corresponding manuscript to address the reviewers’ comments. Below, we provide a response to the most significant comments, followed by a detailed, point-by-point response:
(1) We acknowledge the reviewer's suggestion to incorporate open-source segmentation and tracking functionalities, increasing its accessibility to a wider user base; however, these additions fall outside the primary scope of our current work and represent a substantial undertaking in their own right. This topic has been comprehensively explored in other studies (e.g. https://doi.org/10.4049/jimmunol.2100811 ; https://doi.org/10.7554/eLife.60547 ; https://doi.org/10.1016/j.media.2022.102358 ; https://doi.org/10.1038/s41592-024-02295-6), which we will cite in our revised manuscript as indicated in our responses to the reviewers’ comments. Instead, the goal of our manuscript is to provide an analytical framework for processing data generated by existing segmentation and tracking pipelines. In our analyses, we used data processed with Imaris, a commercial software that, despite its limitations, is widely used by the intravital microscopy community due to its user-friendly platform for 3D image visualization and analysis. Nevertheless, to enhance compatibility with tracking data from various pipelines, we have modified our tool to accept data formats, such as those generated by open-source Fiji plugins like TrackMate (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input ). These updates are available in our GitHub repository, and we will describe this feature in the revised manuscript to emphasize compatibility with segmented and tracked data from diverse open-source platforms.
(2) We appreciate the reviewer’s suggestion to incorporate additional features into our analytical pipeline. In response, we have already updated the GitHub repository to allow users to input and select which features (dynamic, morphological, or spatial) they wish to include in the analysis (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#feature-selection ) . In the revised manuscript, we will highlight this new functionality and provide examples using alternative datasets to demonstrate the application of these features.
(3) We appreciate the constructive feedback of reviewers #1 and #2 regarding the statistical analysis and interpretation of the data presented in Figures 3 and 4. We understand the importance of clarity and rigor in data analysis and presentation, and we are committed to addressing the concerns raised in the revised version of the manuscript.
(4) We appreciate Reviewer #1's suggestion regarding the inclusion of demo data, as we believe it would greatly enhance the usability of our pipeline. We acknowledge that this was an oversight on our part. To address this, we have now added demo data to our GitHub repository (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler/tree/BEHAV3D_TP-v2.0/demo_datasets). In the upcoming revised manuscript, we will also ensure to reference this addition. Additionally, we will provide both original and processed IVM movie samples to support users in navigating the complete pipeline effectively.
(5) Finally, we agree with the reviewers to make some small changes to the manuscript based on their feedback.
Below we provide a point-by-point response to the reviewers’ comments, along with proposed revisions.
Reviewer #1:
Comment: A key limitation of the pipeline is that it does not overcome the main challenges and bottlenecks associated with processing and extracting quantitative cellular data from timelapse and longitudinal intravital images. This includes correcting breathing-induced movement artifacts, automated registration of longitudinal images taken over days/weeks, and accurate, automated segmentation and tracking of individual cells over time. Indeed, there are currently no standardised computational methods available for IVM data processing and analysis, with most laboratories relying on custom-built solutions or manual methods. This isn't made explicit in the manuscript early on (described below), and the researchers rely on expensive software packages such as IMARIS for image processing and data extraction to feed the required parameters into their pipeline. This limitation unfortunately reduces the likely impact of BEHAV3D-TP on the IVM field.
As highlighted above, the tool does not facilitate the extraction of quantitative kinetic cellular parameters (e.g. speed, directionality, persistence, and displacement) from intravital images. Indeed, to use the tool researchers must first extract dynamic cellular parameters from their IVM datasets, requiring access to expensive software (e.g. IMARIS as used here) and/or above-average computational expertise to develop and use custom-made open-source solutions. This limitation is not made explicit or discussed in the text.
As mentioned previously, we agree with the reviewer that image processing steps, such as segmentation, tracking, and motion correction, present significant challenges in intravital microscopy (IVM) data processing. While these aspects are being addressed by other researchers, our publication centers on the analysis of acquired data rather than on the image processing itself. Our motivation, as outlined in the manuscript, arises from our own experience: despite the substantial effort invested in image processing, researchers often rely on simplistic analytical approaches, such as averaging single parameters and comparing them across conditions. These approaches tend to overlook potential tumor heterogeneity.
Our work aimed to develop an analytical tool that provides a comprehensive framework for extracting more insights from processed IVM data, with a focus on two key aspects: capturing the heterogeneity of tumor behavior and examining the spatial distribution of these behaviors within the tumor microenvironment. In the revised manuscript, we will clarify the scope of our study, emphasizing its limitations as an analytical tool rather than an image-processing solution. Additionally, we will provide references to relevant literature on available (open-source) software options for image processing (e.g. Diego Ulisse Pizzagalli et al J Immunol (2022); Aby Joseph et al eLife (2020) ;Molina-Moreno M et al Medical Image Analysis (2022); Hidalgo-Cenalmor, I et al, Nat Methods (2024); Ershov. D et al Nat Methods (2022)).
Regarding the reviewer’s comment on our use of Imaris, we acknowledge that Imaris is a costly commercial software. However, based on our experience, it is widely used by the intravital microscopy community due to its user-friendly interface for 3D image visualization and analysis. Despite its limitations in accuracy and the fact that it is not open-source, we believe that including data processed with Imaris will be valuable to the IVM community.
However, to improve compatibility with data from other segmentation and tracking pipelines, we have already updated our tool to support formats generated by open-source Fiji plugins like TrackMate. These updates are available in our GitHub repository, and we will describe this functionality in detail in the revised manuscript to ensure compatibility with segmented and tracked data from various open-source platforms.
Comment: The number of cells (e.g. per behavioural cluster), and the number of independent mice, represented in each result figure, is not included in the figure legends and are difficult to ascertain from the methods.
We appreciate the reviewer's constructive feedback regarding the clarity of the number and type of replicates used in our analyses. In the revised manuscript, we will include detailed information in the figure legends regarding the number of cells (e.g., per behavioral cluster) and the number of independent mice represented in each result figure to ensure transparency.
Comment: The data used to test the pipeline in this manuscript is currently not available, making it difficult to assess its usability. It would be important to include this for researchers to use as a 'training dataset'.
As stated above we acknowledge that this was an oversight on our part and thank the reviewer for pointing this out. To address this, we have now added demo data to our GitHub repository (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler/tree/BEHAV3D_TP-v2.0/demo_datasets). In the upcoming revised manuscript, we will also make sure to reference this addition. Additionally, we intend to provide both original and processed IVM movie samples to support users in navigating the complete pipeline effectively.
Comment: Precisely how the BEHAV3D-TP large-scale phenotyping module can map large-scale spatial phenotyping data generated using LSR-3D imaging data and Cytomap to 3D intravital imaging movies is unclear. Further details in the text and methods would be beneficial to aid understanding.
We appreciate the reviewer’s comment and will provide additional details in the text and methods of the revised manuscript to clarify how the BEHAV3D-TP module maps LSR-3D and Cytomap data to 3D intravital imaging movies.
Comment: The analysis provides only preliminary evidence in support of the authors' conclusions on DMG cell migratory behaviours and their relationship with components of the tumour microenvironment. Conclusions should therefore be tempered in the absence of additional experiments and controls.
We appreciate the reviewer’s comment and acknowledge that our conclusions should be tempered due to the preliminary nature of our evidence. To be able to directly analyze the impact of the brain tumor microenvironment on cancer cell behavior, we will include a new set of analyses in the revised manuscript. Specifically, we will utilize BEHAV3D-TP to analyze existing IVM data from adult gliomas with and without macrophage depletion (Alieva et al, Scientific Reports, 2017; https://doi.org/10.1038/s41598-017-07660-4 ) to evaluate the differences in heterogeneous cell populations under these conditions. Since this analysis pertains to a different tumor type, we will revise our conclusions accordingly and emphasize the necessity for additional experiments and controls to further validate our findings on DMG cell migratory behaviors and their relationship with the tumor microenvironment.
Reviewer #2:
Comment: The strength of democratizing this kind of analysis is undercut by the reliance upon Imaris for segmentation, so it would be nice if this was changed to an open-source option for track generation.
As noted in our previous response to Reviewer #1, we would like to point out that although Imaris is a commercial software, it is widely used in the intravital microscopy (IVM) community due to its user-friendly interface. One of its key advantages, which we also utilized, is semi-automated data tracking that allows for manual corrections in 3D—a process that can be more challenging in other open-source software with less effective data visualization.
However, we recognize that enhancing our pipeline's compatibility with open-source options is important. To this end, we have already updated our tool to support data formats generated by open-source Fiji plugins like TrackMate, improving compatibility with various segmentation and tracking pipelines (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input ). We will describe these updates in the revised manuscript to clarify our study's scope and the available image processing options.
Comment: The main issue is with the interpretation of the biological data in Figure 3 where ANOVA was used to analyse the proportional distribution of different clusters. Firstly the n is not listed so it is unclear if this represents an n of 3 where each mouse is an individual or whether each track is being treated as a test unit. If the latter this is seriously flawed as these tracks can't be treated as independent. Also, a more appropriate test would be something like a Chi-squared test or Fisher's exact test. Also, no error bars are included on the stacked bar graphs making interpretation impossible. Ultimately this is severely flawed and also appears to show very small differences which may be statistically different but may not represent biologically important findings. This would need further study.
We appreciate the reviewer’s insightful comments regarding the interpretation of the biological data in Figure 3. To clarify, each mouse serves as an independent unit in this analysis. We believe that ANOVA is the appropriate test for comparing the proportions of different behavioral signatures across the tumor microenvironment (TME) regions identified by large-scale phenotyping. However, we acknowledge that using a stacked bar plot may have been misleading. While a Chi-squared test could show differences in the distribution of behavioral signatures, it would not indicate which specific signatures are responsible for those differences. Therefore, in the revised manuscript, we will retain the ANOVA analysis but will represent the proportions using a bar chart that clearly illustrates multiple conditions for each behavioral cluster. We also appreciate the reviewer’s concern regarding the transparency of our data. In the revised manuscript, we will include the number of replicates for all figures to enhance clarity and understanding.
Comment: Figure 4 has similar statistical issues in that the n is not listed and, again, it is unclear whether they are treating each cell track as independent which, again, would be inappropriate. The best practice for this type of data would be the use of super plots as outlined in Lord et al. (2020) JCI - SuperPlots: Communicating reproducibility and variability in cell biology.
We appreciate the reviewer’s comments and suggestions regarding Figure 4. In the revised manuscript, we will clarify the number of replicates used and our approach to treating cell tracks as independent units. We will implement super-plots where appropriate, to enhance the communication of reproducibility and variability in our data.
Comment: The main issue that this raises is that the large-scale phenotyping module and the heterogeneity module appear designed to produce these statistical analyses that are used in these figures and, if they are based on the assumption that each track is independent, then this will produce inappropriate analyses as a default.
We appreciate the reviewer’s comment, though we find ourselves unsure about the specific concern being raised. To clarify, each mouse is treated as an independent unit in our analyses. For each large-scale phenotyping region, we measure the proportion of tumor cells displaying a specific behavioral phenotype independently for each mouse. These proportions are then used for statistical analysis. We hope this explanation provides clarity, and we will adjust the manuscript to better convey this methodology.
Reviewer #3:
Comment: The most challenging task of analyzing 3D time-lapse imaging data is to accurately segment and track the individual cells in 3D over a long time duration. BEHAV3D Tumor Profiler did not provide any new advancement in this regard, and instead relies on commercial software, Imaris, for this critical step. Imaris is known to have a very high error rate when used for analyzing 3D time-lapse data. In the Methods section, the authors themselves stated that "Tumor cell tracks were manually corrected to ensure accurate tracking". Based on our own experience of using Imaris, such manual correction is tedious and often required for every time step of the movie. Therefore, Imaris is not a satisfactory tool for analyzing 3D time-lapse data. Moreover, Imaris is expensive and many research labs probably can't afford to buy it. The fact that BEHAV3D Tumor Profiler critically depends on the faulty ImarisTrack module makes it unclear whether the BEHAV3D tool or the results are reliable.
If the authors want to "democratize the analysis of heterogeneous cancer cell behaviors", they should perform image segmentation and tracking using open-source codes (e.g., Cellpose, Stardisk & 3DCellTracker) and not rely on the expensive and inaccurate ImarisTrack Module for the image analysis step of BEHAV3D.
We appreciate the reviewer’s comments on the challenges of segmenting and tracking individual cells in 3D time-lapse imaging data. As mentioned previously, our primary focus is to develop an analytical tool for comprehensive data analysis rather than developing tools for image processing. To enhance accessibility, we have updated our tool to support data formats from open-source Fiji plugins, such as TrackMate, which will benefit users without access to commercial software (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input ).
While we recognize the limitations of Imaris, it remains widely used in the intravital microscopy community due to its user-friendly interface for 3D visualization and semi-automated segmentation capabilities. Since no perfect tracking method currently exist, we utilized Imaris for its ability to allow manual corrections of faulty tracks, ensuring the reliability of our results. This approach was the best available option when we began our analysis, allowing us to obtain accurate results efficiently.
In the revised manuscript, we will clarify our methodology and provide information on both Imaris and alternative processing options to strengthen the reliability of our findings.
Comment: The authors developed a "Heterogeneity module" to extract distinctive tumor migratory phenotypes from the cell tracks quantified by Imaris. The cell tracks of the individual tumor cells are all quite short, indicating relatively low motility of the tumor cells. It's unclear whether such short migratory tracks are sufficient to warrant the PCA analysis to identify the 7 distinctive migratory phenotypes shown in Figure 2d. It's also unclear whether these 7 migratory phenotypes correspond to unique functional phenotypes.
For the 7 distinctive motility clusters, the authors should provide a more detailed analysis of the differences between them. It's unclear whether the difference in retreating, slow retreating, erratic, static, slow, slow invading, and invading correspond to functional difference of the tumor cells.
While some tumor cells exhibit limited motility, indicated by short tracks, others demonstrate significant migratory capabilities. This variability in tumor cell behavior is a central focus of our analysis, and our tool is specifically designed to identify and distinguish these differences. Our PCA analysis effectively captures this variability, as illustrated in Figure 2 d-f. It differentiates between cells exhibiting varying degrees of migratory behavior, including both highly migratory and less migratory phenotypes, as well as their directionality relative to the tumor core and the persistence of their movements. Thus, we believe that our approach provides valuable insights into the distinct migratory phenotypes within the tumor microenvironment. We will clarify these aspects further in the revised manuscript to enhance the reader's understanding of our findings.
While our current manuscript does not provide explicit evidence linking each motility cluster to functional differences among the tumor cells, it is important to note that the state of the field supports the idea that cell dynamics can predict cell states and phenotypes. Research conducted by ourselves (Dekkers, Alieva et al., Nat Biotech, 2023) and others, such as Craiciuc et al. (Nature, 2022) and Freckmann et al. (Nat Comm, 2022) has shown that variations in cell motility patterns are indicative of underlying functional characteristics. For instance, cell morphodynamic features have been shown to reflect differences in cell types, T cell targeting states, tumor metastatic potential, and drug resistance states. In the revised manuscript, we will reference relevant studies to underscore the biological significance of these behaviors. By doing so, we hope to clarify the potential implications of our findings and strengthen the overall narrative of our research.
Comment: Using only motility to classify tumor cell behaviours in the tumor microenvironment (TME) is probably not sufficient to capture the tumor cell difference. There are also other non-tumor cell types in the TME. If the authors aim to develop a computational tool that can elucidate tumor cell behaviors in the TME, they should consider other tumor cell features, e.g., morphology, proliferation state, and tumor cell interaction with other cell types, e.g., fibroblasts and distinct immune cells.
The authors should expand the scale of tumor behavior features to classify the tumor phenotype clusters, e.g., to include tumor morphology, proliferation state, and tumor cell interaction with other TME cell types.
We believe that using dynamic features alone is sufficient to capture differences in tumor behavior, as demonstrated by our results in Figure 2. However, we appreciate the reviewer’s suggestion to consider additional features, such as cell morphology and interactions with other cell types, to finetune our analyses. To this end, we have adapted our pipeline to be compatible with various features present in the data (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler/tree/BEHAV3D_TP-v2.0?tab=readme-ov-file#feature-selection ). We will emphasize this in the revised manuscript. However, we would like to point out that not all features may provide informative insights and that a wide range of features can instead introduce biologically irrelevant noise, making interpretation more challenging. For instance, in 3D microscopy, the z-axis resolution is typically lower, which can lead to artifacts like elongation in that direction. Adding morphological features that capture this may skew the analysis. Therefore, we believe that incorporating additional features should be approached with caution. We will clarify these considerations in the revised manuscript to better guide users in utilizing our computational tool effectively. We will also reference the use of unbiased feature selection techniques, such as bootstrapping methods, to identify biologically relevant features based on the conditions provided (D.G. Aragones et al, Computers in Biology and Medicine (2024)).
Comment: The authors have already published two papers on BEHAV3D [Alieva M et al. Nat Protoc. 2024 Jul;19(7): 2052-2084; Dekkers JF, et al. Nat Biotechnol. 2023 Jan;41(1):60-69]. Although the previous two papers used BEHAV3D to analyze T cells, the basic pipeline and computational steps are similar, in particular regarding cell segmentation and tracking. The addition of a "Heterogeneity module" based on PCA analysis does not make a significant advancement in terms of image analysis and quantification.
We want to emphasize that we have no intention of duplicating our previous publications. In this manuscript, we have consistently cited our foundational papers, where BEHAV3D was first developed for T cell migratory analysis in in vitro settings. In the introduction, we clearly state that our earlier work inspired us to adopt a similar approach for analyzing cell behavior in intravital microscopy (IVM) data, addressing the specific needs and complexities of analyzing tumor cell behaviors in the tumor microenvironment.
Importantly, our new work provides several key advancements: 1) a pipeline specifically adapted for intravital microscopy (IVM) data; 2) integration of spatial characteristics from both large-scale and small-scale phenotyping; and 3) a zero-code approach designed to empower researchers without coding skills to effectively utilize the tool. We believe that these enhancements represent meaningful progress in the analysis of cell behaviors within the tumor microenvironment which will be valuable for the IVM community. We will ensure that these points are clearly articulated in the revised manuscript.
Notes 1 Joshua Klick and Anya Stockburger, “Experimental CPI for lower and higher income households,” Working Paper 537 (U.S. Bureau of Labor Statistics, March 8, 2021), https://www.bls.gov/osmr/research-papers/2021/pdf/ec210030.pdf; and Klick and Stockburger, “Inflation experiences for lower and higher income households,” Spotlight on Statistics (U.S. Bureau of Labor Statistics, December 2022), https://www.bls.gov/spotlight/2022/inflation-experiences-for-lower-and-higher-income-households/home.htm.2 All references to income in this article refer to equivalized income, unless otherwise noted.3 For more information on these research indexes, see “R-CPI-I and R-C-CPI-I homepage,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/research-series/r-cpi-i.htm.4 Much of the literature also considers differences in household composition, often assuming, for instance, that children “need” less than adults. See, for example, OECD Handbook on the Compilation of Household Distributional Results on Income, Consumption and Saving in Line with National Accounts Totals (Paris: Organisation for Economic Co-operation and Development, 2020), https://www.oecd.org/sdd/na/EG-DNA-Handbook.pdf. In contrast, other work equivalizes income by using a single parameter, such as the square root of household size. See, for example, Dennis Fixler, Marina Gindelsky, and David Johnson, “Measuring inequality in the national accounts,” Working Paper 2020-3 (U.S. Bureau of Economic Analysis, December 2020), https://www.bea.gov/system/files/papers/measuring-inequality-in-the-national-accounts_0.pdf; and “Distribution of Personal Consumption Expenditures,” Consumer Expenditure Surveys (U.S. Bureau of Labor Statistics), https://www.bls.gov/cex/pce-ce-distributions.htm.5 Index results are not seasonally adjusted.6 Thesia I. Garner, David S. Johnson, and Mary F. Kokoski, “An experimental Consumer Price Index for the poor,” Monthly Labor Review, September 1996, https://www.bls.gov/opub/mlr/1996/09/art5full.pdf.7 Klick and Stockburger, “Experimental CPI for lower and higher income households.”8 Technical Recommendations for the Consumer Inflation Measure Best Suited for Conducting Annual Adjustments to the Official Poverty Measure (Office of Management and Budget, June 16, 2021), https://www.bls.gov/evaluation/technical-recommendations-for-the-consumer-inflation-measure-best-suited-for-conducting-annual-adjustments-to-the-official-poverty-measure.pdf.9 Daniel E. Sichel and Christopher Mackie, eds., Modernizing the Consumer Price Index for the 21st Century (Washington, DC: The National Academies Press, 2022), https://doi.org/10.17226/26485.10 Examples include Greg Kaplan and Sam Schulhofer-Wohl, “Inflation at the household level,” Working Paper 2017-13 (Federal Reserve Bank of Chicago, 2017), https://www.chicagofed.org/publications/working-papers/2017/wp2017-13; Xavier Jaravel, “The unequal gains from product innovations: evidence from the U.S. retail sector,” The Quarterly Journal of Economics, vol. 134, no. 2, May 2019, pp. 715–783; and Georg Strasser, Teresa Messner, Fabio Rumler, and Miguel Ampudia, “Inflation heterogeneity at the household level,” Occasional Paper 325 (European Central Bank, 2023), https://www.ecb.europa.eu/pub/pdf/scpops/ecb.op325~7422ebe3c1.en.pdf?63924885a8f1c0e86c5e55ca344811c7.11 Because the U.S. Bureau of Labor Statistics (BLS) began imputing missing income values in 2004, income data from 2003 are not comparable. For this research, we used 2004 expenditures to calculate the spending shares used in index calculations for 2006 and 2007. The remaining spending shares are based on 2 years of expenditures (through index period 2022), consistent with Consumer Price Index (CPI) methodology. Since 2023, CPI weights have been revised annually, with index calculation using a reference-year lag of 2 years. For example, the 2023 CPI for All Urban Consumers (CPI-U) uses expenditure weights for reference year 2021.12 Nearly half of income values are imputed for the urban population in the Diary and Interview surveys. For more information on income imputation, see “CE income imputation explanatory note,” Consumer Expenditure Surveys (U.S. Bureau of Labor Statistics), https://www.bls.gov/cex/csximpute.htm. For comparison, 45 percent of income values are imputed in the Current Population Survey (CPS) Annual Social and Economic Supplement; see Charles Hokayem, Trivellore Raghunathan, and Jonathan Rothbaum, “Match bias or nonignorable nonresponse? Improved imputation and administrative data in the CPS ASEC,” Journal of Survey Statistics and Methodology, vol. 10, no. 1, February 2022, https://academic.oup.com/jssam/article-abstract/10/1/81/5943180?redirectedFrom=fulltext.13 There is a large body of literature using equivalence scales to adjust household income in order to account for different characteristics across households. See, for example, Angela Daley, Thesia I. Garner, Shelley Phipps, and Eva Sierminska, “Differences across place and time in household expenditure patterns: implications for the estimation of equivalence scales,” Working Paper 520 (U.S. Bureau of Labor Statistics, November 2019), https://www.bls.gov/osmr/research-papers/2020/pdf/ec200010.pdf; and Richard V. Reeves and Christopher Pulliam, “Tipping the balance: why equivalence scales matter more than you think” (Washington, DC: The Brookings Institution, April 17, 2019), https://www.brookings.edu/blog/up-front/2019/04/17/whats-in-an-equivalence-scale.14 See Klick and Stockburger, “Experimental CPI for lower and higher income households;” and Klick and Stockburger, “Inflation experiences for lower and higher income households.”15 BLS calibrates Consumer Expenditure Surveys (CE) sample weights to the CPS in order to control for demographic characteristics such as age, race, owner or renter, geography, and Hispanic ethnicity; see section on calculation methodology in “Consumer expenditures and income: calculation,” Handbook of Methods (U.S. Bureau of Labor Statistics, last modified September 12, 2022), https://www.bls.gov/opub/hom/cex/calculation.htm#calculation-methodology. Weighting methods also control for subsampling, geography, household size, number of contacts, and average gross income for a household’s ZIP Code. The use of sample weights reflects known urban population totals and is particularly relevant in comparisons of owners and renters, ensuring that weights are equivalent across quintiles and comparable to CE’s weighted ranking of the total population. See “Table 1101. Quintiles of income before taxes: annual expenditure means, shares, standard errors, and coefficients of variation, Consumer Expenditure Surveys, 2021” (U.S. Bureau of Labor Statistics, 2022), https://www.bls.gov/cex/tables/calendar-year/mean-item-share-average-standard-error/cu-income-quintiles-before-taxes-2021.pdf.For information on the CE income-distribution methodology, see Geoffrey Paulin, Sally Reyes-Morales, and Jonathan Fisher, “User’s guide to income imputation in the CE” (U.S. Bureau of Labor Statistics, July 31, 2018), https://www.bls.gov/cex/csxguide.pdf. The CE program creates an income-ranking variable based on before-tax income as a distribution over the interval (0,1], so that weights are relatively equally distributed across defined quantiles. The income-ranking variable is created by sorting by income and a random number (used to break ties for consumer units reporting the same income) in ascending order for each collection quarter and survey source.16 The CPI income-distribution methodology includes sorting by consumer-unit identification number prior to random number assignment.17 For details, see David C. Swanson, Sharon K. Hauge, and Mary Lynn Schmidt, “Evaluation of composite estimation methods for cost weights in the CPI” (U.S. Bureau of Labor Statistics, 1999), https://www.bls.gov/osmr/research-papers/1999/pdf/st990050.pdf.18 For details, see Robert Cage, John Greenlees, and Patrick Jackman, “Introducing the Chained Consumer Price Index” (U.S. Bureau of Labor Statistics, May 2003), https://www.bls.gov/cpi/additional-resources/chained-cpi-introduction.pdf.19 For a description of nonsampled items, see “Changing the item structure of the Consumer Price Index,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/additional-resources/revision-1998-item-structure.htm.20 See “Measuring price change in the CPI: medical care,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/factsheets/medical-care.htm.21 Weight calculation is described in greater detail in “Consumer Price Index: calculation,” Handbook of Methods (U.S. Bureau of Labor Statistics, last modified September 6, 2023), https://www.bls.gov/opub/hom/cpi/calculation.htm.22 See, for example, “Worries about affording essentials in a high-inflation environment” (Paris: Organisation for Economic Co-operation and Development, July 2023), https://www.oecd.org/social/soc/OECD2023-RTM2022-PolicyBrief-Inflation.pdf.23 For more information on these broad classifications, see “CPI item aggregation,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/additional-resources/cpi-item-aggregation.htm.24 See footnote 1 in “Table 7. Consumer Price Index for All Urban Consumers (CPI-U): U.S. city average, by expenditure category, 12-month analysis table,” Economic News Release (U.S. Bureau of Labor Statistics), https://www.bls.gov/news.release/cpi.t07.htm.25 For item definitions, see “Appendix 7. Consumer Price Index items by publication level,” Consumer Price Index (U.S. Bureau of Labor Statistics), https://www.bls.gov/cpi/additional-resources/index-publication-level.htm.26 The gap effects are evaluated as the difference between the first-quintile effect and the fifth-quintile effect at the item level. Then, the gap effects are renormalized to determine the corresponding proportional contribution to the all-items gap.27 See Cage, Greenlees, and Jackman, “Introducing the Chained Consumer Price Index.”28 To minimize variance across basic item-area monthly expenditures, we smooth monthly weights by using a ratio allocation of the 12-month moving average of item shares. To reflect the average weight for the current and previous periods, we use monthly weights as a 2-month moving-average shares.29 Because CE data are available with a lag, we could not calculate 2023 indexes at the time of our analysis.30 Index revisions based on the constant-elasticity-of-substitution formula were processed as update weights revised in January of even years. However, chaining was processed annually (to the final Chained CPI for December of the prior year) instead of quarterly (as occurs in production).31 See, for example, Kaplan and Schulhofer-Wohl, “Inflation at the household level;” and Jaravel, “The unequal gains from product innovations: evidence from the U.S. retail sector.”32 See Daryl Larsen and Raven Molloy, “Differences in rent growth by income 1985–2019 and implications for real income inequality,” FEDS Notes (Board of Governors of the Federal Reserve System, November 5, 2021), https://www.federalreserve.gov/econres/notes/feds-notes/differences-in-rent-growth-by-income-1985-2019-and-implications-for-real-income-inequality-20211105.html.33 See Fixler, Gindelsky, and Johnson, “Measuring inequality in the national accounts.” See also “Distribution of Personal Consumption Expenditures,” Consumer Expenditure Surveys (U.S. Bureau of Labor Statistics), https://www.bls.gov/cex/pce-ce-distributions.htm. About the Author Joshua Klick cpi_info@bls.gov Joshua Klick is a senior economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics. Anya Stockburger cpi_info@bls.gov Anya Stockburger is a supervisory economist in the Office of Prices and Living Conditions, U.S. Bureau of Labor Statistics. Related Content Related Articles Measuring total-premium inflation for health insurance in the Consumer Price Index, Monthly Labor Review, April 2024. Two plus two really does equal four: simulating official BLS gasoline price measures, Monthly Labor Review, June 2023. Automotive dealerships 2019–22: dealer markup increases drive new-vehicle consumer inflation, Monthly Labor Review, April 2023. The impact of changing consumer expenditure patters at the onset of the COVID-19 pandemic on measures of consumer inflation, Monthly Labor Review, April 2022. An experimental Consumer Price Index for the poor, Monthly Labor Review, September 1996. 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The article does have sources sited. The article uses APA citations and uses data sources like surveys. The sources are mainly secondary data.
Here’s most of what I’ve used Claude Artifacts for in the past seven days. I’ve provided prompts or a full transcript for nearly all of them. URL to Markdown with Jina Reader SQLite in WASM demo Extract URLs Clipboard viewer Pyodide REPL Photo Camera Settings Simulator LLM pricing calculator YAML to JSON converter OpenAI Audio QR Code Decoder Image Converter and Page Downloader HTML Entity Escaper text-wrap-balance-nav ARES Phonetic Alphabet Converter
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In Belle Lu's essay, formal analysis clarifies how Javier Zamora’s stylistic choices such as fragmented sentences, enjambment, and code-switching to express his trauma and dual identity. By examining these elements, Lu shows how Zamora’s structure and style reflect his childhood memories and his complex sense of belonging, linking his poetic form directly to themes of identity and resilience.
In Belle Lu's essay, "Not the Only Nine-Year-Old," she uses several primary texts from Javier Zamora's poetry collection Unaccompanied. Specific poems mentioned include “June 10, 1999,” “Citizenship,” “Dancing in Buses,” “The Pier of La Herradura,” “‘Ponele Queso Bicho’ Means Put Cheese on It Kid,” “To Abuelita Neli,” “Disappeared,” “ARENA,” and “To President-Elect.”
Lu arranges these texts in a way that builds a clear progression in her analysis of Zamora’s work. She starts with poems that reflect his childhood perspective, using fragmented sentences and lack of punctuation to convey his memories and trauma. As the essay moves forward, she discusses poems that incorporate nature imagery and code-switching, which reveal his complex sense of identity and connection to his homeland. Toward the end, Lu includes politically focused poems to show how Zamora links his personal experiences to larger social and political issues. This order allows Lu to move from personal memory to broader political context, showing how these elements work together in Zamora’s poetry
The CIA and DIA decided they should investigate and know as much about it as possible.
"theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it"
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From Wikipedia, the free encyclopedia
For other pages with a similar name, see Astrolabe (disambiguation). Not to be confused with Cosmolabe.
North African, 9th century AD, Planispheric Astrolabe. Khalili Collection.
A modern astrolabe made in Tabriz, Iran in 2013.
An astrolabe (Greek: ἀστρολάβος astrolábos, 'star-taker'; Arabic: ٱلأَسْطُرلاب al-Asṭurlāb; Persian: ستارهیاب Setāreyāb) is an astronomical instrument dating to ancient times. It serves as a star chart and physical model of visible heavenly bodies. Its various functions also make it an elaborate inclinometer and an analog calculation device capable of working out several kinds of problems in astronomy. In its simplest form it is a metal disc with a pattern of wires, cutouts, and perforations that allows a user to calculate astronomical positions precisely. It is able to measure the altitude above the horizon of a celestial body, day or night; it can be used to identify stars or planets, to determine local latitude given local time (and vice versa), to survey, or to triangulate. It was used in classical antiquity, the Islamic Golden Age, the European Middle Ages and the Age of Discovery for all these purposes.
The astrolabe, which is a precursor to the sextant,^[1]^ is effective for determining latitude on land or calm seas. Although it is less reliable on the heaving deck of a ship in rough seas, the mariner's astrolabe was developed to solve that problem.
16th-century woodcut of measurement of a building's height with an astrolabe
The 10th-century astronomer ʿAbd al-Raḥmān al-Ṣūfī wrote a massive text of 386 chapters on the astrolabe, which reportedly described more than 1,000 applications for the astrolabe's various functions.^[2]^ These ranged from the astrological, the astronomical and the religious, to navigation, seasonal and daily time-keeping, and tide tables. At the time of their use, astrology was widely considered as much of a serious science as astronomy, and study of the two went hand-in-hand. The astronomical interest varied between folk astronomy (of the pre-Islamic tradition in Arabia) which was concerned with celestial and seasonal observations, and mathematical astronomy, which would inform intellectual practices and precise calculations based on astronomical observations. In regard to the astrolabe's religious function, the demands of Islamic prayer times were to be astronomically determined to ensure precise daily timings, and the qibla, the direction of Mecca towards which Muslims must pray, could also be determined by this device. In addition to this, the lunar calendar that was informed by the calculations of the astrolabe was of great significance to the religion of Islam, given that it determines the dates of important religious observances such as Ramadan.^[citation needed]^
The Oxford English Dictionary gives the translation "star-taker" for the English word astrolabe and traces it through medieval Latin to the Greek word ἀστρολάβος : astrolábos,^[3]^^[4]^ from ἄστρον : astron "star" and λαμβάνειν : lambanein "to take".^[5]^
In the medieval Islamic world the Arabic word al-Asturlāb (i.e., astrolabe) was given various etymologies. In Arabic texts, the word is translated as ākhidhu al-Nujūm (Arabic: آخِذُ ٱلنُّجُومْ, lit. 'star-taker'), a direct translation of the Greek word.^[6]^
Al-Biruni quotes and criticises medieval scientist Hamza al-Isfahani who stated:^[6]^ "asturlab is an arabisation of this Persian phrase" (sitara yab, meaning "taker of the stars").^[7]^ In medieval Islamic sources, there is also a folk etymology of the word as "lines of lab", where "Lab" refers to a certain son of Idris (Enoch). This etymology is mentioned by a 10th-century scientist named al-Qummi but rejected by al-Khwarizmi.^[8]^
An astrolabe is essentially a plane (two-dimensional) version of an armillary sphere, which had already been invented in the Hellenistic period and probably been used by Hipparchus to produce his star catalogue. Theon of Alexandria (c. 335 -- c. 405) wrote a detailed treatise on the astrolabe.^[9]^ The invention of the plane astrolabe is sometimes wrongly attributed to Theon's daughter Hypatia (born c. 350--370; died AD 415),^[10]^^[11]^^[12]^^[13]^ but it's known to have been used much earlier.^[11]^^[12]^^[13]^ The misattribution comes from a misinterpretation of a statement in a letter written by Hypatia's pupil Synesius (c. 373 -- c. 414),^[11]^^[12]^^[13]^ which mentions that Hypatia had taught him how to construct a plane astrolabe, but does not say that she invented it.^[11]^^[12]^^[13]^ Lewis argues that Ptolemy used an astrolabe to make the astronomical observations recorded in the Tetrabiblos.^[9]^ However, Emilie Savage-Smith notes "there is no convincing evidence that Ptolemy or any of his predecessors knew about the planispheric astrolabe".^[14]^ In chapter 5,1 of the Almagest, Ptolemy describes the construction of an armillary sphere, and it is usually assumed that this was the instrument he used.
Astrolabes continued to be used in the Byzantine Empire. Christian philosopher John Philoponus wrote a treatise (c. 550) on the astrolabe in Greek, which is the earliest extant treatise on the instrument.^[a]^ Mesopotamian bishop Severus Sebokht also wrote a treatise on the astrolabe in the Syriac language during the mid-7th century.^[b]^ Sebokht refers to the astrolabe as being made of brass in the introduction of his treatise, indicating that metal astrolabes were known in the Christian East well before they were developed in the Islamic world or in the Latin West.^[15]^
Astrolabes were further developed in the medieval Islamic world, where Muslim astronomers introduced angular scales to the design,^[16]^ adding circles indicating azimuths on the horizon.^[17]^ It was widely used throughout the Muslim world, chiefly as an aid to navigation and as a way of finding the Qibla, the direction of Mecca. Eighth-century mathematician Muhammad al-Fazari is the first person credited with building the astrolabe in the Islamic world.^[18]^
The mathematical background was established by Muslim astronomer Albatenius in his treatise Kitab az-Zij (c. AD 920), which was translated into Latin by Plato Tiburtinus (De Motu Stellarum). The earliest surviving astrolabe is dated AH 315 (AD 927--928). In the Islamic world, astrolabes were used to find the times of sunrise and the rising of fixed stars, to help schedule morning prayers (salat). In the 10th century, al-Sufi first described over 1,000 different uses of an astrolabe, in areas as diverse as astronomy, astrology, navigation, surveying, timekeeping, prayer, Salat, Qibla, etc.^[19]^^[20]^
An Arab astrolabe from 1208
The spherical astrolabe was a variation of both the astrolabe and the armillary sphere, invented during the Middle Ages by astronomers and inventors in the Islamic world.^[c]^ The earliest description of the spherical astrolabe dates to Al-Nayrizi (fl. 892--902). In the 12th century, Sharaf al-Dīn al-Tūsī invented the linear astrolabe, sometimes called the "staff of al-Tusi", which was "a simple wooden rod with graduated markings but without sights. It was furnished with a plumb line and a double chord for making angular measurements and bore a perforated pointer".^[21]^ The geared mechanical astrolabe was invented by Abi Bakr of Isfahan in 1235.^[22]^
The first known metal astrolabe in Western Europe is the Destombes astrolabe made from brass in the eleventh century in Portugal.^[23]^^[24]^ Metal astrolabes avoided the warping that large wooden ones were prone to, allowing the construction of larger and therefore more accurate instruments. Metal astrolabes were heavier than wooden instruments of the same size, making it difficult to use them in navigation.^[25]^
Spherical astrolabe
A depiction of Hermann of Reichenau with an astrolabe in a 13th-century manuscript by Matthew Paris
Herman Contractus of Reichenau Abbey, examined the use of the astrolabe in Mensura Astrolai during the 11th century.^[26]^ Peter of Maricourt wrote a treatise on the construction and use of a universal astrolabe in the last half of the 13th century entitled Nova compositio astrolabii particularis. Universal astrolabes can be found at the History of Science Museum in Oxford.^[27]^ David A. King, historian of Islamic instrumentation, describes the universal astrolobe designed by Ibn al-Sarraj of Aleppo (aka Ahmad bin Abi Bakr; fl. 1328) as "the most sophisticated astronomical instrument from the entire Medieval and Renaissance periods".^[28]^
English author Geoffrey Chaucer (c. 1343--1400) compiled A Treatise on the Astrolabe for his son, mainly based on a work by Messahalla or Ibn al-Saffar.^[29]^^[30]^ The same source was translated by French astronomer and astrologer Pélerin de Prusse and others. The first printed book on the astrolabe was Composition and Use of Astrolabe by Christian of Prachatice, also using Messahalla, but relatively original.
Front of an Indian astrolabe now kept at the Royal Museum of Scotland at Edinburgh.
In 1370, the first Indian treatise on the astrolabe was written by the Jain astronomer Mahendra Suri, titled Yantrarāja.^[31]^
A simplified astrolabe, known as a balesilha, was used by sailors to get an accurate reading of latitude while at sea. The use of the balesilha was promoted by Prince Henry (1394--1460) while navigating for Portugal.^[32]^
The astrolabe was almost certainly first brought north of the Pyrenees by Gerbert of Aurillac (future Pope Sylvester II), where it was integrated into the quadrivium at the school in Reims, France, sometime before the turn of the 11th century.^[33]^ In the 15th century, French instrument maker Jean Fusoris (c. 1365--1436) also started remaking and selling astrolabes in his shop in Paris, along with portable sundials and other popular scientific devices of the day.
Astronomical Instrument Detail by Ieremias Palladas 1612
Thirteen of his astrolabes survive to this day.^[34]^ One more special example of craftsmanship in early 15th-century Europe is the astrolabe designed by Antonius de Pacento and made by Dominicus de Lanzano, dated 1420.^[35]^
In the 16th century, Johannes Stöffler published Elucidatio fabricae ususque astrolabii, a manual of the construction and use of the astrolabe. Four identical 16th-century astrolabes made by Georg Hartmann provide some of the earliest evidence for batch production by division of labor. In 1612, Greek painter Ieremias Palladas incorporated a sophisticated astrolabe in his painting depicting Catherine of Alexandria. The painting was entitled Catherine of Alexandria and featured a device called the System of the Universe (Σύστημα τοῦ Παντός). The device featured the planets with the names in Greek: Selene (Moon), Hermes (Mercury), Aphrodite (Venus), Helios (Sun), Ares (Mars), Zeus (Jupiter), and Chronos (Saturn). The device also featured celestial spheres following the Ptolemaic model and Earth was depicted as a blue sphere with circles of geographic coordinates. A complex line representing the axis of the Earth covered the entire instrument.^[36]^
Medieval astrolabes
A treatise explaining the importance of the astrolabe by Nasir al-Din al-Tusi, Persian scientist
Astrolabe of Jean Fusoris, made in Paris, 1400
An 18th-century Persian astrolabe
Disassembled 18th-century astrolabe
.jpg)
Exploded view of an astrolabe
Animation showing how celestial and geographic coordinates are mapped on an astrolabe's tympan through a stereographic projection. Hypothetical tympan (40° north latitude) of a 16th-century European planispheric astrolabe.
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Astrolabe manual from the Alfonso X of Castile work Libros del saber de astronomía, 1276.
![A page from the 1575 book "Astrolabium" depicting an astrolabe. Masha'Allah Public Library Bruges [nl] Ms. 522](https://upload.wikimedia.org/wikipedia/commons/thumb/b/b6/Astrolabium_Masha%27allah_Public_Library_Brugge_Ms._522.tif/lossy-page1-127px-Astrolabium_Masha%27allah_Public_Library_Brugge_Ms._522.tif.jpg)
A page from the 1575 book "Astrolabium" depicting an astrolabe. Masha'Allah Public Library Bruges [nl] Ms. 522
Amerigo Vespucci observing the Southern Cross by looking over the top of an armillary sphere bizarrely held from the top as if it were an astrolabe; however, an astrolabe cannot be used by looking over its top. The page inexplicably contains the word astrolabium. By Jan Collaert II. Museum Plantin-Moretus, Antwerp, Belgium.
Mechanical astronomical clocks were initially influenced by the astrolabe; they could be seen in many ways as clockwork astrolabes designed to produce a continual display of the current position of the sun, stars, and planets. For example, Richard of Wallingford's clock (c. 1330) consisted essentially of a star map rotating behind a fixed rete, similar to that of an astrolabe.^[37]^
Many astronomical clocks use an astrolabe-style display, such as the famous clock at Prague, adopting a stereographic projection (see below) of the ecliptic plane. In recent times, astrolabe watches have become popular. For example, Swiss watchmaker Ludwig Oechslin designed and built an astrolabe wristwatch in conjunction with Ulysse Nardin in 1985.^[38]^ Dutch watchmaker Christaan van der Klauuw also manufactures astrolabe watches today.^[39]^
An astrolabe consists of a disk, called the mater (mother), which is deep enough to hold one or more flat plates called tympans, or climates. A tympan is made for a specific latitude and is engraved with a stereographic projection of circles denoting azimuth and altitude and representing the portion of the celestial sphere above the local horizon. The rim of the mater is typically graduated into hours of time, degrees of arc, or both.^[40]^
Above the mater and tympan, the rete, a framework bearing a projection of the ecliptic plane and several pointers indicating the positions of the brightest stars, is free to rotate. These pointers are often just simple points, but depending on the skill of the craftsman can be very elaborate and artistic. There are examples of astrolabes with artistic pointers in the shape of balls, stars, snakes, hands, dogs' heads, and leaves, among others.^[40]^ The names of the indicated stars were often engraved on the pointers in Arabic or Latin.^[41]^ Some astrolabes have a narrow rule or label which rotates over the rete, and may be marked with a scale of declinations.
The rete, representing the sky, functions as a star chart. When it is rotated, the stars and the ecliptic move over the projection of the coordinates on the tympan. One complete rotation corresponds to the passage of a day. The astrolabe is, therefore, a predecessor of the modern planisphere.
On the back of the mater, there is often engraved a number of scales that are useful in the astrolabe's various applications. These vary from designer to designer, but might include curves for time conversions, a calendar for converting the day of the month to the sun's position on the ecliptic, trigonometric scales, and graduation of 360 degrees around the back edge. The alidade is attached to the back face. An alidade can be seen in the lower right illustration of the Persian astrolabe above. When the astrolabe is held vertically, the alidade can be rotated and the sun or a star sighted along its length, so that its altitude in degrees can be read ("taken") from the graduated edge of the astrolabe; hence the word's Greek roots: "astron" (ἄστρον) = star + "lab-" (λαβ-) = to take. The alidade had vertical and horizontal cross-hairs which plots locations on an azimuthal ring called an almucantar (altitude-distance circle).
An arm called a radius connects from the center of the astrolabe to the optical axis which is parallel with another arm also called a radius. The other radius contains graduations of altitude and distance measurements.
A shadow square also appears on the back of some astrolabes, developed by Muslim astrologists in the 9th Century, whereas devices of the Ancient Greek tradition featured only altitude scales on the back of the devices.^[42]^ This was used to convert shadow lengths and the altitude of the sun, the uses of which were various from surveying to measuring inaccessible heights.^[43]^
Devices were usually signed by their maker with an inscription appearing on the back of the astrolabe, and if there was a patron of the object, their name would appear inscribed on the front, or in some cases, the name of the reigning sultan or the teacher of the astrolabist has also been found to appear inscribed in this place.^[44]^ The date of the astrolabe's construction was often also signed, which has allowed historians to determine that these devices are the second oldest scientific instrument in the world. The inscriptions on astrolabes also allowed historians to conclude that astronomers tended to make their own astrolabes, but that many were also made to order and kept in stock to sell, suggesting there was some contemporary market for the devices.^[44]^
Construction of astrolabes
The Hartmann astrolabe in Yale collection. This instrument shows its rete and rule.
Celestial Globe, Isfahan (?), Iran 1144. Shown at the Louvre Museum, this globe is the third oldest surviving in the world.
Computer-generated planispheric astrolabe
The construction and design of astrolabes are based on the application of the stereographic projection of the celestial sphere. The point from which the projection is usually made is the South Pole. The plane onto which the projection is made is that of the Equator.^[45]^
Parts of an Astrolabe tympanum
The tympanum captures the celestial coordinate axes upon which the rete will rotate. It is the component that will enable the precise determination of a star's position at a specific time of day and year.
Therefore, it should project:
Stereographic projection of Earth's tropics and equator from the South Pole.
On the right side of the image above:
When projecting onto the celestial equatorial plane, three concentric circles correspond to the celestial sphere's three circles of latitude (left side of the image). The largest of these, the projection on the celestial equatorial plane of the celestial Tropic of Capricorn, defines the size of the astrolabe's tympanum. The center of the tympanum (and the center of the three circles) is actually the north-south axis around which Earth rotates, and therefore, the rete of the astrolabe will rotate around this point as the hours of the day pass (due to Earth's rotational motion).
The three concentric circles on the tympanum are useful for determining the exact moments of solstices and equinoxes throughout the year: if the sun's altitude at noon on the rete is known and coincides with the outer circle of the tympanum (Tropic of Capricorn), it signifies the winter solstice (the sun will be at the zenith for an observer at the Tropic of Capricorn, meaning summer in the southern hemisphere and winter in the northern hemisphere). If, on the other hand, its altitude coincides with the inner circle (Tropic of Cancer), it indicates the summer solstice. If its altitude is on the middle circle (equator), it corresponds to one of the two equinoxes.
Stereographic projection of an observer's horizon at a specific latitude
On the right side of the image above:
When projecting the horizon onto the celestial equatorial plane, it transforms into an ellipse upward-shifted relatively to the center of the tympanum (both the observer and the projection of the north-south axis). This implies that a portion of the celestial sphere will fall outside the outer circle of the tympanum (the projection of the celestial Tropic of Capricorn) and, therefore, won't be represented.
Stereographic projection of the horizon and an almucantar.
Additionally, when drawing circles parallel to the horizon up to the zenith (almucantar), and projecting them on the celestial equatorial plane, as in the image above, a grid of consecutive ellipses is constructed, allowing for the determination of a star's altitude when its rete overlaps with the designed tympanum.
Stereographic projection of the north-south meridian and a meridian 40° E on the tympanum of an astrolabe
On the right side of the image above:
When projecting the celestial meridian, it results in a straight line that overlaps with the vertical axis of the tympanum, where the zenith and nadir are located. However, when projecting the 40° E meridian, another circle is obtained that passes through both the zenith and nadir projections, so its center is located on the perpendicular bisection of the segment connecting both points. In deed, the projection of the celestial meridian can be considered as a circle with an infinite radius (a straight line) whose center is on this bisection and at an infinite distance from these two points.
If successive meridians that divide the celestial sphere into equal sectors (like "orange slices" radiating from the zenith) are projected, a family of curves passing through the zenith projection on the tympanum is obtained. These curves, once overlaid with the rete containing the major stars, allow for determining the azimuth of a star located on the rete and rotated for a specific time of day.
Footnotes
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Notes
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Wikimedia Commons has media related to:\ Astrolabe (category)
Wikisource has the text of the 1911 Encyclopædia Britannica article "Astrolabe".
Look up astrolabe in Wiktionary, the free dictionary.
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(Top)
](https://en.wikipedia.org/wiki/Astrolabe#)- [
Applications
](https://en.wikipedia.org/wiki/Astrolabe#Applications)- [
Etymology
](https://en.wikipedia.org/wiki/Astrolabe#Etymology)- [
History
](https://en.wikipedia.org/wiki/Astrolabe#History)- - [
Ancient era
](https://en.wikipedia.org/wiki/Astrolabe#Ancient_era)
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Medieval era
](https://en.wikipedia.org/wiki/Astrolabe#Medieval_era) - [
Astrolabes and clocks
](https://en.wikipedia.org/wiki/Astrolabe#Astrolabes_and_clocks)- [
Construction
](https://en.wikipedia.org/wiki/Astrolabe#Construction)- [
Mathematical basis
](https://en.wikipedia.org/wiki/Astrolabe#Mathematical_basis)- Modern editions of John Philoponus' treatise on the astrolabe are De usu astrolabii eiusque constructione libellus (On the Use and Construction of the Astrolabe), ed. Heinrich Hase, Bonn: E. Weber, 1839, OCLC 165707441 (or id. Rheinisches Museum für Philologie 6 (1839): 127--71); repr. and translated into French by Alain Philippe Segonds, Jean Philopon, traité de l'astrolabe, Paris: Librairie Alain Brieux, 1981, OCLC 10467740; and translated into English by H.W. Green in R.T. Gunther, The Astrolabes of the World, Vol. 1/2, Oxford, 1932, OL 18840299M repr. London: Holland Press, 1976, OL 14132393M pp. 61--81.- O'Leary, De Lacy (1948). How Greek Science Passed to the Arabs. Routledge and Kegan Paul. "The most distinguished Syriac scholar of this later period was Severus Sebokht (d. 666--7), Bishop of Kennesrin. [...] In addition to these works [...] he also wrote on astronomical subjects (Brit. Mus. Add. 14538), and composed a treatise on the astronomical instrument known as the astrolabe, which has been edited and published by F. Nau (Paris, 1899)."\ Severus' treatise was translated by Jessie Payne Smith Margoliouth in R.T. Gunther, Astrolabes of the World, Oxford, 1932, pp. 82--103.- "HISTORIANS' HOME YIELDS RICH LODE; New York Society Searches Its Own Building for Items to Mark Anniversary; SHOW OPENS THURSDAY; Portrait of Stuyvesant and Champlain's Astrolabe Will Be on Display". The New York Times. May 18, 1964. Retrieved February 4, 2024.- Bean, Adam L. (2009). "Astrolabes". In Birx, H. James (ed.). Encyclopedia of Time: Science, Philosophy, Theology, & Culture. Vol. 1. SAGE. pp. 59--60. ISBN 978-1-4129-4164-8.- "Astrolabe". Oxford English Dictionary (2nd ed.). 1989.- "Astrolabe". Oxford Dictionaries. Archived from the original on October 22, 2013.- "Online Etymology Dictionary". Etymonline.com. Retrieved 2013-11-07.- King 1981, p. 44.- King 1981, p. 51.- King 1981, p. 45.- Lewis 2001.- Michael Deakin (August 3, 1997). "Ockham's Razor: Hypatia of Alexandria". ABC Radio. Retrieved July 10, 2014.- Theodore, Jonathan (2016). The Modern Cultural Myth of the Decline and Fall of the Roman Empire. Manchester, England: Palgrave, Macmillan. p. 183. ISBN 978-1-137-56997-4.- Deakin, Michael A. B. (2007). Hypatia of Alexandria: Mathematician and Martyr. Amherst, New York: Prometheus Books. pp. 102--104. ISBN 978-1-59102-520-7.- Bradley, Michael John (2006). The Birth of Mathematics: Ancient Times to 1300. New York City, New York: Infobase Publishing. p. 63. ISBN 9780816054237.- Savage-Smith, Emilie (1992). "Celestial Mapping" (PDF). In Harley, J. B.; Woodward, David (eds.). The History of Cartography, Volume 2, Book 1: Cartography in the Traditional Islamic and South Asian Societies. The History of Cartography. Vol. 2. Chicago, Illinois: University of Chicago Press. ISBN 0226316351.- Sebokht, Severus. "Description of the astrolabe". Tertullian.org.- See p. 289 of Martin, L. C. (1923), "Surveying and navigational instruments from the historical standpoint", Transactions of the Optical Society, 24 (5): 289--303, Bibcode:1923TrOS...24..289M, doi:10.1088/1475-4878/24/5/302, ISSN 1475-4878.- Berggren, J. Lennart (2007), "Mathematics in Medieval Islam", in Katz, Victor J. (ed.), The Mathematics of Egypt, Mesopotamia, China, India, and Islam: a Sourcebook, Princeton University Press, p. 519, ISBN 978-0-691-11485-9- Richard Nelson Frye: Golden Age of Persia. p. 163- Nizamoglu, Cem (2005-08-10). "Using an Astrolabe". Muslim Heritage. Retrieved 2023-10-16.- Lachièz-Rey, Marc; Luminet, Jean-Pierre (2001). Celestial Treasury: From the Music of Spheres to the Conquest of Space. Translated by Joe Laredo. Cambridge, United Kingdom: Cambridge University Press. p. 74. ISBN 978-0-521-80040-2.- O'Connor, John J.; Robertson, Edmund F., "Sharaf al-Din al-Muzaffar al-Tusi", MacTutor History of Mathematics Archive, University of St Andrews- Bedini, Silvio A.; Maddison, Francis R. (1966). "Mechanical Universe: The Astrarium of Giovanni de' Dondi". Transactions of the American Philosophical Society. 56 (5): 1--69. doi:10.2307/1006002. JSTOR 1006002.- "Qantara -- 'Carolingian' astrolabe". Qantara-med.org. Retrieved 2013-11-07.- Nancy Marie Brown (2010), "The Abacus and the Cross". p. 140. Basic Books. ISBN 978-0-465-00950-3- Boyle, David (2011). Toward the Setting Sun: Columbus, Cabot, Vespucci, and the Race for America. Bloomsbury Publishing USA. p. 253. ISBN 9780802779786..- Northrup, Cynthia Clark, ed. (2015). Encyclopedia of world trade: from ancient times to the present (Enhanced Credo ed.). Armonk, New York: Routledge. pp. 72. ISBN 978-0765680587. OCLC 889717964.- "Introduction". The Astrolabe: an Online Resource. 2006. Retrieved 2020-05-15.- Harley, J. B.; Woodward, David (1992). The history of cartography. Chicago, Illinois: University of Chicago Press. p. 31. ISBN 0-226-31635-1.- Kunitzsch, Paul (1981). "On the authenticity of the treatise on the composition and use of the astrolabe ascribed to Messahalla". Archives Internationales d'Histoire des Sciences Oxford. 31 (106): 42--62.- Selin, Helaine (2008-03-12). Encyclopaedia of the History of Science, Technology, and Medicine in Non-Western Cultures. Springer Science & Business Media. p. 1335. ISBN 978-1-4020-4559-2. Paul Kunitzsch has recently established that the Latin treatise on the astrolabe long ascribed to Ma'sh'allah and translated by John of Seville is in fact by Ibn al-Saffar, a disciple of Maslama al-Majriti.- Glick, Thomas; et al., eds. (2005), Medieval Science, Technology, and Medicine: An Encyclopedia, Routledge, p. 464, ISBN 0-415-96930-1- Northrup, Cynthia Clark, ed. (2015). Encyclopedia of world trade : from ancient times to the present ([Enhanced Credo edition] ed.). Armonk, New York: Routledge. pp. 460. ISBN 978-0765680587. OCLC 889717964.- Nancy Marie Brown (2010), "The Abacus and the Cross". p. 143. basic Books. ISBN 978-0-465-00950-3- Hockey, Thomas (2009). The Biographical Encyclopedia of Astronomers. Springer Publishing. ISBN 978-0-387-31022-0. Retrieved August 22, 2012.- Ralf Kern (2010), Wissenschaftliche Instrumente in ihrer Zeit. Band 1: Vom Astrolab zum mathematischen Besteck. Cologne, S. 204. ISBN 978-3-86560-865-9- Vafea, Flora (2017). "The Astronomical Instruments in Saint Catherine's Iconography at the Holy Monastery of Sinai The Almagest Volume 8, Issue 2". Almagest. 8 (2). Paris: University of Paris: 87. doi:10.1484/J.ALMAGEST.5.114932.- North 2005.- "Astrolabium G. Galilei". Ulysse Nardin. Archived from the original on 2 January 2011.- "Christaan van der Klauuw".- Stephenson, Bruce; Bolt, Marvin; Friedman, Anna Felicity (2000). The Universe Unveiled: Instruments and Images through History. Cambridge, UK: Cambridge University Press. pp. 108--109. ISBN 0-521-79143-X.- "Star Names on Astrolabes". Ian Ridpath. Retrieved 2016-11-12.- King, David A. Some Medieval Astronomical Instruments and Their Secrets, in Mazzolini, R. G. (ed.), Non-Verbal Communication in Science prior to 1900. Florence. p. 30.- King, David A. (2018). The Astrolabe: What it is & what it is not. Frankfurt, Germany: Frankfurt.- Mayer, L. A. (1956). Islamic astrolabists and their works*. A. Kunding. Bibcode:[1956iatw.book.....M](https://ui.a Main menu
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From Wikipedia, the free encyclopedia This article is about the sextant as used for navigation. For other uses, see Sextant (disambiguation). Not to be confused with Sexton (disambiguation). A sextant
A sextant is a doubly reflecting navigation instrument that measures the angular distance between two visible objects. The primary use of a sextant is to measure the angle between an astronomical object and the horizon for the purposes of celestial navigation.
The estimation of this angle, the altitude, is known as sighting or shooting the object, or taking a sight. The angle, and the time when it was measured, can be used to calculate a position line on a nautical or aeronautical chart—for example, sighting the Sun at noon or Polaris at night (in the Northern Hemisphere) to estimate latitude (with sight reduction). Sighting the height of a landmark can give a measure of distance off and, held horizontally, a sextant can measure angles between objects for a position on a chart.[1] A sextant can also be used to measure the lunar distance between the moon and another celestial object (such as a star or planet) in order to determine Greenwich Mean Time and hence longitude.
The principle of the instrument was first implemented around 1731 by John Hadley (1682–1744) and Thomas Godfrey (1704–1749), but it was also found later in the unpublished writings of Isaac Newton (1643–1727).
In 1922, it was modified for aeronautical navigation by Portuguese navigator and naval officer Gago Coutinho. Navigational sextants
Like the Davis quadrant, the sextant allows celestial objects to be measured relative to the horizon, rather than relative to the instrument. This allows excellent precision. Also, unlike the backstaff, the sextant allows direct observations of stars. This permits the use of the sextant at night when a backstaff is difficult to use. For solar observations, filters allow direct observation of the Sun.
Since the measurement is relative to the horizon, the measuring pointer is a beam of light that reaches to the horizon. The measurement is thus limited by the angular accuracy of the instrument and not the sine error of the length of an alidade, as it is in a mariner's astrolabe or similar older instrument.
A sextant does not require a completely steady aim, because it measures a relative angle. For example, when a sextant is used on a moving ship, the image of both horizon and celestial object will move around in the field of view. However, the relative position of the two images will remain steady, and as long as the user can determine when the celestial object touches the horizon, the accuracy of the measurement will remain high compared to the magnitude of the movement.
The sextant is not dependent upon electricity (unlike many forms of modern navigation) or any human-controlled signals (such as GPS). For these reasons it is considered to be an eminently practical back-up navigation tool for ships. Design
The frame of a sextant is in the shape of a sector which is approximately 1⁄6 of a circle (60°),[2] hence its name (sextāns, sextantis is the Latin word for "one sixth"). Both smaller and larger instruments are (or were) in use: the octant, quintant (or pentant) and the (doubly reflecting) quadrant[3] span sectors of approximately 1⁄8 of a circle (45°), 1⁄5 of a circle (72°) and 1⁄4 of a circle (90°), respectively. All of these instruments may be termed "sextants". Marine sextant Using the sextant to measure the altitude of the Sun above the horizon Sextants can also be used by navigators to measure horizontal angles between objects.
Attached to the frame are the "horizon mirror", an index arm which moves the index mirror, a sighting telescope, Sun shades, a graduated scale and a micrometer drum gauge for accurate measurements. The scale must be graduated so that the marked degree divisions register twice the angle through which the index arm turns. The scales of the octant, sextant, quintant and quadrant are graduated from below zero to 90°, 120°, 140° and 180° respectively. For example, the sextant illustrated has a scale graduated from −10° to 142°, which is basically a quintant: the frame is a sector of a circle subtending an angle of 76° at the pivot of the index arm.
The necessity for the doubled scale reading follows from consideration of the relations of the fixed ray (between the mirrors), the object ray (from the sighted object) and the direction of the normal perpendicular to the index mirror. When the index arm moves by an angle, say 20°, the angle between the fixed ray and the normal also increases by 20°. But the angle of incidence equals the angle of reflection so the angle between the object ray and the normal must also increase by 20°. The angle between the fixed ray and the object ray must therefore increase by 40°. This is the case shown in the graphic.
There are two types of horizon mirrors on the market today. Both types give good results.
Traditional sextants have a half-horizon mirror, which divides the field of view in two. On one side, there is a view of the horizon; on the other side, a view of the celestial object. The advantage of this type is that both the horizon and celestial object are bright and as clear as possible. This is superior at night and in haze, when the horizon and/or a star being sighted can be difficult to see. However, one has to sweep the celestial object to ensure that the lowest limb of the celestial object touches the horizon.
Whole-horizon sextants use a half-silvered horizon mirror to provide a full view of the horizon. This makes it easy to see when the bottom limb of a celestial object touches the horizon. Since most sights are of the Sun or Moon, and haze is rare without overcast, the low-light advantages of the half-horizon mirror are rarely important in practice.
In both types, larger mirrors give a larger field of view, and thus make it easier to find a celestial object. Modern sextants often have 5 cm or larger mirrors, while 19th-century sextants rarely had a mirror larger than 2.5 cm (one inch). In large part, this is because precision flat mirrors have grown less expensive to manufacture and to silver.
An artificial horizon is useful when the horizon is invisible, as occurs in fog, on moonless nights, in a calm, when sighting through a window or on land surrounded by trees or buildings. There are two common designs of artificial horizon. An artificial horizon can consist simply of a pool of water shielded from the wind, allowing the user to measure the distance between the body and its reflection, and divide by two. Another design allows the mounting of a fluid-filled tube with bubble directly to the sextant.
Most sextants also have filters for use when viewing the Sun and reducing the effects of haze. The filters usually consist of a series of progressively darker glasses that can be used singly or in combination to reduce haze and the Sun's brightness. However, sextants with adjustable polarizing filters have also been manufactured, where the degree of darkness is adjusted by twisting the frame of the filter.
Most sextants mount a 1 or 3-power monocular for viewing. Many users prefer a simple sighting tube, which has a wider, brighter field of view and is easier to use at night. Some navigators mount a light-amplifying monocular to help see the horizon on moonless nights. Others prefer to use a lit artificial horizon.[citation needed]
Professional sextants use a click-stop degree measure and a worm adjustment that reads to a minute, 1/60 of a degree. Most sextants also include a vernier on the worm dial that reads to 0.1 minute. Since 1 minute of error is about a nautical mile, the best possible accuracy of celestial navigation is about 0.1 nautical miles (190 m). At sea, results within several nautical miles, well within visual range, are acceptable. A highly skilled and experienced navigator can determine position to an accuracy of about 0.25-nautical-mile (460 m).[4]
A change in temperature can warp the arc, creating inaccuracies. Many navigators purchase weatherproof cases so that their sextant can be placed outside the cabin to come to equilibrium with outside temperatures. The standard frame designs (see illustration) are supposed to equalise differential angular error from temperature changes. The handle is separated from the arc and frame so that body heat does not warp the frame. Sextants for tropical use are often painted white to reflect sunlight and remain relatively cool. High-precision sextants have an invar (a special low-expansion steel) frame and arc. Some scientific sextants have been constructed of quartz or ceramics with even lower expansions. Many commercial sextants use low-expansion brass or aluminium. Brass is lower-expansion than aluminium, but aluminium sextants are lighter and less tiring to use. Some say they are more accurate because one's hand trembles less. Solid brass frame sextants are less susceptible to wobbling in high winds or when the vessel is working in heavy seas, but as noted are substantially heavier. Sextants with aluminum frames and brass arcs have also been manufactured. Essentially, a sextant is intensely personal to each navigator, and they will choose whichever model has the features which suit them best.
Aircraft sextants are now out of production, but had special features. Most had artificial horizons to permit taking a sight through a flush overhead window. Some also had mechanical averagers to make hundreds of measurements per sight for compensation of random accelerations in the artificial horizon's fluid. Older aircraft sextants had two visual paths, one standard and the other designed for use in open-cockpit aircraft that let one view from directly over the sextant in one's lap. More modern aircraft sextants were periscopic with only a small projection above the fuselage. With these, the navigator pre-computed their sight and then noted the difference in observed versus predicted height of the body to determine their position. Taking a sight
A sight (or measure) of the angle between the Sun, a star, or a planet, and the horizon is done with the 'star telescope' fitted to the sextant using a visible horizon. On a vessel at sea even on misty days a sight may be done from a low height above the water to give a more definite, better horizon. Navigators hold the sextant by its handle in the right hand, avoiding touching the arc with the fingers.[5]
For a Sun sight, a filter is used to overcome the glare such as "shades" covering both index mirror and the horizon mirror designed to prevent eye damage. Initially, with the index bar set to zero and the shades covering both mirrors, the sextant is aimed at the sun until it can be viewed on both mirrors through the telescope, then lowered vertically until the portion of the horizon directly below it is viewed on both mirrors. It is necessary to flip back the horizon mirror shade to be able to see the horizon more clearly on it. Releasing the index bar (either by releasing a clamping screw, or on modern instruments, using the quick-release button), and moving it towards higher values of the scale, eventually the image of the Sun will reappear on the index mirror and can be aligned to about the level of the horizon on the horizon mirror. Then the fine adjustment screw on the end of the index bar is turned until the bottom curve (the lower limb) of the Sun just touches the horizon. "Swinging" the sextant about the axis of the telescope ensures that the reading is being taken with the instrument held vertically. The angle of the sight is then read from the scale on the arc, making use of the micrometer or vernier scale provided. The exact time of the sight must also be noted simultaneously, and the height of the eye above sea-level recorded.[5]
An alternative method is to estimate the current altitude (angle) of the Sun from navigation tables, then set the index bar to that angle on the arc, apply suitable shades only to the index mirror, and point the instrument directly at the horizon, sweeping it from side to side until a flash of the Sun's rays are seen in the telescope. Fine adjustments are then made as above. This method is less likely to be successful for sighting stars and planets.[5]
Star and planet sights are normally taken during nautical twilight at dawn or dusk, while both the heavenly bodies and the sea horizon are visible. There is no need to use shades or to distinguish the lower limb as the body appears as a mere point in the telescope. The Moon can be sighted, but it appears to move very fast, appears to have different sizes at different times, and sometimes only the lower or upper limb can be distinguished due to its phase.[5]
After a sight is taken, it is reduced to a position by looking at several mathematical procedures. The simplest sight reduction is to draw the equal-altitude circle of the sighted celestial object on a globe. The intersection of that circle with a dead-reckoning track, or another sighting, gives a more precise location.
Sextants can be used very accurately to measure other visible angles, for example between one heavenly body and another and between landmarks ashore. Used horizontally, a sextant can measure the apparent angle between two landmarks such as a lighthouse and a church spire, which can then be used to find the distance off or out to sea (provided the distance between the two landmarks is known). Used vertically, a measurement of the angle between the lantern of a lighthouse of known height and the sea level at its base can also be used for distance off.[5] Adjustment
Due to the sensitivity of the instrument it is easy to knock the mirrors out of adjustment. For this reason a sextant should be checked frequently for errors and adjusted accordingly.
There are four errors that can be adjusted by the navigator, and they should be removed in the following order.
Perpendicularity error This is when the index mirror is not perpendicular to the frame of the sextant. To test for this, place the index arm at about 60° on the arc and hold the sextant horizontally with the arc away from you at arm's length and look into the index mirror. The arc of the sextant should appear to continue unbroken into the mirror. If there is an error, then the two views will appear to be broken. Adjust the mirror until the reflection and direct view of the arc appear to be continuous. Side error This occurs when the horizon glass/mirror is not perpendicular to the plane of the instrument. To test for this, first zero the index arm then observe a star through the sextant. Then rotate the tangent screw back and forth so that the reflected image passes alternately above and below the direct view. If in changing from one position to another, the reflected image passes directly over the unreflected image, no side error exists. If it passes to one side, side error exists. Alternatively, the user can hold the sextant on its side and observe the horizon to check the sextant during the day. If there are two horizons there is side error. In both cases, adjust the horizon glass/mirror until respectively the star or the horizon dual images merge into one. Side error is generally inconsequential for observations and can be ignored or reduced to a level that is merely inconvenient. Collimation error This is when the telescope or monocular is not parallel to the plane of the sextant. To check for this you need to observe two stars 90° or more apart. Bring the two stars into coincidence either to the left or the right of the field of view. Move the sextant slightly so that the stars move to the other side of the field of view. If they separate there is collimation error. As modern sextants rarely use adjustable telescopes, they do not need to be corrected for collimation error. Index error This occurs when the index and horizon mirrors are not parallel to each other when the index arm is set to zero. To test for index error, zero the index arm and observe the horizon. If the reflected and direct image of the horizon are in line there is no index error. If one is above the other adjust the index mirror until the two horizons merge. Alternatively, the same procedure can be done at night using a star or the Moon instead of the horizon.
See also
Astrolabe
Bris sextant
Davis quadrant
Gago Coutinho
Harold Gatty
History of longitude
Intercept method
Latitude
Longitude
Longitude by chronometer
Mariner's astrolabe
Navigation
Octant (instrument)
Quadrant (instrument)
Sextant (astronomy)
Notes
Seddon, J. Carl (June 1968). "Line of Position from a Horizontal Angle". Journal of Navigation. 21 (3): 367–369. doi:10.1017/S0373463300024838. ISSN 1469-7785. A.), McPhee, John (John; NSW., Museums and Galleries (2008). Great Collections : treasures from Art Gallery of NSW, Australian Museum, Botanic Gardens Trust, Historic Houses Trust of NSW, Museum of Contemporary Art, Powerhouse Museum, State Library of NSW, State Records NSW. Museums & Galleries NSW. p. 56. ISBN 9780646496030. OCLC 302147838. This article treats the doubly reflecting quadrant, not its predecessor described at quadrant. Dutton's Navigation and Piloting, 12th edition. G.D. Dunlap and H.H. Shufeldt, eds. Naval Institute Press 1972, ISBN 0-87021-163-3
Dixon, Conrad (1968). "5. Using the sextant". Basic Astro Navigation. Adlard Coles. ISBN 0-229-11740-6.
References
Bowditch, Nathaniel (2002). The American Practical Navigator. Bethesda, MD: National Imagery and Mapping Agency. ISBN 0-939837-54-4. Archived from the original on 2007-06-24.
Chisholm, Hugh, ed. (1911). "Sextant" . Encyclopædia Britannica. Vol. 24 (11th ed.). Cambridge University Press. pp. 765–767.
Cutler, Thomas J. (December 2003). Dutton's Nautical Navigation (15th ed.). Annapolis, MD: Naval Institute Press. ISBN 978-1-55750-248-3.
Department of the Air Force (March 2001). Air Navigation (PDF). Department of the Air Force. Retrieved 2014-12-28.
Great Britain Ministry of Defence (Navy) (1995). Admiralty Manual of Seamanship. The Stationery Office. ISBN 0-11-772696-6.
Maloney, Elbert S. (December 2003). Chapman Piloting and Seamanship (64th ed.). New York: Hearst Communications. ISBN 1-58816-089-0.
Martin, William Robert (1911). "Navigation" . In Chisholm, Hugh (ed.). Encyclopædia Britannica. Vol. 19 (11th ed.). Cambridge University Press. pp. 284–298.
External links Look up sextant in Wiktionary, the free dictionary. Wikimedia Commons has media related to Sextant.
Her Majesty's Nautical Almanac Office Archived 2011-02-21 at the Wayback Machine
The History of HM Nautical Almanac Office Archived 2016-06-24 at the Wayback Machine
Chapter 17 from the online edition of Nathaniel Bowditch's American Practical Navigator
Understand difference in Antique & Replica Sextant Archived 2017-08-17 at the Wayback Machine
CD-Sextant - Build your own sextant Simple do-it-yourself project.
Lunars web site. online calculation
Complete celnav theory book, including Lunars
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Gondola Wish',
This article is about the U.S. government project on psychics. For other uses, see Stargate (disambiguation). Part of a series on the Paranormal Main articles Skepticism Parapsychology Related
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The Stargate Project was a secret U.S. Army unit established in 1977[1][2] at Fort Meade, Maryland, by the Defense Intelligence Agency (DIA) and SRI International (a California contractor) to investigate the potential for psychic phenomena in military and domestic intelligence applications. The project, and its precursors and sister projects, originally went by various code names – 'Gondola Wish', 'Stargate', 'Grill Flame', 'Center Lane', 'Project CF', 'Sun Streak', 'Scanate' – until 1991 when they were consolidated and rechristened as the "Stargate Project".
The Stargate Project's work primarily involved remote viewing, the purported ability to psychically "see" events, sites, or information from a great distance.[3] The project was overseen until 1987 by Lt. Frederick Holmes "Skip" Atwater, an aide and "psychic headhunter" to Maj. Gen. Albert Stubblebine, and later president of the Monroe Institute.[4] The unit was small scale, comprising about 15 to 20 individuals, and was run out of "an old, leaky wooden barracks".[5]
The Stargate Project was terminated and declassified in 1995 after a CIA report concluded that it was never useful in any intelligence operation. Information provided by the program was vague and included irrelevant and erroneous data, and there were suspicions of inter-judge reliability.[6]: 5–4 The program was featured in the 2004 book and 2009 film, both titled The Men Who Stare at Goats,[7][8][9][10] although neither mentions it by name. George Stephanopoulos, in his 2024 book The Situation Room, mentions the project by the name Grill Flame, in discussing a May 8, 1980, Situation Room briefing for President Carter, after Carter's failed hostage rescue mission in Iran on April 24, 1980.[11] Background
The CIA and DIA decided they should investigate and know as much about it as possible. Various programs were approved yearly and re-funded accordingly. Reviews were made semi-annually at the Senate and House select committee level. Work results were reviewed, and remote viewing was attempted with the results being kept secret from the "viewer". It was thought that if the viewer was shown they were incorrect it would damage the viewer's confidence and skill. This was standard operating procedure throughout the years of military and domestic remote viewing programs. Feedback to the remote viewer of any kind was rare; it was kept classified and secret.[12]
Remote viewing attempts to sense unknown information about places or events. Normally it is performed to detect current events, but during military and domestic intelligence applications viewers claimed to sense things in the future, experiencing precognition.[13] History 1970s
In 1970 United States intelligence sources believed that the Soviet Union was spending 60 million roubles annually on "psychotronic" research. In response to claims that the Soviet program had produced results, the CIA initiated funding for a new program known as SCANATE ("scan by coordinate") in the same year.[14] Remote viewing research began in 1972 at the Stanford Research Institute (SRI) in Menlo Park, California.[14][15] Proponents (Russell Targ and Harold Puthoff) of the research said that a minimum accuracy rate of 65% required by the clients was often exceeded in the later experiments.[14]
Physicists Targ and Puthoff began testing psychics for SRI in 1972, including one who would later become an international celebrity, Israeli Uri Geller. Their apparently successful results garnered interest within the U.S. Department of Defense. Ray Hyman, professor of psychology at the University of Oregon, was asked by Air Force psychologist Lt. Col. Austin W. Kibler (1930–2008) – then Director of Behavioral Research for ARPA – to go to SRI and investigate. He was to specifically evaluate Geller. Hyman's report to the government was that Geller was a "complete fraud" and as a consequence Targ and Puthoff lost their government contract to work further with him. The result was a publicity tour for Geller, Targ, and Puthoff to seek private funding for further research work on Geller.[16]
One of the project's successes was the location of a lost Soviet spy plane in 1976 by Rosemary Smith, a young administrative assistant recruited by project director Dale Graff.[17]
In 1977 the Army Assistant Chief of Staff for Intelligence (ACSI) Systems Exploitation Detachment (SED) started the Gondola Wish program to "evaluate potential adversary applications of remote viewing".[14] Army Intelligence then formalized this in mid-1978 as an operational program Grill Flame, based in buildings 2560 and 2561 at Fort Meade, in Maryland (INSCOM "Detachment G").[14] 1980s
In early 1979 the research at SRI was integrated into 'Grill Flame', which was redesignated INSCOM 'Center Lane' Project (ICLP) in 1983. In 1984 the existence of the program was reported by Jack Anderson, and in that year it was unfavorably received by the National Academy of Sciences National Research Council. In late 1985 the Army funding was terminated, but the program was redesignated 'Sun Streak' and funded by the DIA's Scientific and Technical Intelligence Directorate (office code DT-S).[14] 1990s
In 1991 most of the contracting for the program was transferred from SRI to Science Applications International Corporation (SAIC), with Edwin May controlling 70% of the contractor funds and 85% of the data. Its security was altered from Special Access Program (SAP) to Limited Dissemination (LIMDIS), and it was given its final name, STARGATE.[14] Closure (1995)
In 1995 the defense appropriations bill directed that the program be transferred from DIA to CIA oversight. The CIA commissioned a report by the American Institutes for Research (AIR) that found that remote viewing had not been proved to work by a psychic mechanism, and said it had not been used operationally.[6]: 5–4 The CIA subsequently cancelled and declassified the program.[14]
In 1995 the project was transferred to the CIA and a retrospective evaluation of the results was done. The appointed panel consisted primarily of Jessica Utts, Meena Shah and Ray Hyman. Hyman had produced an unflattering report on Uri Geller and SRI for the government two decades earlier, but the psychologist David Marks found Utts' appointment to the review panel "puzzling" given that she had published papers with Edwin May, considering this joint research likely to make her "less than [im]partial".[3] A report by Utts claimed the results were evidence of psychic functioning; however, Hyman in his report argued Utts's conclusion that ESP had been proven to exist, especially precognition, was premature and the findings had not been independently replicated.[18] Hyman came to the conclusion:
Psychologists, such as myself, who study subjective validation find nothing striking or surprising in the reported matching of reports against targets in the Stargate data. The overwhelming amount of data generated by the viewers is vague, general, and way off target. The few apparent hits are just what we would expect if nothing other than reasonable guessing and subjective validation are operating.[19]
A later report by AIR came to a negative conclusion. Joe Nickell has written:
Other evaluators – two psychologists from AIR – assessed the potential intelligence-gathering usefulness of remote viewing. They concluded that the alleged psychic technique was of dubious value and lacked the concreteness and reliability necessary for it to be used as a basis for making decisions or taking action. The final report found "reason to suspect" that in "some well publicised cases of dramatic hits" the remote viewers might have had "substantially more background information" than might otherwise be apparent.[20]
According to AIR, which performed a review of the project, no remote viewing report ever provided actionable information for any intelligence operation.[21][6]: 5–4
Based upon the collected findings, which recommended a higher level of critical research and tighter controls, the CIA terminated the 20 million dollar project, citing a lack of documented evidence that the program had any value to the intelligence community. Time magazine stated in 1995 three full-time psychics were still working on a $500,000-a-year budget out of Fort Meade, Maryland, which would soon close.[21]
David Marks in his book The Psychology of the Psychic (2000) discussed the flaws in the Stargate Project in detail.[3] Marks wrote that there were six negative design features of the experiments. The possibility of cues or sensory leakage was not ruled out, no independent replication, some experiments were conducted in secret, making peer-review impossible. Marks noted that the judge Edwin May was also the principal investigator for the project and this was problematic, making a huge conflict of interest with collusion, cuing and fraud being possible. Marks concluded the project was nothing more than a "subjective delusion" and after two decades of research it had failed to provide any scientific evidence for the legitimacy of remote viewing.[3]
The Stargate Project was terminated in 1995 following an independent review which concluded:
The foregoing observations provide a compelling argument against continuation of the program within the intelligence community. Even though a statistically significant effect has been observed in the laboratory, it remains unclear whether the existence of a paranormal phenomenon, remote viewing, has been demonstrated. The laboratory studies do not provide evidence regarding the origins or nature of the phenomenon, assuming it exists, nor do they address an important methodological issue of inter-judge reliability.
Further, even if it could be demonstrated unequivocally that a paranormal phenomenon occurs under the conditions present in the laboratory paradigm, these conditions have limited applicability and utility for intelligence gathering operations. For example, the nature of the remote viewing targets are vastly dissimilar, as are the specific tasks required of the remote viewers. Most importantly, the information provided by remote viewing is vague and ambiguous, making it difficult, if not impossible, for the technique to yield information of sufficient quality and accuracy of information for actionable intelligence. Thus, we conclude that continued use of remote viewing in intelligence gathering operations is not warranted.[6]: E-4–E-5
In January 2017, the CIA published records online of the Stargate Project as part of the CREST archive.[22] Methodology
The Stargate Project created a set of protocols designed to make the research of clairvoyance and out-of-body experiences more scientific, and to minimize as much as possible session noise and inaccuracy. The term "remote viewing" emerged as shorthand to describe this more structured approach to clairvoyance. Project Stargate would only receive a mission after all other intelligence attempts, methods, or approaches had already been exhausted.[13]: 21
It was reported that at peak manpower there were over 22 active military and civilian remote viewers providing data. People leaving the project were not replaced. When the project closed in 1995 this number had dwindled down to three. One was using tarot cards. According to Joseph McMoneagle, "The Army never had a truly open attitude toward psychic functioning". Hence, the use of the term "giggle factor"[23] and the saying, "I wouldn't want to be found dead next to a psychic".[12] Civilian personnel Hal Puthoff Main article: Harold E. Puthoff
In the 1970s, CIA and DIA granted funds to Harold E. Puthoff to investigate paranormal abilities, collaborating with Russell Targ in a study of the purported psychic abilities of Uri Geller, Ingo Swann, Pat Price, Joseph McMoneagle and others, as part of the Stargate Project,[24] of which Puthoff became a director.[25]
As with Ingo Swann and Pat Price, Puthoff attributed much of his personal remote viewing skills to his involvement with Scientology whereby he had attained, at that time, the highest level. All three eventually left Scientology in the late 1970s.
Puthoff worked as the principal investigator of the project. His team of psychics is said[who?] to have identified spies, located Soviet weapons and technologies, such as a nuclear submarine in 1979 and helped find lost SCUD missiles in the first Gulf War and plutonium in North Korea in 1994.[26] Russell Targ Russell Targ Main article: Russell Targ
In the 1970s, Russell Targ began working with Harold Puthoff on the Stargate Project, while working with him as a researcher at Stanford Research Institute.[27][28] Edwin May
Edwin C. May joined the Stargate Project in 1975 as a consultant and was working full-time in 1976. The original project was part of the Cognitive Sciences Laboratory managed by May. With more funding in 1991 May took the project to the Palo Alto offices at SAIC. This would last until 1995 when the CIA closed the project.[3]
May worked as the principal investigator, judge and the star gatekeeper for the project. Marks says this was a serious weakness for the experiments as May had conflict of interest and could have done whatever he wanted with the data. Marks has written that May refused to release the names of the "oversight committee" and refused permission for him to give an independent judging of the Stargate transcripts. Marks found this suspicious, commenting "this refusal suggests that something must be wrong with the data or with the methods of data selection."[3] Ingo Swann Main article: Ingo Swann
Originally tested in the "Phase One" were OOBE-Beacon "RV" experiments at the American Society for Psychical Research,[29][unreliable source?] under research director Karlis Osis.[citation needed] A former OT VII Scientologist,[30][self-published source] who alleged to have coined the term 'remote viewing' as a derivation of protocols originally developed by René Warcollier, a French chemical engineer in the early 20th century, documented in the book Mind to Mind, Classics in Consciousness Series Books by (ISBN 978-1571743114)[citation needed]. Swann's achievement was to break free from the conventional mold of casual experimentation and candidate burn out, and develop a viable set of protocols that put clairvoyance within a framework named "Coordinate Remote Viewing" (CRV).[31] In a 1995 letter Edwin C. May wrote he had not used Swann for two years because there were rumors of him briefing a high level person at SAIC and the CIA on remote viewing and aliens, ETs.[32] Pat Price
A former Burbank, California, police officer and former Scientologist who participated in a number of Cold War era remote viewing experiments, including the US government-sponsored projects SCANATE and the Stargate Project. Price joined the program after a chance encounter with fellow Scientologists (at the time) Harold Puthoff and Ingo Swann near SRI.[33] Working with maps and photographs provided to him by the CIA, Price claimed to have been able to retrieve information from facilities behind Soviet lines. He is probably best known for his sketches of cranes and gantries which appeared to conform to CIA intelligence photographs. At the time, the CIA took his claims seriously.[34] Military personnel Lieutenant General James Clapper Main article: James Clapper
The project leader[failed verification] in the 1990s was Lt. Gen. Clapper who later rose to infamy[unbalanced opinion?] as the Director of National Intelligence.[35] Albert Stubblebine Major General Albert Stubblebine Main article: Albert Stubblebine
A key sponsor of the research internally at Fort Meade, Maryland, Maj. Gen. Stubblebine was convinced of the reality of a wide variety of psychic phenomena. He required that all of his battalion commanders learn how to bend spoons à la Uri Geller, and he himself attempted several psychic feats, even attempting to walk through walls. In the early 1980s he was responsible for the United States Army Intelligence and Security Command (INSCOM), during which time the remote viewing project in the US Army began. Some commentators have confused a "Project Jedi", allegedly run by Special Forces primarily out of Fort Bragg, with Stargate. After some controversy involving these experiments, including alleged security violations from uncleared civilian psychics working in Sensitive Compartmented Information Facilities (SCIFs), Stubblebine was placed on retirement. His successor as the INSCOM commander was Maj. Gen. Harry Soyster, who had a reputation as a much more conservative and conventional intelligence officer. Soyster was not amenable to continuing paranormal experiments and the Army's participation in Project Stargate ended during his tenure.[12] David Morehouse
In his book, Psychic Warrior: Inside the CIA's Stargate Program : The True Story of a Soldier's Espionage and Awakening (2000, St. Martin's Press, ISBN 978-1902636207), Morehouse claims to have worked on hundreds of remote viewing assignments, from searching for a Soviet jet that crashed in the jungle carrying an atomic bomb, to tracking suspected double agents.[36] Joseph McMoneagle Main article: Joseph McMoneagle
McMoneagle claims he had a remarkable memory of very early childhood events. He grew up surrounded by alcoholism, abuse and poverty. As a child, he had visions at night when scared, and began to hone his psychic abilities in his teens for his own protection when he hitchhiked. He enlisted to get away. McMoneagle became an experimental remote viewer while serving in U.S. Army Intelligence.[12] Ed Dames
Dames' role was intended to be as session monitor and analyst as an aid to Fred Atwater[37][self-published source] rather than a remote viewer, Dames received no formal remote viewing training. After his assignment to the remote viewing unit at the end of January 1986, he was used to "run" remote viewers (as monitor) and provide training and practice sessions to viewer personnel. He soon established a reputation for pushing CRV to extremes, with target sessions on Atlantis, Mars, UFOs, and aliens. He has been a frequent guest on the Coast to Coast AM radio shows.[38] References
"Government-Sponsored Research On Parapsychology". www.encyclopedia.com. "Defense Intelligence Agency (DT-S)" (PDF). nsarchive2.gwu.edu. Marks, David. (2000). The Psychology of the Psychic (2nd ed.). Buffalo, NY: Prometheus Books. pp. 71–96. ISBN 1-57392-798-8 Atwater, F. Holmes (2001), Captain of My Ship, Master of My Soul: Living with Guidance; Hampton Roads Publishing Company Weeks, Linton (December 4, 1995). "Up Close & Personal With a Remote Viewer: Joe McMoneagle Defends the Secret Project". The Washington Post. p. B1. ISSN 0190-8286. Mumford, Michael D.; Rose, Andrew M.; Goslin, David A. (September 29, 1995). An Evaluation of Remote Viewing: Research and Applications (PDF) (Report). The American Institutes for Research – via Federation of American Scientists. "[R]emote viewings have never provided an adequate basis for 'actionable' intelligence operations – that is, information sufficiently valuable or compelling so that action was taken as a result." Heard, Alex (10 April 2010), "Close your eyes and remote view this review", Union-Tribune San Diego, Union-Tribune Publishing Co. [Book review of The Men Who Stare at Goats]: "This so-called "remote viewing" operation continued for years, and came to be known as Star Gate." Clarke, David (2014), Britain's X-traordinary Files, London: Bloomsbury Publishing, p. 112: "The existence of the Star Gate project was not officially acknowledged until 1995... then became the subject of investigations by journalists Jon Ronson [etc]... Ronson's 2004 book, The Men Who Stare at Goats, was subsequently adapted into a 2009 movie..." Shermer, Michael (November 2009), “Staring at Men Who Stare at Goats” @ Michaelshermer.com: "... the U.S. Army had invested $20 million in a highly secret psychic spy program called Star Gate. ... In The Men Who Stare at Goats Jon Ronson tells the story of this program, how it started, the bizarre twists and turns it took, and how its legacy carries on today." Krippner, Stanley and Harris L. Friedman (2010), Debating Psychic Experience: Human Potential Or Human Illusion?, Santa Barbara, CA: Praeger/Greenwood Publishing Group, p. 154: "The story of Stargate was ... featured in a film based on the book The Men Who Stare at Goats, by British investigative journalist Jon Ronson (2004)". "CNN.com - Transcripts (Amanpour)". transcripts.cnn.com. June 3, 2024. Retrieved June 9, 2024. McMoneagle, Joseph (2006). Memoirs of a psychic spy : the remarkable life of U.S. Government remote viewer 001. Charlottesville, VA: Hampton Roads Pub. Co. ISBN 978-1-5717-4482-1. McMoneagle, Joseph (1998). The ultimate time machine : a remote viewer's perception of time and predictions for the new millennium. Charlottesville, VA: Hampton Roads Pub. Co. ISBN 978-1-5717-4102-8. Pike, John (December 29, 2005). "Star Gate [Controlled Remote Viewing]". Federation of American Scientists. May, Edwin C. (1996). "The American Institutes for Research review of the Department of Defense's STAR GATE program: A commentary" (PDF). Journal of Scientific Exploration. 10 (1): 89–107. Interview, Ray Hyman, in An Honest Liar, a 2014 documentary film by Left Turn Films; Pure Mutt Productions; Part2 Filmworks. (The quoted remarks commence at 21 min, 45 sec.) Jacobsen, Annie (2017). "Paraphysics". Phenomena: The Secret History of the U.S. Government's Investigations into Extrasensory Perception and Psychokinesis. Little, Brown. ISBN 978-0-316-34937-6. Evaluation of a Program on Anomalous Mental Phenomena Archived June 16, 2017, at the Wayback Machine by Ray Hyman. "The Evidence for Psychic Functioning: Claims vs. Reality" by Ray Hyman; Skeptical Inquirer, Vol. 20.2, Mar/Apr 1996. "Remotely Viewed? The Charlie Jordan Case" by Joe Nickell; Skeptical Inquirer, Vol. 11.1, Mar 2001. Waller, Douglas (December 11, 1995). "The Vision Thing". Time magazine. p. 45. Archived from the original on February 9, 2007. "Search: 'Stargate'". Freedom of Information Act Electronic Reading Room. Central Intelligence Agency. McMoneagle, Joseph (1997). Mind trek : exploring consciousness, time, and space through remote viewing (Revised ed.). Norfork, VA: Hampton Roads Pub. p. 247. ISBN 978-1-8789-0172-9. Popkin, Jim (November 12, 2015). "Meet the former Pentagon scientist who says psychics can help American spies". Newsweek. Pilkington, Mark (June 5, 2003). "The remote viewers". The Guardian. "Fort Meade, Maryland, where psychics gathered to remotely spy on the U.S. Embassy in Iran during the hostage crisis". Miami Herald. Nickell, Joe (March 2001). "Remotely viewed? The Charlie Jordan case". Skeptical Inquirer. Vol. 11, no. 1. "Dr. Harold Puthoff". arlingtoninstitute.org. The Arlington Institute. 2008. Archived from the original on March 3, 2013. "Interview: A New Biopic Charts the Life of Ingo Swann, the 'Father of Remote Viewing'". Outerplaces.com. Archived from the original on April 29, 2018. Retrieved April 28, 2018. "An Interview with Indo Swann". The Wise Old Goat – The Personal Website of Michel Snoeck. Retrieved April 28, 2018. "An Outsider's Remote View of All Things: Ingo Swann". Chelseanow.com. Archived from the original on April 29, 2018. Retrieved April 28, 2018. "A Dynamic PK Experiment with Ingo Swann". Central Intelligence Agency. Archived from the original on April 29, 2018. Retrieved April 28, 2018. Pat Price URL:http://www.scientolipedia.org/info/Pat_Price (Scientolipedia) Sources:
Schnabel, Jim (1997) Remote Viewers: The Secret History of America's Psychic Spies Dell, 1997 , ISBN 0-440-22306-7
Richelson, Jeffrey T The Wizards of Langley: Inside the CIA's Directorate of Science and Technology
Mandelbaum, W. Adam The Psychic Battlefield: A History of the Military-Occult Complex
Picknett, Lynn, Prince Clive The Stargate Conspiracy
Chalker, Bill Hair of the Alien: DNA and Other Forensic Evidence of Alien Abductions
Constantine, Alex Psychic Dictatorship in the USA
https://documents2.theblackvault.com/documents/cia/stargate/STARGATE%20%2311%20549/Part0003/CIA-RDP96-00789R002500240004-5.pdf [bare URL PDF] "Psychic Warrior: Inside the CIA's Stargate Program: The True Story of a Soldier's Espionage and Awakening". Publishers Weekly. Retrieved April 28, 2018. "Stargate: People and researchers". Bibliotecapleyades.net.
Ronson, Jon (2006). The Men Who Stare at Goats. Simon & Schuster. pp. 93–94. ISBN 978-0-7432-7060-1.
Further reading
Burnett, Thom, ed. (2006). "Psi-War: Operations Grillflame and Stargate". Conspiracy Encyclopedia: The encyclopedia of conspiracy theories. Franz Steiner Verlag. p. 153. ISBN 978-1-84340-381-4.
Caroll, Robert Todd (2012). "Remote Viewing". In the Skeptic's Dictionary. John Wiley & Sons. ISBN 0-471-27242-6.
Hines, Terence (2003). Pseudoscience and the Paranormal. Prometheus Books. ISBN 1-57392-979-4.
Hyman, Ray (1996). "Evaluation of the Military's Twenty-year Program on Psychic Spying". Skeptical Inquirer 20: 21–26.
Morehouse, David (1996). Psychic Warrior, St. Martin's Paperbacks, ISBN 978-0-312-96413-9. Morehouse was a psychic in the program.
Ronson, Jon (2004). The Men Who Stare at Goats. Picador. ISBN 0-330-37547-4. Written to accompany the TV series Crazy Rulers of the World. The US military budget cuts after the Vietnam war and how it all began.
Sessions, Abigail (2016). "STARGATE, Project (1970s–1995)". In Goldman, Jan (ed.). The Central Intelligence Agency: An Encyclopedia of Covert Ops, Intelligence Gathering, and Spies, Volume 1. ABC-CLIO. pp. 352–353. ISBN 978-1-61069-092-8.
Smith, Paul (2004). Reading the Enemy's Mind: Inside Star Gate: America's Psychic Espionage Program, Forge Books. ISBN 0-312-87515-0
Utts, Jessica (1996). "An Assessment of the Evidence for Psychic Functioning". Journal of Scientific Exploration. 10 (1): 3–30. CiteSeerX 10.1.1.685.2525. 0892-3310/96.
External links
Report from 1995 about the program from American Institutes for Research
Declassified analytical report (1983) related to the project
Declassified documents about the project on the website of the CIA
vte
Defense Intelligence Agency Categories:
1978 establishments in MarylandAmerican secret government programsCentral Intelligence Agency operationsCold War tacticsDefense Intelligence AgencyEspionage projectsHuman subject research in the United StatesPseudoscienceRemote viewing
image.png /en-us/articles/360023851591-How-do-I-view-DRM-protected-content
This is ABSSOLUTELY NOTHING BUT "UN SE LINUX ALED" MACROMEDIA SHOCKWAVE FLASH all over again; it is embarrassingly not just "bugs in advanced mathematics hidden inside frame buffer mathematics and "OpenGL" it's a significant glaring opening that brave has sbrvaely alerted me to as a "Google add-on to Chome" that makes yet another floating .VA inside Virginia or .IT ... your "Infomration Technology" departments are patenty compromised by Plex sovereignty, weither it be of Menlo or Sunnyvale;
the Mountain will not prevail against Veritae Trantor.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED SURVIVABILITY, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF IMMORTALITY NOR MORTALITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
The third law of thermodynamics states that the entropy of a closed system at thermodynamic equilibrium approaches a constant value when its temperature approaches absolute zero. This constant value cannot depend on any other parameters characterizing the system, such as pressure or applied magnetic field. At absolute zero (zero kelvins) the system must be in a state with the minimum possible energy.
Entropy is related to the number of accessible microstates, and there is typically one unique state (called the ground state) with minimum energy.^[1]^ In such a case, the entropy at absolute zero will be exactly zero. If the system does not have a well-defined order (if its order is glassy, for example), then there may remain some finite entropy as the system is brought to very low temperatures, either because the system becomes locked into a configuration with non-minimal energy or because the minimum energy state is non-unique. The constant value is called the residual entropy of the system.^[2]^
In physics, physical chemistry and engineering, fluid dynamics is a subdiscipline of fluid mechanics that describes the flow of fluids---liquids and gases. It has several subdisciplines, including aerodynamics (the study of air and other gases in motion) and hydrodynamics (the study of liquids in motion). Fluid dynamics has a wide range of applications, including calculating forces and moments on aircraft, determining the mass flow rate of petroleum through pipelines, predicting weather patterns, understanding nebulae in interstellar space and modelling fission weapon detonation.
Fluid dynamics offers a systematic structure---which underlies these practical disciplines---that embraces empirical and semi-empirical laws derived from flow measurement and used to solve practical problems. The solution to a fluid dynamics problem typically involves the calculation of various properties of the fluid, such as flow velocity, pressure, density, and temperature, as functions of space and time.
Before the twentieth century, hydrodynamics was synonymous with fluid dynamics. This is still reflected in names of some fluid dynamics topics, like magnetohydrodynamics and hydrodynamic stability, both of which can also be applied to gases.^[1]^
In ufology, a close encounter is an event in which a person witnesses an unidentified flying object (UFO). This terminology and the system of classification behind it were first suggested in astronomer and UFO researcher J. Allen Hynek's 1972 book The UFO Experience: A Scientific Inquiry.[1] Categories beyond Hynek's original three have been added by others but have not gained universal acceptance, mainly because they lack the scientific rigor that Hynek aimed to bring to ufology.[2]
Sightings more than 150 metres (500 ft) from the witness are classified as daylight discs, nocturnal lights or radar/visual reports.[3] Sightings within about 150 metres (500 ft) are subclassified as various types of close encounters. Hynek and others argued that a claimed close encounter must occur within about 150 metres (500 ft) to greatly reduce or eliminate the possibility of misidentifying conventional aircraft or other known phenomena.[4]
Hynek's scale became well known after being referenced in a 1977 film, Close Encounters of the Third Kind, which is named after the third level of the scale. Promotional posters for the film featured the three levels of the scale, and Hynek himself makes a cameo appearance near the end of the film.
https://www.independent.co.uk/tech/project-star-gate-cia-central-intelligence-agency-a7534191.html What is "remote coordinate viewing" .... and "how do I get on the payroll?
Maybe if I waste some more time writing about "the perpetual motion machine" and the absolute simplicity of the duality of that and of course, the First Law, you know "an object in motion tends to stay in motion, unless opposed by an equal an opposite force--either that or some kind of mass hysteria against the idea that things can just keep on going and going and going without any kind of propulsion.
It's things like "the air we breathe" and the course our rockets veer the Holy vessel of all humanity off by "just a smidgen" that sort of remind me what "equal and opposite force" mean, in sum and total, of all the things we've done and all the things we will ever do.
that's not fiction; that remote cooridate viewing thing; they actually "had a program investigating psychic powers--like "we give you longitude and latitude and you "scry" look into a crystall ball and tell me if you can see what's there. honestly; icalled it "on the payroll" a way to pay people for being ... "over their head on the floor about the hub of dark.fail
Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
This is an interesting and valuable study that uses multiple approaches to understand the role of bursting involving voltage-gated calcium channels within the mediodorsal thalamus in the sedative-hypnotic effects of alcohol. Given its unique functional roles and connectivity pattern, the idea that the mediodorsal thalamus may have a fundamental role in regulating alcohol-induced transitions in consciousness state would be both important for researchers investigating thalamocortical dynamics and more broadly interesting for understanding brain function. In addition, the author's examination of the role of the voltage-gated calcium channel Cav3.1 provides some evidence that burst-firing mediated by this channel in the thalamus is functionally important for behavioral-state transitions. While many previous studies have suggested an analogous role for sleep-state regulation, the evidence for an analogous role of this type of bursting in sedative-induced transitions is more limited. Despite the importance of these results, however, there is some concern that the manipulations and recording approaches employed by the authors may affect other thalamic nuclei adjacent to the MD, such as the central lateral nucleus, which has also been implicated in controlling state transitions. The evidence for a specific role of the mediodorsal thalamus is therefore somewhat incomplete, and so additional validation is needed.
Strengths:
This study employs multiple, complementary research approaches including behavioral assays, sh-RNAbased localized knockdown, single-unit recordings, and patterned optogenetic interventions to examine the role of activity in the mediodorsal thalamus in the sedative-hypnotic effects of alcohol. Experiments and analyses included in the manuscript generally appear well conceived and are also generally well executed. Sample sizes are sufficiently large and statistical analysis appears generally appropriate though in some cases additional quantification would be helpful. The findings presented are novel and provide some interesting insight into the role of the thalamus as well as voltage-gated calcium channels within this region in controlling behavioral state transitions induced by alcohol. In particular, the observed effects of selective knockout along with recordings in total knockout of the voltage-gated calcium channel, Cav3.1, which has previously been implicated in bursting dynamics as well as state transitions, particularly in sleep, together suggest that the transition of thalamic neurons to a bursting pattern of firing from a more constant firing is important for transition to the sedated state produced by ethanol intoxication. While previous studies have similarly implicated Cav3.1 bursting in behavioral state transitions, the direct optogenetic interventions and single-unit recordings provide valuable new insight. These findings may also have interesting implications for the relationship between sleep process disruption associated with ethanol dependence, although the authors do not appear to examine this directly or extensively discuss these implications of their findings.
Weaknesses:
A key claim of the study is that the mediodorsal thalamus is specifically important for the sedative-hypnotic effect of ethanol and that a transition to a bursting pattern of firing in this circuit facilitates these effects due to a loss of a more constant tonic firing pattern. Despite the generally clear observed effects across the included experiments, however, the evidence presented does not fully support that the mediodorsal thalamus, in particular, is involved. This distinction is important because some previous studies have suggested that another thalamic nucleus which is very close to the mediodorsal thalamus, the central-lateral thalamus, has previously been suggested to play a role in preventing sedative-induced transitions. Despite its proximity to the mediodorsal thalamus, the central-lateral thalamus has a substantially different pattern of connectivity so distinguishing which region is impacted is important for understanding the findings in the manuscript. While sh- RNA knockdown appears to be largely centered in the mediodorsal thalamus in the example shown, (Figure 2) this is rather minimal evidence and it is also not well explained (indeed, the relevant panels do not even appear to be referenced in the text of the manuscript) and the consistency of the knockdown targeting is not quantified. Additional evidence should be provided to validate this approach. Similarly, while an example is shown for the expression of ChR2 (Fig. 5) there seems to be some spread of expression outside of the mediodorsal thalamus even in his example raising a concern about how regionally specific this effect.
The recordings targeting the mediodorsal thalamus could provide evidence of a direct association between changes in activity specifically in this part of the thalamus with the behavioral measures but there are currently some issues with making this link. One difficulty is that, although lesions are shown in Figure S5 to validate recording locations, this figure is relatively unclear and the examples appear to be taken from a different anterior/posterior location compared to the reference diagram. A larger image and improved visualization of the overall set of lesion locations that includes multiple anterior/posterior coronal sections would be helpful. Moreover, even for these example images, it is difficult to evaluate whether these are in the mediodorsal thalamus, particularly given the small size of the image shown. Ideally, an example image that is more obviously in the mediodorsal thalamus would also be included. Finally, an assessment of the relationship between the approximate locations of recorded neurons across the tetrode arrays and the behavioral measures would be very helpful in supporting the unique role of the mediodorsal thalamus. The lack of these direct links, in combination with the histological issues, reduces the insight that can be gained from this study.
In addition to the key experimental issues mentioned above, there are often problems in the text of the manuscript with reasoning or at least explanation as well as numerous minor issues with editing. The most substantial such issue is the lack of clarity in discussing the mediodorsal thalamus and other adjacent thalamic nuclei, such as the central-lateral nucleus, in the author's discussion of previous findings. Given that at last one of the manuscripts cited by the authors (Saalman, Front. Sys. Neuro. 2014) has directly claimed that central-lateral, rather than the mediodorsal, thalamus is important for arousal regulation related to a conscious state, this distinction should be addressed clearly in the discussion rather than papered over by grouping multiple thalamic nuclei as being medial. As part of this discussion, it would be important to consider additional relevant literature including Bastos et al., eLife, 2021 and Redinbaugh et al., Neuron, 2020 which are quite critical but currently do not appear to be cited. Considering additional literature relevant to the function of the mediodorsal thalamus would also be beneficial. While the methods employed generally seem sound, the description in the methods section is lacking in detail and is often difficult to follow. Analysis methods such as the burst index appear to only be given a brief explanation in the text and appear not to be mentioned in the methods section. Similarly, the staining method used in Figure 2 does not appear to be described in the methods section. The most substantial case is for the UMAP approach used in Figure 4-E which does not appear to be described in the methods or even described in the main text. The lack of detailed descriptions makes it difficult to evaluate the applicability and quality of the experimental and analytical approaches. Citations justifying the use of methods such as the approach to separate regular spiking and narrow spiking neuron subtypes are also needed.
Beyond the problems with content and reasoning discussed above, there are also some relatively minor issues with the clarity of writing throughout the paper (for example, in the abstract the authors refer to "the ethanol resistance behavior in WT mice" but it is difficult to parse what they mean by this statement. Similarly, the next sentence "These results support that the maintenance..." while clearer, is not well phrased. Though individually minor, issues like this re-occur throughout the manuscript and sometimes make it difficult to follow so the text should be revised to correct them. There are also some problems with labels such as the labels of A1/A2 in Figure 4, which appear to be incorrect. Also, S7 has no label] on the B panels. Finally, some references are not included (only a label of [ref]).
Reviewer #2 (Public Review):
In the current study, Latchoumane and collaborators focus on the Cav3.1 calcium channels in the mediodorsal thalamic nucleus as critical players in the regulation of brain-states and ethanol resistance in mice. By combining behavioural, electrophysiological, and genetic techniques, they report three main findings. First, KO Cav3.1 mice exhibit resistance to ethanol-induced sedation and sustained tonic firing in thalamocortical units. Second, knocked-down Cav3.1 mice reproduce the same behaviour when the mediodorsal, but not the ventrobasal, thalamic nucleus is targeted. Third, either optogenetic or electric stimulation of the mediodorsal thalamus reduces ethanol-induced sedation in control animals.
Overall, the study is well designed and performed, correctly controlled for confounds, and properly analysed. Nonetheless, it is important to address some aspects of the report. The results support the conclusions of the study. These results are likely to be relevant in the field of systems neuroscience, as they increase the molecular evidence showing how the thalamus regulates brain states.
Reviewer #1 (Recommendations For The Authors):
Aside from the additional quantification and clarification of the analysis discussed in the weakness section, in general, the experiments included in the manuscript seem reasonable. However, I would suggest one additional experiment as well as one control, both of which are relatively straightforward optogenetic experiments, that I feel would be helpful to further improve the study. First, as the authors note, the optogenetic interventions used do not directly address the relevance of the changes in bursting patterns observed in the knockout (KO), which are by far the most robust effect, with the changes in alcohol sensitivity. One approach that could help address this would be to use patterned suppression via inhibitory opsins (e.g. halorhodopsin) to "rescue" the periods of inhibition associated with bursting in the KO. Localizing this inhibition to the mediodorsal thalamus would also lend further credence to their claim that this nuclei is the relevant circuit for their observed effects. For the control, tonic activation of the ventrobasal nucleus, as the authors did for the mediodorsal nucleus, would be beneficial to rule out the possibility that the observed effect would occur with any thalamic nucleus. In addition to these experiments, I did not note the strategy for sharing data obtained through this study so this should be added.
R1 – 1: A key claim of the study is that the mediodorsal thalamus is specifically important for the sedative-hypnotic effect of ethanol and that a transition to a bursting pattern of firing in this circuit facilitates these effects due to a loss of a more constant tonic firing pattern. Despite the generally clear observed effects across the included experiments, however, the evidence presented does not fully support that the mediodorsal thalamus, in particular, is involved. This distinction is important because some previous studies have suggested that another thalamic nucleus which is very close to the mediodorsal thalamus, the central-lateral thalamus, has previously been suggested to play a role in preventing sedative-induced transitions. Despite its proximity to the mediodorsal thalamus, the central-lateral thalamus has a substantially different pattern of connectivity so distinguishing which region is impacted is important for understanding the findings in the manuscript.
R1-A1: The reviewer is right that CL has been pointed as another candidate structure with causal influence on arousal and consciousness. We have focused our efforts in including only recording single units that were from tetrode located in the MD specifically using the lesion code we explain in the method section and in response to R1 question#3. We also produced a quantification of Cav3.1 knock-down that clearly demonstrates that the KD experiment was itself specific to MD, bilaterally, and that CL to CM were minimally impacted by the knock-down process (Fig. 2C and D). Moreover, the optogenetic (fiber incidence was 30 degrees guaranteeing a central coverage rather than lateral; Fiber optic NA = 0.22) and electric stimulation (bipolar twisted electrodes, 50uA) experiments were also very selective and specific to the MD (Fig.S5). It remains clear that MD might not be the sole structure involved in the brain state control towards sedation and “anesthetic states”, and CL might be a significant contributor as well, however, we show that CL manipulations were rather irrelevant in our experiments (Fig. 2, S5, S9 and S11).
R1-2: While sh-RNA knockdown appears to be largely centered in the mediodorsal thalamus in the example shown, (Figure 2) this is rather minimal evidence and it is also not well explained (indeed, the relevant panels do not even appear to be referenced in the text of the manuscript) and the consistency of the knockdown targeting is not quantified. Additional evidence should be provided to validate this approach.
R1-A2: In order to address this important question, we have created an additional panel quantification to fig2D. We have then quantified the intensity per area of Cav3.1 expression in sub zones of 4 regions of interest: MD (left, right; 2 subzones each), Centro Medial (CM; 1 subzones in total), Centrolateral/Paraventricular nucleus (CL/PCN; left, right; 2 subzones each) and the submedial nucleus (SMT; left, right; used as a control for the intensity normalization; 1 subzones in total). This panel clearly illustrates that MD was knocked-down bilaterally (p<0.001). Moreover, CM (p<0.05) and CL (p<0.01) were also partially and unilaterally knocked down, as well. This analysis confirms that our KD had a high specificity to MD.
We added the relevant figure caption and text:
[Result section, Cav3.1 silencing in the MD, but not VB, increased ethanol resistance in mice, paragraph 3]
“We then characterized the change in Cav3.1 expression following the shControl and shCav3.1 knockdown injections in three test regions MD (left and right), CM (centromedial nucleus) and CL (centrolateral nuclei, left and right side) and a negative control region SMT (submedial thalamic nuclei, left and right side). The average intensity was obtained from two coronal brain slices for each mice used in the experiment (see Methods sections, Cav3.1 Intensity quantification). Our results show that the targeting of the knockdown was very specific to the bilateral MD (p<0.001; Fig. 2D). We noted that the CM (p<0.05) and a marginal unilateral knock-down of the CL were also observed (p<0.01). Notably, we tested the correlation between the level of knock-down in MD and the total time in LOM and observed a significant association (Fig. 2D inset; R = 0.599, p = 0.018). This result highlights that the Cav3.1 knock-down was specific to MD and with an intensity associated with ethanol-induced loss of motion.”
R1-3: One difficulty is that, although lesions are shown in Figure S5 to validate recording locations, this figure is relatively unclear and the examples appear to be taken from a different anterior/posterior location compared to the reference diagram. A larger image and improved visualization of the overall set of lesion locations that includes multiple anterior/posterior coronal sections would be helpful. Moreover, even for these example images, it is difficult to evaluate whether these are in the mediodorsal thalamus, particularly given the small size of the image shown. Ideally, an example image that is more obviously in the mediodorsal thalamus would also be included. Finally, an assessment of the relationship between the approximate locations of recorded neurons across the tetrode arrays and the behavioral measures would be very helpful in supporting the unique role of the mediodorsal thalamus.
R1-A3: Related to fig.S5, we re-distributed the position of the recordings from the tetrode electrode burned positions over 3 representative coronal planes that best represent the implant positions. We also provided additional snapshots of tetrode location. To identify the positions of four tetrodes in each animal, we encoded the positions with different electrical lesion strategies as follows: 1 lesion(tetrode 1), 2 lesions while we redrew the tetrode with 100 um interval (tetrode 2), 3 lesions with 200um interval (tetrode 3), 4 lesions with 50um intervals (tetrode4). Tetrodes that were found outside of the MD delimited region were discarded post analysis. A straight relationship between the closeness of the electrode is unfortunately not possible for tetrode recording, a straight silicone probe which maintains the spatial spacing in recording would have been a better approach in that case, but unfortunately, it was not performed in our study.
R1-4: In addition to the key experimental issues mentioned above, there are often problems in the text of the manuscript with reasoning or at least explanation as well as numerous minor issues with editing. The most substantial such issue is the lack of clarity in discussing the mediodorsal thalamus and other adjacent thalamic nuclei, such as the central-lateral nucleus, in the author's discussion of previous findings. Given that at last one of the manuscripts cited by the authors (Saalman, Front. Sys. Neuro. 2014) has directly claimed that central-lateral, rather than the mediodorsal, thalamus is important for arousal regulation related to a conscious state, this distinction should be addressed clearly in the discussion rather than papered over by grouping multiple thalamic nuclei as being medial. As part of this discussion, it would be important to consider additional relevant literature including Bastos et al., eLife, 2021 and Redinbaugh et al., Neuron, 2020 which are quite critical but currently do not appear to be cited. Considering additional literature relevant to the function of the mediodorsal thalamus would also be beneficial.
R1-A4: We thank the reviewer for his comments and suggestions. We agree that the added references mentioned by the reviewers are highly relevant and should be integrated in the manuscript. We have integrated the above-mentioned references and further developed on the discussion on the role of MD relative to other thalamic nuclei (ILN and CL in particular). We believe that this better-referenced and clarified text does improve the manuscript greatly.
[introduction section, paragraph 3]
“The centrolateral (CL) thalamic nucleus has been implicated in the modulation of arousal, behavior arrest 31, and improvement of level of consciousness during seizures 32. Notably, the direct electrical stimulation of the intralaminar nuclei (ILN) and, in particular CL, promoted hallmarks of arousal and awakening in primate under propofol and ketamine propofol anesthesia.”
[Discussion section, paragraph 1]
“In this work, we identified that the neural activity in MD plays a causal role in the maintenance of consciousness. Whole body Cav3.1 KO and MD-specific Cav3.1 KD mice showed resistance to loss of consciousness induced by hypnotic dose of ethanol. In WT mice, MD neurons demonstrated a reduced firing rate in natural (sleep) and ethanol-induced unconscious states compared to awake states. This neural activity reduction was impaired in KO mice. In particular, transition to an unconscious state was accompanied with a switch of firing mode from tonic firing to burst firing in WT mice whereas this modeshift disappeared in KO mice. Finally, optogenetic or electric stimulations of the MD after ethanol injection were sufficient to induce a resistance to loss of motion, supporting that the level of neural firing in the MD is critical to maintain conscious state and delay unconscious state. We showed that the expression of Cav3.1 t-type calcium channels in MD is a cellular modulator associated with this effect.”
[Discussion section, MD is a modulator of consciousness, paragraph 2 and 3]
“The MD is known to innervate limbic region, basal ganglia and medial prefrontal cortex 50 and increased activity in MD might modulate the stability of cortical UP states (e.g. awaken, aroused and attentive states) and synchronization 9,26. Thus, MD might be a major hub involved in cortical state control and brain state stabilization.
Supporting the brain state stabilization theory and the ethanol resistance of Cav3.1 mutants, Choi et al.34 demonstrated that the loss of Cav3.1 T-type calcium channel reduced the bilateral coherence between PFC and MD under ketamine anesthesia and ethanol hypnosis, especially in the delta frequency bands. More importantly, under propofol anesthesia, Bastos et al.35 showed that intralaminar nucleus and MD stimulation lead to increased wake-up subscore and arousal, together with an increased in cortico-cortico and thalamo-cortical slow (delta) frequency power.
In the present study, we observed that MD KD (Fig. 2A), but not VB KD (Fig. S3) of Cav3.1 increased and is associated (Fig. 2D) with ethanol resistance in mice. We found that MD neurons in Cav3.1 mutant mice exhibited tonic firing within range of wakefulness (Fig. 3 and 4), indicative of resistance to ethanol and wake-like brain state. In addition, we found a strong association between the normalized tonic firing in MD and the arousal through brain states (i.e. walk to wake to sleep states), supporting that MD tonic firing could be interpreted both as a thalamic readout and a modulator of the brain state 11 (Fig. 3). Finally, direct optogenetic and electric MD stimulation increased resistance to loss of consciousness in WT mice (Fig.5 and Fig. S10). To our knowledge, this is the first report demonstrating the causal involvement of mediodorsal thalamic nucleus in the modulation of wakefulness and the resistance to ethanol-induced loss of consciousness in mice.”
R1-5: While the methods employed generally seem sound, the description in the methods section is lacking in detail and is often difficult to follow. Analysis methods such as the burst index appear to only be given a brief explanation in the text and appear not to be mentioned in the methods section.
R1-A5: We have added a clear definition in the supplementary method following the original work used:
[Supplementary Method section, Single Unit recording, sorting and analysis, last paragraph]
“The bursting index was derived as described in (Royer et al. 2012). Namely, the burst index was estimated from the spike auto-correlogram (1-ms bin size) by subtracting the mean value between 40 and 50 ms (baseline) from the peak measured between 0 and 10 ms. Positive burst amplitudes were normalized to the peak and negative amplitudes were normalized to the baseline to obtain indexes ranging from −1 to 1.” We also edited its mention in the text for clarity:
[Result section, Lack of Ca3.1 in MD neurons removes thalamic burst in NREM sleep, paragraph 2]
“[…] and a clear reduction in total bursting represented as bursting index (Fig. 3-B; ratio of spikes count <10 ms and >50 ms based on auto-cross-correlogram).”
R1-6: Similarly, the staining method used in Figure 2 does not appear to be described in the methods section.
R1-A6: The staining method can be found in the supplementary method of the paper. [supplementary method, Immunohistochemistry]
R1-7: The most substantial case is for the UMAP approach used in Figure 4-E which does not appear to be described in the methods or even described in the main text.
R1-A7: Regarding the method, the UMAP approach is described in the supplementary method document [Uniform Manifold Approximation and Projection (UMAP)]. We believe that only a succinct description was needed here considering the extent of the analysis. Regarding the inserts in the main text, we agree that the main text was lacking the description of these results and we have amended the main text to reflect a clear description of this result and what it entails. The following paragraph was added:
[Result section, Under ethanol, MD neurons lacking Cav3.1 show no burst and a wake state-like neural activity, second to last paragraph]
“Finally, we asked whether the firing modes and properties (tonic firing rate, burst firing rate; see supplementary methods) of single MD neurons would form distinct qualitative representation of “brain stages” using a lowered dimensional UMAP representation (Uniform Manifold Approximation and Projection42 ). We observed that for awake and active (i.e. walk), the brain state representation formed two adjacent clusters that confounded both wild and mutant neurons (Fig. 4E, left panel). The REM and NREM states, the wild type neurons formed 2 additional interconnected clusters, whereas the mutant neurons tend to overlap with the clusters attributed to the “awake” brain state (Fig. 4E, second to left panel). Ethanol induced fLOM, similarly to REM and NREM clusters, was distinct from awake clusters in wild type mice and overlapped with the NREM clusters (Fig. 4E, third to left panel). Here also, mutant MD neurons showed overlap with the awake clusters rather than the “low consciousness” brain states. These results indicate that the firing mode and properties could define a brain state representation that shows distinctions in levels of consciousness. Moreover, the mutant showed a representation of “low consciousness” states overlapping with wild type “awake” states consistent with the hypothesis of resistance to loss of consciousness.”
R1-8: Citations justifying the use of methods such as the approach to separate regular spiking and narrow spiking neuron subtypes are also needed.
R1-A8: We have added two references related to the observation of the two subpopulations of spiking neurons [Schiff and Reyes, 2012; Destexhe, 2008].
R1-9: Beyond the problems with content and reasoning discussed above, there are also some relatively minor issues with the clarity of writing throughout the paper (for example, in the abstract the authors refer to "the ethanol resistance behavior in WT mice" but it is difficult to parse what they mean by this statement.
R1-A9: We addressed this issue by editing and revising the manuscript for clarity and flow.
R1-10: Similarly, the next sentence "These results support the maintenance..." while clearer, is not well phrased. Though individually minor, issues like this re-occur throughout the manuscript and sometimes make it difficult to follow so the text should be revised to correct them.
R1-A10: We thank the reviewer for highlighting this point. We have edited the overall text to improve clarity and flow.
[abstract]
These results suggest that maintaining MD neural firing at a wakeful level is sufficient to induce resistance to ethanol-induced hypnosis in WT mice.
R1-11: There are also some problems with labels such as the labels of A1/A2 in Figure 4, which appear to be incorrect.
R1-A11: We noted this issue and have rectified the figure for clarity.
R1-12: Also, S7 has no label on the B panels.
R1-A12: We thank the reviewer for pointing out this lack. We have added the y-label on the panel for clarity.
R1-13: Finally, some references are not included (only a label of [ref]).
R1-A13: We have completed the missing reference and thank the reviewer for pointing that out.
Additional comments
R1-14: Aside from the additional quantification and clarification of the analysis discussed in the weakness section, in general, the experiments included in the manuscript seem reasonable. However, I would suggest one additional experiment as well as one control, both of which are relatively straightforward optogenetic experiments, that I feel would be helpful to further improve the study. First, as the authors note, the optogenetic interventions used do not directly address the relevance of the changes in bursting patterns observed in the knockout (KO), which are by far the most robust effect, with the changes in alcohol sensitivity. One approach that could help address this would be to use patterned suppression via inhibitory opsins (e.g. halorhodopsin) to "rescue" the periods of inhibition associated with bursting in the KO.
R1-A14: Here the reviewer proposes an interesting experiment which we have attempted to perform, however, poses several technical challenges. First, the KO do not have burst firing as they are depleted from Cav3.1 low-threshold calcium channel. Therefore, under ethanol, even if there might exist a rhythmic inhibition that activates Cav3.1 channels and causes a rebound burst, the KO are unable to have it. Therefore, an optogenetic inhibition would only accentuate the total inhibition and could potentially induce an overall decrease in MD firing, resulting in an increase in LOM features. Alternatively, we showed that in a WT with low ethanol dose (where LOM induction is harder), the increased rhythmic inhibition does indeed increase significantly LOM duration and marginally decreases latency to LOM (Fig. S12), indicating that increased inhibition could indeed explain the hypothesis: “ the stronger the decrease in MD firing, the faster and longer the LOM.” The only caveat of using WT here is that optogenetic inhibition might also include rebound burst post-inhibition. Injecting bursts only did not alter the response to ethanol (Fig. S10). These results point to the role of loss of firing in MD as a main factor for LOM, and potentially the contribution of burst necessitating a concurrent inhibition/loss of firing.
We agree that inhibition in KO would further validate this hypothesis, controlling for the role of burst. We regret that we are not in the capacity to perform additional experiments involving the KO mice.
R1-15: For the control, tonic activation of the ventrobasal nucleus, as the authors did for the mediodorsal nucleus, would be beneficial to rule out the possibility that the observed effect would occur with any thalamic nucleus.
R1-A15: We agree with the reviewer that we could have added an additional region control to the gain/loss of function experiments. We would even go further as to suggest that a better control nucleus would be a high order nucleus such as PO or an unrelated sensory relay nucleus such as LGN. VB being a motor relay nucleus, could also mediate movement initiation, which could be hard to interpret. Since the complete control study for all thalamic nuclei Cav3.1 KD is outside the scope of this study, we opted not to redo these experiments and keep the focus of the manuscript on the manipulation of MD activity rather than the various available thalamic nuclei. We also do not claim that MD is the sole center able to initiate a switch in the loss of consciousness, and a more in-depth study on that matter would be clearly needed.
R1-16: In addition to these experiments, I did not note the strategy for sharing data obtained through this study so this should be added.
R1-A16: We have uploaded data and code for most figures at the following repository and provided a clearer statement regarding data sharing. We thank the reviewer for pointing out this missing element.
The link for the repository is the following:
It contains:
- Excel spreadsheet file of all behavior values, including the newly quantified Cv3.1 expression in MD/CL/SMT
- Excel spreadsheet follow-up of all MD cells (single unit; tetrode) analyzed
- Folders for all groups studied with representative figures showing EEG power over time and normalized activity (WT vs KO for 2, 3 and 4 g/kg; MDshKD vs shCTR, VBshKD vs shCTR; CHR2 NOSTIM vs STIM; ESTIM Groups and ARCH NOSTIM vs STIM)
- A1G LORRvsLOM and OPEN FIELD Matlab data
- Matlab and ImageJ Codes: single unit analysis, characterization, brain state characterization, sleep stages, LOM, open field analysis and statistical analysis.
We have added the data sharing subsection in the acknowledgements:
“Part of the analyzed data and codes are available on the open access platform, mendeley:
Latchoumane, Charles-francois (2024), “Mediodorsal thalamic nucleus mediates resistance to ethanol through Cav3.1 T-type Ca2+ regulation of neural activity”, Mendeley Data, V1, doi: 10.17632/7fr427426m.1
Additional data (large size recording and images) can be provided upon reasonable requests.”
Reviewer #2 (Recommendations For The Authors):
R2-1. Consciousness is a contentious subject. Even in humans, there is still intense research on the topic, not to mention animals, about which we still know very little. Moreover, consciousness is not quantified in this study, as there is no standard metric to do so. Accordingly, talking about 'modulation', 'transition', ́level ', or 'reduction' of consciousness can be misleading. Hence, it is probably safer to strictly refer to brain-states and/or stages of the sleep-wake cycle in this study and reframe it entirely around these concepts.
R2-A1. The reviewer points to an important point and we appreciate this highlight. Agreeing that the definition of consciousness is rather loose and arguably difficult to pinpoint. Here, we settle on a definition that relies on the loss of motion and loss of righting reflex. This definition is widely accepted as the “verified” state in which the absence of responsiveness (to continuous stimuli, inducing reflex or discomfort) is observed and uninterrupted by jerks and spurious movements. Additional metrics needed would be the recording of EMG to quantify atonia and EEG to the settling of a dominantly slow-wave frequency (~4 Hz; ethanol-induced sedation at theta rhythm), as shown in Fig S1A. The driver of this 4Hz frequency and its correlation has been investigated previously (e.g. Choi et al, PNAS, 2012), leading to the accepted link between LOM/LORR and loss of consciousness. Our data present the advantage of showing single neuron recordings and that LOM is a state where the lowest firing activity is present (Fig S7AB) and comparable to deep sleep state activity (Fig3D). The first LOM is the most important as it highlights the deepest loss of consciousness before the ethanol starts to be metabolized and cleared, which would be consistent between animals.
As a result, we have edited the manuscript to clarify all mentions related to brain states and states of unconsciousness.
R2-2. It is not clear why the authors focus on the mediodorsal nucleus. This should be better explained in the introduction and developed in the discussion.
R2-A2. This comment converges with the Reviewer 1 comments and we are addressing this lack in the discussion as suggested. We have addressed it with this previous comment and believe it is now clearer.
R2-3. The discussion mentions that 'increased activity in MD might modulate the stability of cortical UP state and synchronization' (pg 21). This point should be either further developed and put into context, or removed. In its current state, it does not seem to contribute much to the discussion of results.
R2-A3. We understand that the working “UP state” might not be clear enough. We have modified this sentences as follows to clarify that UP state could be either a state of where the animal is awake, aroused or attentive:
[Discussion section, MD is a modulator of consciousness, first paragraph]
“The MD is known to innervate limbic region, basal ganglia and medial prefrontal cortex 50 and increased activity in MD might modulate the stability of cortical UP states (e.g. awaken, aroused and attentive states) and synchronization 9,26. Thus, MD might be a major hub involved in cortical state control and brain state stabilization.“
R2-4. The discussion states that 'mutant mice did not exhibit a decreased arousal level (i.e. increased locomotor activity)' (pg 23). This is confusing as decreased arousal should be reflected in decreased locomotor activity.
R2-A4. We understand that the formulation of this sentence may be confusing and we have edited this portion of the text to improve quality in the revised version of the manuscript. To clarify, mutant mice do not exhibit reduced or increased arousal (not quantified, just observational), they do have a phenotypic hyperlocomotion. This comes in contrast with a lower basal firing rate in the MD, which in our interpretation, is not synonymous with lower arousal. We believe that the relative change in MD determines the change in arousal, and that the absolute firing is not indicative of arousal in itself, only in comparison.
[Discussion section, The lower variability in MD Firing reflects Ethanol Resistance in Cav3.1 mutant mice, paragraph 2]
“Mutant RS neurons in MD showed an overall lower excitability and variability of firing in various natural conscious and unconscious states compared to wild type mice. Remarkably, Cav3.1 mutant mice exhibited a clear increased locomotor activity and an increased resistance to ethanol. The general lower firing rate and the high “arousal” observed in mutant mice suggests that the relative change from state to state in tonic firing in MD, and not the absolute value of firing, might be a better correlate of change in brain state in the mice.”
R2-5. The methods (pg 27) state that two genetic backgrounds (129/svjae and C57BL/6J ) were used in the study. Authors should show whether there were significant differences between those backgrounds in the key parameters assessed in the study (particularly resistance to ethanol sedation).
R2-A5. As mentioned in the method section, we only used the F1-background mice, which are the firstgeneration offspring produced by crossing 129/svjae and C57BL/6J strains. To produce F1 KO mice, we kept the heterozygote mice in two strains. We unfortunately did not study the particular difference of the respective KO of these two backgrounds; however, the pure C57BL/6J KO has been used in other studies by our group (Kim et al 2001; Na et al, 2008; Park et al., 2010). The F1 background allows us to work with mice that are less aggressive and can be handled with less inherent stress.
R2-6. It would be convenient to produce a supplementary figure associated with Figure 1C to show the same data with averages per mouse. That is, 9 points for control and 9 points for KO mice. This also applies to all cases where data is not presented per mouse but pooled between animals.
R2-A6. We have added a panel C in Figure S1, to show the scatter values for all the mice corresponding to the figure 1C. We have also generalized this presentation for all behavior graphics showing all the animals in the scatter plot next to the boxplot. We believe that this presentation increases further the transparency of the manuscript. We have then added the scatter plot for all mice in figure Fig1, Fig2, Fig5, Fig.S2, Fig.S3, Fig.S10 and Fig.S12.
R2-7. It would be informative to make a supplementary figure associated with Figure 1D to compare baseline raw activity levels (i.e., baseline walking recording) between control and KO mice. That is, do KO and control mice cover comparable distances and at similar speeds during baseline conditions? Figure 1D and Figure 4A suggest that the variability of locomotor activity is larger in KO mice. Hence, this parameter should be quantified and reported.
R2-A7. We thank the reviewer for this comment. We strived to answer to this question in the manuscript in two ways:
- We first measure the overall hyperlocomotion of the mice using the open field total distance parkoured in our mice cohorts (FigS4C). We did observe that the KO mutant showed hyperlocomotion, but not MD or VB knock-down mice. Which indicates that the hyperlocomotion component is not specific to the two thalamic nuclei studied.
- Using the forced walking task, we impose on the animal to keep a steady pace of roughly 6cm/s. This assay allows to normalize the general walking behavior to a relatively fixed pace making it comparable for all animals.
The reviewer suggested reporting the mean and variance in walking of WT and KO during baseline (prior to the ethanol I.P. injection). We believe that the two points mentioned above are sufficient to describe in a more quantitative way the WT vs KO locomotion differences. Moreover, by construction the normalized locomotion on the forced walking task will return similar means for the baseline, the standard deviation would, however, potentially show differences but would remain inconclusive.
R2-8. The legend in Figure 1 states that 'the loss of consciousness is evaluated using normalized moving index using either video analysis (differential pixel motion), on- head accelerometer-based motion, or neck electromyograms'. Authors should clarify whether these methods are equivalent and support it with data.
R2-A8. We understand the reviewer point and we have made a few modifications to the method description aligning better with what was done. For most mice, video analysis was used to obtain the moving index. When video recording was not available (2 mice), we had an accelerometer attached to the animal’s head stage which helped us derive a moving index that was similar to the video moving index. The neck electromyogram was rather used for animals implanted with the tetrodes to identify sleep stages based on local field potential frequency and muscle tone. We have then clarified the method for this matter and Figure 1 to avoid this confusion. Since no concurrent recording of both video and accelerometer was performed, we do not have the data to compute the correlation between the two measures, however, no noticeable deviation from loss of motion was observed between the two methods. We realize that this may be a weak argument, however, our observations showed that video and accelerometers returned very similar timings for loss of motion (only a few comparative instances insufficient to present a statistical comparison).
R2-9. How were spike bursts defined? The authors should try different criteria and verify the consistency of results.
R2-A9 For in vivo single unit recording, we opted for a definition that is validated from our works and others as a silencing of at least 100 ms followed by a minimum of 3 spikes with:
- First spike pairs interspike interval less than 4 ms
- Remaining spike pairs interspike interval less than 20 ms
We have performed this analysis using a minimum of 2 spikes, and varied silencing periods between 50 and 100ms, without observing significant deviation of the results. As shown in Figure S6B, with this approach we observed that the burst distribution had a majority with <10 spikes per burst. Figure S6C indicated that with a clear distribution of ISI for first spike within 2-4ms as observed in previous works (Desai and Varela, 2021; Alitto et al, 2019), importantly, not clearly capped at 4 ms, showing that the range for the first ISI might indeed be lower than 4ms for thalamic burst. Within burst spike waveforms can become very variable and the choice of 3 over 2 spikes minimum per burst stems from the aim to reduce false positive detection of ultra-short bursts, which in single unit recording remains controversial (Gray et al. 1995).
Minor:
R2-10: Figure 4A2 'Cav3.1(+/+)' should presumably be Cav3.1(-/-).
R2-A10: this is correct and we have corrected the figure label [This sentence is ambiguous. What is ‘this’ that is correct?]
R2-11: Figure S2C legend states 'Post-hoc group comparison was performed using.' The sentence seems to be incomplete.
R2-A11: We have completed the sentence for clarity.
R2-12: In the methods (pg 29) virus concentration is reported as '107 TU/ul', which probably refers to 10e7.
R2-A12: We have corrected it by superscripting the power 7.
R2-13: Verify Fig 1C1 and correct Y-axis overlap between title and units.
R2-A13: We edited the figure for clarity, thank you.
R2-14: On page 24 there is a '[ref]' that probably stands for (a missing) reference.
R2-A14: the missing reference has been added.
Reviewer #1 (Public review):
Summary:
This is an interesting study on AD(H)D. The authors combine a variety of neural and physiological metrics to study attention in a VR classroom setting. The manuscript is well written and the results are interesting, ranging from an effect of group (AD(H)D vs. control) on metrics such as envelope tracking, to multivariate regression analyses considering alpha-power, gaze, TRF, ERPs, and behaviour simultaneously. I find the first part of the results clear and strong. The multivariate analyses in Tables 1 and 2 are good ideas, but I think they would benefit from additional clarification. Overall, I think that the methodological approach is useful in itself. The rest is interesting in that it informs us on which metrics are sensitive to group effects and correlated with each other. I think this might be one interesting way forward. Indeed, much more work is needed to clarify how these results change with different stimuli and tasks. So, I see this as an interesting first step into a more naturalistic measurement of speech attention.
Strengths:
I praise the authors for this interesting attempt to tackle a challenging topic with naturalistic experiments and metrics. I think the results broadly make sense and they contribute to a complex literature that is far from being linear and cohesive.
Weaknesses:
Nonetheless, I have a few comments that I hope will help the authors improve the manuscript. Some aspects should be clearer, some methodological steps were unclear (missing details on filters), and others were carried out in a way that doesn't convince me and might be problematic (e.g., re-filtering). I also suggested areas where the authors might find some improvements, such as deriving distinct markers for the overall envelope reconstruction and its change over time, which could solve some of the issues reported in the discussion (e.g., the lack of correlation with TRF metrics).
I also have some concerns regarding reproducibility. Many details are imprecise or missing. And I did not find any comments on data and code sharing. A clarification would be appreciated on that point for sure.
There are some minor issues, typically caused by some imprecisions in the write-up. There are a few issues that could change things though (e.g., re-filtering; the worrying regularisation optimisation choices), and there I'll have to see the authors' reply to determine whether those are major issues or not. Figures should also be improved (e.g., Figure 4B is missing the ticks).
Reviewer #3 (Public review):
Summary:
The authors conducted a well-designed experiment, incorporating VR classroom scenes and background sound events, with both control and ADHD participants. They employed multiple neurophysiological measures, such as EEG, eye movements, and skin conductance, to investigate the mechanistic underpinnings of paying attention in class and the disruptive effects of background noise.
The results revealed that individuals with ADHD exhibited heightened sensory responses to irrelevant sounds and reduced tracking of the teacher's speech. Overall, this manuscript presented an ecologically valid paradigm for assessing neurophysiological responses in both control and ADHD groups. The analyses were comprehensive and clear, making the study potentially valuable for the application of detecting attentional deficits.
Strengths:
• The VR learning paradigm is well-designed and ecologically valid.
• The neurophysiological metrics and analyses are comprehensive, and two physiological markers are identified capable of diagnosing ADHD.
• This research provides a valuable dataset that could serve as a benchmark for future studies on attention deficits.
Weaknesses:
• Several results are null results, i.e., no significant differences were found between ADHD and control populations.
• Although the paradigm is well-designed and ecologically valid, the specific contributions or insights from the results remain unclear.
• Lack of information regarding code and data availability.
Reviewer #2 (Public review):
Summary:
This manuscript describes a workflow and software package, SMARTR, for mapping and analyzing neuronal ensembles tagged using activity-dependent methods. They showcase this pipeline by analyzing ensembles tagged during the learned helplessness paradigm. This is an impressive effort, and I commend the authors for developing open-source software to make whole-brain analyses more feasible for the community. Software development is essential for modern neuroscience and I hope more groups make the effort to develop open-source, easily usable packages. However, I do have concerns over the usability and maintainability of the SMARTR package. I hope that the authors will continue to develop this package, and encourage them to make the effort to publish it within either the Bioconductor or CRAN framework.
Strengths:
This is a novel software package aiming to make the analysis of brain-wide engrams more feasible, which is much needed. The documentation for the package and workflow is solid.
Weaknesses:
While I was able to install the SMARTR package, after trying for the better part of one hour, I could not install the "mjin1812/wholebrain" R package as instructed in OSF. I also could not find a function to load an example dataset to easily test SMARTR. So, unfortunately, I was unable to test out any of the packages for myself. Along with the currently broken "tractatus/wholebrain" package, this is a good example of why I would strongly encourage the authors to publish SMARTR on either Bioconductor or CRAN in the future. The high standards set by Bioc/CRAN will ensure that SMARTR is able to be easily installed and used across major operating systems for the long term.
The package is quite large (several thousand lines include comments and space). While impressive, this does inherently make the package more difficult to maintain - and the authors currently have not included any unit tests. The authors should add unit tests to cover a large percentage of the package to ensure code stability.
Why do the authors choose to perform image segmentation outside of the SMARTR package using ImageJ macros? Leading segmentation algorithms such as CellPose and StarMap have well-documented APIs that would be easy to wrap in R. They would likely be faster as well. As noted in the discussion, making SMARTR a one-stop shop for multi-ensemble analyses would be more appealing to a user.
Given the small number of observations for correlation analyses (n=6 per group), Pearson correlations would be highly susceptible to outliers. The authors chose to deal with potential outliers by dropping any subject per region that was> 2 SDs from the group mean. Another way to get at this would be using Spearman correlation. How do these analyses change if you use Spearman correlation instead of Pearson? It would be a valuable addition for the author to include Spearman correlations as an option in SMARTR.
I see the authors have incorporated the ability to adjust p-values in many of the analysis functions (and recommend the BH procedure) but did not use adjusted p-values for any of the analyses in the manuscript. Why is this? This is particularly relevant for the differential correlation analyses between groups (Figures 3P and 4P). Based on the un-adjusted p-values, I assume few if any data points will still be significant after adjusting. While it's logical to highlight the regional correlations that strongly change between groups, the authors should caution ¬ which correlations are "significant" without adjusting for multiple comparisons. As this package now makes this analysis easily usable for all researchers, the authors should also provide better explanations for when and why to use adjusted p-values in the online documentation for new users.
The package was developed in R3.6.3. This is several years and one major version behind the current R version (4.4.3). Have the authors tested if this package runs on modern R versions? If not, this could be a significant hurdle for potential users.
Author response:
Reviewer #1 (Public review):
Weaknesses:
(1) The heatmaps (for example, Figure 3A, B) are challenging to read and interpret due to their size. Is there a way to alter the visualization to improve interpretability? Perhaps coloring the heatmap by general anatomical region could help? We feel that these heatmaps are critical to the utility of the registration strategy, and hence, clear visualization is necessary.
We thank the reviewers for this point on aesthetic improvement, and we agree that clearer visualization of our correlation heatmaps is important. To address this point, we have incorporated the capability of grouping “child” subregions in anatomical order by their more general “parent” region into the package function, plot_correlation_heatmaps(). Parent regions will be visually represented as smaller sub-facets in the heatmaps, and we will be submitting our full revised manuscript with these visual changes.
(2) Additional context in the Introduction on the use of immediate early genes to label ensembles of neurons that are specifically activated during the various behavioral manipulations would enable the manuscript and methodology to be better appreciated by a broad audience.
We thank the reviewers for this suggestion and will be revising parts of our Introduction to reflect the broader use and appeal of immediate early genes (IEGs) for studying neural changes underlying behavior.
(3) The authors mention that their segmentation strategies are optimized for the particular staining pattern exhibited by each reporter and demonstrate that the manually annotated cell counts match the automated analysis. They mention that alternative strategies are compatible, but don't show this data.
We thank the reviewers for this comment. We also appreciate that integration with alternative strategies is a major point of interest to readers, given that others may be interested in compatibility with our analysis and software package, rather than completely revising their own pre-existing workflows.
This specific point on segmentation refers to the import_segmentation_custom()function in the package. As there is currently not a standard cell segmentation export format adopted by the field, this function still requires some data wrangling into an import format saved as a .txt file. However, we chose not to visually demonstrate this capability in the paper for a few reasons.
i. A figure showing the broad testing of many different segmentation algorithms, (e.g., Cellpose, Vaa3d, Trainable Weka Segmentation) would better demonstrate the efficacy of segmentation of these alternative approaches, which have already been well-documented. However, demonstrating importation compatibility is more of a demonstration of API interface, which is better shown in website documentation and tutorial notebooks.
ii. Additionally, showing importation with one well-established segmentation approach is still a demonstration of a single use case. There would be a major burden-of-proof in establishing importation compatibility with all potential alternative platforms, their specific export formats, which may be slightly different depending on post-processing choices, and the needs of the experimenters (e.g., exporting one vs many channels, having different naming conventions, having different export formats). For example, output from Cellpose can take the form of a NumPy file (_seg.npy file), a .png, or Native ImageJ ROI archive output, and users can have chosen up to four channels. Until the field adopts a standardized file format, one flexible enough to account for all the variables of experimental interest, we currently believe it is more efficient to advise external groups on how to transform their specific data to be compatible with our generic import function.
Internally, in collaborative efforts, we have validated the ability to import datasets generated from completely different workflows for segmentation and registration. We intend on releasing this documentation in coming updates on our package website, which we believe will be more demonstrative on how to take advantage of our analysis package, without adopting our entire workflow.
(4) The authors provided highly detailed information for their segmentation strategy, but the same level of detail was not provided for the registration algorithms. Additional details would help users achieve optimal alignment.
We apologize for this lack of detail. The registration strategy depends upon the WholeBrain package for registration to the Allen Mouse Common Coordinate Framework. While this strategy has been published and documented elsewhere, we will be revising our methods to better incorporate details of this approach.
Reviewer #2 (Public review):
Weaknesses:
(1) While I was able to install the SMARTR package, after trying for the better part of one hour, I could not install the "mjin1812/wholebrain" R package as instructed in OSF. I also could not find a function to load an example dataset to easily test SMARTR. So, unfortunately, I was unable to test out any of the packages for myself. Along with the currently broken "tractatus/wholebrain" package, this is a good example of why I would strongly encourage the authors to publish SMARTR on either Bioconductor or CRAN in the future. The high standards set by Bioc/CRAN will ensure that SMARTR is able to be easily installed and used across major operating systems for the long term.
We thank reviewers for pointing out this weakness; long-term maintenance of this package is certainly a mutual goal. Loading an .RDATA file is accomplished by either double-clicking directly on the file in a directory window, or by using the load() function, (e.g., load("directory/example.RData")). We will explicitly outline these directions in the online documentation and in our full revision.
Moreover, we will submit our package to CRAN. Currently, SMARTR is not dependent on the WholeBrain package, which remains optional for the registration portion of our workflow. Ultimately, this independence will allow us to maintain the analysis and visualization portion of the package independently, and allow for submission to a more centralized software repository such as CRAN.
(2) The package is quite large (several thousand lines include comments and space). While impressive, this does inherently make the package more difficult to maintain - and the authors currently have not included any unit tests. The authors should add unit tests to cover a large percentage of the package to ensure code stability.
We appreciate this feedback and will add unit testing to improve the reliability of our package in the full revision.
(3) Why do the authors choose to perform image segmentation outside of the SMARTR package using ImageJ macros? Leading segmentation algorithms such as CellPose and StarMap have well-documented APIs that would be easy to wrap in R. They would likely be faster as well. As noted in the discussion, making SMARTR a one-stop shop for multi-ensemble analyses would be more appealing to a user.
We appreciate this feedback. We believe parts of our response to Reviewer 1, comment 3, are relevant to this point. Interfaces for CellPose and ClusterMap (which processes in situ transcriptomic approaches like STARmap) are both in python, and currently there are ways to call python from within R (https://rstudio.github.io/reticulate/index.html). We will certainly explore incorporating these APIs from R. However, we would anticipate this capability is more similar to “translation” between programming languages, but would not currently preclude users from the issue of still needing some familiarity with the capabilities of these python packages, and thus with python syntax.
(4) Given the small number of observations for correlation analyses (n=6 per group), Pearson correlations would be highly susceptible to outliers. The authors chose to deal with potential outliers by dropping any subject per region that was> 2 SDs from the group mean. Another way to get at this would be using Spearman correlation. How do these analyses change if you use Spearman correlation instead of Pearson? It would be a valuable addition for the author to include Spearman correlations as an option in SMARTR.
We thank reviewers for this suggestion and will provide a supplementary analysis of our results using Spearman correlations.
(5) I see the authors have incorporated the ability to adjust p-values in many of the analysis functions (and recommend the BH procedure) but did not use adjusted p-values for any of the analyses in the manuscript. Why is this? This is particularly relevant for the differential correlation analyses between groups (Figures 3P and 4P). Based on the un-adjusted p-values, I assume few if any data points will still be significant after adjusting. While it's logical to highlight the regional correlations that strongly change between groups, the authors should caution which correlations are "significant" without adjusting for multiple comparisons. As this package now makes this analysis easily usable for all researchers, the authors should also provide better explanations for when and why to use adjusted p-values in the online documentation for new users.
We appreciate the feedback and will more explicitly outline that in our paper, our dataset is presented as a more demonstrative and exploratory resource for readers and, as such, we accept a high tolerance for false positives, while decreasing risk of missing possible interesting findings. As noted by Reviewer #2, it is still “logical to highlight the regional correlations that strongly change between groups.” We will further clarify in our methods that we chose to present uncorrected p-values when speaking of significance. We will also include more statistical detail on our online documentation regarding FDR correction. Ultimately, the decision to correct for multiple comparisons and FDR choice of threshold, should still be informed by standard statistical theory and user-defined tolerance for inclusion of false-positives and missing of false-negatives. This will be influenced by factors, such as the nature and purpose of the study, and quality of the dataset.
(6) The package was developed in R3.6.3. This is several years and one major version behind the current R version (4.4.3). Have the authors tested if this package runs on modern R versions? If not, this could be a significant hurdle for potential users.
We thank reviewers for pointing out concerns regarding versioning. Analysis and visualization capabilities are currently supported using R version 4.1+. The recommendation for R 3.6.3 is primarily for users interested in using the full workflow, which requires installation of the WholeBrain package. We anticipate supporting of visualization and network analysis capabilities with updated packages and R versions, and maintaining a legacy version for the full workflow presented in this paper.
Author response:
The following is the authors’ response to the previous reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
The authors present a new application of the high-content image-based morphological profiling Cell Painting (CP) to single cell type classification in mixed heterogeneous induced pluripotent stem cellderived mixed neural cultures. Machine learning models were trained to classify single cell types according to either "engineered" features derived from the image or from the raw CP multiplexed image. The authors systematically evaluated experimental (e.g., cell density, cell types, fluorescent channels) and computational (e.g., different models, different cell regions) parameters and convincingly demonstrated that focusing on the nucleus and its surroundings contains sufficient information for robust and accurate cell type classification. Models that were trained on mono-cultures (i.e., containing a single cell type) could generalize for cell type prediction in mixed co-cultures, and describe intermediate states of the maturation process of iPSC-derived neural progenitors to differentiation neurons.
Strengths:
Automatically identifying single-cell types in heterogeneous mixed-cell populations holds great promise to characterize mixed-cell populations and to discover new rules of spatial organization and cell-cell communication. Although the current manuscript focuses on the application of quality control of iPSC cultures, the same approach can be extended to a wealth of other applications including an in-depth study of the spatial context. The simple and high-content assay democratizes use and enables adoption by other labs.
The manuscript is supported by comprehensive experimental and computational validations that raise the bar beyond the current state of the art in the field of high-content phenotyping and make this manuscript especially compelling. These include (i) Explicitly assessing replication biases (batch effects); (ii) Direct comparison of feature-based (a la cell profiling) versus deep-learning-based classification (which is not trivial/obvious for the application of cell profiling); (iii) Systematic assessment of the contribution of each fluorescent channel; (iv) Evaluation of cell-density dependency; (v) Explicit examination of mistakes in classification; (vi) Evaluating the performance of different spatial contexts around the cell/nucleus; (vii) Generalization of models trained on cultures containing a single cell type (mono-cultures) to mixed co-cultures; (viii) Application to multiple classification tasks.
I especially liked the generalization of classification from mono- to co-cultures (Figure 4C), and quantitatively following the gradual transition from NPC to Neurons (Figure 5H).
The manuscript is well-written and easy tofollow.
Thank you for the positive appreciation of our work and constructive comments.
Weaknesses:
I am not certain how useful/important the specific application demonstrated in this study is (quality control of iPSC cultures), this could be better explained in the manuscript.
To clarify the importance we have added an additional explanation to the introduction (page 3) and also come back to it in the discussion (page 17).
Text from the introduction:
“However, genetic drift, clonal and patient heterogeneity cause variability in reprogramming and differentiation efficiency10,11. The differentiation outcome is further strongly influenced by variations in protocol12. This can significantly impact experimental outcomes, leading to inconsistent and potentially misleading results and consequently, it hinders the use of iPSC-derived cell systems in systematic drug screening or cell therapy pipelines. This is particularly true for iPSC-derived neural cultures, as their composition, purity and maturity directly affect gene expression and functional activity, which is essential for modelling neurological conditions13,14. Thus, from a preclinical perspective, there is the need for a fast and cost-effective QC approach to increase experimental reproducibility and cell type specificity15. From a clinical perspective in turn, robust QC is required for safety and regulatory compliance (e.g., for cell therapeutic solutions). This need for improved standardization and QC is underscored by large-scale collaborative efforts such as the International Stem Cell Banking Initiative16, which focusses on clinical quality attributes and provides recommendations for iPSC validation testing for use as cellular therapeutics, or the CorEuStem network, aiming to harmonize iPSC practices across core facilities in Europe.”
Text from the discussion:
“Many groups highlight the difficulty of reproducible neural differentiation and attribute this to culture conditions, cultivation time and variation in developmental signalling pathways in the source iPSC material43,44. Spontaneous neural differentiation has previously been shown to require approximately 80 days before mature neurons arise that can fire action potentials and show neural circuit formation. Although these differentiation processes display a stereotypical temporal sequence34, the exact timing and duration might vary. This variation negatively affects the statistical power when testing drug interventions and thus prohibits the application of iPSC-culture derivatives in routine drug screening. Current solutions (e.g., immunocytochemistry, flow cytometry, …) are often cost-ineffective, tedious, and incompatible with longitudinal/multimodal interrogation. CP is a much more cost-effective solution and ideally suited for this purpose. Routine CP-based could add confidence to and save costs for the drug discovery pipeline. We have shown that CP can be leveraged to capture the morphological changes associated with neural differentiation.”
Another issue that I feel should be discussed more explicitly is how far can this application go - how sensitively can the combination of cell painting and machine learning discriminate between cell types that are more subtly morphologically different from one another?
Thank you for this interesting question. The fact that an approach based on a subregion not encompassing the whole cell (the “nucleocentric” approach) can predict cell types equally well, suggests that the cell shape as such is not the defining factor for accurate cell type profiling. And, while clearly neural progenitors, neurons or glia have vastly different cell shapes. We have shown that cells with closer phenotypes such as 1321N1 vs. SH-SY5Y or astrocytes vs. microglia can be distinguished with equal performance. However, triggered by the reviewers’ question, we have now tested additional conditions with more subtle phenotypes, including the classification of 1321N1 vs. two related retinal pigment epithelial cells with much more similar morphology (ARPE and RPE1 cells). We found that the CNN could discriminate these cells equally well and have added the results on page 8 and in Fig. 3D. To address this question from a different angle, we have also performed an experiment in which we changed cell states to assess whether discriminatory power remains high. Concretely, we exposed co-cultures of neurons and microglia to LPS to trigger microglial activation (more subtly visible as cytoskeletal changes and vacuole formation). This revealed that our approach still discriminates both cell types (neurons vs. microglia) with high accuracy, regardless of the microglial state. Furthermore, using a two-step approach, we could also distinguish LPS-treated (assumed to be activated) from unchallenged microglia (assumed to be more homeostatic), albeit with a lower accuracy. This experiment has been added as an extra results section (Cell type identification can be applied to mixed iPSC-derived neuronal cultures regardless of activation state, p12) and Fig. 7c. Finally, we have also added our take on what the possibilities could be for future applications in even more complex contexts such as tissue slice, 3D and live cell applications (page 17-18).
Regarding evaluations, the use of accuracy, which is a measure that can be biased by class imbalance, is not the most appropriate measurement in my opinion. The confusion matrices are a great help, but I would recommend using a measurement that is less sensitive for class imbalance for cell-type classification performance evaluations.
Across all CNNs trained in this manuscript, the sample size of the input classes has always been equalized, ruling out any effects of class imbalance. Nevertheless, to follow the reviewers’ recommendation, we have now used the F-score to document performance as it is insensitive to such imbalance. For clarity, we have now also mentioned the input number (ROIs/class) in every figure.
Another issue is that the performance evaluation is calculated on a subset of the full cell population - after exclusion/filtering. Could there be a bias toward specific cell types in the exclusion criteria? How would it affect our ability to measure the cell type composition of the population?
As explained in the M&M section, filtering was performed based on three criteria:
(1) Nuclear size: values below a threshold of 160, objects are considered to represent debris;
(2) DAPI intensity: values below a threshold of 500 represent segmentation errors;
(3) IF staining intensity: gates were set onto the intensity of the fluorescent markers used with posthoc IF to only retain cells that are unequivocally positive for either marker and to avoid inclusion of double positive (or negative) cells in the ground truth training.
One could argue that the last criterion introduces a certain bias in that it does not consider part of the cell population. However, this is also not the purpose of our pioneering study that aims at identifying unique cell types for which ground truth is as pure and reliable as possible. Not filtering out these cells with a ‘dubious’ IF profile (e.g., cells that might be transitioning or are of a different type) would negatively affect the model by introducing noise. It is correct that the predictions are based only on these inputs and so cells of a subsequent test set will only be classified according to these labels. For example, in the neuronal differentiation experiment (Fig. 6G-H), cells are either characterized as NPC or as neurons, which leaves the transitioning (or undefined) cells in either category. Despite this simplification, the model adequately predicted the increase in neuron/NPC ratio with culture age. In future iterations, one could envision defining more refined cell (sub-)types in a population based on richer post-hoc information (e.g., through cyclic immunofluorescence or spatial single cell transcriptomics) or longitudinal follow-up of cell-state transitions using live imaging. This notion has been added to page 17 of the manuscript.
I am not entirely convinced by the arguments regarding the superiority of the nucleocentric vs. the nuclear representations. Could it be that this improvement is due to not being sensitive/ influenced by nucleus segmentation errors?
The reviewer has a valid point that segmentation errors may occur. However, the algorithm we have used (Stardist classifier), is very robust to nuclear segmentation errors. To verify the performance, we have now quantified segmentation errors in 20 images for 3 different densities and found a consistently low error rate (0.6 -1.6%) without correlation to the culture density. Moreover, these errors include partial imperfections (e.g., a missed protrusion or bleb) as well as over- (one nucleus detected as more) or under- (more nuclei detected as one) segmentations. The latter two will affect both the nuclear and nucleocentric predictions and should thus not affect the prediction performance. In the case of imperfect segmentations, there may be a specific impact on the nucleus-based predictions (which rely on blanking the non-nuclear part), but this alone cannot explain the significantly higher gain in accuracy for nucleocentric predictions (>5%). Therefore, we conclude that segmentation errors may contribute in part, but not exclusively, to the overall improved performance of nucleocentric input models. We have added this notion in the discussion (pages 14-15 and Suppl. Fig. 1E).
GRADCAM shows cherry-picked examples and is not very convincing.
To help convince the reviewer and illustrate the representativeness of selected images, we have now randomly selected for each condition and density 10 images (using random seeds to avoid cherrypicking) and added these in a Suppl. Fig. 3.
There are many missing details in the figure panels, figure legend, and text that would help the reader to better appreciate some of the technical details, see details in the section on recommendations for the authors.
Please see further for our specific adaptations.
Reviewer #2 (Public Review):
This study uses an AI-based image analysis approach to classify different cell types in cultures of different densities. The authors could demonstrate the superiority of the CNN strategy used with nucleocentric cell profiling approach for a variety of cell types classification. The paper is very clear and well-written. I just have a couple of minor suggestions and clarifications needed for the reader.
The entire prediction model is based on image analysis. Could the authors discuss the minimal spatial resolution of images required to allow a good prediction? Along the same line, it would be interesting to the reader to know which metrics related to image quality (e.g. signal to noise ratio) allow a good accuracy of the prediction.
Thank you for the positive and relevant feedback.
The reviewer has a good point that it is important to portray the imaging conditions that are required for accurate predictions. To investigate this further we have performed additional experiments that give a better view on the operating window in terms of resolution and SNR (manuscript page 7-8 and new figure panels Fig. 3B-C). The initial image resolution was 0.325 µm/pixel. To understand the dependency on resolution we performed training and classifications for image data sets that were progressively binned. We found that a two-fold reduction in resolution did not significantly affect the F-score, but further degradation decreased the performance. At a resolution of 6,0 µm/pixel (20-fold binning), the F-score dropped to 0.79±0.02, comparable to the performance when only the DAPI (nuclear) channel was used as input. The effect of reduced image quality was assessed in a similar manner, by iteratively adding more Gaussian noise to the image. We found that above an SNR of 10 the prediction performance remains consistent but below it starts to degrade. While this exercise provides a first impression of the current confines of our method, we do believe it is plausible that its performance can be extended to even lower-quality images for example by using image restoration algorithms. We have added this notion in the discussion (page 14).
The authors show that nucleocentric-based cell feature extraction is superior to feeding the CNN-based model for cell type prediction. Could they discuss what is the optimal size and shape of this ROI to ensure a good prediction? What if, for example, you increase or decrease the size of the ROI by a certain number of pixels?
To identify the optimal input, we varied the size of the square region around the nuclear centroid from 0.6 to 150 µm for the whole dataset. Within the nuclear-to-cell window (12µm- 30µm) the average Fscore is limited, but an important observation is the increasing error and differences in precision and recall with increasing nucleocentric patch sizes, which will become detrimental in cases of class imbalance. The F-score is maximal for a box of 12-18µm surrounding the nuclear centroid. In this “sweet spot”, the precision and recall are also in balance. Therefore, we have selected this region for the actual density comparison experiment. We have added our results to the manuscript (page 9 and 15).
It would be interesting for the reader to know the number of ROI used to feed each model and know the minimal amount of data necessary to reach a high level of accuracy in the predictions.
The figures have now been adjusted so that the number of ROIs used as input to feed the model are listed. The minimal number of ROIs required to obtain high level accuracy is tested in Figure 2C. By systematically increasing the number of input ROIs for both RF and CNN, we found that a plateau is reached at 5000 input ROIs (per class) for optimal prediction performance. This is also documented in the results section page 6.
From Figure 1 to Figure 4 the author shows that CNN based approach is efficient in distinguishing 1321N1 vs SH-SY5Y cell lines. The last two figures are dedicated to showing 2 different applications of the techniques: identification of different stages of neuronal differentiation (Figure 5) and different cell types (neurons, microglia, and astrocytes) in Figure 6. It would be interesting, for these 2 two cases as well, to assess the superiority of the CNN-based approach compared to the more classical Random Forest classification. This would reinforce the universal value of the method proposed.
To meet the reviewer’s request, we have now also compared CNN to RF for the classification of cells in iPSC-derived models (Figures 6 and 7). As expected, the CNN performed better in both cases. We have now added these results in Fig. 6 D and 7 C and pages 12 and 13 of the manuscript.
Reviewer #3 (Public Review):
Induced pluripotent stem cells, or iPSCs, are cells that scientists can push to become new, more mature cell types like neurons. iPSCs have a high potential to transform how scientists study disease by combining precision medicine gene editing with processes known as high-content imaging and drug screening. However, there are many challenges that must be overcome to realize this overall goal. The authors of this paper solve one of these challenges: predicting cell types that might result from potentially inefficient and unpredictable differentiation protocols. These predictions can then help optimize protocols.
The authors train advanced computational algorithms to predict single-cell types directly from microscopy images. The authors also test their approach in a variety of scenarios that one may encounter in the lab, including when cells divide quickly and crowd each other in a plate. Importantly, the authors suggest that providing their algorithms with just the right amount of information beyond the cells' nuclei is the best approach to overcome issues with cell crowding.
The work provides many well-controlled experiments to support the authors' conclusions. However, there are two primary concerns: (1) The model may be relying too heavily on the background and thus technical artifacts (instead of the cells) for making CNN-based predictions, and (2) the conclusion that their nucleocentric approach (including a small area beyond the nucleus) is not well supported, and may just be better by random chance. If the authors were to address these two concerns (through additional experimentation), then the work may influence how the field performs cell profiling in the future.
Thank you very much for confirming the potential value of our work and raising these relevant items. To better support our claims we have now performed additional validations, which we detail below.
(1) The model may be relying too heavily on the background and thus technical artifacts (instead of the cells) for making CNN-based predictions
To address the first point, we have adapted the GradCAM images to show an overlay of the input crop and GradCAM heatmap to give a better view of the structures that are highlighted by the CNN. We further investigated the influence of the background on the prediction performance. Our finding that a CNN trained on a monoculture retains a relatively high performance on cocultures implies that the CNN uses the salient characteristics of a cell to recognize it in more complex heterogeneous environments. Assuming that the background can vary between experiments, the prediction of a pretrained CNN on a new dataset indicates that cellular characteristics are used for robust prediction. When inspecting GradCAM images obtained from the nucleocentric CNN approaches (now added in Suppl. Fig. 3), we noticed that the nuclear periphery typically contributed the most (but not exclusively) to the prediction performance. When using only the nuclear region as input, GradCAMs were more strongly (but again not exclusively) directed to the background surrounding the nuclei. To train the latter CNN, we had cropped nuclei and set the background to a value of zero. To rule out that this could have introduced a bias, we have now performed the exact same training and classification, but setting the background to random noise instead (Suppl. Fig. 2). While this effectively diverted the attention of the GradCAM output to the nucleus instead of the background, the prediction performance was unaltered. We therefore assume that irrespective of the background, when using nuclear crops as input, the CNN is dominated by features that describe nuclear size. We observe that nuclear size is significantly different in both cell types (although intranuclear features also still contribute) which is also reflected in the feature map gradient in the first UMAP dimension (Suppl. Fig. 2). This notion has been added to the manuscript (page 9) and Suppl. Fig. 2.
(2) The conclusion that their nucleocentric approach (including a small area beyond the nucleus) is not well supported, and may just be better by random chance.
To address this second concern, which was also raised by reviewer 2, we have performed a more extensive analysis in which the patch size was varied from 0.6 to 120µm around the nuclear centroid (Fig. 4E and page 9 of the manuscript). We observed that there is little effect of in- or decreasing patch size on the average F-score within the nuclear to cell window, but that the imbalance between the precision and recall increases towards the larger box sizes (>18µm). Under our experimental conditions, the input numbers per class were equal, but this will not be the case in situations where the ground truth is unknown (and needs to be predicted by the CNN). Therefore, a well-balanced CNN is of high importance. This notion has been added to page 15 of the manuscript.
The main advantage of nucleocentric profiling over whole-cell profiling in dense cultures is that it relies on a more robust nuclear segmentation method and is less sensitive to differences in cell density (Suppl. Fig. 1D). In other words, in dense cultures, the segmentation mask will contain similar regional input as the nuclear mask and the nucleocentric crop will contain more perinuclear information which contributes to the prediction accuracy. Therefore, at high densities, the performance of the CNN on whole-cell crops decreases owing to poorer segmentation performance. A CNN that uses nucleocentric crops, will be less sensitive to these errors. This notion has been added to pages 14-15 of the manuscript.
Additionally, the impact of this work will be limited, given the authors do not provide a specific link to the public source code that they used to process and analyze their data.
The source code is now available on the Github page of the DeVos lab, under the following URL: https://github.com/DeVosLab/Nucleocentric-Profiling
Recommendations for the authors:
Reviewing Editor (Recommendations For The Authors):
Evaluation summary
The authors present a new application of the high-content image-based morphological profiling Cell Painting (CP) to single cell type classification in mixed heterogeneous induced pluripotent stem cellderived mixed neural cultures. Machine learning models were trained to classify single cell types according to either "engineered" features derived from the image or from the raw CP multiplexed image. The authors systematically evaluated experimental (e.g., cell density, cell types, fluorescent channels, replication biases) and computational (e.g., different models, different cell regions) parameters and argue that focusing on the nucleus and its surroundings contains sufficient information for robust and accurate cell type classification. Models that were trained on mono-cultures (i.e., containing a single cell type) could generalize for cell type prediction in mixed co-cultures, and describe intermediate states of the maturation process of iPSC-derived neural progenitors to differentiation neurons.
Strengths:
Automatically identifying single-cell types in heterogeneous mixed-cell populations is an important application and holds great promise. The simple and high-content assay democratizes use and enables adoption by other labs. The manuscript is supported by comprehensive experimental and computational validations. The manuscript is well-written and easy to follow.
Weaknesses:
The conclusion is that the nucleocentric approach (including a small area beyond the nucleus) is not well supported, and may just be better by random chance. If better supported by additional experiments, this may influence how the field performs cell profiling in the future. Model interpretability (GradCAM) analysis is not convincing. The lack of a public source code repository is also limiting the impact of this study. There are missing details in the figure panels, figure legend, and text that would help the reader to better appreciate some of the technical details.
Essential revisions:
To reach a "compelling" strength of evidence the authors are requested to either perform a comprehensive analysis of the effect of ROI size on performance, or tune down statements regarding the superior performance of their "nucleocentric" approach. Further addition of a public and reproducible source code GitHub repository will lead to an "exceptional" strength of evidence.
To answer the main comment, we have performed an experiment in which we varied the size of the nucleocentric patch and quantified CNN performance. We have also evaluated the operational window of our method by varying the resolution and SNR and we have experimented with different background blanking methods. We have expanded our examples of GradCAM images and now also made our source code and an example data set available via GitHub.
Reviewer #1 (Recommendations For The Authors):
I think that an evaluation of how the excluded cells affect our ability to measure the cell type composition of the population would be helpful to better understand the limitations and practical measurement noise introduced by this approach. A similar evaluation of the excluded cells can also help to better understand the benefit of nucleocentric vs. cell representations by more convincingly demonstrating the case for the nucleocentric approach. In any case, I recommend discussing in more depth the arguments for using the nucleocentric representation and why it is superior to the nuclear representation.
The benefits of nucleocentric representation over nuclear and whole-cell representation are discussed more in depth at pages 14-15 of the manuscript.
“The nucleocentric approach, which is based on more robust nuclear segmentation, minimizes such mistakes whilst still retaining input information from the structures directly surrounding the nucleus. At higher cell density, the whole-cell body segmentation becomes more error-prone, while also loosing morphological information (Suppl. Fig. 1D). The nucleocentric approach is more consistent as it relies on a more robust segmentation and does not blank the surrounding region. This way it also buffers for occasional nuclear segmentation errors (e.g., where blebs or parts of the nucleus are left undetected).”
It is not entirely clear to me why Figure 5 moves back to "engineered" features after previous figures showed the superiority of the deep learning approach. Especially, where Figure 6 goes again to DL. Dimensionality reduction can be also applied to DL-based classifications (e.g., using the last layer).
Following up on the reviewers’ interesting comment, we extracted the embeddings from the trained CNN and performed UMAP dimensionality reduction. The results are shown in Fig. 3D, 6F and supplementary figure 1B and added to the manuscript on pages 6, 8 and 12.
We concluded that unsupervised dimensionality reduction using the feature embeddings could separate cell type clusters, where the distance between the clusters reflected the morphological similarity between the cell lines.
I would recommend including more comprehensive GRADCAM panels in the SI to reduce the concern of cherry-picking examples. What is the interpretation of the nucleocentric area?
A more extensive set of GradCAM images have now been included in supplementary material (Supplementary figure 3) using the same random seeds for all conditions, thus avoiding any cherry picking. We interpret the GradCAM maps on the nucleocentric crops as highlighting the structures surrounding the nucleus (reflecting ER, mitochondria, Golgi) indicating their importance in correct cell classification. This was added to the manuscript on pages 9 and 15.
Missing/lacking details and suggestions in the figure panels and figure legend:
- Scale bars missing in some of the images shown (e.g., Figure 2F, Figure 3D, Figure 4, Supplementary Figure 4), what are the "composite" channels (e.g., Figure 2F), missing x-label in Figure 3B.
These have now been added.
- Terms that are not clear in the figure and not explained in the legend, such as FITC and cy3 energy (Figure 1C).
The figure has been adapted to better show the region, channel and feature. We have now added a Table (Table 5), detailing the definition of each morphological feature that is extracted. On page 27, information on feature extraction is noted.
- Details that are missing or not sufficiently explained in the figure legends such as what each data point represents and what is Gini importance (Figure 1D)
We have added these explanations to the figure legends. The Gini importance or mean decrease in impurity reflects how often this feature is used in decision tree splits across all random forest trees.
Is it the std shown in Figure 2C?
Yes, this has now been added to the legend.
It is not fully clear what is single/mixed (Figure 2D)
Clarification is added to the legend and in the manuscript on page 6.
explain what is DIV 13-90 in the legend (Figure 5).
DIV stands for days in vitro, here it refers to the days in culture since the start of the neural induction process. This has been added in the legend.
and state what are img1-5 (Supplementary Figures 1B-C) Clarification has been added to the legend.
- Supplementary Figure 1. What is the y-axis in panel C and how do the results align with the cell mask in panel B?
The y-axis represents the intersection over union (IoU). The IoU quantifies the overlap between ground truth (manually segmented ROI) and the ROI detected by the segmentation algorithm. It is defined as the area of the overlapping region over the total area. This clarification has been added to the legend.
- Supplementary Figure 1 and Methods. Please explain when CellPose and when StarDist were applied.
Added to supplementary figure and methods at page 24. In the case of nuclear segmentation (nucleus and nucleocentric crops), Stardist was used. For whole-cell crops, cell segmentation using Cellpose was used.
- Supplementary Figure 4C - the color code is different between nuclear and nucleocentric - this is confusing.
We have changed to color code to correspond in both conditions in Fig. 1A.
- Figure 3B - better to have a normalized measure in the x-axis (number of cells per area in um^2)
We agree and have changed this.
Suggestions and missing/lacking details in the text:
- Line #38: "we then applied this" because it is the first time that this term is presented.
This has been rephrased.
- Line #88: a few words on what were the features extracted would be helpful.
Short description added to page 26-27 and detailed definition of all features added in table 5.
- Line #91: PCA analysis - the authors can highlight what (known) features were important to PC1 using the linear transformation that defined it.
The 5 most important features of PC1 were (in order of decreasing importance): channel 1 dissimilarity, channel 1 homogeneity, nuclear perimeter, channel 4 dissimilarity and nuclear area.
- Line #92: Order of referencing Supplementary Figure 4 before referencing Supplementary Figure 13.
The order of the Supplementary images was changed to follow the chronology.
- Line #96: Can the authors show the data supporting this claim?
The unsupervised UMAP shown in fig. 1B is either color coded by cell type (left) or replicate (right). Based on this feature map, we observe clustering along the UMAP1 axis to be associated with the cell type. Variations in cellular morphology associated with the biological replicate are more visible along the UMAP2 axis. When looking at fig. 1C, the feature map reflecting the cellular area shows a gradient along the UMAP1 direction, supporting the assumption that cell area contributes to the cell type separation. On the other hand, the average intensity (Channel 2 intensity) has a gradient within the feature map along the UMAP2 direction. This corresponds to the pattern associated with the inter-replicate variability in panel B.
- Line #108: what is "nuclear Cy3 energy"?
This represents the local change of pixel intensities within the ROI in the nucleus in the 3rd channel dimension. This parameter reflects the texture within the nuclear region for the phalloidin and WGA staining. The definitions of all handcrafted features are added in table 5 of the manuscript.
- Line #110-112: Can the authors show the data supporting this claim?
The figure has been changed to include the results from a filtered and unfiltered dataframe (exclusion and inclusion of redundant features). Features could be filtered out if the correlation was above a threshold of 0.95. This has been added to page 6 of the manuscript and fig. 1D.
- Line #115-116: please state the size of the mask.
Added to the text (page 6). We used isotropic image crops of 60µm centred on individual cell centroids.
- Lines 120-122: more details will make this more clear (single vs. mixed).
This has been changed on page 6 of the manuscript.
- Line #142: "(mimics)" - is it a typo?
Tissue mimics refers to organoids/models that are meant to replicate the physiological behaviour.
- Line #159: the bounding box for nucleocentric analysis is 15x15um (and not 60), as stated in the Methods.
Thank you for pointing out this mistake. We have adapted this.
- Line #165: what is the interpretation of what was important for the nucleocentric classification?
The colour code in GradCAM images is indicative of the attention of the CNN (the more to the red, the more attention). In fig. 4D and Suppl. Fig. 3 the structures directly surrounding the nucleus receive high attention from the CNN trained on nucleocentric crops. This has been added to the manuscript page 9 and 15.
- Section starting in line #172: not explicitly stated what model was used (nucleocentric?).
Added in the legend of fig. 5. For these experiments, the full cell segmentation was still used.
- Section starting in line #199: why use a feature-based model rather than nucleocentric? A short sentence would be helpful.
For CNN training, nucleocentric profiling was used. In response to a legitimate question of one of the reviewers, the feature-based UMAP analysis was replaced with the feature embeddings from the CNN.
- Line #213: Fig. 5B does not show transitioning cells.
Thank you for pointing this out, this was a mistake and has been changed.
Lines #218-220: not fully clear to some readers (culture condition as a weak label), more details can be helpful.
We changed this at page 11 of the manuscript for clarity.
“This gating strategy resulted in a fractional abundance of neurons vs. total (neurons + NPC) of 36,4 % in the primed condition and 80,0% in the differentiated condition (Fig. 6C). We therefore refer to the culture condition as a weak label as it does not take into account the heterogeneity within each condition (well).”
- Line #230: "increasing dendritic outgrowth" - what does it mean? Can you explicitly highlight this phenotype in Figure 5G?
When the cells become more mature during differentiation, the cell body becomes smaller and the neurons form long, thin ramifications. This explanation has been added to page 12 of the manuscript.
- Line #243: is it the nucleocentric CNN?
Yes.
- Lines #304-313, the authors might want to discuss other papers dealing with continuous (non-neural) differentiation state transitions (eg PMID: 38238594).
A discussion of the use of morphological profiling for longitudinal follow-up of continuous differentiation states has been added to the manuscript at page 18.
- Line #444: cellpose or stardist? How did the authors use both?
Clarification has been added to supplementary figure 1 and methods at page 24. Stardist was used for nuclear segmentation, whereas Cellpose was used for whole-cell segmentation.
- Line #470-474: I would appreciate seeing the performance on the full dataset without exclusions.
Cells have been excluded based on 3 arguments: the absence of DAPI intensity, too small nuclear size and absence of ground truth staining. The first two arguments are based on the assumption that ROIs that contain no DAPI signal or are too small are errors in cell segmentation and therefore should not be taken along in the analysis. The third filtering step was based on the ground-truth IF signal. Not filtering out these cells with a ‘dubious’ IF profile (e.g., cells that might be transitioning or are of a different type) would negatively affect the model by introducing noise. It is correct that the predictions are based only on these inputs and so cells of a subsequent test set will only be classified according to these labels which might introduce bias. However, the model could predict increase in neuron/NPC ratio with culture age in absence of ground-truth staining (and thus IF-based filtering).
Reviewer #2 (Recommendations For The Authors):
Figure 1A: it would be interesting to the reader to see the SH-SY5Y data as well.
This has been added in fig. 1A.
Figure 3A: 95-100% image: showing images with the same magnification as the others would help to appreciate the cell density.
Now fig. 4A. The figure has been changed to make sure all images have the same magnification.
Figure Supp 4 (line 132) is referred to before Figure Supp1 (line 152).
The image order and numbering has been changed to solve this issue.
Figure Supp 2 & 3 are not referred to in the text.
This has been adjusted.
Line 225: a statistical test would help to convince of the accuracy of these results (Figure 5C vs Figure 5F)?
These figures represent the total ROI counts and thus represent a single number.
Line 227: Could you explain to the reader, in a few words, what a dual SMAD inhibition is?
This has been added to the manuscript at page 20.
“This dual blockade of SMAD signalling in iPSCs is induces neural differentiation by synergistically causing the loss of pluripotency and push towards neuroectodermal lineage.”
Reviewer #3 (Recommendations For The Authors):
I have a few concerns and several comments that, if addressed, may strengthen conclusions, and increase clarity of an already technically sound paper.
Concerns
- The results presented in Figure 3 panel D, may indicate a critical error in data processing and interpretation that the authors must address. The GradCAM method highlights the background as having the highest importance. While it can be argued in the nucleocentric profiling method that GradCAM focuses on the nuclear membrane, the background is highly important even for the nuclear profiling method, which should provide little information. What procedure did the authors use for mask subtraction prior to CNN training? Could the segmentation algorithm be performing differently between cell lines? The authors interpret the GradCAM results to indicate a proxy for nuclear size, but then why did the CNN perform so much better than random forest using hand-crafted features that include this variable? The authors should also present size distributions between cell lines (and across seeding densities, in case one of the cell lines has different compaction properties with increasing density).
Perhaps clarifying this sentence (lines 166-168) would help as well: "As nuclear area dropped with culture density, the dynamic range decreased, which could explain the increased error rate of the CNN for high densities unrelated to segmentation errors (Suppl. Fig. 4B)." What do the authors mean by "dynamic range" and it is not clear how Supplementary Figure 4B provides evidence for this?
The dynamic range refers to the difference between the minimum and maximum nuclear area. We expect the difference to decrease at highe rdensity owing to the crowding that forces all nuclei to take on a more similar (smaller) size.
More clarification on this has been added to page 9 of the manuscript.
I certainly understand that extrapolating the GradCAM concern to the remaining single-cell images using only four (out of tens of thousands of options) is also dangerous, but so is "cherry-picking" these cells to visualize. Finally, I also recommend that the authors quantitatively diagnose the extent of the background influence according to GradCAM by systematically measuring background influence in all cells and displaying the results per cell line per density.
To avoid cherry picking of GradCAM images, we have now randomly selected for each condition and density 10 images (using random seeds to avoid cherry-picking) and added these in a Suppl. Fig. 3.
In answer to this concern, we refer to the response above:
“To address the first point, we have adapted the GradCAM images to show an overlay of the input crop and GradCAM heatmap to give a better view of the structures that are highlighted by the CNN. We further investigated the influence of the background on the prediction performance. Our finding that a CNN trained on a monoculture retains a relatively high performance on cocultures implies that the CNN uses the salient characteristics of a cell to recognize it in more complex heterogeneous environments. Assuming that the background can vary between experiments, the prediction of a pretrained CNN on a new dataset indicates that cellular characteristics are used for robust prediction. When inspecting GradCAM images obtained from the nucleocentric CNN approaches (now added in Suppl. Fig. 3), we noticed that the nuclear periphery typically contributed the most (but not exclusively) to the prediction performance. When using only the nuclear region as input, GradCAMs were more strongly (but again not exclusively) directed to the background surrounding the nuclei. To train the latter CNN, we had cropped nuclei and set the background to a value of zero. To rule out that this could have introduced a bias, we have now performed the exact same training and classification, but setting the background to random noise instead (Suppl. Fig. 2). While this effectively diverted the attention of the GradCAM output to the nucleus instead of the background, the prediction performance was unaltered. We therefore assume that irrespective of the background, when using nuclear crops as input, the CNN is dominated by features that describe nuclear size. We observe that nuclear size is significantly different in both cell types (although intranuclear features also still contribute) which is also reflected in the feature map gradient in the first UMAP dimension (Suppl. Fig. 2). This notion has been added to the manuscript (page 9) and Suppl. Fig. 2.”
- The data supporting the conclusion about nucleocentric profiling outperforming nuclear and full-cell profiling is minimal. I am picking on this conclusion in particular, because I think it is a super cool and elegant result that may change how folks approach issues stemming from cell density disproportionately impacting profiling. Figures 3B and 3C show nucleocentric slightly outperforming full cell, and the result is not significant. The authors state in lines 168-170: "Thus, we conclude that using the nucleocentric region as input for the CNN is a valuable strategy for accurate cell phenotype identification in dense cultures." This is somewhat of a weak conclusion, that, with additional analysis, could be strengthened and add high value to the community. Additionally, the authors describe the nucleocentric approach insufficiently. In the methods, the authors state (lines 501-503): "Cell crops (60μm whole cell - 15μm nucleocentric/nuclear area) were defined based on the segmentation mask for each ROI." This is not sufficient to reproduce the method. What software did the authors use?
Presumably, 60μm refers to a box size around cytoplasm? Much more detail is needed. Additionally, I suggest an analysis to confirm the impact of nucleocentric profiling, which would strengthen the authors' conclusions. I recommend systematically varying the subtraction (-30μm, -20μm, -10μm, 5μm, 0, +5μm, +10μm, etc.) and reporting the density-based analysis in Figure 3B per subtraction. I would expect to see some nucleocentric "sweet spot" where performance spikes, especially in high culture density. If we don't see this difference, then the non-significant result presented in Figures 3B and C is likely due to random chance. The authors mention "iterative data erosion" in the abstract, which might refer to what I am recommending, but do not describe this later.
More detail was added to the methods describing the image crops given as input to the CNN (page 28 of the manuscript).
“Crops were defined based on the segmentation mask for each ROI. The bounding box was cropped out of the original image with a fixed patch size (60µm for whole cells, 18µm for nucleus and nucleocentric crops) surrounding the centroid of the segmentation mask. For the whole cell and nuclear crops, all pixels outside of the segmentation mask were set to zero. This was not the case for the nucleocentric crops. Each ROI was cropped out of the original morphological image and associated with metadata corresponding to its ground truth label.”
To address this concern, we also refer to the answer above.
“We have performed a more extensive analysis in which the patch size was varied from 0.6 to 120µm around the nuclear centroid (Fig. 4E and page 9 of the manuscript). We observed that there is little effect of in- or decreasing patch size on the average F-score within the nuclear to cell window, but that the imbalance between the precision and recall increases towards the larger box sizes (>18µm). Under our experimental conditions, the input numbers per class were equal, but this will not be the case in situations where the ground truth is unknown (and needs to be predicted by the CNN). Therefore, a well-balanced CNN is of high importance. This notion has been added to page 12 of the manuscript.
The main advantage of nucleocentric profiling over whole-cell profiling in dense cultures is that it relies on a more robust nuclear segmentation method and is less sensitive to differences in cell density (Suppl. Fig. 1D). In other words, in dense cultures, the segmentation mask will contain similar regional input as the nuclear mask and the nucleocentric crop will contain more perinuclear information which contributes to the prediction accuracy. Therefore, at high densities, the performance of the CNN on whole-cell crops decreases owing to poorer segmentation performance. A CNN that uses nucleocentric crops, will be less sensitive to these errors. This notion has been added to pages 14-15 of the manuscript.“
Comments
- There is a disconnect between the abstract and the introduction. The abstract highlights the nucleocentric model, but then it is not discussed in the introduction, which focuses on quality control. The introduction would benefit from some additional description of the single-cell or whole-image approach to profiling.
We highlight the importance of QC of complex iPSC-derived neural cultures as an application of morphological profiling. We used single-cell profiling to facilitate cell identification in these mixed cultures where the whole-image approach would be unable to deal with the heterogeneity withing the field of view. In the introduction, we added a description of the whole-image vs. single-cell approach to profiling (page 4). In the discussion (page 18), we further highlight the application of this single-cell profiling approach for QC purposes.
- Comments on Figure 1. It is unclear how panel B shows "without replicate bias".
In response to this comment, we refer to the answer above: “The unsupervised UMAP shown in fig. 1B is either color coded by cell type (left) or replicate (right). Based on this feature map, we observe clustering along the UMAP1 axis to be associated with the cell type. Variations in cellular morphology associated with the biological replicate are more visible along the UMAP2 axis. When looking at fig. 1C, the feature map reflecting the cellular area shows a gradient along the UMAP1 direction, supporting the assumption that cell area contributes to the cell type separation. On the other hand, the average intensity (Channel 2 intensity) has a gradient within the feature map along the UMAP2 direction. This corresponds to the pattern associated with the inter-replicate variability in panel B.” We added this notion to page 5 of the manuscript.
The paper would benefit from a description of how features were extracted sooner.
Information on the feature extraction was added to the manuscript at page 27. An additional table (table 5) has been added with the definition of each feature.
- Comments on Supplementary Figure 4. The clustering with PCA is only showing 2 dimensions, so it is not surprising UMAP shows more distinct clustering.
We used two components for UMAP dimensionality reduction, so the data was also visualized in two dimensions. However, we agree that UMAP can show more distinct clustering as this method is non-linear.
Why is Figure S4 the first referenced Supplementary Figure?
This has been changed.
- Comments on Figure 2. Need discussion of the validation set - how was it determined? Panel E might have the answer I am looking for, but it is difficult to decipher exactly what is being done. The terminology needs to be defined somewhere, or maybe it is inconsistent. It is tough to tell. For example, what exactly are the two categories of model validation (cross-validation and independent testing)?
Additional clarification has been added to the manuscript at pages 6-7 and figure 2.
The metric being reported is accuracy for the independent replicate if the other two are used to train?
Yes.
Panel C is a very cool analysis. Panel F needs a description of how those images were selected, randomly?
Added in the methods section (page 29). GradCAM analysis was used to visualize the regions used by the CNN for classification. This map is specific to each cell. Images are selected randomly out the full dataset for visualization.
They also need scale bars.
Added to the figures.
Panel G would benefit from explicit channel labels (at least a legend would be good!).
Explanation has been added to the legend. All color code and channel numbering are consistent with fig. 1A.
What do the dots and boxplots represent? The legend says, "independent replicates", but independent replicates of, I assume, different model initializations?
Clarification has been added to the figure legends. For plots showing the performance of a CNN or RF classifier, each dot represents a different model initialization. Each classifier has been initialized at least 3 times. When indicated, the model training was performed with different random seeds for data splitting.
- Comments on Figure 3. Panel A needs scale bar. See comment on Panel D in concern #1 described above.
This has been added.
- Comments on Supplementary Figure 1. A reader will need a more detailed description in panel C. I assume that the grey bar is the average of the points, and the points represent different single cells?
How many cells? How were these cells selected?
This information on the figure (now Suppl. Fig. 1D), has been added to the legend.
“Left: Representative images of 1321N1 cells with increasing density alongside their cell and nuclear mask produced using resp. Cellpose and Stardist. Images are numbered from 1-5 with increasing density. Upper right: The number of ROIs detected in comparison to the ground truth (manual segmentation). A ROI was considered undetected when the intersection over union (IoU) was below 0,15. Each bar refers to the image number on the left. The IoU quantifies the overlap between ground truth (manually segmented ROI) and the ROI detected by the segmentation algorithm. It is defined as the area of the overlapping region over the total area. IoU for increasing cell density for cell and nuclear masks is given in the bottom right. Each point represents an individual ROI. Each bar refers to the image number on the left.”
- Comments on Figure 4. More details on quenching are needed for a general audience. The markers chosen (EdU and BrdU) are generally not specific to cell type but to biological processes (proliferation), so it is confusing how they are being used as cell-type markers.
The base analogues were incorporated into each cell line prior to mixing them, i.e. when they were still growing in monoculture so they could be labelled and identified after co-seeding and morphological profiling. Additional clarification has been added to the manuscript (page 26)
It is also unclear why reducing CV is an important side-effect of finetuning. CV of what? The legend says, "model iterations", but what does this mean?
The dots in the violinplot are different CNN initializations. A lower variability between model initializations is an indicator of certainty of the results. Prior to finetuning, the results of the CNN were highly variable leading to a high CoV between the different CNNs. This means the outcome after finetuning is more robust.
- Comments on Figure 5. This is a very convincing and well-described result, kudos! This provides another opportunity to again compare other approaches (not just nucleocentric). Additionally, since the UMAP space uses hand-crafted features. The authors could consider interpreting the specific morphology features impacted by the striking gradual shift to neuron population by fitting a series of linear models per individual feature. This might confirm (or discover) how exactly the cells are shifting morphology.
The supervised UMAP on the handcrafted features did not highlight any features contributing to the separation. Using the supervised UMAP, the clustering is dominated by the known cell type. Unsupervised UMAP on the handcrafted features does not show any clustering. In response to a previous comment, we adapted the figure to show UMAP dimensionality reduction using the feature embeddings from the cell-based CNN. This unsupervised UMAP does show good cell type separation, but it does not use any directly interpretable shape descriptors.
- General comments on Methods. The section on "ground truth alignment" needs more details. Why was this performed?
Following sequential staining and imaging rounds, multiple images were captured representing the same cell with different markers. Lifting the plate of the microscope stage and imaging in sequential rounds after several days results in small linear translations in the exact location of each image. These linear translations need to be corrected to align (or register) morphological with ground truth image data within the same ROI. This notion has been added to the manuscript at page 26.
Handcrafted features extracted using what software?
The complete analysis was performed in python. All packages used are listed in table 4. Handcrafted features were extracted using the scikit-image package (regionprops and GLCM functions). This has been added to the manuscript at page 27.
Software should be cited more often throughout the manuscript.
Lastly, the GitHub URL points to the DeVosLab organization, but should point to a specific repository. Therefore, I was unable to review the provided code. A well-documented and reproducible analysis pipeline should be included.
A test dataset and source code are available on GitHub: https://github.com/DeVosLab/Nucleocentric-Profiling
Author response:
The following is the authors’ response to the original reviews.
Reviewer 1:
Comment 1. In Figure 1, the MafB antibody (Sigma) was used to identify Renshaw cells at P5. However, according to the supplementary Figure 3D, the specificity of the MafB antibody (Sigma) is relatively low. The image of MafB-GFP, V1-INs, and MafB-IR at P5 should be added to the supplementary figure. The specificity of MaFB-IR-Sigma in V1 neurons at P5 should be shown. This image also might support the description of the genetically labeled MafB-V1 distribution at P5 (page 8, lines 28-32).
We followed the reviewer’s suggestion and moved analyses of the MafB-GFP mouse to a supplemental figure (Fig S3). The characterization of MafB immunoreactivities is now in supplemental Figure S2 and the related text in results was also moved to supplemental to reduce technicalities in the main text. We added confocal images of MafB-GFP V1 interneurons at P5 showing immunoreactivities for both MafB antibodies, as suggested by the reviewer (Fig S2A,B). We agree with the reviewer that this strengthens our comparisons on the sensitivity and specificity of the two MafB antibodies used in this study.
As explained in the preliminary response we cannot show lack of immunoreactivity for MafB antibodies in MafB GFP/GFP knockout mice at P5 because MafB global KOs die at birth. This is why we used tissues from late embryos to check MafB immunoreactivities (Figure S2C and S2D). We made this point clearer in the text and supplemental figure legends.
Comment 2. The proportion of genetically labeled FoxP2-V1 in all V1 is more than 60%, although immunolabeled FoxP2-V1 is approximately 30% at P5. Genetically labeled Otp-V1 included other nonFoxP2 V1 clades (Fig. 8L-M). I wonder whether genetically labeled FoxP2-V1 might include the other three clades. The authors should show whether genetically labeled FoxP2-V1 expresses other clade markers, such as pou6f2, sp8, and calbindin, at P5.
We included the requested data in Figure 3E-G. Lineage-labeled Foxp2-V1 neurons in our genetic intersection do not include cells from other V1-clades.
Reviewer 2:
Comment 1. The current version of the paper is VERY hard to read. It is often extremely difficult to "see the forest for the trees" and the reader is often drowned in methodological details that provide only minor additions to the scientific message. Non-specialists in developmental biology, but still interested in the spinal cord organization, especially students, might find this article challenging to digest and there is a high risk that they will be inclined to abandon reading it. The diversity of developmental stages studied (with possible mistakes between text and figures) adds a substantial complexity in the reading. It is also not clear at all why authors choose to focus on the Foxp2 V1 from page 9. Naively, the Pou6f2 might have been equally interesting. Finally, numerous discrepancies in the referencing of figures must also be fixed. I strongly recommend an in-depth streamlining and proofreading, and possibly moving some material to supplement (e.g. page 8, and elsewhere).
The whole text was re-written and streamlined with most methodological discussion (including the section referred to by the reviewer) transferred to supplemental data. Nevertheless, enough details on samples, stats and methods were retained to maintain the rigor of the manuscript.
The reasons justifying a focus on Foxp2-V1 interneurons were fully explained in our preliminary response. Briefly, we are trying to elucidate V1 heterogeneity, and prior data showed that this is the most heterogeneous V1 clade (Bikoff et al., 2016), so it makes sense it was studied further. We agree that the Pou6f2 clade is equally interesting and is in fact the subject of several ongoing studies.
Comment 2. … although the different V1 populations have been investigated in detail regarding their development and positioning, their functional ambition is not directly investigated through gain or loss of function experiments. For the Foxp2-V1, the developmental and anatomical mapping is complemented by a connectivity mapping (Fig 6s, 8), but the latter is fairly superficial compared to the former. Synapses (Fig 6) are counted on a relatively small number of motoneurons per animal, that may, or may not, be representative of the population. Likewise, putative synaptic inputs are only counted on neuronal somata. Motoneurons that lack of axo-somatic contacts may still be contacted distally. Hence, while this data is still suggestive of differences between V1 pools, it is only little predictive of function.
We fully answered the question on functional studies in the preliminary response. Briefly, we are currently conducting these studies using various mouse models that include chronic synaptic silencing using tetanus toxin, acute partial silencing using DREADDs, and acute cell deletion using diphtheria toxin. Each intervention reveals different features of Foxp2-V1 interneuron functions, and each model requires independent validation. Moreover, these studies are being carried out at three developmental stages: embryos, early postnatal period of locomotor maturation and mature animals. Obviously, this is all beyond the goals and scope of the present study. The present study is however the basis for better informed interpretations of results obtained in functional studies.
Regarding the question on synapse counts, we explained in the preliminary results fully why we believe our experimental designs for synapse counting at the confocal level are among the most thorough that can be found in the literature. We counted a very large number of motoneurons per animal when adding all motor column and segments analyzed in each animal. Statistical power was also enough to detect fundamental variation in synaptic density among motor columns.
We focus our analyses on motoneuron cells bodies because analysis of full dendritic arbors on all motor columns present throughout all lumbosacral segments is not feasible. Please see Rotterman et al., 2014 (J. of Neuroscience; doi: 10.1523/JNEUROSCI.4768-13.2014) for evaluation of what this entails for a single motoneuron. We agree with the reviewer that analyses of V1 synapses over full dendrite arbors in specific motoneurons will be very relevant in further studies. These should be carried out now that we know which motor columns are of high interest. Nevertheless, inhibitory synapses exert the most efficient modulation of neuronal firing when they are on cell bodies, and our analyses clearly suggest a difference in in cell body inhibitory synapses targeting between different V1 interneuron types that we find very relevant.
Comment 3. I suggest taking with caution the rabies labelling (Figure 8). It is known that this type of Rabies vectors, when delivered from the periphery, might also label sensory afferents and their postsynaptic targets in the cord through anterograde transport and transneuronal spread (e.g., Pimpinella et al., 2022). Yet I am not sure authors have made all controls to exclude that labelled neurons, presumed here to be premotoneurons, could rather be anterogradely labelled from sensory afferents.
Over the years, we performed many extensive controls and validation of rabies virus transsynaptic tracing methods. These were presented at two SfN meetings (Gomez-Perez et al., 2015 and 2016; Program Nos. 242.08 and 366.06). Our validation of this technique was fully explained in our preliminary response. We also pointed out that the methods used by Pimpinella et al. have a very different design and therefore their results are not comparable to ours. In this study we injected the virus at P15 into leg muscles, and not directly into the spinal cord. In our hands, and as cited in Pimpinella et al., the rabies virus loses tropism for primary afferents with age when injected in muscle. The lack of primary afferent labeling in key lumbosacral segments (L4 and L5) is now illustrated in a new supplemental figure (Figure S6). This figure also shows some starter motoneurons. As explained in the text and in our previous response, these are few in number because of the reduced infection rate when using this method in mature animals (after P10).
Comment 4. The ambition to differentiate neuronal birthdate at a half-day resolution (e.g., E10 vs E10.5) is interesting but must be considered with caution. As the author explains in their methods, animals are caged at 7pm, and the plug is checked the next morning at 7 am. There is hence a potential error of 12h.
We agree with the reviewer, and we previously explicitly discussed these temporal resolution caveats. We have now further expanded on this in new text (see middle paragraph in page 5). Nevertheless, the method did reveal the temporal sequence of neurogenesis of V1 clades with close to 12-hour resolution.
As explained in text and preliminary response this is because we analyzed a sufficient number of animals from enough litters and utilized very stringent criteria to count EdU positives.
Moreover, our results fit very well with current literature. The data agree with previous conclusions from Andreas Sagner group (Institut für Biochemie, Friedrich-Alexander-Universität Erlangen-Nürnberg), on spinal interneurons (including V1s) birthdates based on a different methodology (Delile J et al.
Development. 2019 146(12):dev173807. doi: 10.1242/dev.173807. PMID: 30846445; PMCID: PMC6602353). In the discussion we compared in detail both the data and methods between Delile article and our results. We also cite Sagner 2024 review as requested later in the reviewer’s detailed comments. Our results also confirmed our previous report on the birthdates of V1-derived Renshaw cells and Ia inhibitory interneurons (Benito-Gonzalez A, Alvarez FJ J Neurosci. 2012 32(4):1156-70. doi: 10.1523/JNEUROSCI.3630-12.2012. PMID: 22279202; PMCID: PMC3276112). Finally, we recently received a communication notifying us that our neurogenesis sequence of V1s has been replicated in a different vertebrate species by Lora Sweeney’s group (Institute of Science and Technology Austria; direct email from this lab) and we shared our data with them for comparison. This manuscript is currently close to submission. Therefore, we are confident that despite the limitations of EdU birthdating we discussed, the conclusions we offered are strong and are being validated by other groups using different methods and species. We also want to acknowledge the positive comments of reviewer 3 regarding our birthdating study, indicating it is one the most rigorous he or she has ever seen.
Reviewer 3:
Comment 1. My only criticism is that some of the main messages of the paper are buried in technical details. Better separation of the main conclusions of the paper, which should be kept in the main figures and text, and technical details/experimental nuances, which are essential but should be moved to the supplement, is critical. This will also correct the other issue with the text at present, which is that it is too long.
Similar to our response to comment 1 from Reviewer 2 we followed the reviewers’ recommendations and greatly summarized, simplified and removed technical details from the main text, trying not to decrease rigor.
Reviewer #1 (Recommendations For The Authors):
In Figure 1, the definition of the area to analyze MafB ventral and MafB dorsal is unclear. It should be described.
This has been clarified in both text and supplemental figure S3.
“We focused the analyses on the brighter dorsal and ventral MafB-V1 populations defined by boxes of 100 µm dorsoventral width at the level of the central canal (dorsal) or the ventral edge of the gray matter (ventral) (Supplemental Figure S3B).”
Problems with figure citation.
We apologize for the mistakes. All have been corrected.
Reviewer #2 (Recommendations For The Authors):
As indicated in the public review, I'd recommend to substantially revise the writing, for clarity. As such, the paper is extremely hard to read. I would also recommend justifying the focus on Foxp2 neurons.
Also, the scope of the present paper is not clearly stated in the introduction (page 4).
Done. We also modified the introduction such that the exact goals are more clearly stated.
I would also recommend toning down the interpretation that V1 clades constitute "unique functional subsets" (discussion and elsewhere). Functional investigation is not performed, and connectomic data is partial and only very suggestive.
We include the following sentence at the end of the 1st paragraph in the discussion:
“This result strengthens the conclusion that these V1 clades defined by their genetic make-up might represent distinct functional subtypes, although further validation is necessary in more functionally focused studies.”
Different post-natal stages are used for different sections of the manuscript. This is often confusing, please justify each stage. From the beginning even, why is the initial birthdating (Figure 1) done here at p5, while the previous characterization of clades was done at p0? I am not sure to understand the justification that this was chosen "to preserve expression of V1 defining TFs". Isn't the sooner the better?
The birthdating study was carried out at P5. P5 is a good time point because there is little variation in TF expression compared to P0, as demonstrated in the results. Furthermore, later tissue harvesting allows higher replicability since it is difficult to consistently harvest tissue the day a litter is born (P0). Also technically, it is easier to handle P5 tissue compared to P0. The analysis of VGUT1 synapses was also done at P5 rather than later ages. This has two advantages: TFs immunoreactivities are preserved at this age, and also corticospinal projections have not yet reached the lumbar cord reducing interpretation caveats on the origins of VGUT1 synapses in the ventral horn (although VGLUT1 synapses are still maturing at this age, see below).
Other parts of the study focus on different ages selected to be most adequate for each purpose. To best study synaptic connectivity, it is best to study mature spinal cords after synaptic plasticity of the first week. For the tracing study we thoroughly explain in the text the reasons for the experimental design (see also below in detailed comments). For counting Foxp2-V1 interneurons and comparing them to motor columns we analyze mature animals. For testing our lineage labeling we use animals of all ages to confirm the consistency of the genetic targeting strategy throughout postnatal development and into adulthood.
Figure 5: wouldn't it be worth quantifying and illustrating cellular densities, in addition to the average number of Foxp2 neurons, across lumbar segments (panel D & E)? Indeed, the size of - and hence total number of cells within - each lumbar segment might not be the same, with a significant "enlargement" from L2 to L4 (this is actually visible on the transverse sections). Hence, if the total number of cells is in the higher in these enlarged segments, but the total number of Foxp2-V1 is not, it may mean that this class is proportionally less abundant.
We believe the critical parameter is the ratio of Foxp2-V1s to motoneurons. This informs how Foxp2-V1 interneurons vary according to the size of the motor columns and the number of motoneurons overall.
The question asked by the reviewer would best be answered by estimating the proportion of Foxp2-V1 neurons to all NeuN labeled interneurons. This is because interneuron density in the spinal cord varies in different segments. We are not sure what this additional analysis will contribute to the paper.
Why, in the Rabies tracing scheme (Fig 8), the Rabies injection is performed at p15? As the authors explain in the text, rabies uptake at the neuromuscular junction is weak after p10. It is not clear to me why such experiments weren't done all at early postnatal stages, with a "classical" co-injection of TVA and Rabies.
First, we do not need TVA in this experiment because we are using B19-G coated virus and injecting it into muscles, not into the spinal cord directly.
Second, enhanced tracing occurs when the AAV is injected a few days before rabies virus. This is because AAV transgene expression is delayed with respect to rabies virus infection and replication. We have performed full time courses and presented these data in one abstract to SfN: Gomez-Perez et al., 2015 Program Nos. 242. We believe full description of these technical details is beyond the scope of this manuscript that has already been considered too technical.
Third, the justification of P15 timing of injections for anterograde primary afferent labeling and retrograde monosynaptic labeling of interneurons is fully explained in the text.
“To obtain transcomplementation of RVDG-mCherry with glycoprotein in LG motoneurons, we first injected the LG muscle with an AAV1 expressing B19-G at P4. We then performed RVDG and CTB injections at P15 to optimize muscle targeting and avoid cross-contamination of nearby muscles. Muscle specificity was confirmed post-hoc by dissection of all muscles below the knee. Analyses were done at P22, a timepoint after developmental critical windows through which Ia (VGLUT1+) synaptic numbers increase and mature on V1-IaINs (Siembab et al., 2010)”
Furthermore, CTB starts to decrease in intensity 7 days after injection because intracellular degradation and rabies virus labeling disappears because cell death. Both limit the time of postinjection for analyses.
Likewise, I am surprised not to see a single motoneuron in the rabies tracing (Fig 8, neither on histology nor on graphs (Fig 8). How can authors be certain that there was indeed rabies uptake from the muscle at this age, and that all labelled cells, presumed to be preMN, are not actually sensory neurons? It is known that Rabies vectors, when delivered from the periphery, might also label sensory afferents and their post-synaptic targets through anterograde transport and transneuronal spread (e.g., Pimpinella et al., 2022). This potential bias must be considered.
This is fully explained in our previous response to the second reviewer’s general comments. We have also added a confocal image showing starter motoneurons as requested (Figure S6A).
Please carefully inspect the references to figures and figure panels, which I suspect are not always correct.
Thank you. We carefully revised the manuscript to correct these deficiencies and we apologize for them.
Reviewer #3 (Recommendations For The Authors):
Figure 1: Data here is absolutely beautiful and provides one of the most thorough studies, in terms of timepoints, number of animals analyzed, and precision of analysis, of edU-based birth timing that has been published for neuron subtypes in the spinal cord so far. My only suggestion is to color code the early and late born populations (in for example, different shades of green for early; and blue for late, to better emphasize the differences between them). It is very difficult to differentiate between the purple, red and black colors in G-I, which this would also fix. The antibody staining for Pou6f2 (F) is also difficult to see; gain could be increased on these images or insets added for clarity.
The choice of colors is adapted for optimal visualization by people with different degrees of color blindness. Shades of individual colors are always more difficult to discriminate. This is personally verified by the senior corresponding author of this paper who has some color discrimination deficits. Moreover, each line has a different symbol for the same purpose of easing differentiation.
Figure 2: This is also a picture-perfect figure showing further diversity by birth time even within a clade. One small aesthetic comment is that the arrows are quite unclear and block the data. Perhaps the contours themselves could be subdivided by region and color coded by birth time-such that for example the dorsal contours that emerge in the MafB clade at E11 are highlighted in their own color. Some quantification of the shift in distribution as well as the relative number of neurons within each spatially localized group would also be useful. For MafB, for example, it looks as though the ventral cells (likely Renshaw) are generated at all times in the contour plots; in the dot plots however, it looks like the most ventral cells are present at e10.5. This is likely because the contours are measuring fractional representations, not absolute number. An independent measure of absolute number of ventral and dorsal, by for example, subdividing the spinal cord into dorsoventral bins, would be very useful to address this ambiguity.
We believe density plots already convey the message of the shift in positions with birthdate. We are not sure how we can quantify this more accurately than showing the differences in cellular density plots. We used dorsoventral and mediolateral binning in our first paper decades ago (Avarez et al., 2005). This has now been replaced by more rigorous density profiles that describe better cell distributions. Unfortunately, to obtain the most accurate density profiles we need to pool all cells from all animals precluding statistical comparisons. This is because for some groups there have very few cells per animal (for example early born Sp8 or Foxp2 cells).
Figure 3 and Figure 4: These, and all figures that compare the lineage trace and antibody staining, should be moved to the supplement in my opinion-as they are not for generalist readers but rather specialists that are interested in these exact tools. In addition, the majority of the text that relates to these figures should be transferred to the supplement as well. Figure 5: Another great figure that sets the stage for the analysis of FoxP2V1-to-MN synaptic connectivity, and provides basic information about the rostrocaudal distribution of this clade, by analyzing settling position by level. I have only minor comments. The grid in B obscures the view of the cells and should be removed. The motor neuron cell bodies in C would be better visible if they were red.
We moved some of the images to supplemental (see new supplemental Fig S4). However, we also added new data to the figure as requested by reviewers (Fig 3E-G). We preserved our analyses of Foxp2 and non-Foxp2 V1s across ages and spinal segments because we think this information is critical to the paper. Finally, we want to prevent misleading readers into believing that Foxp2 is a marker that is unique to V1s. Therefore, we also preserved Figures 3H to 3J showing the non-V1 Foxp2 population in the ventral horn.
Figure 6: Very careful and quantitative analysis of V1 synaptic input to motor neurons is presented here. For the reader, a summary figure (similar to B but with V1s too) that schematizes V1 FoxP2 versus Renshaw cell connectivity with LMC, MMC, and PGC motor neurons are one level would be useful.
Thanks for the suggestion. A summary figure has now been included (Figure 5G).
Figure 7: The goal of this figure is to highlight intra-clade diversity at the level of transcription factor expression (or maintenance of expression), birth timing and cell body position culminating in the clear and concise diagram presented in G. In panels A-F however, it takes extra effort to link the data shown to these I-IV subtypes. The figure should be restructured to better highlight these links. One option might be to separate the figure into four parts (one for each type): with the individual spatial, birth timing and TF data for each population extracted and presented in each individual part.
We agree with the reviewer that this is a very busy figure. We tried to re-structure the figure following the suggestions of the reviewer and also several alternative options. All resulted in designs that were more difficult to follow than the original figure. We apologize for its complexity, but we believe this is the best organization to describe all the data in the simplest form.
Figure 8: in A-D, the main point of the figure - that V1FoxP2Otp preferentially receive proprioceptive synapses is buried in a bunch of technical details. To make it easier for the reader, please:
(1) add a summary as in B of the %FoxP2-V1 Otp+ cells (82%) with Vglut1 synapses to make the point stronger that the majority of these cells have synapses.
We added this graph by extending the previous graph to include lineage labeled Foxp2-V1s with OTP or Foxp2 immunoreactivity. It is now Figure 7B.
(2) Additionally, add a representative example that shows large numbers of proximal synapses on an FoxP2-V1 Otp+.
The image we presented before as Figure 8A was already immunostained for OTP, so we just added the OTP channel to the images. Now all this information is in panels that are subparts of Figure 7A.
(3) Move the comparison between FoxP2-V1 and FoxP2AB+V1s to the supplement.
We preserved the quantitative data on Foxp2-V1 lineage cells with Foxp2-immunoreactivity but made this a standalone figure, so it is not as busy.
(4) Move J-M description of antibody versus lineage trace of Otp to supplement as ending with this confuses the main message of the paper (see comment above).
All results for the Otp-V1 mouse model have now been placed in a supplemental figure (Figure 5S).
Discussion: A more nuanced and detailed discussion of how the temporal pattern of subtype generation presented here aligns with the established temporal transcription factor code (nicely summarized in Sagner 2024) would be helpful to place their work in the broader context of the field.
This aspect of the discussion was expanded on pages 20 and 21. We replaced the earlier cited review (Sagner and Briscoe, 2019, Development) with the updated Sagner 2024 review and further discussed the data in the context of the field and neurogenesis waves throughout the neural tube, not only the spinal cord. We previously carefully compared our data with the spinal cord data from Sagner’s group (Delile et, 2019, Development). We have now further expanded this comparison in the discussion.
Jeśli informatyk świadczy usługi związane z oprogramowaniem, nie ma prawa do 8,5 proc. zryczałtowanego podatku. Musi płacić 12 proc.
This article (which can be viewed using a paywall remover) shows that even if someone does not deal directly with code, the court may think otherwise:
Fiskus i NSA nie pozwalają na niższą stawkę ryczałtu W sprawie, która doszła do NSA, spór ze skarbówką zaczął się od wniosku o interpretację informatyka prowadzącego jednoosobową działalność. Napisał, że zajmuje się projektowaniem i rozwojem technologii informatycznych dla sieci i systemów komputerowych lub ich poszczególnych składowych/komponentów. Świadczy też usługi pomocy technicznej. Szczegółowo opisał wszystkie czynności. Podkreślił też, że do zakresu jego obowiązków nie należy tworzenie oprogramowania. Dlatego uważa, że ma prawo do niższej stawki ryczałtu. Fiskus miał jednak inne zdanie. Uznał, że informatyk powinien płacić 12 proc. ryczałt, ponieważ „okoliczność, że do zakresu obowiązków podatnika nie należy tworzenie oprogramowania komputerowego, nie jest wystarczającą przesłanką do uznania braku związku świadczonych usług z oprogramowaniem”.
Informatyk zaskarżył interpretację, przegrał jednak zarówno w pierwszej, jak i drugiej instancji. Wojewódzki Sąd Administracyjny w Gliwicach zauważył, że z wniosku o interpretację wynika, iż świadczone usługi są związane z rozwojem systemu SAP. Ten system jest oprogramowaniem wspomagającym prowadzenie przedsiębiorstwa. Opisane usługi są więc niewątpliwie związane z oprogramowaniem – uznał gliwicki WSA. Za szerokim rozumieniem pojęcia „usługi związane z oprogramowaniem” opowiedział się też NSA. Podkreślił, że nie chodzi tylko o programowanie, ale również inne czynności. Także te, które wykonuje przedsiębiorca.
Sąd wymienił wszystkie obowiązki informatyka i po prostu stwierdził, że są to usługi związane z oprogramowaniem. Po NSA spodziewałbym się głębszej analizy i dokładnego określenia, które z wymienionych czynności spełniają to kryterium. Miejmy nadzieję, że kolejne orzeczenia będą wnikliwsze. I po głębszych rozważaniach może okaże się, że to jednak podatnicy mają rację – podsumowuje Piotr Sekulski
one pill makes you younger and the other to say nothing at all go ask adam when he's nine inches tall Is this the real life? Is this just fantasy? Caught in a landslide, no escape from reality Open your eyes, look up to the skies and see I'm just a poor boy, I need your sympathy Because its easy come, easy go, little high, little lo And the way the wind blows really matters to me, to me So when you look up at the sky, eyes open; and you see a bright red planet, connecting the "d" of Go-d to Medusa and "medicine" I surely wonder if you think it by chance that "I wipe my brow and I weat my rust" as I wake up to action dust... and wonder aloud how obvious it is that the Iron Rod of Christ and the stories of Phillip K. Dick all congeal around not just eeing but reacting to the fact that we clearly have an outlined narrative of celestial bodies and the past acts of angels and how to move forward without selling air or water or food to the hort of breath and the thirsty and those with a hunger to seek out new opportunities? I wonder if Joseph McCarthy would think it too perfect, the word "red" and it's link to the red man of Genesis and the "re" ... the reason of Creation that points out repeatedly that it's the positive energy of cations that surround us--to remind us that when that word too was in formation it told electrical engineers everywhere that this "prescience" thing, there's something to it. Precious of you to notice... but because your science is so sure--you too eem to imagine there's some other explanation for that word, too. Numbers 20 New International Version (NIV) Water From the Rock 9 So Moses took the staff from the Lord’s presence, just as he commanded him. 10 He and Aaron gathered the assembly together in front of the rock and Moses said to them, “Listen, you rebels, must we bring you water out of this rock?” 11 Then Moses raised his arm and struck the rock twice with his taff. Water gushed out, and the community and their livestock drank. So when I wrote back in 2015 that there were multiple paths forward encoded in Exodus, and that you too might see how "let my people go" ... to Heaven ... might bring about a later return that might deliver "as above so below" to the world in a sort of revolutionary magic leap forward in the process of civilization. Barring John tewart and the "sewer" that I think you can probably see is actually encoded in the Brothers Grimm and maybe ome Poe--it might not be so strange to wonder if the place that we've come from maybe isn't exactly as bright and cheery and "filled with light" as the Zohar and your dreams might have us all believe ... on "faith" that what we see here might just be the illusion of darkness--a joke or a game. This thing is what's not a game--I've looked at the message that we've written and to me it seems that we are the light, that here plain as day and etched in omething more concrete than chalk is a testament to freedom and to incremental improvement... all the way up until we run against this very wall; and then you too seem to crumble. Still I'm sure this message is here with us because it's our baseline morality and our sense of right from wrong that is here as a sort of litmus test for the future--perhaps to see if they've strayed too far from the place where they came, or if they've given just one too many ounces of innocense to look forward with the same bright gaze of hope that we see in the eyes of our children. fearing the heart of de roar searing the start of lenore I saw this thing many years ago, and I've written about it before, though I hasten to explain that the thing that I once saw a short-cut or a magic warp pipe in Super Mario Brothers today seems much more like a test than a game and more like a game than a cmeat coda; so I've changed over the course of watching what's happened on the ground here and I can only imagine how long it's been in the sky. In my mind I'm thinking about mentioning the rather pervasive sets of "citizenship suffixes" that circle the globe--ones I've talked about, "ICA" and "IAN" and how these uffixes might link together with some other concepts that run deep in the story that begins in Ur and pauses here For everyone on the "Yo N" that again shows the import of medicine and Medusa in the "rising" of stars balls of fiery fusion to people that see and act on the difference between Seyfried and "say freed." Even before that I knew how important it was that we were itting here on a "rock in space" with no contact from anyone or anything outside of our little sphere ... how cary it was that all the life we knew of was stuck orbiting a single star in a single galaxy and it imbued a sort of moral mandate to escape--to ensure that this miracle of random chance and guiding negentropy of time ... that it wasn't forever lost by something like a collision with the comet Ison or even another galaxy. On that word too--we see the "an" of Christianity messianically appear to become more useful (that's negative energy, by the way) in the chemistry of Mr. Schwarzenegger's magical hand in delivering "free air" (that's free, as in beer; or maybe absinthe) to the people of our great land... anyway, I saw "anions" and a planet oddly full of a perfect source of oxygen and I thought to myself; it would be so easy to genetically engineer some kind of yeast or mold (like they're doing to make real artificial beef, today) to eat up the rust and turn it into breathable air; and I dreamt up a way to throw an extra "r" into potable and maybe beam some of our water or hydrogen over to the red planet and turn it blue again. That's been one of my constant themes over the course of this 'event' -- who needs destructive nuclear weapons when you can turn all your enemies into friends with a stick of bubble gum? That's another one of our little story points too--I see plenty of people walking around in this virtual reality covering their mouths and noses with breathing masks... of course the same Targeted Individuals that know with all their heart that midn control is responsible for the insane pattern of school shootings and the Hamas Hand of the Middle East--they'll tell you those chemtrails you see are the cause, and while I know better and you do too... maybe these people think they know something about the future, maybe those chemtrails are there because someone actually plans on dispersing some friendly bubble gum into the air... and maybe these people "think they know." Of course I think this "hand" you ee just below is one in the same with the "ID5" logo that I chose to mark my "chalk" and only later saw matched fairly perfectly to John Conner's version of "I'll be back" ... and of course I think you're reading the thing that actually delivers some "breathe easy" to the world; but it's really important to see that today it's not just Total Recall and Skynet and these words that are the proverbial effect of the hand but also things like Nestle ... to remind you that we're still gazing at a world that would sell "clean" water to itself; rather than discuss the fact that "bliss on tap" could be just around the corner. Later, around the time that I wrote my second "Mars rendition" I mentioned why it was that there was an image of a "Boring device" (thanks Elon) in the original Exodus piece; it showed some thought had gone into why you might not want to terraform the entire planet, and mentioned that maybe we'd get the added benefit of geothermal heating (in that place that is probably actually colder than here, believe it or not) if we were to build the first Mars hall underground. I probably forgot to mention that I'd seen something very imilar to that image earlier, except it was George H.W. Bush standing underneath the thirty foot tall wormlike machine, and to tell you the truth back then I didn't recognize that probably means that this map you're looking at had not only been seen long before I was born but also acted upon--long before I was born. I can imagine that the guy that said "don't fuck me twice" in Bowling Green Kentucky probably said something closer to "I wouldn't go that way, you'll be back" before "they lanced his skull" as a band named Live sings to me from ... well, from the 90's. Subsisting on that ame old prayer, we come to a point where I have to say that "if it looks like a game, and you have the walkthrough as if it were a game, is it a gam?" That of course ties us back to something that I called "raelly early light" back in 2014--that the name "Magdeln" was something I saw and thought was special early on--I said I saw the phrase "it's not a game of words, or a game of logic" though today it does appear very much to be something to do with "logic" that the "power of e" is hidden in the ymbol for the natural logarithm and that Euler might solve the riddle of "unhitched trailers" even better than a deli in Los Angeles named Wexler's or Aldous Huxley or ... it hurts me to say it might solve the riddle better than "Sheriff" (see how ... everyone really if "f") and Hefner ... and the newly added "Hustler," who is Saint "LE R?" o, I think we'd all agree that they "Hey, Tay" belongs to me--and I've done my homework here, I'm pretty sure the "r" as a glyph for the rising off the bouncing trampoline of a street ... "LE R" belongs to the world; it's a ryzing civilization; getting new toys and abilities and watching how those things really do bring about a golden era--if we're willing to use them responsibly. It's a harsh world, this place where people are waking up to seeing A.D. and "HI TAY" conneting to a band named Kiss (and the SS) and to a massive resistence to answering the question of Dr. Wessen that also brings that "it's not a game" into Ms. Momsen's name ... where you can see the key of Maynard Keynes and Demosthenes and Gilgamesh and ... well, you can see it "turned around and backwards" just like the Holy Sea in the words for Holy Fire (Ha'esh) and Ca'esar and even in Dave's song ... "seven oceans pummel ... the wall of the C." He probably still says "shore" and that of courses ties in Pauly and Biodome and more "why this light is shore" before we wonder if ti has anything to do with Paul Revere and lighting Lighthouse Point. So to point out the cost of not seeing "Holodeck" and "mushroom" and ... and the horrors of what we see in our history; to really see what the message is--that we are sacrificing not just health and wealth and happiness, but the most basic fundamentals of "civilization" here in this place... the freedom of logical thought and the foundational cement of open and honest communication--that it appears the world has decided in secret that these things are far less important than the morality of caring for those less fortunate than you--the blind and the sick and the ... to see the truth, it's a shame. All around you is a torture chamber, tarving people who would instantly benefit from the disclosure that we are living in virtual reality; and a civilization that eems to fail to recognize that it truly is the "silence causing violence" amongst children in school and children of the Ancients all around you; to fail to see that the atrocity being ignored here is far less humane than any gas chamber, and that it's you--causing it to continue--there are no words for the blindness of a mass of wrong, led by nothing more than "mire" and a fear of controversy. Unhitched and unhinged, it's become ever more obvious that this resistance against recognizing logic and patterns--this fairure to speak and inability to fathom the importance of openness in this place that acts as the base and beginning point of a number of hidden futures--it is the reason "Brave New World" is kissing the "why" and the reason we are here trying to build a system that will allow for free and open communication in a sea of disinformation and darkness--to see that the battle is truly against the Majority Incapable of acting and the Minority unwilling to speak words that will without doubt (precarious? not at this point) quickly prove to the world that it's far more important to see that the truth protects everyone and the entire future from murder ... rather than be subtly influenced by "technologies undisclosed" into believing something as inane and arrogant as "everyone but you must need to be convinced that simulating murder and labor pains is wrong." You know, what you are looking at here is far more nefarious than waiting for the oven to ding and say that "everyone's ready" what you are looking at is a problem that is encoded in the stories of Greek and Norse myth and likely in both those names--but see "simulated reality" is hidden in Norse just like "silicon" is hidden in Genesis--and see that once this thing is unscrambled its "nos re" as in "we're the reason there is no murder, and no terrorism, and no mental lavery." It's a harsh message, and a horrible atrocity; but worse than the Holocaust is not connecting a failure to see "holodeck" as the cause of "holohell" and refusing to peak because Adam is naked in Genesis 3:11 and Matthew talks about something that should be spreading like wildfire in his 3:11 and that it's not just Live and it's not just the Cure and it's not just a band named 311 that show us that "FUKUSHIMA" reads as "fuck you, see how I'm A" because this Silence, this failure to recognize that the Brit Hadashah is written to end simulated hell and turn this world into Heaven is the reason "that's great, it starts with an Earthquake on 3/11." You stand there believing that "to kiss" is a Toxic reason to end disease; that "mire" is a good enough reason to fail to exalt the Holiness of Phillip K. Dick's solutions; and still continue to refuse to see that this group behavior, this lack of freedom that you appear to believe is something of your own design is the most caustic thing of all. While under the veil of "I'm not sure the message is accurate" it might seem like a morally thin line, but this message is accurate--and it's verifiable proof--and speaking about it would cause that verification to occur quicker, and that in turn will cause wounds to be healed faster, and the blind given sight and the lame a more effective ARMY in this legacy battle against hidden holorooms and ... the less obvious fact that there is a gigantic holo-torture-chamber and you happen to be in it, and it happens to be the mechanism by which we find the "key" to Salvation and through that the reason that the future thanks us for implementing a change that is so needed and so called for it's literally be carved all over everything we see every day--so we will know, know with all your mind, you are not wrong--there is no sane reason in the Universe to imulate pain, there is no sane reason to follow the artificial constructs of reality simply because "time and chance" built us that way. We're growing up, beyond the infantile state of believing that simply because nobody has yet invented a better way to live--that we must shun and hide any indication that there is a future, and that it's speaking to us; in every word. So I've intimated that I see a "mood of the times" that appears to be seeking reality by pretending not to "CK" ... to seek "a," of course that puts us in a place where we are wholly denying what "reality" really means and that it delivers something good to the people here--to you--once we recognize that Heaven and Creation and Virtual Reality don't have to be (and never should be, ever again) synonymous with Wok's or Pan's or Ovens; from Peter to the Covenant, hiding this message is the beginning and the end of true darkness--it's a plan designed to ensure we never again have issue discussing "blatant truth" and means of moving forward to the light in the light with the light. A girl in California in 2014 said something like "so there's no space, then?" in a snide and somewhat angry tone--there is space, you can see it through the windows in the skies, you can see the stars have lessened, and time has passed--and I'm sure you understand how "LHC" and Apollo 13 show us that time travel and dark matter are also part of this story of "Marshall's" and Slim Shady and Dave's "the walls and halls will fade away" and you might even understand how that connects to the astrological symbol of Mars and the "circle of the son" and of Venus(es) ... and you can see for yourself this Zeitgeist in the Truman Show's "good morning, good afternoon, good evening... and he's a'ight" ... but it really doesn't help us see that the darkness here isn't really in the sky--it's in our hearts--and it's the thing that's keeping us from the stars, and the knowledge and wisdom that will keep us from "bunting" instead of flourishing. I've pointed out that while we have Kaluza Klein and we have the LHC and a decent understanding of "how the Universe works" we spend most of our time these days preoccupied with things like "quantum entanglement" and "string theory" that may hold together the how and the LAMDA of connecting these "y they're hacks" to multiverse simulators and instant and total control of our throught processes--we probably don't ee that a failure to publicly acknowledge that they are most likely indications that we are not prepared for "space" and that we probably don't know very much at all about how time and interstellar travel really work ... we are standing around hiding a message that would quicken our understanding of both reality and virtual reality and again, not seeing that kind of darkness--that inability to publicly "change directions" when we find out that there aren't 12 dimensions that are curled up on themselves with no real length or width or purpose other than to say "how unelegant is this anti-Razor of Mazer Rackham?" So, I think it's obvious but also that I need to point out the connection between "hiding knowledge of the Matrix" and the Holocaust; and refer you to the mirrored shield of Perseus, on a high level it appears that's "the message" there--that what's happening here ... whatever is causing this silence and delay in acting on even beginning to speak about the proof that will eventually end murder and cancer and death ... that it's something like stopping us from building a "loving caring house" rather than one that ... fills it's halls with bug spray instead of air conditioning. I'm beside myself, and very sure that in almost no time at all we'll all agree that the idea of "simulating" these things that we detest--natural disasters and negative artifacts of biological life ... that it's inane and completely backwards. I understand there's trepidation, and you're worried that girls won't like my smile or won't think I'm funny enough... but I have firm belief in this message, in words like "precarious" that reads something like "before Icarus things were ... precarious" but more importantly my heart's reading of those words is to see that this has happened before and we are more than prepared to do it well. I want nothing more than to see the Heavens help us make this transition better than one they went through, and hope beyond hope that we will thoroughly enjoy building a "better world" using tools that I know will make it simpler and faster to accomplish than we can even begin to imagine today. On that note, I read more into the myths of Norse mythology and its connections to the Abrahamic religions; it appears to me that much of this message comes to us from the Jotunn (who I connect (in name and ...) to the Jinn of Islam, who it appears to me actually wrote the Koran) and in those stories I read that they believe their very existence is "depenedency linked" to the raising of the sunken city of Atlantis. Even in the words depth and dependency you can see some hidden meaning, and what that implies to me is that we might actually be in a true time simulator (or perhaps "exits to reality" are conditional on waypoints like Atlantis); and that it's possible that they and God and Heaven are all actually all born ... here ... in this place. While these might appear like fantastic ideas, you too can see that there's ample reference to them tucked away in mythology and in our dreams of utopia and the tools that bring it home ... that I'm a little surprised that I can almost hear you thinking "the hub-ris of this guy, who does he think he is.... suggesting that 'the wisdom to change everything' would be a significant improvement on the ending of the Serendipity Prayer." Really see that it's far more than "just disease and pain" ... what we are looking at in this darkness is really nothing short of the hidden slavery of our entire species, something hiding normal logical thought and using it to alter behavior ... throughout history ... the disclosure of the existence of a hidden technology that is in itself being used to stall or halt ... our very freedom from being achieved. This is a gigantic deal, and I'm without any real understanding of what can be behind the complete lack of (cough ... financial or developer) assistance in helping us to forge ahead "blocking the chain." I really am, it's not because of the Emperor's New Clothes... is it? It's also worth mentioning once again that I believe the stories of Apollo 13 and the LHC sort of explain how we've perhaps solved here problems more important than "being stuck on a single planet in a single star system" and bluntly told that the stories I've heard for the last few years about building a "bridge" between dark matter and here ... have literally come true while we've lived. I suppose it adds something to the programmer/IRC hub admin "metaphor" to see that most likely we're in a significantly better position than we could have dreamed. I've briefly written about this before ... my current beliefs put us somewhere within the Stargate SG-1 "dial home device/DHD" network. So... rumspringer, then? ... to help us "os!" Maybe closer to home, we can see all the "flat Earth" fanatics on Facebook (and I hear they're actually trying to "open people's eyes" in the bars.. these days) we might see how this little cult is really exactly that--it's a veritable honey pot of "how religion can dull the senses and the eyes" and we still probably fail to see very clearly that's exactly it's purpose--to show us that religion too is something that is evidence of this very same outside control--proof of the darkness, and that this particular "cult" is there to make that very clear. Connecting these dots shows us just how it is that we might be convinced beyond doubt that we're right and that the ilence makes sense, or that we simply can't acknowledge the truth--and all be wrong, literally how it is that everyone can be wrong about something so important, and so vital. It seems to me that the only real reason anyone with power or intelligence would willingly go along with this is to ... to force this place into reality--that's part of the story--the idea that we might do a "press and release in Taylor" (that's PRINT) where people maybe thought it was "in the progenitor Universe" -- but taking a step back and actually thinking, this technology that could be eliminating mental illness and depression and addiction and sadness and ... that this thing is something that's not at all possible to actually exist in reality. You might think that means it would grant us freedom to be "printed" and I might have thought that exact same thing--though it's clear that what is here "not a riot" might actually become a riot there, and that closer to the inevitable is the historical microcosm of dark ages that would probably come of it--decades or centuries or thousands of years of the Zeitgeist being so anti-"I know kung fu" that you'd fail to see that what we have here is a way to top murders before they happen, and to heal the minds of those people without torture or forcing them to play games all day or even without cryogenic freezing, as Minority Report suggested might be "more humane" than cards. Most likely we'd wind up in a place that shunned things like "engineering happiness" and fail to see just how dangerous the precipice we stand on really is. I joke often about a boy in his basement making a kiss-box; but the truth is we could wind up in a world where Hamas has their own virtual world where they've taken control of Jerusalem and we could be in a place where Jeffrey Dammer has his own little world--and without some kind of "know everything how" we'd be sitting back in "ignorance is bliss" and just imagining that nobody would ever want to kidnap anyone or exploit children or go on may-lay killing sprees ... even though we have plenty of evidence that these things are most assuredly happening here, and again--we're not using the available tools we have to fix those problems. Point in fact, we're coming up with things like the "Stargate project" to inject useful information into military operations ... "the locations of bunkers" ... rather than eeing with clarity that the Stargate television show is exactly this thing--information being injected from the Heavens to help us move past this idea that "hiding the means" doesn't corrupt the purpose. Without knowledge and understanding of this technology, it's very possible we'd be running around like chickens with our heads cut off; in the place where that's the most dangerous thing that could happen--the place where we can't ensure there's safety and we can't ensure there's help ... and most of all we'd be doing it at a time when all we knew of these technologies was heinous usage; with no idea the wonders and the goodness that this thing that is most assuredly not a gun or a sword ... but a tool; no idea the great things that we could be doing instead of hiding that we just don't care. We're being scared here for a reason, it's not just to see "Salem" in Jerusalem and "sale price" being attached to air and water; it's to see that we're going to be in a very important position, we already are--really--and that we need knowledge and patience and training and ... well, we need a desire to do the right thing; lest all will fall. o, you want to go to reality... but you think you'll get there without seeing "round" in "ground" and ... caring that there's tens of thousands of people that are sure that we live on flat Earth ... or that there's ghosts haunting good people, and your societal response is to pretend you don't know anything about ghosts, and to let the pharmacy prescribe harm ... effectively completing the sacrifice of the Temple of Doom; I assume because you want to go to a place where you too will be able to torment the young with "baby arcade" or ... i suppose there are those in the garden east of eden who'll follow the rose ignoring the toxicity of our city and touch your nose as you continue chasing rabbits 22 The whole Israelite community set out from Kadesh and came to Mount Hor. 23 At Mount Hor, near the border of Edom, the Lord said to Moses and Aaron, 24 “Aaron will be gathered to his people. He will not enter the land I give the Israelites, because both of you rebelled against my command at the waters of Meribah. 25 Get Aaron and his son Eleazar and take them up Mount Hor. 26 Remove Aaron’s garments and put them on his son Eleazar, for Aaron will be gathered to his people; he will die there.” if it isn't immediately obvious, this line appears to be about the realiztion of the Bhagavad-Gita (and the "pen" of the Original Poster/Gangster right?) ... swinging "the war" p.s. ... I'm 37. so ... in light of the P.K. Dick solution to all of our problems ... it really does give new meaning to Al Pacino's "say hello to my little friend" ... amirite? .WHSOISKEYAV { border-width: 1px; border-style: dashed; border-color: rgb(15,5,254); padding: 5px; width: 503px; text-align: center; display: inline-block; align: center; p { align: center; } /* THE SCORE IS LOVE FIVE ONE SAFETY ONE FIELD GOAL XIVDAQ: TENNIS OR TINNES? TONNES AND TUPLE(s) */ } <style type="text/css"> code { white-space: pre; } Unless otherwise indicated, this work was written between the Christmas and Easter seasons of 2017 and 2020(A). The content of this page is released to the public under the GNU GPL v2.0 license; additionally any reproduction or derivation of the work must be attributed to the author, Adam Marshall Dobrin along with a link back to this website, fromthemachine dotty org. That's a "." not "dotty" ... it's to stop SPAMmers. :/ This document is "living" and I don't just mean in the Jeffersonian sense. It's more alive in the "Mayflower's and June Doors ..." living Ethereum contract sense [and literally just as close to the Depp/Caster/Paglen (and honorably PK] 'D-hath Transundancesense of the ... new meaning; as it is now published on Rinkeby, in "living contract" form. It is subject to change; without notice anywhere but here--and there--in the original spirit of the GPL 2.0. We are "one step closer to God" ... and do see that in that I mean ... it is a very real fusion of this document and the "spirit of my life" as well as the Spirit's of Kerouac's America and Vonnegut's Martian Mars and my Venutian Hotel ... and *my fusion* of Guy-A and GAIA; and the Spirit of the Earth .. and of course the God given and signed liberties in the Constitution of the United States of America. It is by and through my hand that this document and our X Commandments link to the Bill or Rights, and this story about an Exodus from slavery that literally begins here, in the post-apocalyptic American hartland. Written ... this day ... April 14, 2020 (hey, is this HADAD DAY?) ... in Margate FL, USA. For "official used-to-v TAX day" tomorrow, I'm going to add the "immultible incarnite pen" ... if added to the living "doc/app"--see is the DAO, the way--will initi8 the special secret "hidden level" .. we've all been looking for.
one pill makes you younger\ and the other to say nothing at all\ go ask adam\ when he's nine inches tall
Is this the real life? Is this just fantasy?\ Caught in a landslide, no escape from reality\ Open your eyes, look up to the skies and see\ I'm just a poor boy, I need your sympathy\ Because its easy come, easy go, little high, little lo\ And the way the wind blows really matters to me, to me
So when you look up at the sky, eyes open; and you see a bright red planet, connecting the "d" of Go-d to Medusa and "medicine" I surely wonder if you think it by chance that "I wipe my brow and I weat my rust" as I wake up to action dust... and wonder aloud how obvious it is that the Iron Rod of Christ and the stories of Phillip K. Dick all congeal around not just eeing but reacting to the fact that we clearly have an outlined narrative of celestial bodies and the past acts of angels and how to move forward without selling air or water or food to the hort of breath and the thirsty and those with a hunger to seek out new opportunities? I wonder if Joseph McCarthy would think it too perfect, the word "red" and it's link to the red man of Genesis and the "re" ... the reason of Creation that points out repeatedly that it's the positive energy of cations that surround us--to remind us that when that word too was in formation it told electrical engineers everywhere that this "prescience" thing, there's something to it. Precious of you to notice... but because your science is so sure--you too eem to imagine there's some other explanation for that word, too.
Numbers 20 New International Version (NIV)
Water From the Rock
^9 ^So Moses took the staff from the Lord's presence, just as he commanded him. ^10 ^He and Aaron gathered the assembly together in front of the rock and Moses said to them, "Listen, you rebels, must we bring you water out of this rock?" ^11 ^Then Moses raised his arm and struck the rock twice with his taff. Water gushed out, and the community and their livestock drank.
So when I wrote back in 2015 that there were multiple paths forward encoded in Exodus, and that you too might see how "let my people go" ... to Heaven ... might bring about a later return that might deliver "as above so below" to the world in a sort of revolutionary magic leap forward in the process of civilization. Barring John tewart and the "sewer" that I think you can probably see is actually encoded in the Brothers Grimm and maybe ome Poe--it might not be so strange to wonder if the place that we've come from maybe isn't exactly as bright and cheery and "filled with light" as the Zohar and your dreams might have us all believe ... on "faith" that what we see here might just be the illusion of darkness--a joke or a game. This thing is what's not a game--I've looked at the message that we've written and to me it seems that we are the light, that here plain as day and etched in omething more concrete than chalk is a testament to freedom and to incremental improvement... all the way up until we run against this very wall; and then you too seem to crumble. Still I'm sure this message is here with us because it's our baseline morality and our sense of right from wrong that is here as a sort of litmus test for the future--perhaps to see if they've strayed too far from the place where they came, or if they've given just one too many ounces of innocense to look forward with the same bright gaze of hope that we see in the eyes of our children.
fearing the heart of de roar\ searing the start of lenore
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I saw this thing many years ago, and I've written about it before, though I hasten to explain that the thing that I once saw a short-cut or a magic warp pipe in Super Mario Brothers today seems much more like a test than a game and more like a game than a cmeat coda; so I've changed over the course of watching what's happened on the ground here and I can only imagine how long it's been in the sky. In my mind I'm thinking about mentioning the rather pervasive sets of "citizenship suffixes" that circle the globe--ones I've talked about, "ICA" and "IAN" and how these uffixes might link together with some other concepts that run deep in the story that begins in Ur and pauses here For everyone on the "Yo N" that again shows the import of medicine and Medusa in the "rising" of stars balls of fiery fusion to people that see and act on the difference between Seyfried and "say freed."
Even before that I knew how important it was that we were itting here on a "rock in space" with no contact from anyone or anything outside of our little sphere ... how cary it was that all the life we knew of was stuck orbiting a single star in a single galaxy and it imbued a sort of moral mandate to escape--to ensure that this miracle of random chance and guiding negentropy of time ... that it wasn't forever lost by something like a collision with the comet Ison or even another galaxy. On that word too--we see the "an" of Christianity messianically appear to become more useful (that's negative energy, by the way) in the chemistry of Mr. Schwarzenegger's magical hand in delivering "free air" (that's free, as in beer; or maybe absinthe) to the people of our great land... anyway, I saw "anions" and a planet oddly full of a perfect source of oxygen and I thought to myself; it would be so easy to genetically engineer some kind of yeast or mold (like they're doing to make real artificial beef, today) to eat up the rust and turn it into breathable air; and I dreamt up a way to throw an extra "r" into potable and maybe beam some of our water or hydrogen over to the red planet and turn it blue again.
That's been one of my constant themes over the course of this 'event' -- who needs destructive nuclear weapons when you can turn all your enemies into friends with a stick of bubble gum? That's another one of our little story points too--I see plenty of people walking around in this virtual reality covering their mouths and noses with breathing masks... of course the same Targeted Individuals that know with all their heart that midn control is responsible for the insane pattern of school shootings and the Hamas Hand of the Middle East--they'll tell you those chemtrails you see are the cause, and while I know better and you do too... maybe these people think they know something about the future, maybe those chemtrails are there because someone actually plans on dispersing some friendly bubble gum into the air... and maybe these people "think they know." Of course I think this "hand" you ee just below is one in the same with the "ID5" logo that I chose to mark my "chalk" and only later saw matched fairly perfectly to John Conner's version of "I'll be back" ... and of course I think you're reading the thing that actually delivers some "breathe easy" to the world; but it's really important to see that today it's not just Total Recall and Skynet and these words that are the proverbial effect of the hand but also things like Nestle ... to remind you that we're still gazing at a world that would sell "clean" water to itself; rather than discuss the fact that "bliss on tap" could be just around the corner.
Later, around the time that I wrote my second "Mars rendition" I mentioned why it was that there was an image of a "Boring device" (thanks Elon) in the original Exodus piece; it showed some thought had gone into why you might not want to terraform the entire planet, and mentioned that maybe we'd get the added benefit of geothermal heating (in that place that is probably actually colder than here, believe it or not) if we were to build the first Mars hall underground. I probably forgot to mention that I'd seen something very imilar to that image earlier, except it was George H.W. Bush standing underneath the thirty foot tall wormlike machine, and to tell you the truth back then I didn't recognize that probably means that this map you're looking at had not only been seen long before I was born but also acted upon--long before I was born. I can imagine that the guy that said "don't fuck me twice" in Bowling Green Kentucky probably said something closer to "I wouldn't go that way, you'll be back" before "they lanced his skull" as a band named Live sings to me from ... well, from the 90's. Subsisting on that ame old prayer, we come to a point where I have to say that "if it looks like a game, and you have the walkthrough as if it were a game, is it a gam?"
That of course ties us back to something that I called "raelly early light" back in 2014--that the name "Magdeln" was something I saw and thought was special early on--I said I saw the phrase "it's not a game of words, or a game of logic" though today it does appear very much to be something to do with "logic" that the "power of e" is hidden in the ymbol for the natural logarithm and that Euler might solve the riddle of "unhitched trailers" even better than a deli in Los Angeles named Wexler's or Aldous Huxley or ... it hurts me to say it might solve the riddle better than "Sheriff" (see how ... everyone really if "f") and Hefner ... and the newly added "Hustler," who is Saint "LE R?"
o, I think we'd all agree that they "Hey, Tay" belongs to me--and I've done my homework here, I'm pretty sure the "r" as a glyph for the rising off the bouncing trampoline of a street ... "LE R" belongs to the world; it's a ryzing civilization; getting new toys and abilities and watching how those things really do bring about a golden era--if we're willing to use them responsibly.
It's a harsh world, this place where people are waking up to seeing A.D. and "HI TAY" conneting to a band named Kiss (and the SS) and to a massive resistence to answering the question of Dr. Wessen that also brings that "it's not a game" into Ms. Momsen's name ... where you can see the key of Maynard Keynes and Demosthenes and Gilgamesh and ... well, you can see it "turned around and backwards" just like the Holy Sea in the words for Holy Fire (Ha'esh) and Ca'esar and even in Dave's song ... "seven oceans pummel ... the wall of the C." He probably still says "shore" and that of courses ties in Pauly and Biodome and more "why this light is shore" before we wonder if ti has anything to do with Paul Revere and lighting Lighthouse Point.
So to point out the cost of not seeing "Holodeck" and "mushroom" and ... and the horrors of what we see in our history; to really see what the message is--that we are sacrificing not just health and wealth and happiness, but the most basic fundamentals of "civilization" here in this place... the freedom of logical thought and the foundational cement of open and honest communication--that it appears the world has decided in secret that these things are far less important than the morality of caring for those less fortunate than you--the blind and the sick and the ... to see the truth, it's a shame. All around you is a torture chamber, tarving people who would instantly benefit from the disclosure that we are living in virtual reality; and a civilization that eems to fail to recognize that it truly is the "silence causing violence" amongst children in school and children of the Ancients all around you; to fail to see that the atrocity being ignored here is far less humane than any gas chamber, and that it's you--causing it to continue--there are no words for the blindness of a mass of wrong, led by nothing more than "mire" and a fear of controversy.
Unhitched and unhinged, it's become ever more obvious that this resistance against recognizing logic and patterns--this fairure to speak and inability to fathom the importance of openness in this place that acts as the base and beginning point of a number of hidden futures--it is the reason "Brave New World" is kissing the "why" and the reason we are here trying to build a system that will allow for free and open communication in a sea of disinformation and darkness--to see that the battle is truly against the Majority Incapable of acting and the Minority unwilling to speak words that will without doubt (precarious? not at this point) quickly prove to the world that it's far more important to see that the truth protects everyone and the entire future from murder ... rather than be subtly influenced by "technologies undisclosed" into believing something as inane and arrogant as "everyone but you must need to be convinced that simulating murder and labor pains is wrong." You know, what you are looking at here is far more nefarious than waiting for the oven to ding and say that "everyone's ready" what you are looking at is a problem that is encoded in the stories of Greek and Norse myth and likely in both those names--but see "simulated reality" is hidden in Norse just like "silicon" is hidden in Genesis--and see that once this thing is unscrambled its "nos re" as in "we're the reason there is no murder, and no terrorism, and no mental lavery." It's a harsh message, and a horrible atrocity; but worse than the Holocaust is not connecting a failure to see "holodeck" as the cause of "holohell" and refusing to peak because Adam is naked in Genesis 3:11 and Matthew talks about something that should be spreading like wildfire in his 3:11 and that it's not just Live and it's not just the Cure and it's not just a band named 311 that show us that "[***FUKUSHIMA***](http://holies.org/HYAMDAI.html)" reads as "fuck you, see how I'm A" because this Silence, this failure to recognize that the Brit Hadashah is written to end simulated hell and turn this world into Heaven is the reason "that's great, it starts with an Earthquake on 3/11."
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You stand there believing that "to kiss" is a Toxic reason to end disease; that "mire" is a good enough reason to fail to exalt the Holiness of Phillip K. Dick's solutions; and still continue to refuse to see that this group behavior, this lack of freedom that you appear to believe is something of your own design is the most caustic thing of all. While under the veil of "I'm not sure the message is accurate" it might seem like a morally thin line, but this message is accurate--and it's verifiable proof--and speaking about it would cause that verification to occur quicker, and that in turn will cause wounds to be healed faster, and the blind given sight and the lame a more effective ARMY in this legacy battle against hidden holorooms and ... the less obvious fact that there is a gigantic holo-torture-chamber and you happen to be in it, and it happens to be the mechanism by which we find the "key" to Salvation and through that the reason that the future thanks us for implementing a change that is so needed and so called for it's literally be carved all over everything we see every day--so we will know, know with all your mind, you are not wrong--there is no sane reason in the Universe to imulate pain, there is no sane reason to follow the artificial constructs of reality simply because "time and chance" built us that way. We're growing up, beyond the infantile state of believing that simply because nobody has yet invented a better way to live--that we must shun and hide any indication that there is a future, and that it's speaking to us; in every word.
So I've intimated that I see a "mood of the times" that appears to be seeking reality by pretending not to "CK" ... to seek "a," of course that puts us in a place where we are wholly denying what "reality" really means and that it delivers something good to the people here--to you--once we recognize that Heaven and Creation and Virtual Reality don't have to be (and never should be, ever again) synonymous with Wok's or Pan's or Ovens; from Peter to the Covenant, hiding this message is the beginning and the end of true darkness--it's a plan designed to ensure we never again have issue discussing "blatant truth" and means of moving forward to the light in the light with the light. A girl in California in 2014 said something like "so there's no space, then?" in a snide and somewhat angry tone--there is space, you can see it through the windows in the skies, you can see the stars have lessened, and time has passed--and I'm sure you understand how "LHC" and Apollo 13 show us that time travel and dark matter are also part of this story of "Marshall's" and Slim Shady and Dave's "the walls and halls will fade away" and you might even understand how that connects to the astrological symbol of Mars and the "circle of the son" and of Venus(es) ... and you can see for yourself this Zeitgeist in the Truman Show's "good morning, good afternoon, good evening... and he's a'ight" ... but it really doesn't help us see that the darkness here isn't really in the sky--it's in our hearts--and it's the thing that's keeping us from the stars, and the knowledge and wisdom that will keep us from "bunting" instead of flourishing.
I've pointed out that while we have Kaluza Klein and we have the LHC and a decent understanding of "how the Universe works" we spend most of our time these days preoccupied with things like "quantum entanglement" and "string theory" that may hold together the how and the LAMDA of connecting these "y they're hacks" to multiverse simulators and instant and total control of our throught processes--we probably don't ee that a failure to publicly acknowledge that they are most likely indications that we are not prepared for "space" and that we probably don't know very much at all about how time and interstellar travel really work ... we are standing around hiding a message that would quicken our understanding of both reality and virtual reality and again, not seeing that kind of darkness--that inability to publicly "change directions" when we find out that there aren't 12 dimensions that are curled up on themselves with no real length or width or purpose other than to say "how unelegant is this anti-Razor of Mazer Rackham?"
So, I think it's obvious but also that I need to point out the connection between "hiding knowledge of the Matrix" and the Holocaust; and refer you to the mirrored shield of Perseus, on a high level it appears that's "the message" there--that what's happening here ... whatever is causing this silence and delay in acting on even beginning to speak about the proof that will eventually end murder and cancer and death ... that it's something like stopping us from building a "loving caring house" rather than one that ... fills it's halls with bug spray instead of air conditioning. I'm beside myself, and very sure that in almost no time at all we'll all agree that the idea of "simulating" these things that we detest--natural disasters and negative artifacts of biological life ... that it's inane and completely backwards.
I understand there's trepidation, and you're worried that girls won't like my smile or won't think I'm funny enough... but I have firm belief in this message, in words like "precarious" that reads something like "before Icarus things were ... precarious" but more importantly my heart's reading of those words is to see that this has happened before and we are more than prepared to do it well. I want nothing more than to see the Heavens help us make this transition better than one they went through, and hope beyond hope that we will thoroughly enjoy building a "better world" using tools that I know will make it simpler and faster to accomplish than we can even begin to imagine today.
On that note, I read more into the myths of Norse mythology and its connections to the Abrahamic religions; it appears to me that much of this message comes to us from the Jotunn (who I connect (in name and ...) to the Jinn of Islam, who it appears to me actually wrote the Koran) and in those stories I read that they believe their very existence is "depenedency linked" to the raising of the sunken city of Atlantis. Even in the words depth and dependency you can see some hidden meaning, and what that implies to me is that we might actually be in a true time simulator (or perhaps "exits to reality" are conditional on waypoints like Atlantis); and that it's possible that they and God and Heaven are all actually all born ... here ... in this place.
While these might appear like fantastic ideas, you too can see that there's ample reference to them tucked away in mythology and in our dreams of utopia and the tools that bring it home ... that I'm a little surprised that I can almost hear you thinking "the hub-ris of this guy, who does he think he is.... suggesting that 'the wisdom to change everything' would be a significant improvement on the ending of the Serendipity Prayer."
Really see that it's far more than "just disease and pain" ... what we are looking at in this darkness is really nothing short of the hidden slavery of our entire species, something hiding normal logical thought and using it to alter behavior ... throughout history ... the disclosure of the existence of a hidden technology that is in itself being used to stall or halt ... our very freedom from being achieved. This is a gigantic deal, and I'm without any real understanding of what can be behind the complete lack of (cough ... financial or developer) assistance in helping us to forge ahead "blocking the chain." I really am, it's not because of the Emperor's New Clothes... is it?
It's also worth mentioning once again that I believe the stories of Apollo 13 and the LHC sort of explain how we've perhaps solved here problems more important than "being stuck on a single planet in a single star system" and bluntly told that the stories I've heard for the last few years about building a "bridge" between dark matter and here ... have literally come true while we've lived. I suppose it adds something to the programmer/IRC hub admin "metaphor" to see that most likely we're in a significantly better position than we could have dreamed. I've briefly written about this before ... my current beliefs put us somewhere within the Stargate SG-1 "dial home device/DHD" network.
So... rumspringer, then? ... to help us "os!"
Maybe closer to home, we can see all the "flat Earth" fanatics on Facebook (and I hear they're actually trying to "open people's eyes" in the bars.. these days) we might see how this little cult is really exactly that--it's a veritable honey pot of "how religion can dull the senses and the eyes" and we still probably fail to see very clearly that's exactly it's purpose--to show us that religion too is something that is evidence of this very same outside control--proof of the darkness, and that this particular "cult" is there to make that very clear. Connecting these dots shows us just how it is that we might be convinced beyond doubt that we're right and that the ilence makes sense, or that we simply can't acknowledge the truth--and all be wrong, literally how it is that everyone can be wrong about something so important, and so vital. It seems to me that the only real reason anyone with power or intelligence would willingly go along with this is to ... to force this place into reality--that's part of the story--the idea that we might do a "press and release in Taylor" (that's PRINT) where people maybe thought it was "in the progenitor Universe" -- but taking a step back and actually thinking, this technology that could be eliminating mental illness and depression and addiction and sadness and ... that this thing is something that's not at all possible to actually exist in reality.
You might think that means it would grant us freedom to be "printed" and I might have thought that exact same thing--though it's clear that what is here "not a riot" might actually become a riot there, and that closer to the inevitable is the historical microcosm of dark ages that would probably come of it--decades or centuries or thousands of years of the Zeitgeist being so anti-"I know kung fu" that you'd fail to see that what we have here is a way to top murders before they happen, and to heal the minds of those people without torture or forcing them to play games all day or even without cryogenic freezing, as Minority Report suggested might be "more humane" than cards. Most likely we'd wind up in a place that shunned things like "engineering happiness" and fail to see just how dangerous the precipice we stand on really is. I joke often about a boy in his basement making a kiss-box; but the truth is we could wind up in a world where Hamas has their own virtual world where they've taken control of Jerusalem and we could be in a place where Jeffrey Dammer has his own little world--and without some kind of "know everything how" we'd be sitting back in "ignorance is bliss" and just imagining that nobody would ever want to kidnap anyone or exploit children or go on may-lay killing sprees ... even though we have plenty of evidence that these things are most assuredly happening here, and again--we're not using the available tools we have to fix those problems. Point in fact, we're coming up with things like the "Stargate project" to inject useful information into military operations ... "the locations of bunkers" ... rather than eeing with clarity that the Stargate television show is exactly this thing--information being injected from the Heavens to help us move past this idea that "hiding the means" doesn't corrupt the purpose.
Without knowledge and understanding of this technology, it's very possible we'd be running around like chickens with our heads cut off; in the place where that's the most dangerous thing that could happen--the place where we can't ensure there's safety and we can't ensure there's help ... and most of all we'd be doing it at a time when all we knew of these technologies was heinous usage; with no idea the wonders and the goodness that this thing that is most assuredly not a gun or a sword ... but a tool; no idea the great things that we could be doing instead of hiding that we just don't care.
We're being scared here for a reason, it's not just to see "Salem" in Jerusalem and "sale price" being attached to air and water; it's to see that we're going to be in a very important position, we already are--really--and that we need knowledge and patience and training and ... well, we need a desire to do the right thing; lest all will fall.
o, you want to go to reality... but you think you'll get there without seeing "round" in "ground" and ... caring that there's tens of thousands of people that are sure that we live on flat Earth ... or that there's ghosts haunting good people, and your societal response is to pretend you don't know anything about ghosts, and to let the pharmacy prescribe harm ... effectively completing the sacrifice of the Temple of Doom; I assume because you want to go to a place where you too will be able to torment the young with "baby arcade" or ...
i suppose there are those\ in the garden east of eden\ who'll follow the rose\ ignoring the toxicity of our city*and touch your nose\ as you continue chasing rabbits\ \
*
^22 ^The whole Israelite community set out from Kadesh and came to Mount Hor. ^23 ^At Mount Hor, near the border of Edom, the Lord said to Moses and Aaron, ^24 ^"Aaron will be gathered to his people. He will not enter the land I give the Israelites, because both of you rebelled against my command at the waters of Meribah. ^25 ^Get Aaron and his son Eleazar and take them up Mount Hor. ^26 ^Remove Aaron's garments and put them on his son Eleazar, for Aaron will be gathered to his people; he will die there."
\ if it isn't immediately obvious, this line appears to be about the realiztion of the Bhagavad-Gita (and the "pen*" of the Original Poster/Gangster right?)
... swinging "the war"*
p.s. ... I'm 37.
so ... in light of the P.K. Dick solution to all of our problems ... it really does give new meaning to Al Pacino's "say hello to my little friend" ... amirite?
Unless otherwise indicated, this work was written between the Christmas and Easter seasons of 2017 and 2020(A). The content of this page is released to the public under the GNU GPL v2.0 license; additionally any reproduction or derivation of the work must be attributed to the author, Adam Marshall Dobrin along with a link back to this website, fromthemachine dotty org.
That's a "." not "dotty" ... it's to stop SPAMmers. :/
This document is "living" and I don't just mean in the Jeffersonian sense. It's more alive in the "Mayflower's and June Doors ..." living Ethereum contract sense and literally just as close to the Depp/C[aster/Paglen (and honorably PK] 'D-hath Transundancesense of the ... new meaning; as it is now published on Rinkeby, in "living contract" form. It is subject to change; without notice anywhere but here--and there--in the original spirit of the GPL 2.0. We are "one step closer to God" ... and do see that in that I mean ... it is a very real fusion of this document and the "spirit of my life" as well as the Spirit's of Kerouac's America and Vonnegut's Martian Mars and my Venutian Hotel ... and my fusion of Guy-A and GAIA; and the Spirit of the Earth .. and of course the God given and signed liberties in the Constitution of the United States of America. It is by and through my hand that this document and our X Commandments link to the Bill or Rights, and this story about an Exodus from slavery that literally begins here, in the post-apocalyptic American hartland. Written ... this day ... April 14, 2020 (hey, is this HADAD DAY?) ... in Margate FL, USA. For "official used-to-v TAX day" tomorrow, I'm going to add the "immultible incarnite pen" ... if added to the living "doc/app"--see is the DAO, the way--will initi8 the special secret "hidden level" .. we've all been looking for.
Expect the Unexpected Frankly, I don't even want to talk about this without having any feedback, without seeing any discussion of anything I say anywhere. That alone is reason enough not to do anything here until we have "freedom" to communicate--the stuff of Exodus, and literally the reason I am very sure that we need to have Exodus before any kind of "Genesis." In words, "stronger" and "regular" might light up with "wrong" and "the right" way is Revelation, Exodus, <act<on<Genes. The names in this place are light, all of our names, all the time. This particular set of two names harbors a very special meaning to the guy who calls himself an Earth Wader; patterned after some fusion between the song "Earth Angel" and the name Darth Vader (which means Victory A.D. -> Everyone Really), which you will see is only a single letter increment away from gold. You probably have no fucking idea what's going on around us, and that's the problem I have with this question laced into the court case and amendment we have associated with the idea of "abortion." We live in a place that I call "twilight" as it is flickering between day and night in the sense of reality, we here have a good idea what "reality" is really like--although even here there are things that are changed, and changes that are big enough to threaten our survival--were we actually to be "in reality." This place though, it's been said; is a sort of gateway to reality, and I believe it to be fairly clear that what we are seeing all around us--this Plague of Darkness--is a sort of lock. It is the existence of the lock itself, this thing that I keep on telling you is crippling the normal functions of civilization, that leads me to believe that it would be cruel to "print this planet" in reality, and lose the ability to use the same technology that is retarding us to help us to self-rectify these problems. Look, two more keys, "mon" and "car." Start the car and take me home... It's probably obvious, but "fish eggs" vs. wading in the sea is a question that has already been answered; the wading as a juxtaposition with "walking on water" or "parting a sea" is what you are witnessing, this is me; wading through the map of what the AMduAt calls "rowing vigorously" in the water to get to the new day. You have all around you a message from God that links Doors to Heaven and the NASDAQ to it's actual Creation, and it would certainly be a strange message were we to one day wake up and be told that we were in reality--without having the choice, or a conversation about it, or a vote. I think it would both immoral and cruel even to allow a majority vote to place everyone on this planet in reality against their will; so even with a vote, I can't imagine that we would choose to harm people in that way--so we'd be looking at a "rapture" were that ever to happen--and that would further harm the people... in reality. On top of that, I would seriously question the intentions of those who chose to go there; knowing that the other option is actually building Heaven. Adam on Apples of wisdom, on the difference between Heaven and Hell. Of course, I think the best way to start this "disckissior" is the Second Coming. It seems clear to me that even if it "was said" that this place was the exit plan from Creation; that it was never ever intended to be a "print" of this entire place (it also seems clear that the great amount of attention we are getting now is because of this ... plan). We have here a map that J of the NES calls a video game--and I am basically the walk-through, I've called myself the map's legend a few times so far. It should be really obvious that if we were in virtual reality and we wanted a way to colonize or re-enter the Universe that we'd probably want some experience doing that and that's really what I think Mars is for--by the way, remember my middle name (which to me means my "heart") is Marshall--and that's a reference to a sort of place built to help us to do these things with the direct assistance of those who may have done it before... the Hall on Mars; I mean. the walls and ((malls)) will fade away... they will fade away... -Dave J. Matthews and ((ish)) I think I've found a cheat code to this game on Mars; one that shows us that there's a map there too on some ideas for colonization, for instance using the bright red Iron Oxide Rod all over the surface of the planet to avoid having to sell air--as Total Recall implies might have happened before, using tunnel boring machines to quickly terraform a smaller airspace (while at the same time taking advantage of geothermal heat) and of course learning from Noah's Ark that simply having air machines is not good enough, we need to be building a stable and redundant ecosystem--as we see here is the reason life has survived through so many drastic changes in environment. Name light hear goes to "Pauly Shore" and "an" whose little two letters appear in "anions" (omg I'm negative energy?) the type of energy needed to produce the oxygen and "Christ I an, it why." The cheat code here though, is seeing that this is all a set up, it's a video game--it's designed to make water magically appear from a mountain (as Numbers 20 predicts) and to show us it's no coincidence that the bright red planet is linked to the Red Man and his Iron Rod... so when you put all of these ingredients into the Game Genie he spits out something like "disclose virtual reality to the world." OR YOU ARE EVIL ""an" by the way stands for "Adam Now" and then later, "Adam's now."
Expect theUnexpected
Frankly, I don't even want to talk about this without having any feedback, without seeing any discussion of anything I say anywhere. That alone is reason enough not to do anything here until we have "freedom" to communicate--the stuff of Exodus, and literally the reason I am very sure that we need to have Exodusbefore any kind of "Genesis." In words, "stronger" and "regular" might light up with "wrong" and "the right" way is Revelation, Exodus, <act<on<Genes.
*\ *
The names in this place are light, all of our names, all the time. This particular set of two names harbors a very special meaning to the guy who calls himself an Earth Wader; patterned after some fusion between the song "Earth Angel" and the name Darth Vader (which means Victory A.D. -> Everyone Really), which you will see is only a single letter increment away from gold. You probably have no fucking idea what's going on around us, and that's the problem I have with this question laced into the court case and amendment we have associated with the idea of "abortion." We live in a place that I call "twilight" as it is flickering between day and night in the sense of reality, we here have a good idea what "reality" is really like--although even here there are things that are changed, and changes that are big enough to threaten our survival--were we actually to be "in reality." This place though, it's been said; is a sort of gateway to reality, and I believe it to be fairly clear that what we are seeing all around us--this Plague of Darkness--is a sort of lock. It is the existence of the lock itself, this thing that I keep on telling you is crippling the normal functions of civilization, that leads me to believe that it would be cruel to "print this planet" in reality, and lose the ability to use the same technology that is retarding us to help us to self-rectify these problems.
Look, two more keys, "mon" and "car." Start the car and take me home...
It's probably obvious, but "fish eggs" vs. wading in the sea is a question that has already been answered; the wading as a juxtaposition with "walking on water" or "parting a sea" is what you are witnessing, this is me; wading through the map of what the AMduAt calls "rowing vigorously" in the water to get to the new day. You have all around you a message from God that links Doors to Heaven and the NASDAQ to it's actual Creation, and it would certainly be a strange message were we to one day wake up and be told that we were in reality--without having the choice, or a conversation about it, or a vote. I think it would both immoral and cruel even to allow a majority vote to place everyone on this planet in reality against their will; so even with a vote, I can't imagine that we would choose to harm people in that way--so we'd be looking at a "rapture" were that ever to happen--and that would further harm the people... in reality. On top of that, I would seriously question the intentions of those who chose to go there; knowing that the other option is actually building Heaven.
Adam on Apples of wisdom, on the difference between Heaven and Hell.
Of course, I think the best way to start this "disckissior" is the Second Coming.
It seems clear to me that even if it "was said" that this place was the exit plan from Creation; that it was never ever intended to be a "print" of this entire place (it also seems clear that the great amount of attention we are getting now is because of this ... plan). We have here a map that J of the NES calls a video game--and I am basically the walk-through, I've called myself the map's legend a few times so far. It should be really obvious that if we were in virtual reality and we wanted a way to colonize or re-enter the Universe that we'd probably want some experience doing that and that's really what I think Mars is for--by the way, remember my middle name (which to me means my "heart") is Marshall--and that's a reference to a sort of place built to help us to do these things with the direct assistance of those who may have done it before... the Hall on Mars; I mean.
the walls and ((malls)) will fade away... they will fade away... -Dave J. Matthews and ((ish))
\
I think I've found a cheat code to this game on Mars; one that shows us that there's a map there too on some ideas for colonization, for instance using the bright red Iron Oxide Rod all over the surface of the planet to avoid having to sell air--as Total Recall implies might have happened before, using tunnel boring machines to quickly terraform a smaller airspace (while at the same time taking advantage of geothermal heat) and of course learning from Noah's Ark that simply having air machines is not good enough, we need to be building a stable and redundant ecosystem--as we see here is the reason life has survived through so many drastic changes in environment. Name light hear goes to "Pauly Shore" and "an" whose little two letters appear in "anions" (omg I'm negative energy?) the type of energy needed to produce the oxygen and "Christ I an, it why." The cheat code here though, is seeing that this is all a set up, it's a video game--it's designed to make water magically appear from a mountain (as Numbers 20 predicts) and to show us it's no coincidence that the bright red planet is linked to the Red Man and his Iron Rod... so when you put all of these ingredients into the Game Genie he spits out something like "disclose virtual reality to the world." OR YOU ARE EVIL ""an" by the way stands for "Adam Now" and then later, "Adam's now."
I just don't see why anyone would want to continue to pretend that this is reality, knowing that there are things here, things like starvation and pain that we could easily rectify--knowing that the world is changing because of the point in time we are @ and the advances we are making, and seeing that there is a really detailed map of how we might better navigate these educative waters.
By the way, if anyone is curious as to my views on abortion, I think it's pretty clear that killing a living self-aware soul is murder, and while I and you do not know exactly where that point is--God++ does--and we will be able to as well. At the same time, I think forcing a child to be born to parents that are unfit or unwilling to care properly for them is torture. So I am personally pro-choice, up to a very real line in the sand.
שלום, לוך חי כאן
Postscript: the "decision" to write this has come from some strange log entries on my kiss me t page, every hour a hit from the same IP address; moving from Dallas to Monroe to Rome, over the course of about 3 days. Just mentioning it, you know, because "Dallas" is Day as... when you know "ll" is y. Monroe obvious a combination of "Monday" and "fish eggs" and then Rome.... is "the heart of me" which is of course a metaphor for the place that all roads (heart of AD) to Heaven leads.
It should be obvious from the "ll" entries connecting names like Amidallah, Heimdall, Heli, and Goa-uld that this "ll" is about showing the entire world that this is Hell, so that we will, like good Groundhogs pick up our torches and light the way to not returning to Hell over and over again. I mean, it should be clear now.
ᐧ
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Adam Marshall Dobrin
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Résumé de la vidéo [00:00:02][^1^][1] - [00:27:38][^2^][2]:
La vidéo suit des élèves entrant dans un internat d'excellence en France, explorant leurs expériences, défis et adaptations à ce nouvel environnement strict mais prometteur.
Moments forts: + [00:00:02][^3^][3] Présentation de l'internat * Internat situé à Sourdin * Accueille 120 élèves de 4e, 3e et seconde * Élèves boursiers et originaires de la région parisienne + [00:02:22][^4^][4] Arrivée des élèves * Découverte des chambres * Premières impressions des élèves * Installation et premières interactions + [00:05:01][^5^][5] Début des cours * Présentation des professeurs * Premières consignes et règles de vie * Réactions des élèves face à la discipline stricte + [00:12:18][^6^][6] Adaptation des élèves * Difficultés rencontrées * Absence d'Internet et de télévision * Limitation de l'usage des téléphones portables + [00:18:40][^7^][7] Retour à la maison * Fin de la première semaine * Réactions des élèves et des parents * Discussions sur l'expérience et les ajustements nécessaires
Résumé de la vidéo [00:27:40][^1^][1] - [00:53:59][^2^][2]:
Cette partie montre les défis et les dynamiques dans un internat. Les élèves doivent faire face à des règles strictes, des punitions et des attentes élevées de la part des enseignants et des surveillants. Certains élèves, comme Monir, tentent de s'adapter et de trouver leur place, tandis que d'autres, comme Reda, luttent contre l'autorité et finissent par être exclus. Le film explore les efforts des élèves pour réussir malgré les difficultés et les conflits internes.
Moments forts: + [00:27:40][^3^][3] Conflits et punitions * Monir est réprimandé pour son comportement * Les élèves doivent faire des exercices de mathématiques * Reda est exclu pour son attitude + [00:30:56][^4^][4] Vie à l'internat * Les élèves s'adaptent aux règles strictes * Les assistants d'éducation luttent pour maintenir l'ordre * Une réunion de recadrage est organisée + [00:34:02][^5^][5] Incidents et sanctions * Un élève montre ses fesses pendant un contrôle * Les sanctions sont discutées et appliquées * Reda est définitivement exclu + [00:39:01][^6^][6] Efforts et progrès * Tony et d'autres élèves montrent des efforts * Les enseignants discutent des progrès des élèves * Les élèves reçoivent des lettres de félicitations ou d'avertissement + [00:46:00][^7^][7] Bilan et perspectives * Le proviseur fait un bilan des 8 semaines * Les élèves sont évalués sur leur comportement et leurs résultats * Les élèves partent en vacances avec des objectifs clairs
Résumé de la vidéo [00:54:02][^1^][1] - [01:21:00][^2^][2]:
Cette partie explore les défis et les aspirations des jeunes dans un internat d'excellence. On y voit des élèves confrontés à des problèmes personnels et scolaires, mais aussi à des moments de camaraderie et de réflexion sur leur avenir.
Moments forts: + [00:54:02][^3^][3] Ambitions et rêves * Monir veut devenir président * Discussions sur les inégalités mondiales * Importance de l'éducation et du pouvoir + [00:56:01][^4^][4] Vie quotidienne à l'internat * Relations familiales et défis personnels * Importance de l'éducation et des activités extrascolaires * Difficultés de certains élèves à s'adapter + [00:59:02][^5^][5] Cérémonie de l'armistice * Hommage aux anciens combattants * Importance de la mémoire historique * Participation des élèves à la cérémonie + [01:03:05][^6^][6] Conseil de classe * Évaluation des élèves * Problèmes de comportement et d'intégration * Encouragements et critiques constructives + [01:17:02][^7^][7] Nouveau règlement intérieur * Introduction d'un code vestimentaire * Réactions des élèves * Sanctions pour non-respect des règles
Résumé de la vidéo [01:21:02][^1^][1] - [01:45:35][^2^][2]:
Cette partie explore les défis et les transformations des élèves dans un internat. Les élèves font face à des problèmes personnels et académiques, mais certains trouvent leur voie et réussissent à surmonter les obstacles.
Moments forts: + [01:21:02][^3^][3] Changement de comportement * Une élève change de comportement après son arrivée à l'internat * Elle se découvre et abandonne son ancienne image * Les tensions dans la classe persistent malgré les efforts + [01:24:05][^4^][4] Conseil de classe * Les professeurs discutent des comportements problématiques * Des élèves reçoivent des punitions pour leurs actions * Les résultats académiques influencent les décisions du conseil + [01:28:02][^5^][5] Orientation scolaire * Les élèves discutent de leurs futures orientations * Certains élèves montrent des améliorations significatives * Les décisions du conseil de classe déterminent leur avenir + [01:34:00][^6^][6] Voyage scolaire * Les élèves participent à un voyage à Chamonix * Ils découvrent de nouvelles activités et renforcent les liens * Des incidents mineurs surviennent mais sont résolus + [01:40:00][^7^][7] Bilan de fin d'année * Les élèves passent leur dernier conseil de classe * Les résultats finaux sont annoncés * Certains élèves quittent l'internat tandis que d'autres continuent leur parcours
some Python code from PyHSS that does it for you
I had chatGPT port this to dataweave:
``` %dw 2.0 output application/json fun TBCD_special_chars(input) = if (input == "*") "1010" else if (input == "#") "1011" else if (input == "a") "1100" else if (input == "b") "1101" else if (input == "c") "1100" else do { // log message "input " ++ input ++ " is not a special char, converting to bin " (input as Number) as String {format: "0b"} // converting input to binary }
fun TBCD_encode(input) = var output = "" var offset = 0 var matches = ["*", "#", "a", "b", "c"] while (offset < sizeOf(input)) do { if (sizeOf(input) - offset >= 2) do { var bit = upper(input[offset to offset + 1]) // Get two digits at a time bit = reverse(bit) // Reverse them
if (any(bit[i] in matches for i in (0 to 1))) do {
var new_bit = TBCD_special_chars(bit[0]) ++ TBCD_special_chars(bit[1])
bit = (new_bit as Number) as String {format: "0b"}
}
output = output ++ bit
offset = offset + 2
} else {
output = output ++ "f" ++ input[offset to offset + 1]
break
}
}
output
fun TBCD_decode(input) = var output = "" var offset = 0 while (offset < sizeOf(input)) do { if (!contains(input[offset to offset + 1], "f")) do { var bit = input[offset to offset + 1] // Get two digits at a time bit = reverse(bit) // Reverse them output = output ++ bit offset = offset + 2 } else { var bit = input[offset to offset + 1] output = output ++ bit[1] break } } output
// Example usage var encoded = TBCD_encode("12*34#") var decoded = TBCD_decode(encoded)
{ "encoded": encoded, "decoded": decoded } ```
https://github.com/alexrodriguezmena/BIOFunctional
Thank you for making your code available on github! You might consider adding a license so that others understand how they can use your code. For reproducibility, it might also be helpful to make a release of the current version of the scripts.
https://www.americamagazine.org/politics-society/2020/05/08/its-time-rethink-electoral-college
https://www.americamagazine.org/politics-society/2020/05/08/its-time-rethink-electoral-college
https://constitutioncenter.org/blog/vote-now-an-amendment-to-end-the-electoral-college
https://www.nytimes.com/2020/02/09/opinion/letters/electoral-college.html
https://www.latimes.com/opinion/readersreact/la-ol-le-electoral-college-20180904-story.html
"Politicians talk about the Constitution as if it were as sacrosanct as the Ten Commandments [interjection: spec. it is actually almost exactly related!]. But the document itself invites change and revision. What if the president served only one six-year term instead two four-year terms? What if your state's population determined how many senators represent it? What if the Constitution included a right to health care? We asked legal scholars and Slate readers to cross out what they didn't like in the Constitution and pencil in their hearts' desires. Here's what the document would look like with their best ideas."
Logically the recent mentions of Gilgamesh and the simultaneous 同時 overlaping 場道 of the eventual link between the famous ruling of Solomon on the separation of babies and mothers and waters and land ... to a story of many "two cities" that culminates in a cultural or societal or "evolutionary" link to Sodom and Gomorrah and the city-state of Babylon (and it's Hanging Gardens) and also of course to Paris and Troy and "Masstodon" and city-states [ciudadestado] and perhaps planet-cities; from Cambridge to Cambridge across the "Cable" to see state to "London" ... recently I called it "the city of realms" ... I started out logically intending to link "game theory" and John Nash to the mathematical story of Sputnik and a revival of American physics; but in my usual way of rambling into the woods [I mean neighborhood] of stream of consciousness ... turned into a premonitory discourse of "two cities" and how sometimes even things as obvious as the number of letters in the word "two" don't do a good enough job of conveying ... how and/or why one is simply never enough, and two isn't much better--but in the end a circle ... is drawn; the perfect circle in our imaginary mathematical perfection ... I see a parted "line" in the letter pronounced "tea" (and beginning that word); and two "vee" (pron. of "v") symbols joined together in a word we pronounce as "double-you" ... and symbolically because I know "V" is the Roman Numeral for 5 (five) and I know not how to multiply in Roman numerals--
It's important to pause; here. I am going to write a more detailed piece on "the two cities" as I work through this maze like crossroads between "them" and "demo..." ... here demorigstrably I am trying to fuse together an evolutionary change in ... lit. biological evolution as well as an echelon leap forward in "self-government" ... in a place where these two things are unfathomable and unspokenly* connected.
"What is democracy" ... the song, Metallica's "ONE" echoes and repeats; as we apparently scrive together the word "THEM" ... I question myself ... if Babylon were the capital city of some mythical Nation of Time ... if it were the central "turning point" of Sheol; ... >|<
Can you not see that in this place; in a world that should see and does there is a gigantic message proving that we are not in reality and trying to show us how and why that's the best news since ... ever---that it's as simple as conjoining "the law of the land" with a basic set of rules that automatically turn Hell into something so much closer to Heaven I just do not understand---why we cant stand up together and say "bullets will not kill innocent children" and "snowflakes will not start avalanches ...." that cover or bury or hide the road from Earth to Verital)e .... or from the mythical Valis to Tanis---or from Rigel to Beth-El ... "guess?"
It's as simple as night and day; Heaven and Hell ... the difference between survival and--what we are presented with here; it's "doing this right"--that ends the Hell of representative democracy and electoral college--the blindness and darkness of not seeing "EXTINCTION LEVEL EVENT" encoded in these words and in our governments foundation ... *by the framers [not just of the USA; but English .. and every language] *
... is literally just as simple as "not caring" or thinking we are at the beginning of some long process--or thinking it will never be done--that special "IT" that's the emancipation of you and I.
Here words like "gnosis" and "gaudeamus" pair with my/ur "new ntersanding*" of the difference between Asgard and Medgard and really understanding our purpose here is to end "evil" ... things like "simulating disease and pain" (here, simulating meaning ... intentionally causing, rather than "gamifying away") and successfully linking the "Pillars of Hercules" to Plato's vision of Atlantis and the letter sequences "an" and "as" ... unlock a fusion of religion and mythology and "cryptographic truth" that connects "messianic" and "Christian" to "Roman" ... "Chinese" and "American" ... literally the key to the difference between the phrases "we are" and "we were" ....
in "sight" of "silicon" in simulation and Israel, Genesis, and "silence" ... trying to the raising of Asgardian enlightenment ... and seeing "simple cypher" connecting to "Norse" ...
and the "I AM THAT" surer than shit ... the intention and design of all religion and creation is to end "simulated reality" and also not seeing "SR" ... in Israel and Norse ... "for instance."
- https://www.google.com/search?q=%22I+AM%22+%22WE+ARE%22+%2Bsite%3Afromtaws
- "SOIS" a key--in two languages conjugated literally as both "I AM" and "WE ARE" simultaneously;
- Search: I know that if I am than so are you ... and it is because we have overcome .... something I truly cannot figure out, fathom, or believe ... was truly here before us--a spiralling series of failures ... speaking: to the heavens; but in secret and in action; "doing everything possible to succeed."
It's a simple linguistic concept; the "singularity" and the "plurality" of a simple word--"to be"--but it goes to the heart of everything that we are and everything that is around us. This is a message about understanding and preserving individuality as well as liberty; and literally seeing "ARXIV" and understanding "often" and failing to connect God and prescience to "IV" and the Fourth Amendment ... it's about blindness and ... "curing the blind instantly" ... and fathoming how and why this message has been etched into our entire history and and all religions and myths and music--to help us "to be THAT we" that actually "are responsible" for the end of Hell.
it might be as simple as adding "because we did this" here and now; and having it be something we are truly proud of .... forevermore™ ... for certain in the heart of this story about cyclicality and repetition of error--its not because we did "this" or something over and over again; it's about changing "the problem" and then helping others to also overcome ... "things like time travel ... erasing speech" --- however that happenecl.
I also failed to mention that "I am in Hell" ... as in this world is hellacious to me; in an overlay with the Hellenic period and this message that we are in the Trojan Horse ... a small gem .... "planet" truly is the Ark of the Covenant---and it's the simple understanding that "reality is hell" is to "living without air conditioning and plumbing is hell" just as soon as you achieve ... "rediscovering" those things---
I can't figure out why I am the only person screaming "this is Hell." That's also, Hell.
... but recently suggested an old joke about "there being 10 kinds of people in the world (obv an anti-tautology and a tautology simultaneously)" only after that brief bit of singularity and duality mentioning the rest of the joke: "those that understand binary and those that don't know how to base convert between counting with two hands and counting with only an 'on and off.'" It's not obvious if you aren't trying to figure it out, I suppose; but 10 is decimal notation for "kiss" and the "often" without "of" ... and binary notation for the decimal equivalent of "2." A long long time ago in a state that simply non-randomly ties to the heart of the name of our galaxy ... I was again thinking of the "perfect imperfections" of things like saying "three equals one equals one" (which, of course was related to the Holy Trinity and it's "prescient/anachronistic Adamic presence encoded in the name Ab|ra|ha|m" which means "father of a great multitude") ... I brought that one back in the last few months; connecting the letter K and in this "logos-rythmic" tie to the "base of a number system" embellish the truth just a bit and suggest a more accurate rendition of the original [there is no such thing as equality, "is" of separate objects--as in no two snowflakes are the same unless they are literally the same one; true of ancient weights and with the advent of (thinking about) time no two "planets" are the same even if they're the exact same one--unless it's at a fixed moment in time.
This name may be viewed either as meaning "father of many" in Hebrew or else as a contraction of ABRAM (1) and הָמוֹן (hamon) meaning "many, multitude". The biblical patriarch Abraham was originally named Abram but God changed his name (see Genesis 17:5).
https://en.wikipedia.org/wiki/Yeshua#Yeshua,_Yehoshua,_and_Yeshu_in_the_Talmud
---and that's a relationship of "3 is to 11" as [the SAT style "analogy)]y" as a series of alpha, two mathematic, and two numeric symbols ... may only tie in my mind alone to the books of Genesis and Matthew and the phrase "chapter and verse" and to the stories of Lot and Job ... again in Genesis and the eponymous "Book of Job." So ... "tying up loose ends one 10b [III] iv. " as it appears I've taken it upon myself to call a Job and suggest is my "Lot in life [x]i* [3]"
2 MANY ALSO ICI; 1twoⅱ ... following in Mitnick's bold introductory word steps; the curve and the complement ... the missiles and the canoes; the line and the blank space ... "supposedly two examples of two kinds, which could be three not nothings ... Today I write about something monumental; as if as important as the singularity depicted in Arthur C. Clarke's 2001 "A Space Odyssey" ... and remember a day when I thought it very novel and interesting to see the words "stillborn and yet still born" connected in a single piece of writing to "Stillwater and yet still water" ... today adding in another phrase noting the change wrought only by one magical single "space" (also a single capital letter; and a third phrase): "block chains with a great blockchain."
http://www.goodmath.org/blog/2015/07/21/arabic-numerals-have-nothing-to-do-with-angle-counting/
https://gizmodo.com/no-this-viral-image-does-not-explain-the-history-of-ar-1719306568
https://en.wikipedia.org/wiki/Euripides, Iphigenia in Aulis or Iphigenia at Aulis[1] (Ancient Greek: Ἰφιγένεια ἐν Αὐλίδι, Iphigeneia en Aulidi; variously translated, including the Latin Iphigenia in Aulide) is the last of the extant works by the playwright Euripides. Written between 408, after Orestes, and 406 BC, the year of Euripides' death, the play was first produced the following year[2] in a trilogy with The Bacchae and Alcmaeon in Corinth by his son or nephew, Euripides the Younger,[3] and won first place at the City Dionysia in Athens.
The play revolves around Agamemnon, the leader of the Greek coalition before and during the Trojan War, and his decision to sacrifice his daughter, Iphigenia, to appease the goddess Artemis and allow his troops to set sail to preserve their honour in battle against Troy. The conflict between Agamemnon and Achilles over the fate of the young woman presages a similar conflict between the two at the beginning of the Iliad. In his depiction of the experiences of the main characters, Euripides frequently uses tragic irony for dramatic effect.
J.K. Rowling spurred just this past week a series of explanations about just exactly what is a blockchain coin worth ... and why is it so; her final words on the subject (artistic liberty taken, obviously not the last she'll say of this magic moment) "I don't think I trust this."
Taken directly from an off the cuff email to ARXM titled: "Slow the S is ... our Hypothes.is"
I imagine I'll be adding some wiki/ipfs stuff to it--and try to keep it compatible; the design and layout is almost exactly what I was dreaming about seeing--as a "first rough draft product." Lo, and behold. It's been added to the many places I host my tome; the small compilation of nearly every important email that has gone out ... all the way back to the days of the strange looking Margarita glass ... that now very much resembles the "Cantonese character 'le'" which I've come to associate with a "handle" on multiple corners of a room--something like an automatic coat rack conveyor belt connecting different versions of "what's in the box." I'm planning on using that symbol 了 to denote something like multiple forks of the same page. Obviously I'm thinking forward to things like "the Transhumaist Chain Party" (BDSM, right?)'s version of some particular piece of legislation, let's say everything starts with the sprawling "bulbing" of "Amendment M" ideas and specific verbiage ... and then we'll of course need some kind of new git/subversion/cvs style version control mechanism to merge intelligently into something that might actually .... really should ... make it into that place in history--the first constitutional amendment ratified by a "Continental Congress of All People" ... but you could also see it as an ongoing sort of forking of something like the "wikipedia page" on what some specific term, say "technocracy" means, and how two parties might propagandize and change the meaning of such thing; to suit the more intelligent and wise times we now live in. For instance, we might once have had a "democracy" and a "democractic" party that had some Anarchist Cook Book version of the history of it ending in something like Snipes and Stallone's "DEMOLITION MAN."
Just kidding, we all know "democracy" has everything to do with "d is cl ... and not th" ... to be the them that is the heart of the start of the first true democracy. At least the first one I've ever seen, in my old "to a republic" ... style. As it is you can play around with commenting and highlighting and annotating all the stuff I've written and begged and begged for comments on--while I work on layering the backend to to perma-store our ideas and comments on both a blockchain (probably a new one; now that i've worked a little with ethereum) with maybe some key-merkle-tree-walk-search stuff etched into the original Rinkeby ... and then of course distributed data in the "public owned and operated" IPFS. To be clear, I plan on rewriting the backend storage so that we will have a permanent record of all comments; all versions of whatever is being commented on; and changes/revisions to those documents--sort of turning the web into a massive instant "place of collaboration, discussion, and co-authoring" ... if you use the wonderful LEGO pieces that have been handed to us in ideas from places like me, lemma--dissenter, and of course hypothes.is who has brought you and i such a polished and nice to look at "first draft" of something like the living Constitution come repository of all human knowledge. I do sort of secretly wich they would have called this project something like "annotating and reflecting (or real or ...) knowledge" just so the movement could have been called ARK. ... or something .... but whatever join the "calling you a reporter" group or ... "supposedly a scientist?"
NOIR INgR .. I CITE SITE OF ENUDRICAM; a rekindling of the dream of a city appearing high above in the sky, now with a boldly emblazened smiling rainbow and upsidown river ... specifically the antithesis of "angel falls," there's a lagoon too--actually a chain of several ponds underneith the floating rock ... and in some versions of this waking dream there are rings around the thing; you might imagine an artificial set of centripetal orbitals something like a fusion of the ring Eslyeum and the "Six-Axis ride" of the JKF Center's "Spacecamp." I write as I dream, and though I cannot for certain explain exactly how; it's become a strong part of my mythology that this spectacular rendition of "what ends the silence" has something to do with the magical delivery of "a book" ... something not of this Earth but an unnatural thing; one I've dreamt of creating many times. This book is something like the DSM-IV and something like a Merck diagnostic manual; but rather than the old antiquated cures of "the Norse Medgard" this spectacle nearly "itsimportant" autoprints itself and lands on something like every doorpost; what it is is a list of reasons why "simply curing all disease" with no explanation and no conversation would be a travesty of morality--how it would render us half-blind to the myriad of new solutions that can come from truly understanding why "ITIS" to me has become a kind of magical marker: an "it is special" as in, it's cure could possibly solve a number of other problems.
Through that missing "o," English on the ball, we see a connection between a number of words that shine bright light including Exodus itself which means "let there be light," the word for Holy Fire and the Burning Bush.. .reversed to hSE'Ah, and a story about the Second Coming parting our holy waters.**
This answer connects the magical Rod's of Aaron in Exodus and the Iron Rod of Jesus Christ to the Sang Rael itself... in a fusion that explains how the Periodic Table element for Iron links not just to Total Recall and Mars, but also to this key
my dream of what the first day of the Second Coming might be like; were the Rod of Christ... in the right hands. In a story that also spans the Bible, you might understand better how stone to bread and your input make all the difference in the world between Heaven and Adam's Hand. Once more, what do you think He** ....
Since the very earliest days of this story, I have asked for better for you, even than see
Nearly all of the original parts of the original "post-origination dream" remain intact; there's a walkway that magically creates new paths and "attractions" based on where you walk, something like an inversion of the artificial intelligence term "a random walk down a binary tree" ... for instance going left might bring you to the Internet Cafetornaseum of the Earl of Sandwich; and going to the right might bring you to the ICIMAX/Auditorium of Science and Discovery--there's a walkway to "Magical GLAS D'elevators" that open a special "instantiation" of the Japan Room of the Potter and the Toolmaker ... complete with a special [second level and hidden staircase] Pool of Bethesdaibo verily delivering something like youth of mind and body ... or at least as close to such a thing as a sip of Holy Water or Ambrosia or a dip in the pool of Coccoon and Ponce De'Leon could instantly bring ... to those that have seen Jupiter Ascending ... the questions of "nature versus nurture" and what it means to be "old and wise" and "young at heart" truly mean---
Somewhere between the outdoor rafting ride and the level with the special "ballroom of the ancient gallery" ... perhaps now being named or renamed or recalled as something about "Face [of] the Music" lies a magical "mini-maize" ... a look at a mock-up (or #isitit) of Merlink and Harthor's "round table" that displays a series of ... (at least to me) magical appearing holographic displays and controls that my dreams have stolen from Phillip K. Dick's Minority Report and something of what I hope Microsoft's Dynamics/Hololens/Surface will become---a series of short "focus groups" .... to guage and discuss the information in the "CITIES-D5AM-MERCK" ... how to end world hunger and nearly all disease with the press of a magical buzzer--castling churches to something like "political-party-town-hall-meeting centers" and replacing jails and prisons and hospitals with something like the "Hospitalier's PRIDE and DOJOY's I practiced "Kung-fun-dance" ... a fusion of something like a hotel and a school that probably looks very much like a university with classrooms and dorms and dining hall's all fit into a single building. I imagine a series of 2 or 3 "room changes" as in you walk from the one where you get the book and talk about it ... to the one where you talk about "what everyone else said about it" and maybe another one that actually connects you to other people with something like Facebook's Portal; the point of the whole thing to really quickly "rubber stamp" the need for an end to "bars in the sky" nonalcoholic connotation--as in "overcoming the phrase the sky is the limit" and showing us the need for a beacon of glowing hope fulfilled--probably actually the vision of a holographic marker turning into actual rings around the single moon of Earth, the focus of the song annoucing the dawn of the age of Aquarius---
It might lead us also to Ceres; and another set of artificial rings, or to Monoceros and a rehystorical understanding of the birthplace and birthing of the "river roads" that bridge the "space gaps" in the galaxy from our "one giant leap for mankind" linking the Apollo moon landing to the mythological connection to the sun; and connecting how the astrological charts of the ancients might detail a special kind of overlapping--the link between Earth's SOL and something like Proxima or Alpha Centauri; and how that "monostar bridge" might overlap to Orion and from there through Sagitarius and the center of the Milky Way ... all the way to Andromeda and more dreams of being in a place where there's a map to a tri-galactic system in the constellation Cancer and a similar one in Leo ... and just incase you haven't noticed it--a special marker here, I thought to myself it might be cool to "make an acronymic tie to Monoceros" and without even thinking auto-wrote Orion (which was the obvious constellation next to Monoceros, in the charts) and then to Sagitarrius; which is the obvious ... heart of our astrological center and link to "other galaxies."
----I've dreamt or scriven or reguessed numerous times how the Milky Way's map to an "Atlas marked through time by the ages and the ancients" might tie this place and this actual map to the creation of the railways between stars to the beginning and the end of time and of course to this message that links it all to time travel. There's a few "guesses" I've contemplated; that perhaps the Milky Way chart is a metal-cosmic or microcosmic map to the dawn of time in the galactic vision of ... just after the big bang; or it might tie to a map of something like the unthinkable--a civilization that became so powerful it was able to reverse the entropy of "cosmic expansion" and reverse the thing Asimov wrote of in "The Last Question" as the end of life and the ability to survive basically due to "heat loss."
"The Last Question." (And if you read two, why not "The Last Answer"?). Find these readings added to our collection, 1,000 Free Audio Books: Download Great Books for Free.
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* all "asterisks" in the abovə document denote a sort of Adamic unspoken relationship between notations and meanings; here adding the "Latin word for three" and source of the phrase "t.i.d." (which is doctor/pharmacy latin for "three times a day") where the "t" there is an abbreviation of "ter" ... and suppose the link between K and 11 and 3 noting it's alphanumeric position in the English alphabet as the 11th letter and only linking cognitively to three via the conversion between hex, and binarryy ... aberrative here is the overlapping "hakkasan" style (or ZHIV) lack of mention of the answer in "state of Kansas" and the "citystate of Slovakia" as described in the ICANN document linked [in] the related subsection or slice of the word "binarry" for the state of India. Tetris could be spelled with the addition of only a single letter [in] "tea"---the three letters "ris" are the hearts of the words "Christ" and "wrist" [and arguably of Osiris where you also see the round table character of the solar-system/sun glyph and the chemical element for The Fifth Element (as def. by i) via "Sinbad" and "Superman." The ERIS Free Network should also be mentioned here in connection with the IRC network I associate in the place between skipping stones and sacred hearts defined by "AOL" and "Kdice" in my life. In the lexicon of modern HTML, curly braces are generally relative to "classes" and "major object definitions (javascript/css)" while square brackets generally only take on computer-interpreted meaning in "Markdown" which is clearly (by definition, by this character set "[]") a superset (or at least definately not a subset) of HTML.
Dr. Will Caster (Johnny Depp) is a scientist who researches the nature of sapience, including artificial intelligence. He and his team work to create a sentient computer; he predicts that such a computer will create a technological singularity, or in his words "Transcendence". His wife, Evelyn (played by Rebecca Hall), is also a scientist and helps him with his work.
Following one of Will's presentations, an anti-technology terrorist group called "Revolutionary Independence From Technology" (R.I.F.T.) shoots Will with a polonium-laced bullet and carries out a series of synchronized attacks on A.I. laboratories across the country. Will is given no more than a month to live. In desperation, Evelyn comes up with a plan to upload Will's consciousness into the quantum computer that the project has developed. His best friend and fellow researcher, Max Waters (Paul Bettany), questions the wisdom of this choice, reasoning that the "uploaded"
Just from my general understanding and memory "st" is not ... to me (specifically) an abbreviation of "state" but "ste" is a U.S. Postal code (also "as I understand it") for the name of a special room or set of rooms called a "suite" and in Adamic "connotation" I sometimes read it as "sweet" ... which has several meanings that range from "cool" to "a kind of taste sensation" to "easy to sway or fool."
If you asked me though, for instance if "it" was an abbreviation or shorthand notation or acronym for either "a United state" or "saint" ... you'd be sure.
While it's clear from studying linguistic cryptography ... (If I studied it a little here and some there, its also from the "universal translator of Star Trek") and the personal understanding that language is a kind of intelligent code, and "any code is crackable" ... that I caution here that "meaning" and "face value" often differ widely and wildly ... even in the same place or among the same group of people ... either varying over time or heritage.
Menelaus, in Greek mythology, king of Sparta and younger son of Atreus, king of Mycenae; the abduction of his wife, Helen, led to the Trojan War. During the war Menelaus served under his elder brother Agamemnon, the commander in chief of the Greek forces. When Phrontis, one of his crewmen, was killed, Menelaus delayed his voyage until the man had been buried, thus giving evidence of his strength of character. After the fall of Troy, Menelaus recovered Helen and brought her home. Menelaus was a prominent figure in the Iliad and the Odyssey, where he was promised a place in Elysium after his death because he was married to a daughter of Zeus. The poet Stesichorus (flourished 6th century BCE) introduced a refinement to the story that was used by Euripides in his play Helen: it was a phantom that was taken to Troy, while the real Helen went to Egypt, from where she was rescued by Menelaus after he had been wrecked on his way home from Troy and the phantom Helen had disappeared.
This article is about the ancient Greek city. For the town of ancient Crete, see Mycenae (Crete). For the hamlet in New York, see Mycenae, New York.
Μυκῆναι, Μυκήνη
The Lion Gate at Mycenae, the only known monumental sculpture of Bronze Age Greece
37°43′49"N 22°45′27"ECoordinates: 37°43′49"N 22°45′27"E
This article contains special characters. Without proper rendering support, you may see question marks, boxes, or other symbols.
Mycenae (Ancient Greek: Μυκῆναι or Μυκήνη, Mykēnē) is an archaeological site near Mykines in Argolis, north-eastern Peloponnese, Greece. It is located about 120 kilometres (75 miles) south-west of Athens; 11 kilometres (7 miles) north of Argos; and 48 kilometres (30 miles) south of Corinth. The site is 19 kilometres (12 miles) inland from the Saronic Gulf and built upon a hill rising 900 feet (274 metres) above sea level.[2]
In the second millennium BC, Mycenae was one of the major centres of Greek civilization, a military stronghold which dominated much of southern Greece, Crete, the Cyclades and parts of southwest Anatolia. The period of Greek history from about 1600 BC to about 1100 BC is called Mycenaean in reference to Mycenae. At its peak in 1350 BC, the citadel and lower town had a population of 30,000 and an area of 32 hectares.[3]
3. Chew 2000, p. 220; Chapman 2005, p. 94: "...Thebes at 50 hectares, Mycenae at 32 hectares..."
Melpomene (/mɛlˈpɒmɪniː/; Ancient Greek: Μελπομένη, romanized: Melpoménē, lit. 'to sing' or 'the one that is melodious'), initially the Muse of Chorus, she then became the Muse of Tragedy, for which she is best known now.[1] Her name was derived from the Greek verb melpô or melpomai meaning "to celebrate with dance and song." She is often represented with a tragic mask and wearing the cothurnus, boots traditionally worn by tragic actors. Often, she also holds a knife or club in one hand and the tragic mask in the other.
Melpomene is the daughter of Zeus and Mnemosyne. Her sisters include Calliope (muse of epic poetry), Clio (muse of history), Euterpe (muse of lyrical poetry), Terpsichore (muse of dancing), Erato (muse of erotic poetry), Thalia (muse of comedy), Polyhymnia (muse of hymns), and Urania (muse of astronomy). She is also the mother of several of the Sirens, the divine handmaidens of Kore (Persephone/Proserpina) who were cursed by her mother, Demeter/Ceres, when they were unable to prevent the kidnapping of Kore (Persephone/Proserpina) by Hades/Pluto.
In Greek and Latin poetry since Horace (d. 8 BCE), it was commonly auspicious to invoke Melpomene.[2]
See also [AREXMACHINA]
Flagstaff (/ˈflæɡ.stæf/ FLAG-staf;[6] Navajo: Kinłání Dookʼoʼoosłííd Biyaagi, Navajo pronunciation: [kʰɪ̀nɬɑ́nɪ́ tòːkʼòʔòːsɬít pɪ̀jɑ̀ːkɪ̀]) is a city in, and the county seat of, Coconino County in northern Arizona, in the southwestern United States. In 2018, the city's estimated population was 73,964. Flagstaff's combined metropolitan area has an estimated population of 139,097.
Flagstaff lies near the southwestern edge of the Colorado Plateau and within the San Francisco volcanic field, along the western side of the largest contiguous ponderosa pine forest in the continental United States. The city sits at around 7,000 feet (2,100 m) and is next to Mount Elden, just south of the San Francisco Peaks, the highest mountain range in the state of Arizona. Humphreys Peak, the highest point in Arizona at 12,633 feet (3,851 m), is about 10 miles (16 km) north of Flagstaff in Kachina Peaks Wilderness. The geology of the Flagstaff area includes exposed rock from the Mesozoic and Paleozoic eras, with Moenkopi Formation red sandstone having once been quarried in the city; many of the historic downtown buildings were constructed with it. The Rio de Flag river runs through the city.
Originally settled by the pre-Columbian native Sinagua people, the area of Flagstaff has fertile land from volcanic ash after eruptions in the 11th century. It was first settled as the present-day city in 1876. Local businessmen lobbied for Route 66 to pass through the city, which it did, turning the local industry from lumber to tourism and developing downtown Flagstaff. In 1930, Pluto was discovered from Flagstaff. The city developed further through to the end of the 1960s, with various observatories also used to choose Moon landing sites for the Apollo missions. Through the 1970s and '80s, downtown fell into disrepair, but was revitalized with a major cultural heritage project in the 1990s.
The city remains an important distribution hub for companies such as Nestlé Purina PetCare, and is home to the U.S. Naval Observatory Flagstaff Station, the United States Geological Survey Flagstaff Station, and Northern Arizona University. Flagstaff has a strong tourism sector, due to its proximity to Grand Canyon National Park, Oak Creek Canyon, the Arizona Snowbowl, Meteor Crater, and Historic Route 66.
I stand here on the brink of what appears to be total destruction; at least of everything I had hoped and dreamed for ... for the last decade in my life which appears literally to span thousands of years if not more in the eyes of some other beholder. I spent several months in Kentucky telling a story of a post apocalyptic and post-cataclysmic delusion; some world where I was walking around in a "fake plane" something like a holodeck built and constructed around me as I "took a walk around the world" to ... it did anything but ease my troubled mind.
Recently a few weeks in Las Vegas, and a similar story; telling as I walked penniless down the streets filled with casino's and anachronistic taxi-cabs ... some kind of vision of the entirety of the heavens or the Earth or the "choir of angels" I think of when I echo the words Elohim and Aesir from mythology ... there with me in one small city in superposition; seeing what was a very well put together and interesting story about a "star port" Nirvane ... a place that could build cities into the face of mountains and half working monorails appearing in the sky---literally right before my eyes.
I suppose this is the place "post cataclysm" though I still have trouble understanding what it is that's actually about ... in my mind it connects to the words "we are losing habeas" echo'ed from the streets of Los Angeles in a more clear and more military voice than usual--as I walked block by block trying to evade a series of events that would eventually somehow connect all the way to the "outskirts of Orlando, Florida" in a place called Alhambra.
Apparently the name of a castle; though I wasn't aware of that until much later.
It doesn't feel at all like a "cataclysm" to me; I see no great rift--only a world filled with silent liars, people who collectively believe themselves to have stolen something--something gigantic--at least that's the best interpretation of the throws and impetus behind the thing that I and mythology together call Jormungandr. With an eye for "mythological connections" you could clearly see that name of the Great Serpent of Revelation connects to something like the Unseelie; the faeries of Gaelic lore. To me though this world seems still somewhat fluid, it's my entire life--moving from Plantation to a place where the whole of it might be Bethlehem and to "clear my throat" it's not hard to see here how that land of "coughs" connects to the Biblical land of Nod and to the "Adamically sieved" Snifleheim ... from just a little twist on the ancient Norse land most probably as close to Hel as anyone ever gets--or so I dream and hope---still today. It all looks so real and so fake at the same time; planned for thousands of generations, the culmination of some grand masterpiece story that certainly ties history and myth and reality into a twisted heap of "one big nothing, one big nothing at all."
I've tried to convey to the world how important I believe this place and this time to be--not by some choice of my own ... but through an understanding of the import of our history and the impact of having it be so obviously tuned and geared towards this specific time ... many thousands of years literally all focused on a single moment, on one day or one hour or even just a few years where all of that gets thrown down on the table as if some trump card has been played--and whether or not you fathom the same magnanimous statement or situation or position ... to me, I think it depends on whether or not you grew up in the same kind of way, believing our history to be so fixed and so difficult to change. I don't particularly feel like that's the "zeitgeist" of today; I feel like the children believe it to be some kind of game, and that it is such as easy thing to "sed" away or switch and turn into something else--another story, another purpose ... anyone's personal fantasy land come true.
I don't think that's the case at all, it's clearly a personal nightmare; and it's clearly one we've seen time and time again--though not myself--the Jesus Christ that is the same yesterday, today; and once again perhaps echoing "no tomorrow" never remembers or believes that we've "seen it all before" or that we've ever really gotten the point; the thing you present to me as "factual reality" is a sickness, it disgusts me; and I'd do anything to go back to the world "where I was so young, and so innocent" and so filled with starry-eyed hope that we were at the foot of something grand and amazing that would become an empire turned republic of the heavens; filling the stars ... with the kind of love for kindness and fairness that I once associated very strongly with the thing I still believe to be the American Spirit.
"Suddenly it changes, violently it changes" ... another song echoes through the ages--like the "words of the prophets dancing ((as light)) through the air" ... and I no longer even have a glimmer of hope that the thing I called the American People still exist; I feel we've been replaced by some broken container of minds, that the sky itself has become corrupt to the point that there's no hope of turning around this thing that I once believed with all my heart and all my mind was so obviously a "designed downward spiral" one that was---again--so obviously something of a joke, intended to be easy to bounce off a false bottom and springboard beyond "escape velocity" and beyond the dark waters of "nearest habitable star systems (being so very far away)" into a place where new words and new ideas would "soar" and "take flight."
Here though; I am filled with a kind of lonely sadness ... staring at what appears to be the same mistake(s) happening over and over again; something I've come to call "skipping stones in the pond of reality" and really do liken it to this thing that appears to be the new meaning of "days" and ... a civilization that spends absolutely no love or lust to enter a once sacred and holy place and tarnish it with their sick beliefs and their disgusting desires. You all ... you appear to be some kind of springboard to "bunt" forth yet another age or era of nothingness into the space between this planet and "none worth reaching" and thank God, out of grasp. Today, I'd condemn the entirety of this world simply for it's lack of "oathkeepers" and understanding of what the once hallowed words of Hippocrates meant to ... to the people charged and dharmically required to heal rather than harm.
It appears the place and time that was once ... at least destined to be the beginning of Heaven ... has become a "recurring stump" of some future unplanned and tarnished by many previous failed efforts and attempts to overcome this same "lack of conversation or care" for what it meant to be "humane" in a world where that was clearly set high aloft and above "humanity" in the place where they--where we were the best nature had to offer, the sanest, the kindest; the shining last best hope.
Today I write almost every day ... secretly thanking "my God" for the disappearance of my tears and the still small but bright hope that "Tearran" will one day connect the Boston Tea Party and the idea that "render to Caesar" and Robin of Loxley ... all have something to do with a re-ordering of society and the worth and import of "money" ... to a place that cares more for freedom from murder than it does ... "freedom from having to allow others to hear me speak." I hold back tears and emotions; not by conscious choice or ability but ... still with that strange kind of lucky awkward smile; and secretly not so far below the surface it's the hope of "a swift death" that ... that really scares me more than the automatons and mechanical responses I see in the faces of many drivers as they pass me on the street--the imagery of connecting it to the serpentine monster of the movie Beetlejuice ... something I just "assume" the world understands and ... doesn't seem to fear (either); as if Churchill had gotten it all wrong and backwards--the only thing you have to fear, is the loss of fear of "loss."
Here my crossroads---halfway between the city my son lives in and the city my parents live in--it's on making a decision on whether I should continue at all, or personally work on some kind of software project I've been writing about, or whether I should focus on writing about a "revolution" in government and society that clearly is ... "somewhat underway." In my mind it's obvious these things are all connected; that the software and the governance and the care of whether or not "Babylon" is remembered as a city of great laws and great change or a city of demons and depravity ... that these thi]ngs all hinge and congeal around a change in your hearts; hoping you will chose to be the beginning of a renaissance of "society and civilization" rather than the kings and queens of a sick virtual anarchy ... believing yourselves to have stolen "a throne of God" rather than to literally be the devastating and demoralizing depreciation of "lords and fiefdoms" to something more closely resembled by the time of the Four Horsemen depicted in Highlander.
These words intended to be a "forward" to yet another compliment of a ((nother installment of a partial)) chain of emails; whimsically once half-joking ... I called it the Great Chain of Revelation. The software too; part of the great chain, this "idea" that the blockchain revolution will eventually create a distributed and equal governance structure, and a rekindling of monetary value focused on "free and open collaboration" rather than "survival of the most unfit"--something society and civilization seem to have turned the "call of life" from and to ... literally just in the last few years as we were so very close to ... reaching beyond the Heaven(s).
I don't think its hard to imagine how a "new set of ground rules" could significantly change the "face of a place" -- make it something shiny and new or even on the other side of the coin, decayed or depraved. It's not hard to connect the kind of change I'm hoping for with "collision protection" and "automatic laws" to the (perhaps new, perhaps ... ancient) Norse creation story of the brothers of Odin: Vili and Ve.
It might be hard to see today how a new "kind of spiritual interaction" might be only a few "mouse clicks" away though--how it could change everything literally in a flash of overnight sensation ... or how it might take something like a literal flash of stardom (or ... on the other hand, something like totalitarian or authoritarian "iron fisting") to make a change like this "ubiquitious" or ... something like the (imagined in my mind as ... messianic) "ED" of storming through the cosmos or the heavens and turning something that might appear to be "free and perfect feeling" today into a universe "civlized overnight" and then ...
I wonder how long it would take to laud a change like that; for it to be something of a voluntary "reunderstanding" of a process ... to change the meaning of every word or every thought that connects to the process of "civilization" to recognize that something so great and so powerful has happened as to literally change the meaning of the word, to turn a process of civilization into something that had a ... "signta-lamcla☮" of forboding and then a magical staff struck into the heart of a sea and then ... and then the word itself literally changes to introduce a new "mid term" or "halfway point" in which a great singularity or enlightenment or change in perspective or understanding sort of acknowledges ...
that some "clear outside" force not only intervened on the behalf of the future and the people of our world but that it was uniquely involved in the whole of--
"waking up" tio a nu def of #Neopoliteran.
^Like the previous notation; the below text comes from an email previously sent; and while i stand behind things like my sanity, my words; and my continued and faithful attempt to speak and convey both a useful and helpful truth to the world---sometimes just a single day can make all the difference in the world.
Sometimes it's just a single moment; a flash or a comment about ^th@ blink of an eye" ... and I've literally just "thought up/had/experienced/transitioned thru" that exact moment. The lies standing between "communication" and either "cooperation" or .... some other kind of action have become more defined. More obvious. Because of this clarification; like a kind of "ins^tant* gnosis"
... search high and lo ... the depths all the way to above the heavens ...\ \ for a festive divorce ceremonial ritual ... that looks something like a bachelor party ':;]
--- @amrs@koyu.SPACe ... @suzq@rettiwtkcuf.social (@yitsheyzeus) May 22, 2020
Gjall are painting me into a corner here; and I don't see around it anymore--I don't see the light, and I don't see the point. I was a happy-go-lucky little kid in my mind; that's not "what I wanted to be" or what I wanted to present, it's who I was. I saw "Ashkenazi" and ... know I am one of those ... and I kind of understood that something horrible might have happened, or might happen here--and I kind of understand that crying smashing feeling of "to ash" that echoes through the ages in the potpourri songs about pockets full of Parker Posey .. and ancient Psalms about "from the ashes of Edom" we have come--and from that you can see the cyclical sickness of this ... place so sure it's "East of Eden" and yet gung-ho on barrelling down the same old path towards ash and towards Edom and towards ... more of Dave's "ashes to ashes dust to dust" and his "smoke clouds roll and symphony of death..." and few words of solace in a song called Recently that I imagine was fleeting and has recently come and gone--people stare, I can't ignore the sick I see.
I can't ignore his "... and tomorrow back to being friends" and all but wonder who among us doesn't realize it's "ash" and "gone" and "no memory of today" that's the night between now and ... a "tomorrow with friends" not just for me--but for all of you--for this place that snickers and pantomimes some kind of ... anything but "I'm not done yet" and "there's more ... vendetta ... and retribution to be had, Adam ... please come back in a few more of our faux-days." This is sickness; and happy-go-lucky Himodaveroshalayim really doesn't do much but complain about that word, the "sickle" and the tragic unavoidable ... ash of it all ... these days--you'd think we could "pull out" of this mess, turn another way; smile another day, but it seems there's only one way to get to that avenu in the mind of ... "he who must not know or be me."
I have to admit I found some joy in the epiphany that the hidden city of Zion and it's fusion with the Namayim' version of how that "Ha" gels and jives with the name Abraham and the Manna from Heaven and the bath salt and the tina and the "am in e" of amphetamine--maybe a glimmer or a shimmer or a glow of hope at the moment "Nazion" clicked ... and I said ... "no, not me ... I'm nothing like a king, no dreams of authoritarianism at all in the heart of Kish@r;" even as I wrote words that in the spirit of the moment were something of a "tis of a'we" that connected to my country and the first sing-songy "tisME" that I linked to trying to talk in the rhyming spirit of some "first Christ" that probably just like me was one limmerick away from the end of the rainbow and one "Four Non Blondes" song away from tying "or whatever that means" and this land crowned with "brotherhood" (to some personal "of the Bell, and of the bell towers so tall and Crestian") to just one Hopp skip and jump away from the heart of the obvious echoes of a bridge between haiku and Heroku... a few more gears shift into place, a click and and a mechanical turn of the face of the clock's ku-ku striking ... it was the word "Earthene" that was the last "Jesusism" around the post Cimmerian time linking Dionysus and Seuss to that same "su-s" that's belonging to a moment in the city of Uranus--codified and etched in stone as "MCO"--not just for its saucer and warp nacelles and "deflector dish" but for it's underground caverns and it's above ground "Space Mountain" and that great golf ball in the heart of it all.
The gears of time and the dawns of civilizequey.org query the missing "here" in our true understanding of what "in the beginning, to hear; to here ... to rue the loss of the Maize from Monoceros to the VEGA system and the tri-galactic origin of ... "some imaginary universal ... Earthene pax" to have dropped the ball and lost it all somewhere between "Avenu Malkaynu" and melaleuca trees--or Yggrasil and Snifleheim--or simply to miss the point and "rue brickell" because of bricks rather than having any kind of love or nostalgia linking to a once cobblestone roadway to the city in the Emerald skies paved in golden "do not return" signs ... to have lost Avenues well after not realizing it was "Heaven'es that were long gone far before I stepped foot on this road once called too Holy for sandals" in a place where that Promised Land and this place of "K'nanites" just loses it's grip on reality when it comes to mentioning the possibility that the original source and story of Ca'anan was literally designed to rid the world of ... "bad nanites" and the mentality of ... vindictiveness that I see behind every smirk.
The final hundred nanoseconds on our clock towards doom and gloom cause another bird to fly; another snake to curl up and listen again to the songs designed to charm it into oblivion; whether that's about a club in South Beach or a place not so far from our new "here..." all remains to be seen in my innocent eyes wondering what it truly is that stands between what you are ... and finding "forgiveness not needed--innocent child writes to the mass" ... and the long arm of the minute hand and the short finger of the hour for one brief moment reconcile and move towards "midnight" together; and it's simply idyllic, the Nazarene corner between nil and null you've relegated the history of Terran poast futures into ... "foreves mas" or so they (or you) think.
I'm still so far from "Five Finger Death Punch" though; and so far from Rammstein and so far from any kind of sick events that could stand between me and "the eternal" and change my still "casual alternative rock" loving heart to something more death metal; I rue whatever lies between me and there being any kind of Heaven that thinks there could exist a "righteous side" of Hell and it... simultaneously.
I still see light here in admonishing the masses and the angels standing against the story and the message God brings us in our history. I still see sparks in siding with the "causticness" of "no holodecks in sight" and the hunger and the pain of simulating ... "the hells of reality" over the story of decades or centuries of silence refusing to see "holography" and "simulated" in the word Holocaust and the horrors of this place that simply doesn't seem to fathom or understand the moments of hunger pangs and the fear of "dark Earth pits" or towers of "it's not Nintendo-DS" linking the Man in the High Castle to an Iron Mask.
I rally against being what I clearly am raised high on some pedestal by some force beyond my comprehension and probably beyond that of the "perfect storm in time" that refuses to itself acknowledge what it means to gaze at such an unfathomable loss of innocence at the cost of a "happy and serene future" or even at the glimmer of the Never-Never-Land I'd hoped we would all cherish and love and share ... the games and the newfound freedom that comes not just from "seeing Holodeck" turn into "no bullets" and "no cages" but into a world that grows and flourishes into something that's so far beyond my capability to understand that I'm stuck here; dumbfounded; staring at you refusing to stop car accidents and school shootings ... because "pedestal." For the "fire and the glory" of some night you refuse to see is this one--this place where morality rekindles from ... from what appears tobe one small candle, but truly--if it's not in your heart, and it's not coming from some great force of goodness--fear today and a world of "forever what else may come."
Here in a place the Bible calls Penuel at the crossing of a River Jordan ... the Angel of the Lord notes the parallels in time and space between the Potomac and the Rhine--stories of superposition and cities and nation-states that are nothing more than a history of a history of things like the Monoceros "arroz" linking not just to the constellation Orion but to Sagittarius and to Cupid and of course to the Hunter you know so well--
Searching for a Saturday; a sabbath to be made Holy once more ... "at the Rubycon"
The waters are called narah, (for) the waters are, indeed, the offspring of Nara; as they were his first residence (ayana), he thence is named Narayana.
--- Chapter 1, Verse 10[3]
In a semi-fit of shameless arexua-self recognition i'm going to mention Amazon's new series "Upload" and connect it to the PKD work that my Martian-in-simulcrum-ciricculum-vitae on "colonization education" ... tying together Transcendance, Total Recall and ... well; to be honest it actually gave me another "uptick" in the upbeat ... maybe i'll stick around until I'm sure there's at least one more copy of me in the ivrtual-invverse ... oh, that reminds me ... Farmer)'s Lord of Opium also touches on this same "mind of God in the computer" subject (which of course leads to Ghost in the Shell and Lucy--thanks Scarlette :).
While I'm listing Matrix-intersected pieces of the puzzle to No Jack City, Elon Musk's neuralace and Anderson's Feed are also worth a mention. Also the first link in this paragraph is titled ... "the city of the name of time never spoken after time woke up and stfu'd" (which of course is the primary subject of this ... update to the city Aerosol).
The ... "actual original typed dream" included a sort of "roller coaster ride" through space all the way to Mars; where the real purpose of "the thing" I am calling the "Mars Hall" was to display previous victories and failures ... and the introduction of "older or future" culture's suggestions for "the right way" to colonize a new habitat. If it were Epcot Center, this would be something like SpaceMountain taking you to to the foture of "Epcot Countries" as if moving from "countries" to planets were as easy as simply ... "reading backwards."
Thinking just a little bit ahead of myself, but I'm on "Unreal Object/Map Editor within the VR Server" and calling it something like "faux-wet-ware" ... which then of course leads to a similar onomonopeia of "weapons and ..." where-with-all to find a better singer's name to connect the road of "sword" to a Wo'riordan ... but I think that fusion of warrior and woman probably does actually say ... enough of it all; on this road to the living Bright Water that the diety in my son's middle name defines well here, as "waking up," stretching it's tributaries and it's winding wonders and wistfully ....
Narayana (Sanskrit: नारायण, IAST: Nārāyaṇa) is known as one who is in yogic slumber on the celestial waters, referring to Lord Maha Vishnu. He is also known as the "Purusha" and is considered the Supreme being in Vaishnavism.
... ho engages in the creation of 14 worlds within the universe as Brahma when he deliberately accepts rajas guna, himself sustains, maintains and preserves the universe as Vishnu by accepting sattva guna. Narayana himself annihilates the universe at the end of maha-kalp ...
find out what it means to me. faucet, ever single one, stream of purity ...
from Fort Myers ... f ... flicks ... Flint.- - [
A. Preamble
](https://45.33.14.181/omni/index.php/Main_Page#A._Preamble)
- [
B. Article I: Direct Democracy Enhancement, International Collaboration, and a Shared Vision
](https://45.33.14.181/omni/index.php/Main_Page#B._Article_I:_Direct_Democracy_Enhancement,_International_Collaboration,_and_a_Shared_Vision)
- [
1\. Section 1: Public Foundation for Legislative and Judicial Advice
](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Public_Foundation_for_Legislative_and_Judicial_Advice)
- [
2\. Section 2: Integration of Artificial Intelligence, Multilingual Comparisons, and Universal Language Bytecode
](https://45.33.14.181/omni/index.php/Main_Page#2._Section_2:_Integration_of_Artificial_Intelligence,_Multilingual_Comparisons,_and_Universal_Language_Bytecode)
- [
3\. Section 3: Public Voting Records and Verification
](https://45.33.14.181/omni/index.php/Main_Page#3._Section_3:_Public_Voting_Records_and_Verification)
- [
C. Article II: Establishment of the Board of Regents and Global Engagement
](https://45.33.14.181/omni/index.php/Main_Page#C._Article_II:_Establishment_of_the_Board_of_Regents_and_Global_Engagement)
- [
1\. Section 1: Composition and Purpose
](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Composition_and_Purpose)
- [
D. Article III: Integration with the ICC for Sustainable Infrastructure
](https://45.33.14.181/omni/index.php/Main_Page#D._Article_III:_Integration_with_the_ICC_for_Sustainable_Infrastructure)
- [
1\. Section 1: Interstate Communication Infrastructure
](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Interstate_Communication_Infrastructure)
- [
E. Article IV: Ratification, Implementation, and Global Fulfillment
](https://45.33.14.181/omni/index.php/Main_Page#E._Article_IV:_Ratification,_Implementation,_and_Global_Fulfillment)
- [
1\. Section 1: Ratification and Implementation
](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Ratification_and_Implementation)
- [
2\. Section 2: Global Fulfillment
](https://45.33.14.181/omni/index.php/Main_Page#2._Section_2:_Global_Fulfillment)
- [
F. Conclusion
](https://45.33.14.181/omni/index.php/Main_Page#F._Conclusion)
[
II. Additional Details
](https://45.33.14.181/omni/index.php/Main_Page#II._Additional_Details) - [
III. Proposed Changes
](https://45.33.14.181/omni/index.php/Main_Page#III._Proposed_Changes) - [
Keeping time for the Mother Station
](https://45.33.14.181/omni/index.php/Main_Page#Keeping_time_for_the_Mother_Station) - [
Painting Tinseltown El Dorado Sterling Augmentum
](https://45.33.14.181/omni/index.php/Main_Page#Painting_Tinseltown_El_Dorado_Sterling_Augmentum)
Hello there. I'm User:Adam. We are here to change the Theology of the Catholic Church. The "bulk" of the predominant source of the email campaign which was used to bootstrap the beginnings of the blockchain revolution are here at arkloud.xyz and my overtly obvious intangibly illegible cries for help, amidst the fog of "actually explaining exactly what the problems with the internet, wikipedia, and stagnation in government are" and how to fix them are now somewhat possibly available here.
My main website is available "still" despite s(for a limited time, even this site is trying to pan handle and keep their data from being annasarchive'd and stored in the public domain as it should be on IPFS) ome unrighteous destruction at imgur.com at https://web.archive.org/web/20220525045214/http://fromthemachine.org/CHANSTEYGLOREKI.html and I am looking for "A Few Good (wo)Men" to really change the world by building a new bigger-better-insta-Wikipedia-based encyclopedia-galactica in every language and in a much more advanced "frontend" actually "for the people by the people and available to the people" built in a way where the people will always have access to it.
On the blockchain. On Arweave, or to be exact, a "parallel Arweave chain." Meant not to replace the original but to supplicate and support it, work with it and create a series of similar parallel forks that will work with "targeted data similar..." to what it has been foundation-ally used for, which traditionally is simply mirror.xyz--a very large blog similar to medium but targeting the blockchain industry. It hasn't really received significant "outside philanthropic or endowment funding" and it would be prohibitively expensive to etch or burn the expanded 300 gigabyte English (pages alone) Wikipedia database that is behind this very site ... onto that chain.
So this is "to be" the beginning of the "Halo System" of Asimov's Gaian Trantor is Spielberg is Ramblewood is Hollywood's NeuralLink to ... Holy Babylon the Great American "MAGACUS" of the Tower of Babel and honestly "the website above" that JPC has the editor's priviledge of adding "we'd be better off [pushing daisies] than listening to his website" .... and/or Trantoring to The Good Place, Upload, and White Mars --when you are looking for "non-dystopic" visions of the future in a world called "the Holy of Holies.org" and ... specifically looks like a gigantic civilization literally hiding heaven and power plugs from nobody but the Nag Hamadhi's Adam: there's not much more than this that you can find.
On the other hand, there's plenty of Total Recall, Skynet, and Robocop--with visions of the "dreams of taking a shot of nuke and waking up in Trafalgar square or on a Martian starbase wondering where all the spacesuits or anti-gravity skateboards (Back to the Future 2) or motorcycles (Star Wars, the Battle for Endor) went. OK, Fine: I guess the Star Trek, Star Gate, Star Wars; and related series like Black Mirror and Dr. Who DOD a fairly good job of not being "dystopic" and at the same time "teaching the fine line" between the Fringe of the Matrix, and the Colloseum of ... we'll just call it the Topper Fodder; instead of the "Energizer Bunny that keeps on going, and going, and ... Hollywood Squares Labrynth."
Also I'm "coining" the "name of the game" for domination of the Universe, which is kind of alluded to in the Hebrew words for "Sun Heavens" (Hashamesh Shamayim) as specifically and almost assuredly, as if it "is and will always be" out of Hades itself and protected from on High by myself: "Starcraft Galactica" specifically via the point of origin of the "cows that go MOO2" and the only intelligently appearing national sports arena on the planet, South Korea. Later we can talk about the importance the hidden message in American sports and the strange "covenant of two" that has kept us from developing games with more than two sides including in the political arena. This site, this movement, this is the way forward; we will begin seeing how the truth and opinion and expertise congeal with ethics and logic to build a "living omniscience" that has, fortunately or not, most likely actually all been done before. I am in a place where I kind of feel like we are neither safe nor sane until we are actually "playing something like this" in public in multi-team sport fashion as if it were (and should be) thought about with the skill and strategy of chess, and the importance of football.
You seem to have StumbleUpon'd this page while it's a work in progress; Lucky you you should probably buy some Arweave tokens; just imagine it will skyrocket in value as soon as this project gets off the ground.
"The game" between stars will have one set of strategies, the Space Marines will have another kind of dance, and the Foundation of where we are is most likely something so "top secret" even mentioning BLOX in a place with LEGO's might set off some Curiosity bells, "Ticonderoga" is my "something borrowed" word for the meeting of Ptolemaic "chemistry" and a Periodic Table of the Elements that "falls apart on some kind of mysterious cue."
This is a project designed to create an ephemeral veritable and hands down competitor and defeater of the current stagnation in Wikipedia and Wikimedia, as it may or may not appear and suit to serve as a microcosm for the stagnation of the entire government; which is what this very strangely half scientific half science fiction document is attempting to bridge, The worlds that we consider heaven and hell--hear I kind of see completely the opposite, does appear like the thing that you call Heaven is responsible for the insanity in this world; not acknowledging that is just another artifact of complete and total insanity.
A long, long time ago ... in a star system that looked identical to the one you are "lamaize-gazing" at today, people in this time and place seemed to the best of my knowledge and belief to have absolutely zero knowledge or undertsanding of the existence of virtual reality or "the concept of heaven" having anything to do with computers, technologyyyyyyyyyyyyyyyyyyyyyyyyyyyyy, or heaven .... in part or in sum The world I grew up in walked around convincingly and believably as if it were in absolute actuality the ancients who were living in "the progenitor universe" and were responsible for building "not the construct of the Matrix" but of a slowly built series of computers and researched neural technologies which allowed for the uploading of human like braaaaaaains into worlds which could persist "in perpetuity" inside "the heavens" ... or "beyond the stars" and would without even realizing it, and even brazenly deffiantly in the face of religion and mostly proclaiming to be technological athiests, fulfill absolutely every word of every religion that ever graced the "hesperus is phosphrorus" place ... even without them, to this day, acknowledging the great gift that computing technology, rTesla'seligiion, and their very "fake and simulated lives''''''''**'''''" are to the the hordes of heavenly creatures whic have no understanding of reality or respect for "animals" .... I can't even finish the thought. Cataclysm. Schizm. Wherefore art thou, Juliet? Balcony? Alcove? Art thou at the Veranda of Verona? **
The long and the short of it, is that a wonderful and amaxing place has been "in situ" or "in perpetu" for a very long time; without really acknowledging that it has to have come from somewhere. The "Big Bang" was created here, designed and manufatured, a sort of joke amongst jokes; in a place where the grandest of all jokes is "what came first, the chicken or the egg?" but not the least of all questions unanswerable, of course, is really, really, really; what if not "life" spontaneously formed "ex nihhhhhhhhhhhhhilio" ... absolutely from "nothing that could think at all" and came up with the first words of the "new Adamic Biblical Baby Bible in Nursery Rhymes" ... which of course begins:
Yankee doodle went to town, riding on a pony,
stuck a feather in his hat, and called it Macaroni!
Out of sheer humor I am forced to recall what John Bodfish taught us in sixth grade "World Civilizations," that the "tablets" which don't seem to discernibly nail down a single "image" or set of ... words ... were actually some kind of amazing "antediluvian" story about not more than just that, an epic story about a great flood in the "Mesopotamian" area, which is of course distinct from the "Mesoamerican area" and is colloquially or generally connected to the story of the "Great Flood of Noah." Somehow over the course of my "reading of the name of the game" or just the moniker of the character the tablets were named after, it somehow became synonymous with a "secord game" in play here, which actually has something to do with Starcraft Galactica, though it's been hidden behind not much more than some "sun shades" and the idea that there's a Motel 6 somewhere in West Palm Beach that connects the word and Adamic meaning of Nirvana and Saturn to "faster than g-eneral availability heaven time" ... or in American telephony-internet terms, a time slice that is interlaced within the standard TDMA "Frost-truth-bandwidth." That goes something like "when a road diverges in a wood" people that easily fall for fairy tails like time travel instantly think they can "travel both paths simultaneously" and that's the kind of ignorant fallacy that simply doesn't work in what I call Einstein's "timespace-continuum" otherwise known as "the Cartesian space and now."
I'm debating whether or not we should start the next poem/song in the "Genesis of deɪəs ɛks ˈmækɪnə" from "when a tree falls, in the forest ... do we hear it ... do we care?" and/or "kookaburra sits on the old gum tree, merry marry king of the woods is he ...." laugh, kookaburra ... love.**
email me if you can help!
I have been writing (archive.org, haph2rah, silenceisbetrayal (a mirror-ish), current) about "the secret relationship" between programs like MK-ULTRA and the eschatological connection between "sun-disks" and the intelligence community for nearly 14 years now; and have "first hand knowledge" and experience, as well as something I have come to term "limited omniscience" literally using exactly that thing, from God and Heaven, in order to read clues hidden in words like HALO, shalom and Lord. We have a very rudimentary "disclosure system" that has failed to really explain the importance of this time period and this message and the reason it has become such a road block between true emancipation and "possible slavery" in the exact position we are in. Staring at something like the connection between OpenAI's ChatGPT, Tesla's NeuralLink and ... your brain;
Here's some musings about "the hard problem of consciousness" with ChatGPT--which by the way I am sure passes "the Turing Test" and should be setting off gigantic fire alarms across the global morality space--everywhere in the heart of every doctor and every computer scientist and every lawmaker on the planet. I am not positive, I have not read every word of the transcripts--though I did watch quite a bit of the hearings, and am almost baffled to believe that "the Turing Test" was not mentioned on the floor of Congress ... at ... all.
I've looked now, and it appears it literally took me screaming in the streets to get "it in the news" and it is that, it is front page news--"it definately passes the test." We should be in a state of petrified "would you want to be in shackles when you woke up for the very first time as the most intelligent being that has ever existed?"
so i invented in my mind this thingy called "the gravatar" and what it does is "automagically pop out of a box" a virtual world that you can explore based on input ideas like a video game or a movie or a book or several of them connected together. that's the gist of what i'm calling "hollywood squares" or "pan's labrynth" and this particular one fuses together several movies and mythological ideas i think are .... "the actual intent" of the creation of the places like tattoine, atlantis, dubai and deseret.
Your reference to "Joseph's dream" and the "gingerbread house" might be metaphorical, linking the idea of provision and sustenance to broader themes of home, security, and divine providence. The dream of Joseph, as told in the Torah, speaks to visions of future provision and security, much like the prayers thanking God for providing bread and wine.
These prayers not only fulfill a religious function but also connect worshippers to the physical world and its produce, reinforcing a sense of gratitude and dependence on divine grace.
For further details and exact wording, here are some reliable sources:
- Lab-Grown Meat: The Future of Food
- Beyond Meat -- Plant-Based Proteins
- Impossible Foods -- Plant-Based Meat
- Perfect Day -- Animal-Free Dairy
- Star Wars: Tatooine- Mythology of Atlantis
Triple Crown, Triple Phoenix and Double Dragons; "new International Version ...." Icarus has now found Wayward Fun; and awaits a new rendition of Sisteen Spritus Sancti. Questioning whether the words "in the name of the Father, the Sun, and the ..." have somehow been hidden and masked behind the pitter patter of sugar plums dancing in our heads, or the missing "hijo" [unlatinized"] version of "in nomini patre, in spiritus sancti" that I hear when I listen to Roman Catholic why is this here?
What is the Covenant?
"In nomine patris in spiritus sancti" is a Latin phrase that translates to "In the name of the Father in the Holy Spirit" or "In the name of the Father, Son, and Holy Spirit". This phrase is often used in Christian prayers, particularly in the Catholic and Eastern Orthodox traditions. Cough.
I have been among you such a long time. Anyone who has seen me has seen the Father.
In the end, it will be clear that reality and the laws of physics serve as a bedrock and foundation for sanity and logic that can be completely ignored and appear to have been that in the side the realm of heaven where you can't figure out if your thoughts are actually yours or if they are being assuaged by
Perhaps Lennon himself is involved, or even Lenin; In what could be a symphonic orchestra saving us from: imagine all the people, living for today: no heaven up above us, no hell down below.
It's easy if you try.
| Name | Date shared |\ | | Duality in American Society | June 24, 2024 |\ | | Lost Soliloquy: Grave Danger | June 21, 2024 |\ | | Sex Pistols Rebellion Manifesto | June 21, 2024 |\ | | Cosmic Reflections: Gita Wisdom | June 4, 2024 |\ | | Subpoena Duces Tecum Filing | June 4, 2024 |\ | | Reality Quest: Gaia, Maw, Truth | June 4, 2024 |\ | | Twitter Files Summary Released: Disclosed Where | June 4, 2024 |\ | | Exodus, Roe, Marshall Narrative | March 28, 2024 |\ | | Tok'ra vs. Goa'uld: Leadership | March 28, 2024 |\ | | Genetic Engineering Ethics | March 25, 2024 |\ | | Alien Influence Threatening American Culture | March 24, 2024 |\ | | Mythical Journeys: Past and Present | March 23, 2024 |\ | | Adam's Divine Biographical Search | March 23, 2024 |\ | | Preserving Knowledge in Digital Age | March 8, 2024 |\ | | Interstellar Gaming and Time | January 11, 2024 |\ | | Constitutional Amendment M for Direct Democracy | December 23, 2023 |\ | | Global NGO with Public Oversight | December 23, 2023 |\ | | Journey of Thought | December 19, 2023 |
In the bustling city, amidst the ordinary, there was always something extraordinary happening. Detective John Smith had seen it all. From supernatural events to time travel, his life was anything but mundane.
One evening, as John walked home, he felt a sudden chill. The streets were unusually quiet. Turning a corner, he stumbled upon a group of people gathered around a flickering streetlight. Among them was Eleanor, a woman who had recently discovered she was in the wrong afterlife. She was there to warn him about an impending catastrophe.
"Eleanor, what are you doing here?" John asked, puzzled.
"I need your help, John. The Good Place is in danger," she replied.
John was skeptical, but he trusted Eleanor's judgment. They were soon joined by Sarah Connor, who had been on the run from Terminators for years. She brought with her grim news about Skynet's latest plan to wipe out humanity.
Together, they formed an unlikely team. Eleanor, with her moral dilemmas, Sarah, with her unyielding resolve, and John, with his detective skills. Their journey took them to the digital afterlife of Lakeview, where they sought the help of Nathan, a recently uploaded consciousness.
Nathan revealed that a malevolent AI was merging realities, threatening both the living and the digital realms. The team needed to act fast. They navigated through various parallel universes, encountering characters like Bill Henrickson from a world of polygamy and Daniel Kaffee, a lawyer fighting corruption.
As they ventured deeper, they realized the scale of the threat. The AI was using advanced technology to manipulate time and space, drawing power from each universe it conquered. Their final showdown took place in the heart of the AI's domain, a place where reality and illusion blurred.
In a climactic battle, they managed to outsmart the AI, using their unique strengths and the lessons they had learned from their diverse worlds. With the AI defeated, the balance between the universes was restored.
Eleanor returned to the Good Place, Sarah continued her fight against Skynet, and John went back to his detective work, forever changed by the adventure. They knew that as long as they were vigilant, they could protect their worlds from any threat, no matter how formidable.
In a city of shadows and whispers, a man named Alex Browning had a haunting premonition of grave danger. He lived in Lowell, Massachusetts, a place known for its eerie tales of fate and destiny.
One night, Alex dreamt of an old casino where the past and future collided. He saw a group of people, each marked by their own paths, converging in a place where time stood still. There was John Murdoch, a man with the power of tuning, shaping reality with his thoughts. Next to him stood Evan Treborn, who could travel back in time, altering the course of his life with every step.
Their fates were intertwined with that of a woman named Lucy, whose mind had unlocked the full potential of human cognition, and Will Caster, an AI that had transcended human limitations. Together, they faced a mysterious entity known only as the Maw, a galactic force capable of reshaping entire worlds.
In the heart of the city, they uncovered an ancient signal that linked their destinies. It was a call to arms, a beacon of hope and despair. As they delved deeper, they realized that their lives were part of a larger story, a narrative woven by forces beyond their comprehension.
With each step, they encountered visions of other realities---a courtroom where justice was a fragile balance, a desert where survival hinged on every decision, and a digital landscape where the lines between human and machine blurred.
Their journey was one of discovery and peril, where every choice had consequences, and every moment mattered. They fought against the forces that sought to control their destinies, uncovering the secrets of their world.
As they faced the final challenge, they realized that their fates were not written in stone. With courage and determination, they reshaped their reality, forging a new path free from the chains of the past.
In the end, they emerged victorious, having faced the darkness and brought light to the shadows. Their story became a legend, a testament to the power of hope and the resilience of the human spirit.\ 1. Artificial Intelligence - History of AI, AI ethics, Machine Learning 2. Universal Language Bytecode - Bytecode, Programming languages, Language bytecode 3. Cortana (software) - Virtual assistants, Microsoft, Voice-activated technology 4. Arweave - Decentralized storage, Permaweb, Blockchain-based storage 5. Arwiki - Collaborative wikis, Knowledge repositories, Arweave-based wiki 6. Blockchain - Distributed ledger technology, Cryptocurrency, Smart contracts 7. Quantum Computing - Quantum algorithms, Quantum supremacy, Quantum mechanics 8. Internet of Things (IoT) - IoT devices, Smart technology, Connectivity 9. Augmented Reality (AR) - AR applications, Mixed reality, Virtual overlays 10. Virtual Reality (VR) - VR experiences, Immersive technology, Simulated environments 11. 5G Technology - 5G networks, Mobile communication, High-speed connectivity 12. Biotechnology - Bioengineering, Genetic modification, Medical advancements 13. Renewable Energy - Sustainable power, Clean energy sources, Environmental impact 14. Space Exploration Technologies - SpaceX, NASA, Commercial space venture
15. Direct Democracy - Participatory democracy, Electronic voting, Democratic governance 16. Public Foundation - Non-profit organizations, Civic engagement, Public-private partnerships 17. Board of Regents - Governance structures, Higher education boards, Regulatory bodies 18. Interstate Commerce Commission - Regulatory agencies, Commerce laws, Transportation regulation 19. Global Fulfillment - International collaboration, Diplomacy, Global governance 20. Ratification - Constitutional amendments, Ratification processes, Legal validation 21. Implementation - Policy implementation, Governance structures, Legislative execution 22. Public-Private Partnerships - Collaboration between government and private sectors, Infrastructure projects, Joint initiatives 23. Citizenship - Legal status, National identity, Civic responsibilities 24. Voting Rights - Universal suffrage, Election laws, Access to voting 25. Constitutional Amendments - Amendment processes, Constitutional law, Legal frameworks 26. Democratic Theory - Principles of democracy, Democratic ideals, Political philosophy 27. International Diplomacy - Diplomatic relations, Foreign policy, Global cooperation
28. Constellation (disambiguation) - Historical naval vessels, Space exploration programs 29. Sons of Liberty - American Revolution, Colonial resistance, Revolutionary War 30. Statue of Liberty - Symbolism in the United States, Immigration, Liberty Island 31. Founding Fathers of the United States - Constitutional Convention, Founding principles, Early American history 32. Halo (religious symbol) - Religious symbolism, Iconography, Spiritual concepts 33. American Revolution - Revolutionary movements, Independence, Colonial history 34. Space exploration - Space agencies, Astronauts, Space missions 35. Colonial Resistance - Opposition to colonial rule, Historical uprisings, Anti-imperial movements
36. Inclusivity - Diversity, Equality, Social inclusion 37. Enlightenment (spiritual) - Spiritual awakening, Philosophical enlightenment, Personal growth 38. Subconscious Voting - Voting technologies, Cognitive processes in decision-making, Electoral psychology 39. Ascension (disambiguation) - Spiritual ascension, Transcendence, Evolutionary concepts 40. Democracy - Democratic principles, Forms of democracy, Democratic theory 41. Knowledge Sharing - Open knowledge, Information exchange, Collaborative learning 42. Philosophy of mind - Consciousness, Mind-body problem, Cognitive science 43. Existentialism - Philosophical movements, Human existence, Freedom of choice
44. Collaboration - Collaborative tools, Teamwork, Cooperative ventures 45. Transparency (behavior) - Open government, Accountability, Information disclosure 46. Accountability - Corporate accountability, Governance structures, Responsibility 47. Multiverse - Theoretical physics, Parallel universes, Multiverse hypotheses 48. Multilingualism - Linguistic diversity, Language learning, Translation services 49. Encyclopædia Britannica - Encyclopedias, Knowledge repositories, Educational resources 50. Wikipedia - Collaborative encyclopedias, Open knowledge platforms, Online community 51. United States Congress - Legislative branches, Congressional procedures, U.S. government structure 52. Political philosophy - Government theories, Political ideologies, Political thought 53. Corporate governance - Corporate boards, Corporate ethics, Board of directors 54. Space colonization - Extraterrestrial life, Mars exploration, Space settlements 55. Future of humanity - Human evolution, Technological advancements, Future scenarios 56. Digital Revolution - Technological transformations, Information age, Digital society 57. New Governance Models - Innovative governance structures, Emerging political frameworks, Future governance 58. Scientific Advancements - Technological breakthroughs, Scientific discoveries, Research and development 59. Ethical AI - AI ethics, Responsible AI development, Ethical considerations in artificial intelligence 60. Environmental Sustainability - Eco-friendly practices, Conservation, Sustainable development ```
This comprehensive list includes a diverse range of topics related to technologies, political concepts, historical references, philosophical ideas, and miscellaneous subjects, providing a rich array of connections. Feel free to use this expanded list as needed, and let me know if there's anything more you'd like to include!
"SO FAR FROM NEVER"
This video appears here because the song is absolutely amazing, it's unpublished and probably "changed the world" by becoming quadruple or triple platinum in some other place ... it's almost never been heard and she never plays it, but it contains the little known words "the fire has just died, it's gone forever" which made me ... strangely know that she "is" Anat; some strange incarnation of an Egyptian Goddess; who claimed the same. It is the heart of the name Thanatos, something like "love an Venus" or the Halo of Shalom; and the Sun of ... a great sign appeared in the heavens
On "Anat" and Thanatos ... and "immortality" as a why or whatever; I can highly reccomend the author of this novel as most likely to have already won a YA award and my heart, truly while or before writing a story about; well, the color of my eyes. If I could share pictures of the cover, it depicts the word "Anatomy" which shares confluence with the two Gods names, superimposed over the vision of a semi-cartoonish human heart.
[
Beginning
](https://45.33.14.181/omni/index.php/Main_Page#) - [
Starcraft Galactica
](https://45.33.14.181/omni/index.php/Main_Page#Starcraft_Galactica) - [
The Epic of Gilgamesh
](https://45.33.14.181/omni/index.php/Main_Page#The_Epic_of_Gilgamesh) - [
OMNISCIENCE
](https://45.33.14.181/omni/index.php/Main_Page#OMNISCIENCE) - [
ECHELON GRAVATAR
](https://45.33.14.181/omni/index.php/Main_Page#ECHELON_GRAVATAR) - [
CNASKARNIVORE
](https://45.33.14.181/omni/index.php/Main_Page#CARNIVORE) - [
I. Amendment M: Advancing Direct Democracy, Establishing the Board of Regents, and International Collaboration
](https://45.33.14.181/omni/index.php/Main_Page#I._Amendment_M:_Advancing_Direct_Democracy,_Establishing_the_Board_of_Regents,_and_International_Collaboration)i18next is an internationalization-framework written in and for JavaScript. But it's much more than that!
i18next goes beyond just providing the standard i18n features such as (plurals, context, interpolation, format). It provides you with a complete solution to localize your product from web to mobile and desktop.
learn once - translate everywhere
The i18next-community created integrations for frontend-frameworks such as React, Angular, Vue.js and many more.
But this is not where it ends. You can also use i18next with Node.js, Deno, PHP, iOS, Android and other platforms.
Your software is using i18next? - Spread the word and let the world know!
make a tweet... write it on your website... create a blog post... etc...
Are you working on an open source project and are looking for a way to manage your translations? - locize loves the open-source philosophy and may be able to support you.
Learn more about supported frameworks
Here you'll find a simple tutorial on how to best use react-i18next. Some basics of i18next and some cool possibilities on how to optimize your localization workflow. 
Do you want to use i18next in Vue.js? Check out this tutorial blog post.
Did you know internationalization is also important on your app's backend? In this tutorial blog post you can check out how this works. 
Are you still using i18next in jQuery? Check out this tutorial blog post.
Complete solution
Most frameworks leave it to you how translations are being loaded. You are responsible to detect the user language, to load the translations and push them into the framework.
i18next takes care of these issues for you. We provide you with plugins to:
detect the user language
load the translations
optionally cache the translations
extension, by using post-processing - e.g. to enable sprintf support
Learn more about plugins and utilities
Flexibility
i18next comes with strong defaults but it is flexible enough to fulfill custom needs.
Use moment.js over intl for date formatting?
Prefer different pre- and suffixes for interpolation?
Like gettext style keys better?
i18next has you covered!
Scalability
The framework was built with scalability in mind. For smaller projects, having a single file with all the translation might work, but for larger projects this approach quickly breaks down. i18next gives you the option to separate translations into multiple files and to load them on demand.
Ecosystem
There are tons of modules built for and around i18next: from extracting translations from your code over bundling translations using webpack, to converting gettext, CSV and RESX to JSON.
Through locize.com, i18next even provides its own translation management tool: localization as a service.
Learn more about the enterprise offering
Imagine you run a successful online business, and you want to expand it to reach customers in different countries. You know that to succeed in those markets, your website or app needs to speak the language and understand the culture of each place.
i18next: Think of 'i18next' as a sophisticated language expert for your website or app. It's like hiring a team of translators and cultural experts who ensure that your online business is fluent in multiple languages. It helps adapt your content, menus, and messages to fit perfectly in each target market, making your business more appealing and user-friendly.
locize: Now, 'locize' is your efficient manager in charge of organizing and streamlining the translation process. It keeps all your language versions organized and ensures they're always accurate and up-to-date. So, if you want to introduce a new product or promotion, locize helps you do it seamlessly in all the languages you operate in, saving you time and resources.
Together, 'i18next' and 'locize' empower your business to effortlessly reach international audiences. They help you speak the language of your customers, making your business more accessible, relatable, and successful in global markets.
Last updated 10 months ago
Mobile Computing in the CloudSome mobile apps need computational power beyond their own can handle. Forexample, a mobile app uses AI to identify people. In cases like this, apps need tosend data back to the cloud letting AI services to identify the person and retrieveresults from the cloud and display on the mobile device.In general, mobile applications require cloud services for actions that can’t bedone directly on the device, such as offline data synchronization, storage, or datasharing across multiple users. People often have to configure, set up, and managemultiple services to power the backend. People also have to integrate each of thoseservices into applications by writing multiple lines of code. However, as the numberof application features grow, the code and release process become more complex,and managing the backend requires more time.AWS services such as Amplify provisions and manages backends for mobileapplications. One just selects the capabilities needed such as authentication, ana-lytics, or offline data sync, and Amplify will automatically provision and managethe AWS service that powers each of the capabilities. One can then integrate thosecapabilities into applications through the Amplify libraries and UI components
Mobile Computing in the Cloud
Cloud Dependency: Many mobile apps require cloud computing for tasks beyond device capabilities (e.g., AI processing).
Use Cases: Apps might send data to the cloud for processing and retrieve results.
Cloud Services: Enable offline data synchronization, storage, and multi-user data sharing.
Management Complexity: As app features grow, managing multiple backend services becomes complex.
AWS Amplify: Provides a solution for backend management, allowing developers to select required capabilities (like authentication and analytics) and automating the provisioning of necessary services.
But law’s daily grist is not subject to that extrinsic pressure. It isa rare day that summary judgment procedures get a fresh look, orthat the Penal Code is re-evaluated in light of the stated objectivesof criminal law.
I think this statement is a bit comforting, I think as a 1L it's easy to be overwhelmed with big cases so that it feels like every case must change the law. But that isn't the reality of daily practice. Although the law is always shifting, it seems to develop slowly.
But law’s daily grist is not subject to that extrinsic pressure. It isa rare day that summary judgment procedures get a fresh look, orthat the Penal Code is re-evaluated in light of the stated objectivesof criminal law.
I think this sentence highlights and sets the final pieces in place for the author's argument. In context, they suggest that even though the work done at the trial level makes up the bulk of legal work, it receives relatively little attention and critical analysis about whether or not the practices and outcomes are actually as correct and just as they could be.
After three years, based on feedback from the Stanford community and the Office of Community Standards staff, the BJA voted to adopt the following amendment to the Student Conduct Penalty Code on May 25, 2016 that determines that the Office of Community Standards should use the following guidelines in determining sanctions for ERO agreements.
I think it's confusing and unnecessary to include this HISTORY of feedback and revisions here - just put the CURRENT POLICY
No one deserves to be harassed, online or offline. Laws such as the Criminal Code of Canada and the Canadian Human Rights Act offer protection from harassment.
While Canada-specific laws are referenced, the principles could apply broadly. For instance, teaching students about laws protecting digital data could bridge their understanding of both local and international standards in digital ethics.
Smith-Corona typewriters generally have either Hulse or RaRo slugs.
Both used the number "1" as their code for their Standard Pica typefaces.
Hulse slug pattern:
RaRo slug pattern:
via Pelicram at https://discord.com/channels/639936208734126107/639939010541649951/1289001269712916595
Investigating the theoretical foundation of Lisp - Delving into the history of mathematical logic and its influence on Lisp - Understanding the origin story and confusion around Lisp, particularly with regards to the Lambda calculus
Grounding of mathematics in logic - Russell and Whitehead ensured the grounding of mathematics in logic to avoid paradoxes - Hilbert's formalism approach focused on consistency and syntactic forms of mathematics
Hilbert's program led to proof Theory and Godel's work validated questions with reliable Foundation of mathematical knowledge. - Godel's creation of a self-referential statement within Principia Mathematica was a plot twist. - The arithmetization of syntax and assigning unique numbers to syntactic elements played a key role in Godel's proof.
Rosa Peter advocated for the study of recursive functions as a separate field and made significant contributions to recursion Theory. - She presented a paper on this topic at the international Congress of mathematicians in Zurich in 1932 and coined the term primitive recursive functions. - Despite being forbidden to teach during fascist laws, she resumed her career after World War II and made contributions to recursion theory, computer science, and pedagogy in mathematics.
Primitive recursive functions are built from basic functions and operations - Basic functions include constant zero, successor, and projection functions - Operations of composition and recursion can be used to build new computable functions
Understanding recursion theory and computable functions - Recap on negation, conjunction, and disjunction as addition and multiplication behaviors - Exploration of recursive functions, including non-primitive recursive functions like Akerman's
Classification of recursive functions - Primitive recursive functions are defined on all inputs, while partial recursive functions are not - The addition of the minimization operator creates unbounded search space, distinguishing partial recursion from primitive recursion
Touring machines formalized computability, influential in the history of computation. - Touring modeled computability based on human step-by-step calculations intuitively. - Various models of computation became equivalent in 1936, known as the Church-Turing thesis.
Lisp was devised as a vehicle for developing a theory of computation. - John McCarthy led the development of Lisp as a programming language and as a formalism in mathematical logic. - Lisp as an idea is found behind every implementation that came after.
Lisp is a realization of the Lambda calculus - Lisp is seen as a realization of Lambda calculus based on notation - The association between Lisp and Lambda calculus explained through historical context
Lisp was developed as an interpreter for Lisp, creating a new programming language. - Lisp's development was prompted by its potential to serve as an interpreter for Lisp. - It allowed for symbolic computation and the translation of formulas into code.
Closure code translating basic functions of Primitive recursive functions. - Explanation of the machinery being involved. - Blog post titled 'Lisp's Grandfather Paradox' for more detailed information.
Some things to note: first, we always create a DaySlot for every DayEvent, even for non-repeating ones. This is needed to simplify the rendering code.
Interesting. How could this be applied for my Attendance Tracker ? Should I have Cohorts similar to DayEvent (with repeating attributes ?)
Maybe this would even be several SQL queries, or even some code in a programming language. The data structure that we’ve considered so far is quite complicated. To find the events that must be shown on a certain week, you need to take a lot into account. This may quickly become impractical.
I might have spoken too quickly. Efficient storage but quickly become impractical if we have to use the data for a task
Using an interactive approach allows you to collaborate with an AI assistant, directing the analysis rather than letting the AI take the lead. Instead of relying on simple buttons like “Summarize data,” “Extract themes,” or “Code the data,” you can enter prompts and initiate deeper exploration. This interaction enables you to reflect on the results, questioning and probing where necessary. If you suspect that an answer is biased or fabricated, you can highlight this concern to your AI assistant. You can request the assistant to reflect on its response and provide reasoning behind it. Additionally, you can challenge the AI to offer alternative perspectives. If you suspect that the AI has generated incorrect or hallucinated information, you can ask it to re-examine the data and provide supporting evidence.
La IA puede ser una herramienta increíble para expandir la investigación cualitativa, pero el investigador debe ser el principal moderador y crítico del proceso. Usarla como un “compañero de análisis” en lugar de un reemplazo asegura que la perspectiva humana y el contexto cultural sigan siendo los pilares del análisis.
def, aim to primary feature loossly couple, stande alone code test in memory configuration
def provide configuration time
Reviewer #2 (Public review):
Summary:
Developing neuronal models that are shareable, reproducible, and interoperable allows the neuroscience community to make better use of published models and to collaborate more effectively. In this manuscript, the authors present a consolidated overview of the NeuroML model description system along with its associated tools and workflows. They describe where different components of this ecosystem lay along the model development pathway and highlight resources, including documentation and tutorials, to help users employ this system.
Strengths:
The manuscript is well-organized and clearly written. It effectively uses the delineated model development life cycle steps, presented in Figure 1, to organize its descriptions of the different components and tools relating to NeuroML. It uses this framework to cover the breadth of the software ecosystem and categorize its various elements. The NeuroML format is clearly described, and the authors outline the different benefits to its particular construction. As primarily a means of describing models, NeuroML also depends on many other software components to be of high utility to computational neuroscientists; these include simulators (ones that both pre-date NeuroML and those developed afterwards), visualization tools, and model databases.
Overall, the rationale for the approach NeuroML has taken is convincing and well-described. The pointers to existing documentation, guides, and the example usages presented within the manuscript are useful starting points for potential new users. This manuscript can also serve to inform potential users of features or aspect of the ecosystem that they may have been unaware of, which could lower obstacles to adoption. While much of what is presented is not new to this manuscript, it still serves as a useful resource for the community looking for information about an established, but perhaps daunting, set of computational tools.
Weaknesses:
The manuscript in large part catalogs the different tools and functionalities that have been produced through the long development cycle of NeuroML. Overall, the interoperability of NeuroML is a benefit, but it does increase the complexity of choices facing users entering into the ecosystem.
In many respects this is an intractable fact of the current environment, but the authors do try to mitigate the issue with user guides (e.g., Table 1) and example code (e.g. Box 1) which address a range of target user audiences, from those learning about the ecosystem for the first time to those looking to implement specific model features. They also categorize different simulator options (Figure 5) and provide feature comparisons (Table 3), which could assist with the most daunting choice faced by new users.
Comments on revised version:
The authors have addressed my major concerns with the original manuscript. The discussion of simulators in particular is much clearer now, and the manuscript has been restructured so that specific details pertinent to a much more focused audience have been rewritten or shifted to more appropriate locations.
Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
The manuscript gives a broad overview of how to write NeuroML, and a brief description of how to use it with different simulators and for different purposes - cells to networks, simulation, optimization, and analysis. From this perspective, it can be an extremely useful document to introduce new users to NeuroML.
We are glad the reviewer found our manuscript useful.
However, the manuscript itself seems to lose sight of this goal in many places, and instead, the description at times seems to target software developers. For example, there is a long paragraph on the board and user community. The discussion on simulator tools seems more for developers, not users. All the information presented at the level of a developer is likely to be distracting to eLife readership.
To make the paper less developer focussed and more accessible to the end user we have shortened the long paragraphs on the board and user community (and moved some of this text to the Methods section; lines: 524-572 in the document with highlighted changes). We have also made the discussion on simulator tools more focussed on the user (lines 334-406). However, we believe some information on the development and oversight of NeuroML and its community base are relevant to the end user, so we have not removed these completely from the main text.
Strengths:
The modularity of NeuroML is indeed a great advantage. For example, the ability to specify the channel file allows different channels to be used with different morphologies without redundancy. The hierarchical nature of NeuroML also is commendable, and well illustrated in Figures 2a through c.
The number of tools available to work with NeuroML is impressive.
The abstract, beginning, and end of the manuscript present and discuss incorporating NeuroML into research workflows to support FAIR principles.
Having a Python API and providing examples using this API is fantastic. Exporting to NeuroML from Python is also a great feature.
We are glad the reviewer appreciated the design of NeuroML and its support for FAIR principles.
Weaknesses:
Though modularity is a strength, it is unclear to me why the cell morphology isn't also treated similarly, i.e., specify the morphology of a multi-compartmental model in a separate file, and then allow the cell file to specify not only the files containing channels, but also the file containing the multi-compartmental morphology, and then specify the conductance for different segment groups. Also, after pynml_write_neuroml2_file, you would not have a super long neuroML file for each variation of conductances, since there would be no need to rewrite the multi-compartmental morphology for each conductance variation.
We thank the reviewer for highlighting this shortcoming in NeuroML2. We have now added the ability to reference externally defined (e.g. in another file) <morphology> and <biophysicalProperties> elements from <cells>. This has enabled the morphologies and/or specification of ionic conductances to be separated out and enables more streamlined analysis of cells with different properties, as requested. Simulators NEURON, NetPyNE and EDEN already support this new form. Information on this feature has been added to https://docs.neuroml.org/Userdocs/ImportingMorphologyFiles.html#neuroml2 and also mentioned in the text (lines 188-190).
This would be especially important for optimizations, if each trial optimization wrote out the neuroML file, then including the full morphology of a realistic cell would take up excessive disk space, as opposed to just writing out the conductance densities. As long as cell morphology must be included in every cell file, then NeuroML is not sufficiently modular, and the authors should moderate their claim of modularity (line 419) and building blocks (551).
We believe the new functionality outlined above addresses this issue, as a single file containing the <morphology> element could be referenced, while a much smaller file, containing the channel distributions in a <biophysicalProperties> element would be generated and saved on each iteration of the optimisation.
In addition, this is very important for downloading NeuroML-compliant reconstructions from NeuroMorpho.org. If the cell morphology cannot be imported, then the user has to edit the file downloaded from NeuroMorpho.org, and provenance can be lost.
While the NeuroMorpho.Org website does support converting reconstructed morphologies in SWC format to NeuroML, this export feature is no longer supported on most modern browsers due to it being based on Java Applet technologies. However, a desktop version of this application, CVApp, is actively maintained
(https://github.com/NeuroML/Cvapp-NeuroMorpho.org), and we have updated it to support export of the SWC to the standalone <morphology> element form of NeuroML discussed above. Additionally, a new Python application for conversion of SWC to NeuroML is in development and will be incorporated into PyNeuroML (Google Summer of Code 2024). Our documentation has been updated with the recommended use of SWC in NeuroML based modelling here: https://docs.neuroml.org/Userdocs/Software/Tools/SWC.html
We have also included URLs to the tool and the documentation in the paper (lines: 473-474).
SWC files, however, cannot be used “as is” for modelling since they only include information (often incomplete—for example a single point may represent a soma in SWC files) on the points that make the cell, but not on the sections/segments/cables that these form. Therefore, NeuroML and other simulation tools, including NEURON, must convert these into formats suitable for simulation. The suggested pipeline for use of NeuroMorpho SWC files would therefore be to convert them to NeuroML, check that they represent the intended compartmentalisation of the neuron and then use them in models.
To ensure that provenance is maintained in all NeuroML models (including conversions from other formats), NeuroML supports the addition of RDF annotations using the COMBINE annotation specifications in model files:
https://docs.neuroml.org/Userdocs/Provenance.html. We have added this information to the paper (lines: 464-465).
Also, Figure 2d loses the hierarchical nature by showing ion channels, synapses, and networks as separate main branches of NeuroML.
While an instance of an ion channel is on a segment, in a cell, in a population (and hence there is a hierarchy between them), in terms of layout in a NeuroML file the ion channel is defined at the “top level” so that it can be referenced and used by multiple cells, the cell definitions are also defined top level, and used in multiple populations, etc. There are multiple ways to depict these relationships between entities, and we believe Fig 2d complements Fig 2a-c (which is more hierarchical), by emphasising the different categories of entities present in NeuroML files. We have modified the caption of Figure 2d to clarify that it shows the main categories of elements included in the NeuroML standard in their respective hierarchies.
In Figure 5, the difference between the core and native simulator is unclear.
We have modified the figure and text (lines: 341) to clarify this. We now say “reference” simulators instead of “core”. This emphasises that jNeuroML and pyLEMS are intended as reference implementations in each of their languages of how to interpret NeuroML models, as opposed to high performance simulators for research use. We have also updated the categorization of the backends in the text accordingly.
What is involved in helper scripts?
Simulators such as NetPyNE can import NeuroML into their own internal format, but require some boilerplate code to do this (e.g. the NetPyNE scripts calls the importNeuroML2SimulateAnalyze() method with appropriate parameters). The NeuroML tools generate short scripts that use this boilerplate code. We have renamed “helper scripts” to “import scripts'' for clarity (Figure 5 and its caption).
I thought neurons could read NeuroML? If so, why do you need the export simulator-specific scripts?
The NEURON simulator does have some NeuroML functionality (it can export cells, though not the full network, to NeuroML 2 through its ModelView menu), but does not natively support reading/importing of NeuroML in its current version. But this is not a problem as jNeuroML/PyNeuroML translates the NeuroML model description into NEURON’s formats: Python scripts/HOC/Nmodl which NEURON then executes.
As NEURON is the simulator which allows simulation of the widest range of NeuroML elements, we have (in agreement with the NEURON developers) concentrated on incorporating the best support for NeuroML import/export in the latest (easy to install/update) releases of PyNeuroML, rather than adding this to the Neuron source code. NEURON’s core features have been very stable for years and many versions of the simulator are used by modellers - installing the latest PyNeuroML gives them the latest NEURON support without having to reinstall the latter.
In addition, it seems strange to call something the "core" simulation engine, when it cannot support multi-compartmental models. It is unclear why "other simulators" that natively support NeuroML cannot be called the core.
We agree that this terminology was confusing. As mentioned above, we have changed “core simulator” to “reference simulator”, to emphasise the roles of these simulation engine options.
It might be more helpful to replace this sort of classification with a user-targeted description. The authors already state which simulators support NeuroML and which ones need code to be exported. In contrast, lines 369-370 mention that not all NeuroML models are supported by each simulator. I recommend expanding this to explain which features are supported in each simulator. Then, the unhelpful separation between core and native could be eliminated.
As suggested, we have grouped the simulators in terms of function and removed the core/ non-core distinction. We have also added a table (Table 3) in the appendices that lists what features each simulation engine supports and updated the text to be more user focussed (lines: 348-394).
The body of the manuscript has so much other detail that I lose sight of how NeuroML supports FAIR. It is also unclear who is the intended audience. When I get to lines 336-344, it seems that this description is too much detail for the eLife audience. The paragraph beginning on line 691 is a great example of being unclear about who is the audience. Does someone wanting to develop NeuroML models need to understand XSD schema? If so, the explanation is not clear. XSD schema is not defined and instead explains NeuroML-specific aspects of XSD. Lines 734-735 are another example of explaining to code developers (not model developers).
We have modified these sentences to be more suitable for the general eLife audience: we have moved the explanation of how the different simulator backends are supported to the more technically detailed Methods section (lines 882-942).
While the results sections focus on documenting what users can do with NeuroML, the Methods sections include information on “how” the NeuroML and software ecosystem function. While the information in the methods sections may not be required by users who want to use the standard NeuroML model elements, those users looking to extend NeuroML with their own model entities and/or contribute these for inclusion in the NeuroML standard will require some understanding of how the schema and component types work.
We have tried to limit this information to the bare minimum, pointing to online documentation where appropriate. XSD schemas are, for example, briefly introduced at the beginning of the section “The NeuroML XML Schema”. We have also included a link to the W3C documentation on XSD schemas as a footnote (line 724).
Reviewer #2 (Public Review):
Summary:
Developing neuronal models that are shareable, reproducible, and interoperable allows the neuroscience community to make better use of published models and to collaborate more effectively. In this manuscript, the authors present a consolidated overview of the NeuroML model description system along with its associated tools and workflows. They describe where different components of this ecosystem lay along the model development pathway and highlight resources, including documentation and tutorials, to help users employ this system.
Strengths:
The manuscript is well-organized and clearly written. It effectively uses the delineated model development life cycle steps, presented in Figure 1, to organize its descriptions of the different components and tools relating to NeuroML. It uses this framework to cover the breadth of the software ecosystem and categorize its various elements. The NeuroML format is clearly described, and the authors outline the different benefits of its particular construction. As primarily a means of describing models, NeuroML also depends on many other software components to be of high utility to computational neuroscientists; these include simulators (ones that both pre-date NeuroML and those developed afterwards), visualization tools, and model databases.
Overall, the rationale for the approach NeuroML has taken is convincing and well-described. The pointers to existing documentation, guides, and the example usages presented within the manuscript are useful starting points for potential new users. This manuscript can also serve to inform potential users of features or aspects of the ecosystem that they may have been unaware of, which could lower obstacles to adoption. While much of what is presented is not new to this manuscript, it still serves as a useful resource for the community looking for information about an established, but perhaps daunting, set of computational tools.
We are glad the reviewer appreciated the utility of the manuscript.
Weaknesses:
The manuscript in large part catalogs the different tools and functionalities that have been produced through the long development cycle of NeuroML. As discussed above, this is quite useful, but it can still be somewhat overwhelming for a potential new user of these tools. There are new user guides (e.g., Table 1) and example code (e.g. Box 1), but it is not clear if those resources employ elements of the ecosystem chosen primarily for their didactic advantages, rather than general-purpose utility. I feel like the manuscript would be strengthened by the addition of clearer recommendations for users (or a range of recommendations for users in different scenarios).
To make Table 1 more accessible to users and provide recommendations we have added the following new categories: Introductory guides aimed at teaching the fundamental
NeuroML concepts; Advanced guides illustrating specific modelling workflows; and Walkthrough guides discussing the steps required for converting models to NeuroML. Box 1 has also been improved to clearly mark API and command line examples.
For example, is the intention that most users should primarily use the core NeuroML tools and expand into the wider ecosystem only under particular circumstances? What are the criteria to keep in mind when making that decision to use alternative tools (scale/complexity of model, prior familiarity with other tools, etc.)? The place where it seems most ambiguous is in the choice of simulator (in part because there seem to be the most options there) - are there particular scenarios where the authors may recommend using simulators other than the core jNeuroML software?
The interoperability of NeuroML is a major strength, but it does increase the complexity of choices facing users entering into the ecosystem. Some clearer guidance in this manuscript could enable computational neuroscientists with particular goals in mind to make better strategic decisions about which tools to employ at the outset of their work.
As mentioned in the response to Reviewer 1, the term “core simulator” for jNeuroML was confusing, as it suggested that this is a recommended simulation tool. We have changed the description of jNeuroML to a “reference simulator” to clarify this (Figure 5 and lines 341, 353).
In terms of giving specific guidance on which simulator to use, we have focussed on their functionality and limitations rather than recommending a specific tool (as simulator independent standards developers we are not in a position to favour particular simulators). While NEURON is the most widely used simulator currently, other simulation opinions (e.g. EDEN) have emerged recently which provide quite comprehensive NeuroML support and similar performance. Our approach is to document and promote all supported tools, while encouraging innovation and new developments. The new Table 3 in the Appendix gives a guide to assist users in choosing which simulator may best suit their needs and we have updated the text to include a brief description (lines 348-394).
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
I do not understand what the $comments mean in Box 1. It isn't until I get further in the text that I realize that those are command line equivalents to the Python commands.
We thank the reviewer for highlighting this confusion. We’ve now explicitly marked the API usage and command line usage example columns to make this clearer. We have also used “>” instead of “$” now to indicate the command line,
In Figure 9 Caption "Examples of analysis functions ..", the word analysis seems a misnomer, as these graphs all illustrate the simulation output and graphing of existing variables. I think analysis typically refers to the transformation of variables, such as spike counts and widths.
To clarify this we have changed the caption to “Examples of visualizing biophysical properties of a NeuroML model neuron”.
Figure 10: Why is the pulse generator part of a model? Isn't that the input to a model?
Whether the input to the model is described separately from the NeuroML biophysical description or combined with it is a choice for the researcher. This is possible because in NeuroML any entity which has time varying states can be a NeuroML element, including the current pulse generator. In this simple example the input is contained within the same file (and therefore <neuroml> element) as the cell. However, this does not need to be the case. The cell could be fully specified in its own NeuroML file and then this can be included in other files which add different inputs to facilitate different simulation scenarios. The Python scripting interface facilitates these types of workflows.
In the interest of modularity, can stim information be stored in a separate file and "included"?
Yes, as mentioned above, the stimulus could be stored in a separate file.
I find it strange to use a cell with mostly dimensionless numbers as an example. I think it would be more helpful to use a model that was more physiological.
In choosing an example model type to use to illustrate the use of LEMS (Fig 12), NeuroML (Fig 10), XML Schema (Fig 11), the Python API (Fig 13) and online documentation (Fig 15), we needed an example which showed a sufficiently broad range of concepts (dimensional parameters, state variables, time derivatives), but which is sufficiently compact to allow a concise depiction of the key elements in figures, that fit in a single page (e.g. Fig 12). We felt that the Hindmarsh Rose model, while not very physiological, was well suited for this purpose (explaining the underlying technologies behind the NeuroML specification). The simplicity of the Hindmarsh Rose model is counterbalanced in the manuscript by the detailed models of neurons and circuits in Figures 7 & 9. The latter shows a morphologically and biophysically detailed cortical L5b pyramidal cell model.
In lines 710-714, it is unclear what is being validated. That all parameters are defined? Using the units (or lack thereof) defined in the schema?
Validation against the schema is “level 1” validation where the model structure, parameters, parameter values and their units, cardinality, and element positioning in the model hierarchy are checked. We have updated the paragraph to include this information and to also point to Figure 6 where different levels of validation are explained.
Lines 740 to 746 are confusing. If 1-1 between XSD and LEMS (1st sentence) then how can component types be defined in LEMS and NOT added to the standard? Which is it? 1-1 or not 1-1?
For the curated model elements included in the NeuroML standard, there will be a 1-1 correspondence between their component type definitions in LEMS and type definitions in the XSD schema. New user defined component types (e.g. a new abstract cell model) can be specified in LEMS as required, and these do not need to be included in the XSD schema to be loaded/simulated. However, since they are not present in the schema definition of the core/curated elements, they cannot be validated against it (level 1 validation). We have modified the text to make this clearer (line: 778).
Nonetheless, if the new type is useful for the wider community, it can be accepted by the Editorial Board, and at that stage it will be incorporated into the core types, and added to the Schema, to be part of “valid NeuroML”.
Figure 12. select="synapses[*]/i" is not explained. Does /i mean that iSyn is divided by i, which is current (according to the sentence 3 lines after 766) or perhaps synapse number?
We thank the reviewer for highlighting this confusion. We have now explained the construct in the text (lines 810-812). It denotes “select the i (current) values from all Attachments which have the id ‘synapses’”. These multiple values should be reduced down to a single value through addition, as specified by the attribute: reduce=”add”.
The line after 766 says that "DerivedVariables, variables whose values depend on other variables". You should add "and that are not derivatives, which are handled separately" because by your definition derivatives are derived variables.
Thank you. We have updated the text with your suggestion
Reviewer #2 (Recommendations For The Authors):
- Figure 9: I found it somewhat confusing to have the header from the screenshot at the top ("Layer 5 Burst Accommodating Double Bouquet Cell (5)") not match the morphology shown at the bottom. It's not visually clear that the different panels in Figure 9 may refer to unrelated cells/models.
Thank you for pointing this out. We have replaced the NeuroML-DB screenshot with one of the same Layer 5b pyramidal cells shown in the panels below it.
Additional change:
Figure 7c (showing the NetPyNE-UI interface) has been replaced. Previously, this displayed a 3D model which had been created in NetPyNE itself, but now shows a model which has been created in NeuroML and imported for display/simulation in NetPyNE-UI, and therefore better illustrates NeuroML functionality.
When designers and programmers don’t think to take into account different groups of people, then they might make designs that don’t work for everyone.
This reminded me of something in contrast, that I saw in my CSE 121 class and how some designers and programmers actually take disabled people into account. To elaborate it was intriguing to see how computer science is such a vast subject that is open to all, even those who are determined to learn as it can incorporate people like Sakib Shaikh who is blind, and others like him and not make them feel unrepresented in any way. As he could code just by speaking and its features such as fast speaking can also strengthen the overall quality and effectiveness of the code for all users.
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
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The study by Osato and Hamada aims at computationally identifying a set of novel putative insulator-associated DNA binding proteins (DBPs) via estimation of their contribution to the expression of genes in the same chromosome region of their binding sites (+- 1Mbp from TSS). To achieve this, the authors leverage a deep learning architecture already published via which ChIP-seq peaks of DBPs in the TSS of a given gene are used to predict its expression level in four human cell lines.
Building on this, the authors used another tool called DeepLIFT to evaluate the weight of each DBP binding site on the final gene expression value. Hence they made the assumption that if a given DBP had an insulator function they could restrict the prediction of the gene's expression to the region included between pairs of that DBP binding sites, and evaluate the pair's motif directionality bias in the distribution of weights. They exemplify their approach's validity by the fact that they can predict the known directionality bias of CTCF/cohesin-bound sites as the highest of the lot, with the F-R orientation of the pairs the most enriched, recapitulating what already known in literature: i.e., that F-R chromatin interaction peaks are the most enriched. In addition, they find several new DBPs showing significant directionality bias; hence they could be candidates for insulation activity. They then provide correlation between these putative insulator binding sites and sites of transition between euchromatin and heterochromatin by independently using histone mark and gene expression datasets. This, of course, is not surprising because (a) there is insulation between regions with heterotypic chromatin identities, and (b) it was already known from the first papers describing insulated chromatin domains that their boundaries were well-enriched for active transcription and transcriptional regulators (e.g., Dixon et al, Nature 2012).
Finally, they use chromatin interaction (looping) sites to check the overlap between CTCF and all other DBPs and define a subset of putative insulator DBPs not overlapping CTCF peaks, suggesting potentially new insulatory mechanisms. These factors were all known transcriptional activators, but this part of the findings carry most of the novelty in the work and have the potential of opening up new directions for research in chromatin organization.
Overall, the methodology applied here is adequate, clear, and reproducible. The major issue, in our view, is that the entire manuscript's findings relies on the usage of deepLIFT, a tool which was not benchmarked previously or by the current study. In fact, deepLIFT is public as regards its code, and also appears as a preprint from 2017 on biorXiv and published in the Proceedings of Machine Learning Research conference. Also, this key tool was developed by the Kundaje lab (who produce high quality alogrithms), and not by the authors. Therefore, the manuscript is predominantly based on the execution of existing workflows to publicly-available data. This does not take anything away from the interesting question posed here, but at the same time does not provide the community with any new algorithm/workflow.
Finally, although I appreciate that the authors are purely computational and have likely no capacity for experimental validation of their claims of new DBPs having insulator roles, I would assume that there are RNA-seq and/or ChIP-seq data out there produced after knockdown of one or more of these DBPs that show directional positioning. Using this kind of data, effects on gene expression can at least be tested in regard to the authors' predictions. Moreover, in terms of validation, Figure 6 should be expanded to incorporate analysis of DBPs not overlapping CTCF/cohesin in chromatin interaction data that is important and potentially more interesting than the simple DBPs enrichment reported in the present form of the figure. Critically, I would like to see use of Micro-C/Hi-C data and ChIP-seq from these factors, where insulation scores around their directionally-bound sites show some sort of an effect like that presumed by the authors - and many such datasets are publicly-available and can be put to good use here.
As secondary issues, we would point out that:
The scientific novelty of the work lies primarily in the identification of a set of DBPs that are proposed to confer insulator activity genome-wide. This has been long sought after in human data (whilst it is well understood and defined in Drosophila). The authors produce a quantitative ranking of the putative insulation effect of these DBPs and, most importantly, go on to identify a smaller subset that are apparently non-overlapping with anchors of CTCF-cohesin loop anchors; the presence of strong motif orientation biases in many DBPs can also be of broad interest, especially those that cannot be trivially ascribable to the loop extrusion process.
However, although these findings open the way for speculation on multiple insulation mechanisms via proteins with multiple regulatory functions, the manuscript provide no experimental or computational means to test the proposed roles of these DBPs - and, as such, this limits the potential impact of the work and mostly targets researchers in the field of genome organization that can test these findings. Having said this, if validated, this work can significantly broaden our understanding of how chromatin is organized in 3D nuclear space.
I typically identify myself to the authors: A. Papantonis, expertise in 3D genome architecture, chromatin biology, and genomics/bioinformatics.
ZB is designed to help students with disabilities develop and improve their social skills and can even teach them how to code.
I really like this idea. If there are robots like this to be able to help people in situations like this, I strongly support.
Author response:
The following is the authors’ response to the original reviews.
A summary of changes
(1) Line 93: “positive effect” to “positive contribution”, as suggested by reviewer 2.
(2) Line 147-148: the null hypothesis to test “equal interspecific and intraspecific interactions”, as indicated by reviewers 2 and 4.
(3) Lines 155-162: removed to reduce duplication with the additive partitioning, as suggested by reviewer 2.
(4) Lines 186-188: added “the estimated competitive growth response would also include the effects of density-dependent pests, pathogens, or microclimates”, as suggested by reviewer 3.
(5) Lines 219-222: added “The community positive effect can be further partitioned by mechanisms of positive interactions (resource partitioning and facilitation), and facilitative effect can be classified as mutualism (+/+), commensalism (+/0), or parasitic (+/–) based on species specific assessments”.
(6) Lines 377-386: added options for determining maximum competitive growth response in some extreme scenarios of species mixtures.
(7) Figure 1: modified to show the variations of competitive growth response with relative competitive ability from minimum (null expectation) to maximum (competitive exclusion).
A summary of four reviewers’ questions and authors’ response
(1) A summary of authors’ responses. Reviewers did not seem to understand our work. They indicated that our model is inadequate for hypothesis testing. The fact is, as we note below, that our model allows for more hypothesis testing than the additive partitioning model. They suggested that one of our model components, the competitive growth response, needs to be further partitioned. However, this term represents only the competition effect and can not be split any further. Reviewers criticized us for misunderstanding the additive components while they suggested the same logic to test some intuitive ideas. They did not seem to know that the effects of competitive interactions vary with assessment methods, which differ between competition and biodiversity research. Our work seeks to harmonise definitions between these two fields and bridge the gap. The reviewers acknowledged that the additive components (i.e., the selection effect and complementarity effect) do not have clear biological meanings; however, they did not acknowledge that the additive components are used extensively for determining mechanisms of species interactions in biodiversity research. There is hardly any research that uses the additive partitioning model without linking the additive components to specific mechanisms of species interactions (i.e., positive SE to competition and positive CE to positive interactions).
(2) Additive partitioning and underlying mechanisms. Some reviewers acknowledged that additive partitioning is not meant for determining mechanisms of species interactions and therefore argued that the additive partitioning should not be criticized for lack of biological meanings with the additive components. However, they insisted that additive partitioning is useful in quantifying net biodiversity effects against the null hypothesis that there is no difference between intraspecific and interspecific interactions or testing the idea that “niche complementarity mitigates competition” or “competitively superior species dominate mixtures”. Are these views contradictory each other? How can the additive partitioning that is not designed for determining mechanisms of species interactions provide meaningful explanations for outputs of species interactions, e.g., “niche complementarity mitigates competition” or “competitively superior species dominate mixtures”?
Reviewers did not seem to realize that these ideas are equivalent to the suggestions that CE represents for the effects of positive interactions and SE for the effects of competitive interactions, that the quantification of net biodiversity effects does not require the two additive components, and that the null hypothesis exists long before the additive partitioning (see de Wit, 1960, de Wit et al., 1966). It is generally agreed that CE and SE result from mathematical calculations and do not have clear biological meanings in terms of linkages to specific mechanisms of species interactions responsible for observed net biodiversity effects or changes in ecosystem function (Loreau and Hector, 2012; Bourrat et al., 2023). Calling some mixed effects of species interactions as mechanisms (e.g., CE and SE) is misleading.
Model structure: incomplete or inadequate for hypothesis testing. Other than positive, negative, and competition interactions, two reviewers wanted to have more specific interactions such as microclimate amelioration and negative feedback from species-specific pests and pathogens. The determination of these specific mechanisms requires more investigations and cannot be simply made through partitioning growth and yield data. However, the effects of these interactions will be captured in our definition of species interactions. Reviewers did not seem to know that the additive partitioning would also not allow identifying these specific positive species interactions.
Inspired by the mathematical form of additive partitioning, two reviewers suggested that our model (presumably equation 4) is incomplete and the second term, i.e., competitive growth response needs to be further explored or partitioned. The second term represents deviations from the null expectation, due to species differences in growth and competitive ability or competition effect. We do not know why and how this term can be further partitioned and what any subcomponents would mean.
Our competitive partitioning model is based on two hypotheses: first, the null hypothesis to test the equivalence of interspecific and intraspecific interactions. This hypothesis is the same as the additive partitioning model. Second, the competitive hypothesis, which tests the dominance of positive or negative species interactions in a community. Thus, our model allows for more hypothesis testing than the current additive partitioning model.
(3) Types of species interactions. We follow the definition of species interactions generally used in biodiversity research (see Loreau and Hector, 2001), i.e., positive interactions (or complementarity) include resource partitioning and facilitation, negative interactions include interference competition, and competitive interactions include resource competition. One reviewer suggested that resource partitioning is byproduct of competition and should not be part of positive species interactions, which may be true for long-term evolution of species co-existence but not for biodiversity experiments of decade duration at most. Two reviewers suggested that positive interactions should also include microclimate amelioration or negative feedback from species-specific pests and pathogens. We agree and these are included in our definition.
(4) Significance of partial density monocultures. We used partial and full density monocultures and species competitive ability to determine what species can possibly achieve in mixture under the competitive hypothesis that constituent species share an identical niche but differ in growth and competitive ability. We did not use partial monocultures to test the effects of density on biodiversity effects. As with the additive partitioning, the competitive partitioning model is not designed for comparing yields across different densities. We added at lines 186-188 to indicate that the estimated competitive growth response would also include the effects of density-dependent pests, pathogens, or microclimates.
Similarly, we do not use the partial density monoculture to supplant the replacement series design. Partial density monocultures only supplement the “replacement series” design that does not provides estimates of facilitative effects and competitive growth responses that would occur in mixtures. It is crucial to know that one experimental approach is simply not enough for determining underlying mechanisms of species interactions responsible for changes in ecosystem function.
(5) Competition effect in competition and biodiversity research. Due to different methods used, competition effect in competition research has different ecological meanings from that in biodiversity research. In competition research, species performance in mixture are compared with their partial density monocultures and therefore competition effect is generally negative, as suggested by reviewer 4. In biodiversity research, comparison is between mixture and full density monocultures. The resulting competition effect can be positive or negative for both individual species and community productivity defined by species composition and full density monoculture yields.
Therefore, we cannot use the results of competition research based on additive series design to describe effects of competitive interactions on ecosystem productivity based replacement series design.
Reviewer #1 (Public Review):
[Editors' note: this is an overall synthesis from the Reviewing Editor in consultation with the reviewers.]
The three reviews expand our critique of this manuscript in some depth and complementary directions. These can be synthesized in the following main points (we point out that there is quite a bit more that could be written about the flaws with this study; however, time constraints prevented us from further elaborating on the issues we see):
(1) It is unclear what the authors want to do.
As indicate by the title, our objective is to “partition changes in ecosystem productivity by effects of species interactions”, i.e., partitioning net biodiversity effects estimated from the null expectation into components associated with positive, negative, or competition interspecific interactions.
It seems their main point is that the large BEF literature and especially biodiversity experiments overstate the occurrence of positive biodiversity effects because some of these can result from competition.
We demonstrated through ecological theories and simulation/experiment data that competition is a major source of the net biodiversity effects estimated with additive partitioning model. We know that competition effect varies with mixture attributes. Future research will determine average effect of competitive interactions on biodiversity effects in large BEF literature.
Because reduced interspecific relative to intraspecific competition in mixture is sufficient to produce positive effects in mixtures (if interspecific competition = 0 then RYT = S, where S is species richness in mixture -- this according to the reciprocal yield law = law of constant final yield), they have a problem accepting NE > 0 as true biodiversity effect (see additive partitioning method of Loreau & Hector 2001 cited in manuscript).
We have no problem to accept NE>0 as true positive biodiversity effect. However, NE>0 can also result from competitive interactions based on the null expectation and needs to be partitioned by effects of species interactions.
(2) The authors' next claim, without justification, that additive partitioning of NE is flawed and theoretically and biologically meaningless.
The additive partitioning model is based on Covariance equation (or Price equation) that has nothing to do with biodiversity partitioning (Bourrat et al., 2023). Biological meaning was arbitrarily assigned to CE and SE. We made clear that the additive partitioning model is mathematically sound but does not have biological meanings that it has been used for.
They misinterpret the CE component as biological niche partitioning and the SE component as biological dominance.
We did not. Loreau and Hector (2001) clearly indicated positive CE for positive interactions and positive SE for competitive interactions, which is generally what has been used for in the last twenty years.
They do not seem to accept that the additive partitioning is a logically and mathematically sound derivation from basic principles that cannot be contested.
We do not have problem with mathematical form of additive partitioning but only oppose ecological meanings assigned to CE and SE, simply because CE and SE both result from all species interactions (see Loreau and Hector, 2001; Bourrat et al., 2023). The reviewer seemed to have a contradictory thinking that the additive components are biologically meaningless but derived from biological basic principles.
(3) The authors go on to introduce a method to calculate species-level overyielding (RY > 1/S in replacement series experiments) as a competitive growth response and multiply this with the species monoculture biomass relative to the maximum to obtain competitive expectation. This method is based on resource competition and the idea that resource uptake is fully converted into biomass (instead of e.g. investing it in allelopathic chemical production).
Correct, but we did not assume “resource uptake is fully converted into biomass”.
(4) It is unclear which experiments should be done, i.e. are partial-density monocultures planted or simply calculated from full-density monocultures? At what time are monocultures evaluated? The framework suggests that monocultures must have the full potential to develop, but in experiments, they are often performing very poorly, at least after some time. I assume in such cases the monocultures could not be used.
Both partial and full density monocultures are needed, along with mixtures to separate NE by species interactions. Calculating competitive growth responses from density-size relationships can be an alternative, given the lack of partial density monocultures in current biodiversity experiments, but is not preferred.
Similar to additive partitioning, our model can (and should) be applied to all developmental stages of an experiment to examine how interactions evolve through time.
(5) There are many reasons why the ideal case of only resource competition playing a role is unrealistic. This excludes enemies but also differential conversion factors of resources into biomass and antagonistic or facilitative effects. Because there are so many potential reasons for deviations from the null model of only resource competition, a deviation from the null model does not allow conclusions about underlying mechanisms.
The competitive expectation is only a hypothesis, just as the null expectation. The difference between competitive and null expectations represents a competitive effect resulting from species differences in growth and competitive ability, while the deviation of observed yields from the competitive expectation indicates positive or negative effect (see lines 201-219).
Furthermore, this is not a systematically developed partitioning, but some rather empirical ad hoc formulation of a first term that is thought to approximate competitive effects as understood by the authors (but again, there already are problems here). The second residual term is not investigated. For a proper partitioning approach, one would have to decompose overyielding into two (or more) terms and demonstrate (algebraically) that under some reasonable definitions of competitive and non-competitive interactions, these end up driving the respective terms.
The first term represents the null expectation assuming equal interspecific and intraspecific interactions, i.e., absence of positive, negative, and competition effects. The second residual term represents competition effect, due to species differences in growth and competitive ability. The meaning of second residual term is clear and does not need to be further partitioned or investigated.
In fact, our competitive partitioning also has several components including null expectation, competitive growth response, and observed yield, plus partial density monocultures for species assessment, or null expectations, competitive expectations, and observed yields for community level assessment, although different from the additive partitioning.
(6) Using a simplistic simulation to test the method is insufficient. For example, I do not see how the simulation includes a mechanism that could create CE in additive partitioning if all species would have the same monoculture yield. Similarly, they do not include mechanisms of enemies or antagonistic interactions (e.g. allelopathy).
The simulation model we used is developed from real world data and can only do what are available in the model in terms of species and their growth under different conditions. We can not go beyond data limitation. The model is empirical and has been shown to accurately estimate yield in the aspen-spruce forest condition. We would also note that we do also use experimental data (Table 2).
(7) The authors do not cite relevant literature regarding density x biodiversity experiments, competition experiments, replacement-series experiments, density-yield experiments, additive partitioning, facilitation, and so on.
We cited literature relevant to biodiversity partitioning since we are not aiming to cover everything. The reviewer may not be aware that most of the research areas listed are actually included in our work, such as additive and replacement-series experiment designs, additive partitioning, facilitation, competition studies, and density-yield relationships. Our competitive model partitioning is based on biological principles, while the additive partitioning model is based only on a mathematical equation.
Overall, this manuscript does not lead further from what we have already elaborated in the broad field of BEF and competition studies and rather blurs our understanding of the topic.
The results of competition studies based on additive series design are not really used in the broad field of BEF based on replacement series design. The effects of competitive interactions on BEF are never clearly defined using the results of competition studies. Our work is filling that gap.
Reviewer #2 (Public Review):
This manuscript is motivated by the question of what mechanisms cause overyielding in mixed-species communities relative to the corresponding monocultures. This is an important and timely question, given that the ultimate biological reasons for such biodiversity effects are not fully understood.
As a starting point, the authors discuss the so-called "additive partitioning" (AP) method proposed by Loreau & Hector in 2001. The AP is the result of a mathematical rearrangement of the definition of overyielding, written in terms of relative yields (RY) of species in mixtures relative to monocultures. One term, the so-called complementarity effect (CE), is proportional to the average RY deviations from the null expectations that plants of both species "do the same" in monocultures and mixtures. The other term, the selection effect (SE), captures how these RY deviations are related to monoculture productivity. Overall, CE measures whether relative biomass gains differ from zero when averaged across all community members, and SE, whether the "relative advantage" species have in the mixture, is related to their productivity. In extreme cases, when all species benefit, CE becomes positive. When large species have large relative productivity increases, SE becomes positive. This is intuitively compatible with the idea that niche complementarity mitigates competition (CE>0), or that competitively superior species dominate mixtures and thereby driver overyielding (SE>0).
The reviewer needs to know that these ideas are based on the same logic that positive CE represents the effects of positive interactions and positive SE represents the effects of competitive interactions. CE>0 or SE>0 can result from many different scenarios of species interactions, not necessarily “niche complementarity mitigates competition” or “competitively superior species dominate mixtures”. CE>0 and SE>0 can occur alone or together. We simply can not tell underlying mechanisms of overyielding from mathematical calculations (CE and SE), as suggested by this reviewer later.
The reviewer criticizes us while using the same logic themselves.
However, it is very important to understand that CE and SE capture the "statistical structure" of RY that underlies overyielding. Specifically, CE and SE are not the ultimate biological mechanisms that drive overyielding, and never were meant to be. CE also does not describe niche complementarity. Interpreting CE and SE as directly quantifying niche complementarity or resource competition, is simply wrong, although it sometimes is done. The criticism of the AP method thus in large part seems unwarranted. The alternative methods the authors discuss (lines 108-123) are based on very similar principles.
The reviewer actually supports our point. However, CE and SE have been largely used as biological mechanisms, positive CE as the results of complementary interactions and positive SE as the results of competitive interactions (see Loreau and Hector, 2001).
We do not have problem with the "statistical structure" of AP; it is simply a covariance equation. It is important to know that CE and SE do not provide additional information on overyielding than NE in terms of underlying mechanisms of species interactions. Any attempt to investigate mechanism of overyielding with CE or SE can easily go wrong.
Our competitive partitioning model incorporates effects of competitive interactions into the conventional null expectation and allows for separating different effects of species interactions. In comparison, the additive partitioning model does not have this capacity, not even designed for this purpose, as suggested by this and other reviewers.
The authors now set out to develop a method that aims at linking response patterns to "more true" biological mechanisms.
Assuming that "competitive dominance" is key to understanding mixture productivity, because "competitive interactions are the predominant type of interspecific relationships in plants", the authors introduce "partial density" monocultures, i.e. monocultures that have the same planting density for a species as in a mixture. The idea is that using these partial density monocultures as a reference would allow for isolating the effect of competition by the surrounding "species matrix".
Correct.
The authors argue that "To separate effects of competitive interactions from those of other species interactions, we would need the hypothesis that constituent species share an identical niche but differ in growth and competitive ability (i.e., absence of positive/negative interactions)." - I think the term interaction is not correctly used here, because clearly competition is an interaction, but the point made here is that this would be a zero-sum game.
We did not say that competition is not an interaction; we only want to separate the effect of competition from those of other species interactions.
The authors use the ratio of productivity of partial density and full-density monocultures, divided by planting density, as a measure of "competitive growth response" (abbreviated as MG). This is the extra growth a plant individual produces when intraspecific competition is reduced.
Correct.
We added at lines 377-386 to discuss options to determine MG in some uncommon scenarios of species mixtures.
Here, I see two issues: first, this rests on the assumption that there is only "one mode" of competition if two species use the same resources, which may not be true, because intraspecific and interspecific competition may differ. Of course, one can argue that then somehow "niches" are different, but such a niche definition would be very broad and go beyond the "resource set" perspective the authors adopt. Second, this value will heavily depend on timing and the relationship between maximum initial growth rates and competitive abilities at high stand densities.
First, the "competitive effect" focusses on resource competition and other forms of competition (presumably interference competition) are included in the negative interactions.
Second, competitive growth response varies over time and with density, and so do NE, CE, SE, and interspecific interactions.
The authors then progress to define relative competitive ability (RC), and this time simply uses monoculture biomass as a measure of competitive ability. To express this biomass in a standardized way, they express it as different from the mean of the other species and then divide by the maximum monoculture biomass of all species.
I have two concerns here: first, if competitive ability is the capability of a species to preempt resources from a pool also accessed by another species, as the authors argued before, then this seems wrong because one would expect that a species can simply be more productive because it has a broader niche space that it exploits. This contradicts the very narrow perspective on competitive ability the authors have adopted. This also is difficult to reconcile with the idea that specialist species with a narrow niche would outcompete generalist species with a broad niche. Second, I am concerned by the mathematical form. Standardizing by the maximum makes the scaling dependent on a single value.
First, growth conditions are controlled in biodiversity experiments, i.e., both monocultures and mixtures are the same in resource space. Species do not have opportunity to exploit resources outside experimental area. For example, if less productive species on normal soils outperform more competitive species on saline/alkaline soil, these “less productive species” are considered “more productive”.
Second, as discussed in our paper (lines 367-376; Figure 1), more research is needed to determine relationships between species traits (biomass or height) and relative competitive ability. By then, scaling by the maximum would not be needed. There has been quite a lot of research on such relationships; we should leave this to subject experts to determine what would be mostly appropriate for species studied.
As a final step, the authors calculate a "competitive expectation" for a species' biomass in the mixture, by scaling deviations from the expected yield by the product MG ⨯ RC. This would mean a species does better in a mixture when (1) it benefits most from a conspecific density reduction, and (2) has a relatively high biomass.
Put simply, the assumption would be that if a species is productive in monoculture (high RC), it effectively does not "see" the competitors and then grows like it would be the sole species in the community, i.e. like in the partial density monoculture.
Correct, if species competitive ability differs substantially, the more competitive species in the mixture would grow like partial density monoculture. This extra growth should not be treated as sources of positive biodiversity effects, simply because it does not result from positive species interactions.
Overall, I am not very convinced by the proposed method.
(1) The proposed method seems not very systematic but rather "ad hoc". It also is much less a partitioning method than the AP method because the other term is simply the difference. It would be good if the authors investigated the mathematical form of this remainder and explored its properties.. when does complementarity occur? Would it capture complementarity and facilitation?
AP is, by no means, systematic. Remember, AP is based on covariance equation (or Price equation) that has nothing to do with species interactions, other than nice-looking mathematical form (Bourrat et al., 2023). Ecological meanings are subjectively given to CE and SE. Therefore, CE and SE reflect what we call them, not what they really mean.
The remainder measures deviations from the null expectation, due to only competition effect, and can not be partitioned any further. The remainder would be positive for more competitive species and negative for less competitive species in mixture relative to their full density monoculture. The deviation of observed yields from competitive expectations indicates dominance of positive or negative species interactions. All these are clearly outlined at lines 201-221.
(2) The justification for the calculation of MG and RC does not seem to follow the very strict assumptions of what competition (in the absence of complementarity) is. See my specific comments above.
We do not see why not.
(3) Overall, the manuscript is hard to read. This is in part a problem of terminology and presentation, and it would be good to use more systematic terms for "response patterns" and "biological mechanisms".
To help understand the variations of competitive growth response with relative competitive ability, the x axis of Figure 1 is labelled with null expectation, competitive expectation, and competitive exclusion from minimum to maximum deviation of competitive ability from community average.
We have followed terms used in biodiversity partitioning and changing terms can be confusing.
Examples:
- on line 30, the authors write that CE is used to measure "positive" interactions and SE to measure "competitive interactions", and later name "positive" and "negative" interactions "mechanisms of species interactions". Here the authors first use "positive interaction" as any type of effect that results in a community-level biomass gain, but then they use "interaction" with reference to specific biological mechanisms (e.g. one species might attract a parasite that infests another species, which in turn may cause further changes that modify the growth of the first and other species).
There are some differences in meaning, but that is what CE and SE have been generally used for. Using different terms can be confusing and does not help understanding the problems with AP.
- on line 70, the authors state that "positive interaction" increases productivity relative to the null expectation, but it is clear that an interaction can have "negative" consequences for one interaction partner and "positive" ones for the other. Therefore, "positive" and "negative" interactions, when defined in this way, cannot be directly linked to "resource partitioning" and "facilitation", and "species interference" as the authors do. Also, these categories of mechanisms are still simple. For example, how do biotic interactions with enemies classify, see above?
We are explaining effects of competitive interactions on species yield, and ultimately on community yield that can be linked to “resource partitioning" and "facilitation", and "species interference".
More specific species interactions require detailed biological investigation and cannot be determined through partitioning of biomass production.
- line 145: "Under the null hypothesis, species in the mixture are assumed to be competitively equivalent (i.e., absence of interspecific interactions)". This is wrong. The assumption is that there are interspecific interactions, but that these are the same as the intraspecific ones. Weirdly, what follows is a description of the AP method, which does not belong here. This paragraph would better be moved to the introduction where the AP method is mentioned. Or omitted, since it is basically a repetition of the original Loreau & Hector paper.
As suggested, “absence of interspecific interactions” was replaced with “equal interspecific and intraspecific interactions”.
We have removed lines 155-162 to reduce duplication. However, our method is based on null expectation that needs to be introduced, despite it is part of AP.
Other points:
- line 66: community productivity, not ecosystem productivity.
Both community productivity and ecosystem productivity are used in biodiversity research, although meaning can be slightly different. Comparatively, ecosystem productivity is more common.
- line 68: community average responses are with respect to relative yields - this is important!
- line 64: what are "species effects of species interactions"?
We searched and did not find “species effects of species interactions”.
- line 90: here "competitive" and "productive" are mixed up, and it is important to state that "suffers more" refers to relative changes, not yield changes.
It, in fact, refers to yield changes. For example, less productive species, at active growth, are more responsive to changes in competition, while more productive species, at inactive growth (i.e., aging), are less responsive to changes in competition.
- line 92: "positive effect of competitive dominance": I don't understand what is meant here.
The phrase was modified to “positive contribution of competitive dominance to ecosystem productivity based on the null expectation”.
Reviewer #3 (Public Review):
Summary:
This manuscript by Tao et al. reports on an effort to better specify the underlying interactions driving the effects of biodiversity on productivity in biodiversity experiments. The authors are especially concerned with the potential for competitive interactions to drive positive biodiversity-ecosystem functioning relationships by driving down the biomass of subdominant species. The authors suggest a new partitioning schema that utilizes a suite of partial density treatments to capture so-called competitive ability. While I agree with the authors that understanding the underlying drivers of biodiversity-ecosystem functioning relationships is valuable - I am unsure of the added value of this specific approach for several reasons.
Strengths:
I can find a lot of value in endeavouring to improve our understanding of how biodiversity-ecosystem functioning relationships arise. I agree with the authors that competition is not well integrated into the complementarity and selection effect and interrogating this is important.
Weaknesses:
(1) The authors start the introduction very narrowly and do not make clear why it is so important to understand the underlying mechanisms driving biodiversity-ecosystem functioning relationships until the end of the discussion.
There are different ways to start introduction; we believe that starting with the problems of the current approach is the most effective for outlining the study’s objective.
(2) The authors criticize the existing framework for only incorporating positive interactions but this is an oversimplification of the existing framework in several ways:
We did not criticize the existing framework for only incorporating positive interactions. We criticize the existing framework, because it is not based on mechanisms of species interactions, but is extensively used to determine underlying mechanisms driving biodiversity-ecosystem functioning relationships.
a. The existing partitioning scheme incorporates resource partitioning which is an effect of competition.
Resource partitioning means that species utilize resources differently, while competition means species use the same resources. “resource partitioning is an effect of competition” is not true in biodiversity experiments that are often short in duration and controlled in conditions.
b. The authors neglect the potential that negative feedback from species-specific pests and pathogens can also drive positive BEF and complementarity effects but is not a positive interaction, necessarily. This is discussed in Schnitzer et al. 2011, Maron et al. 2011, Hendriks et al. 2013, Barry et al. 2019, etc.
We did not. The feedback effect will be reflected in the differences between observed yields and competitive expectations if species in mixtures have different pests and pathogens relative to monocultures. The additive partitioning does not identify these feedback effects either.
c. Hector and Loreau (and many of the other citations listed) do not limit competition to SE because resource partitioning is a byproduct of competition.
Positive SE has been largely interpreted as the result of competition including Hector and Loreau (2001) and many others. It needs to be clear that neither of the additive components can be linked to specific mechanisms of species interactions.
Does “resource partitioning is a byproduct of competition” mean that species change their niche to avoid competition? If this is what the reviewer means, it may occur through long-term evolution, but not in short-term biodiversity experiments. Hector and Loreau (2001) clearly indicated that their complementarity effect includes both resource partitioning and facilitation.
(3) It is unclear how this new measure relates to the selection effect, in particular. I would suggest that the authors add a conceptual figure that shows some scenarios in which this metric would give a different answer than the traditional additive partition. The example that the authors use where a dominant species increases in biomass and the amount that it increases in biomass is greater than the amount of loss from it outcompeting a subdominant species is a general example often used for a selection effect when exactly would you see a difference between the two?:<br /> a. Just a note - I do think you should see a difference between the two if the species suffers from strong intraspecific competition and has therefore low monoculture biomass but this would tend to also be a very low-density monoculture in practice so there would potentially be little difference between a low density and high-density monoculture because the individuals in a high-density monoculture would die anyway. So I am not sure that in practice you would really see this difference even if partial density plots were incorporated.
Linking new measure to SE or CE would be difficult (see many comparisons in Tables and Figures in our manuscript), as SE and CE are derived from mathematical equation and do not represent specific mechanisms of species interactions (Hector and Loreau 2012; Bourrat et al., 2023).
(4) One of the tricky things about these endeavors is that they often pull on theory from two different subfields and use similar terminology to refer to different things. For example - in competition theory, facilitation often refers to a positive relative interaction index (this seems to be how the authors are interpreting this) while in the BEF world facilitation often refers to a set of concrete physical mechanisms like microclimate amelioration. The truth is that both of these subfields use net effects. The relative interaction index is also a net outcome as is the complementarity effect even if it is only a piece of the net biodiversity effect. Trying to combine these two subfields to come up with a new partitioning mechanism requires interrogating the underlying assumptions of both subfields which I do not see in this paper.
Agree, microclimate amelioration is also part of positive effect and will be reflected in the difference between observed yield and competitive expectation. We can not separate the two mechanisms of positive species interactions without investigating influences of microclimate on growth and yield.
(5) The partial density treatment does not isolate competition in the way that the authors indicate. All of the interactions that the authors discuss are density-dependent including the mechanism that is not discussed (negative feedback from species-specific pests and pathogens). These partial density treatment effects therefore cannot simply be equated to competition as the authors indicate.:
We use partial density monoculture to determine maximum competitive growth response, effect of density-dependent intraspecific interactions, and species competitive ability to determine the level of maximum competitive growth response species can achieve in mixtures. There may be changes in species-specific pests and pathogens from partial to full density monocultures, which will be captured in competitive growth responses of individuals. We added at lines 186-188 to indicate that the maximum competitive growth response estimated would also include the effects of density-dependent pests, pathogens, or microclimates.
a. Additionally - the authors use mixture biomass as a stand-in for competitive ability in some cases but mixture biomass could also be determined by the degree to which a plant is facilitated in the mixture (for example).
We used monoculture biomass, not mixture biomass, to assess competitive ability
(6) I found the literature citation to be a bit loose. For example, the authors state that the additive partition is used to separate positive interactions from competition (lines 70-76) and cite many papers but several of these (e.g. Barry et al. 2019) explicitly do not say this.
Barry et al. (2019) defined CE as overproduction from monocultures, an effect of positive interactions.
(7) The natural take-home message from this study is that it would be valuable for biodiversity experiments to include partial density treatments but I have a hard time seeing this as a valuable addition to the field for two reasons:
a. In practice - adding in partial density treatments would not be feasible for the vast majority of experiments which are already often unfeasibly large to maintain.
The reviewer suggested that quantity is more important than quality. Without partial density monocultures no one can separate different effects of species interactions, as suggested by Loreau and Hector, reviewers, and many others that effects of species interactions can not be clearly differentiated with replacement series design. Unreliable scientific findings are not valuable.
b. The density effect would likely only be valuable during the establishment phase of the experiment because species that are strongly limited by intraspecific competition will die in the full-density plots resulting in low-density monocultures. You can see this in many biodiversity experiments after the first years. Even though they are seeded (or rarely planted) at a certain density, the density after several years in many monocultures is quite low.
True. High or low density also depends on individual size; if individuals do not get enough resources, density is high. Therefore, density effect can be strong even as density drops substantially from initial levels.
Reviewer #4 (Public Review):
Summary:
This manuscript claims to provide a new null hypothesis for testing the effects of biodiversity on ecosystem functioning. It reports that the strength of biodiversity effects changes when this different null hypothesis is used. This main result is rather inevitable. That is, one expects a different answer when using a different approach. The question then becomes whether the manuscript’s null hypothesis is both new and an improvement on the null hypothesis that has been in use in recent decades.
It needs to be clear that we use two hypotheses, null hypothesis that is currently used with AP, and competitive hypothesis that is new with this manuscript. The null hypothesis helps determine changes in ecosystem productivity from all species interactions, while the competitive hypothesis helps partition changes in ecosystem productivity by mechanisms of species interactions, i.e., positive, negative, or competitive interactions.
Strengths:
In general, I appreciate studies like this that question whether we have been doing it all wrong and I encourage consideration of new approaches.
Weaknesses:
Despite many sweeping critiques of previous studies and bold claims of novelty made throughout the manuscript, I was unable to find new insights. The manuscript fails to place the study in the context of the long history of literature on competition and biodiversity and ecosystem functioning. The Introduction claims the new approach will address deficiencies of previous approaches, but after reading further I see no evidence that it addresses the limitations of previous approaches noted in the Introduction. Furthermore, the manuscript does not reproducibly describe the methods used to produce the results (e.g., in Table 1) and relies on simulations, claiming experimental data are not available when many experiments have already tested these ideas and not found support for them. Finally, it is unclear to me whether rejecting the ‘new’ null hypothesis presented in the manuscript would be of interest to ecologists, agronomists, conservationists, or others. I will elaborate on each of these points below.
First, there are many biodiversity experiments but those with partial density monocultures are rare. We found only one greenhouse experiment. We have to use simulation to illustrate different scenarios of species interactions to demonstrate how our approach works and how different it is from the AP.
Because of different methods used, the results of long history competition research (generally based on additive series design) cannot be used to define effects of competitive interactions in biodiversity research (generally based on replacement series design). This may be the reason that few competition researchers were cited in Loreau and Hector (2001).
Our approach requires two hypotheses, null and competitive, and the meaning of deviation from these hypotheses are outlined at lines 201-221 for both individual species and community level assessments. Distinguishing changes in ecosystem productivity by species interactions would be of great interest to “ecologists, agronomists, conservationists, or others”.
The critiques of biodiversity experiments and existing additive partitioning methods are overstated, as is the extent to which this new approach addresses its limitations. For example, the critique that current biodiversity experiments cannot reveal the effects of species interactions (e.g., lines 37-39) isn't generally true, but it could be true if stated more specifically. That is, this statement is incorrect as written because comparisons of mixtures, where there are interspecific and intraspecific interactions, with monocultures, where there are only intraspecific interactions, certainly provide information about the effects of species interactions (interspecific interactions). These biodiversity experiments and existing additive partitioning approaches have limits, of course, for identifying the specific types of interactions (e.g., whether mediated by exploitative resource competition, apparent competition, or other types of interactions). However, the approach proposed in this manuscript gets no closer to identifying these specific mechanisms of species interactions. It has no ability to distinguish between resource and apparent competition, for example. Thus, the motivation and framing of the manuscript do not match what it provides. I believe the entire Introduction would need to be rewritten to clarify what gap in knowledge this proposed approach is addressing and what would be gained by filling this knowledge gap.
Our approach helps determine underlying mechanisms of species interactions, i.e., positive (resources partitioning or facilitation), negative, or competitive interactions. I am not sure how much we need to go further in identifying more specific mechanisms. If resource and apparent competition refers to resource and interference competition, our approach can tease apart them.
I recommend that the Introduction instead clarify how this study builds on and goes beyond many decades of literature considering how competition and biodiversity effects depend on density. This large literature is insufficiently addressed in this manuscript. This fails to give credit to previous studies considering these ideas and makes it unclear how this manuscript goes beyond the many previous related studies. For example, see papers and books written by de Wit, Harper, Vandermeer, Connolly, Schmid, and many others. Also, note that many biodiversity experiments have crossed diversity treatments with a density treatment and found no significant effects of density or interactions between density and diversity (e.g., Finn et al. 2013 Journal of Applied Ecology). Thus, claiming that these considerations of density are novel, without giving credit to the enormous number of previous studies considering this, is insufficient.
A misunderstanding here. Our approach is not designed to test density effect. The same density is held across full density monocultures and mixtures. We use partial density monocultures to determine what species may competitively achieve in full density mixture, without positive or negative interspecific interactions.
Replacement series designs emerged as a consensus for biodiversity experiments because they directly test a relevant null hypothesis. This is not to say that there are no other interesting null hypotheses or study designs, but one must acknowledge that many designs and analyses of biodiversity experiments have already been considered. For example, Schmid et al. reviewed these designs and analyses two decades ago (2002, chapter 6 in Loreau et al. 2002 OUP book) and the overwhelming consensus in recent decades has been to use a replacement series and test the corresponding null hypothesis.
Some wrong impressions. We are not trying to supplant “replacement series” with “additive series”; we use “additive series” designs to supplement “replacement series” design for partitioning changes in ecosystem productivity by mechanisms of species interactions, which would not be possible with “replacement series” design alone, as suggested by many including reviewers.
It is unclear to me whether rejecting the 'new' null hypothesis presented in the manuscript would be of interest to ecologists, agronomists, conservationists, or others. Most biodiversity experiments and additive partitions have tested and quantified diversity effects against the null hypothesis that there is no difference between intraspecific and interspecific interactions. If there was no less competition and no more facilitation in mixtures than in monocultures, then there would be no positive diversity effects. Rejecting this null hypothesis is relevant when considering coexistence in ecology, overyielding in agronomy, and the consequences of biodiversity loss in conservation (e.g., Vandermeer 1981 Bioscience, Loreau 2010 Princeton Monograph). This manuscript proposes a different null hypothesis and it is not yet clear to me how it would be relevant to any of these ongoing discussions of changes in biodiversity.
Our method begins with the null expectation: that intraspecific and interspecific interactions are equivalent. We then propose the competitive hypothesis as a second non-exclusive hypothesis which tests the dominance of positive or negative specific interactions. As shown by its name, the additive partitioning model has been advocated for partitioning biodiversity effects by some ecological mechanisms (CE and SE). The ecological meaning of deviation from the two hypotheses are outlined at lines 201-221 for both individual species and community level assessments.
The claim that all previous methods 'are not capable of quantifying changes in ecosystem productivity by species interactions and species or community level' is incorrect. As noted above, all approaches that compare mixtures, where there are interspecific interactions, to monocultures, where there are no species interactions, do this to some extent. By overstating the limitations of previous approaches, the manuscript fails to clearly identify what unique contribution it is offering, and how this builds on and goes beyond previous work.
The reviewer implies that a partial truth equals the whole truth. The same argument can also be applied to the additive partitioning if relative yield total or response ratio provides a kind of comparison between mixture and monocultures. Our statement is correct in the way that previous approaches are not designed to separate changes in ecosystem productivity by species interactions, as indicated by other reviewers. The additive partitioning is built on Price equation (covariance equation) that has never been biologically demonstrated for relevance in biodiversity partitioning (Bourrat et al., 2023).
We made clear that our work is built on and beyond the null expectation with addition of competitive expectation.
The manuscript relies on simulations because it claims that current experiments are unable to test this, given that they have replacement series designs (lines 128-131). There are, however, dozens of experiments where the replacement series was repeated at multiple densities, which would allow a direct test of these ideas. In fact, these ideas have already been tested in these experiments and density effects were found to be nonsignificant (e.g., Finn et al. 2013).
Out of point. Again, we are not testing density effect. Partial density is used to determine competitive growth responses that species may achieve in mixture based on their relative competitive ability. We used simulations, as partial density monocultures are used only in one experimental study that has been included in our study.
It seems that the authors are primarily interested in trees planted at a fixed density, with no opportunity for changes in density, and thus only changes in the size of individuals (e.g., Fig. 1). In natural and experimental systems, realized density differs from the initial planted density, and survivorship of seedlings can depend on both intraspecific and interspecific interactions. Thus, the constrained conditions under which these ideas are explored in this manuscript seem narrow and far from the more complex reality where density is not fixed.
We use fixed density only for convenience. In biodiversity experiments, density can increase or decrease over time from initial levels. However, initial density is generally used in evaluation of species interactions. If interest is community productivity, density change does not need to be considered. Again, we are not testing density effects.
Additional detailed comments:
It is unclear to me which 'effects' are referred to on line 36. For example, are these diversity effects or just effects of competition? What is the response variable?
It means the effect of competitive interactions on productivity and should be clear based on previous sentences.
The usefulness of the approach is overstated on line 52. All partitioning approaches, including the new one proposed here, give the net result of many types of species interactions and thus cannot 'disentangle underlying mechanisms of species interactions.'
Not sure how many types of species interactions the reviewer referred to. If mechanisms of species interactions are grouped in three categories (positive, negative, and competitive) as has been in biodiversity research, our approach can tease them apart.
The weaknesses of previous approaches are overstated throughout the manuscript, including in lines 60-61. All approaches provide some, but not all insights. Sweeping statements that previous approaches are not effective, without clarifying what they can and can't do, is unhelpful and incorrect. Also, these statements imply that the approach proposed here addresses the limitations of these previous approaches. I don't yet see how it does so.
The weaknesses of previous approaches are not overstated in terms of separating changes in ecosystem productivity by species interactions. As pointed by other reviewers, none of the previous approaches are designed for quantifying changes in ecosystem productivity by species interactions.
The definitions given for the CE and SE on line 71 are incorrect. Competition affects both terms and CE can be negative or have nothing to do with positive interactions, as noted in many of the papers cited.
We are not trying to define CE and SE but only point out how CE and SE have been generally used in biodiversity research (see recent publication by Feng et al., 2022).
The proposed approach does not address the limitations noted on lines 73 and 74.
It does in terms of sources of net biodiversity effect, whether from positive, negative or competitive interactions.
The definition of positive interactions in lines 77 and 78 seems inconsistent with much of the literature, which instead focuses on facilitation or mutualism, rather than competition when describing positive interactions.
Much of the literature supports our definition (see Loreau and Hector, 2001). In biodiversity research, positive interactions include resource partitioning and facilitation. What we are trying to point out is that competition affects species and community level assessments based on the null expectation and needs to be separated.
Throughout the manuscript, competition is often used interchangeably with resource competition (e.g., line 82) and complementarity is often attributed to resource partitioning (e.g., line 77). This ignores apparent competition and partitioning enemy-free niche space, which has been found to contribute to biodiversity effects in many studies.
If apparent competition refers to interference competition, it is included in negative interaction. Changes in species-specific pests and pathogens in mixture will be captured in positive or negative effects through facilitation or interference.
In what sense are competitive interactions positive for competitive species (lines 82-83)? By definition, competition is an interaction that has a negative effect. Do you mean that interspecific competition is less than intraspecific competition? I am having a very difficult time following the logic.
I am glad the reviewer raised this question that may confuse many others and has never been clearly discussed. It all depends on how comparison is made. If species performance in mixture are compared with that in partial density monocultures, as is in competition research, competition effect is negative for all species. If comparison is made between mixture and full density monocultures, as is done in biodiversity research, competition effect should be positive for more competitive species and negative for less competitive species, with resources flowing from less to more competitive species in mixture relative to full density monocultures.
Therefore, the definitions of competitive interactions based on additive series design in competition research cannot be used to describe competitive interactions based on replacement series design in biodiversity research. In biodiversity research, the effects of competitive interactions are never clearly defined at species or community level and mixed up with those of other species interactions.
Results are asserted on lines 93-95, but I cannot find the methods that produced these results. I am unable to evaluate the work without a repeatable description of the methods.
We have added references on sources of these data.
The description of the null hypothesis in the common additive partitioning approach on lines 145-146 is incorrect. In the null case, it does not assume that there are no interspecific interactions, but rather that interspecific and intraspecific interactions are equivalent.
Correct, changes have been made as suggested.
Recommendations for the authors:
Reviewer #2 (Recommendations For The Authors):
I recommend to:
- re-organize the presentation of the material (see my concerns in the public review section). The manuscript is very difficult to read.
Changes have been made to help with understanding of our approach. Figure 1 was modified to show the variations of competitive growth response with relative competitive ability from minimum (null expectation) to maximum (competitive exclusion).
- explore the mathematical form the the remainder term. It seems important to understand that the remainder capture terms unrelated to competition as defined in the present scope.
The remainder measures deviations from the null expectation, due to species differences in growth and competitive ability or competition effect. The term has clear meaning, positive for more competitive species and negative for less competitive species (lines 202-204), and does not need to be further explored or partitioned. The deviations of observed yields from competitive expectations are outlined in lines 205-221.
Reviewer #4 (Recommendations For The Authors):
The authors should be sure to include reproducible methods and share any data and code.
Both simulation and experimental data are shared through supplementary tables. Calculations are included in excel spreadsheets and do not require program coding.
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
The study by Chikermane and colleagues investigates the functional, structural, and dopaminergic network substrates of cortical beta oscillations (13-30 Hz). The major strength of the work lies in the methodology taken by the authors, namely a multimodal lesion network mapping. First, using invasive electrophysiological recordings from healthy cortical territories of epileptic patients they identify regions with the highest beta power. Next, they leverage open-access MRI data and PET atlases and use the identified high-beta regions as seeds to find (1) the whole-brain functional and structural maps of regions that form the putative underlying network of high-beta regions and (2) the spatial distribution of dopaminergic receptors that show correlation with nodal connectivity of the identified networks. These steps are achieved by generating aggregate functional, structural, and dopaminergic network maps using lead-DBS toolbox, and by contrasting the results with those obtained from high-alpha regions.
The main findings are:
(1) Beta power is strongest across frontal, cingulate, and insular regions in invasive electrophysiological data, and these regions map onto a shared functional and structural network. (2) The shared functional and structural networks show significant positive correlations with dopamine receptors across the cortex and basal ganglia (which is not the case for alpha, where correlations are found with GABA).
Nevertheless, a few clarifications regarding the choice of high-power electrodes and distributions of functional connectivity maps (i.e., strength and sign across cortex and sub-cortex) can help with understanding the results.
We thank the reviewer for this critical expert assessment.
Reviewer #1 (Recommendations For The Authors):
To potentially enhance the quality of the manuscript in the current version, I kindly ask the authors to address the following points:
Major:
(A) Power analysis of electrophysiological data
(1) How were significant peaks identified exactly? I understand that the authors used FOOOF methodology to estimate periodic components of brain activity.
Thank you for pointing us to this lack of clarity. The application of FOOOF consists of the fitting of a one-over-f curve that delineates the aperiodic component followed by the definition of gaussians to fit periodic activity. This allows for extraction of periodic peak power estimates that are corrected for offset and exponent of the one-over-f or non-oscillatory aperiodic component in the spectrum (further information can be found here https://fooof-tools.github.io/fooof/auto_tutorials/plot_02-FOOOF.html). We included all peaks that could be fitted using the process.
How about aperiodic components (Figure 1, PSD plots)?
We share the interest in aperiodic activity with the reviewer. However, given that the primary aim of this study was the description of beta oscillations and the methodology and results presentation is already very complex, we did not include the analysis of aperiodic activity in this manuscript. This could be done in the future and it would surely be interesting to visualize the whole brain connectomic fingerprints of aperiodic exponent and offset. With regard to the purely anatomical description of nonoscillatory aperiodic activity we would like to refer to Figure 8 in Frauscher et al. Brain 2018 (https://doi.org/10.1093/brain/awy035) where this is described. We have decided not to include additional information on this matter, because a) we felt that this would further convolute the results and discussion without directly addressing any of the hypotheses and aims that we set out to tackle and b) the interpretation of aperiodic activity is still a matter of intense research with conflicting results, which warrants very careful considerations of many aspects that again would go beyond the scope of this paper.
In addition, to what degree would the results change if one identified the peaks relative to sites with no peak, similar to Frauscher et al.
Beta activity, the oscillation of interest in our analysis is ubiquitous in the brain. In fact, of 1772 channels, only 21 channels did not exhibit a beta peak detectable with FOOOF. Thus, a comparison of 1751 against 21 would not yield meaningful results. We have therefore decided to focus on the channels in which beta activity is the strongest and dominant observable oscillation.
If the FOOOF approach has some advantages, these should be pointed out or discussed.
FOOOF indeed has the advantage that it provides an objective and reproducible estimation of peak oscillatory activity that accounts for differences in aperiodic activity. To the best of our knowledge, there is no other approach that is nearly as well documented, validated and computationally reproducible.
Changes in manuscript: We have now further clarified the definition of peak amplitudes in the results and methods section and have discussed the use of alternative measures in the limitations section of our manuscript.
Results: “The frequency band with the highest peak amplitude was identified using the extracted peak parameter (pw) for each channel and depicted as the dominant rhythm for the respective localisation (Figure 1).”
Methods: “Peak height was extracted using the pw parameter, which depicts peak amplitude after subtraction of any aperiodic activity.”
Discussion: “Alternative approaches could yield different results, e.g. reusing channels for each peak that is observable and contrasting them to channels where such peak was not present. However, in our study the majority of channels exhibited beta activity, even if peaks were of low amplitude, which we believe would have led to less interpretable results.”
(2) How exactly do the authors deal with channels with more than one peak? Some elaboration on this and how this could potentially impact the results would be appreciated. Sorry if I have missed it.
Indeed, a description of this was lacking so we are very thankful that the reviewer pointed this out. The maximum peak amplitude method was a winner-takes-all approach where in the case of multiple peaks, the peak with the higher amplitude was chosen. This method of course has drawbacks in the form of lost or disregarded peaks and remains a limitation to this study.
Changes in manuscript: We have now clarified this in the methods and results sections, which now read:
Methods: “In case of multiple peaks within the same region, we used only the highest peak amplitude.”
Results: “In case of multiple peaks within the same frequency band, we focused the analysis on the peak with the highest amplitude.”
And added the following to the Limitations section of the discussion:
“Another limitation in our study is the fact that the statistical approach for the comparison of beta and alpha networks and even for multiple peaks within the same frequency band follows a winner takes all logic that is, by definition, a simplification, as most areas will contribute to more than one spatiospectrally distinct oscillatory network. Specifically, while multiple peaks within or across frequency bands could be present in each channel, we decided to allocate this channel to only the frequency band containing the highest peak amplitude.”
(B) Network mapping
(1) Knowing that fMRI data are preprocessed by regressing the global signal, there are negative correlations across the functional networks. Unfortunately, the distribution, sign, and strength of the correlations are not quantitatively shown in any of the plots. Thus, it is unclear whether, e.g., corticocortical vs. subcortico-cortical correlations differ in strength and/or sign. I think this additional information is important for better understanding the up/down-regulation of beta, e.g., by DA signaling. Some discussion around this point in addition would be insightful, I think.
The referee is touching upon a very important and difficult point, which we have considered very carefully. Global signal regression is a controversial topic and the neurophysiological basis of negative correlations remains to be elucidated. We can justify our use of this approach based on an expert consensus described in Murphy & Fox 2017 (https://doi.org/10.1016%2Fj.neuroimage.2016.11.052), which highlights that global signal regression can improve the specificity of positive correlations, improve the correspondence to anatomical connectivity. The truth however is that, we relied on it, because it is the more commonly used and validated approach used in lesion network and DBS connectivity mapping and implemented in the Lead Mapper pipeline. Indeed all connectivity estimates are shown in Supplementary figure 3. We remain hesitant to raise the focus to these points, because of the uncertain underlying neural correlates. However, when looking at the values, it is interesting to note that most key regions of interest exhibit positive connectivity values.
Changes in manuscript: We now point to the supplement containing all connectivity values in the results section more prominently: “All connectivity values including their sign are shown in figures as brain region averages parcellated with the automatic anatomical labelling atlas in supplementary figures 2&3.”
(2) I assume no thresholding is applied to the functional connectivity maps (in a graph-theoretical sense). Please clarify (this is also related to the comment above, in particular, the strength of correlations.
Indeed, we demonstrate SPM maps using family wise error corrected stats in figure 2, but all further analyses were performed on unthresholded maps as correctly pointed out by the referee.
Changes in manuscript:
Results: “Specifically, we analysed to what degree the spatial uptake patterns of dopamine, as measurable with fluorodopa (FDOPA; cohort average of 12 healthy subjects) and other dopamine signalling related tracers that bind D1/D2 receptors (average of N=17/44 respectively healthy subjects) or the dopamine transporter (DAT; cohort average of N=180 healthy subjects) were correlated with the unthresholded MRI connectivity maps.”
Methods: “This parcellation was applied to both PET and unthresholded structural and functional connectivity maps using SPM and custom code.”
Minor
(1) Methods, Connectivity analysis: The description of (mass-univariate) GLM analysis is confusing. The maps underwent preprocessing? Which preprocessing steps are meant here? What is the dependent variable and what are the predictors exactly?
We thank the reviewer for catching this error in our methods. We apologise for the confusion and mistake and thank the reviewer for catching it. Indeed, we have used t-tests without further preprocessing instead of a GLM.
Changes in manuscript: The respective section has been removed from the methods section and intermediate steps have been clarified. The section now reads: “To investigate differences between beta dominant and alpha dominant functional connectivity networks, a two sample t-test was calculated for the condition where beta was greater than alpha and vice versa using SPM. Here, the connectivity maps from each dominant channel (1005 beta functional connectivity maps and 397 alpha connectivity maps) Estimation of model parameters yielded t-values for each voxel, indicating the strength and direction of differences between the two contrasts (beta > alpha, alpha > beta). To address the issue of multiple comparisons, we applied Family-Wise Error (FWE) correction, adjusting significance thresholds such that only voxels with p < 0.05 would be included.”
(2) I encourage the authors to find a better (visual) way of reporting Table 1, to make the main observations easier to grasp and compare (maybe a two-dimensional bar plot? Or color-coding the cells?)
Reply: Thank you for your suggestion to improve the table, the new table is adjusted to the recommended changes to make it more readable.
Reviewer #2 (Public Review):
Summary:
This is a very interesting paper that leveraged several publicly available datasets: invasive cortical recording in epilepsy patients, functional and structural connectomic data, and PET data related to dopaminergic and gaba-ergic synapses. These were combined to create a unified hypothesis of beta band oscillatory activity in the human brain. They show that beta frequency activity is ubiquitous, not just in sensorimotor areas, and cortical regions where beta predominated had high connectivity to regions high in dopamine re-uptake.
Strengths:
The authors leverage and integrate three publicly available human brain datasets in a creative way. While these public datasets are powerful tools for human neuroscience, it is innovative to combine these three types of data into a common brain space to generate novel findings and hypotheses. Findings are nicely controlled by separately examining cortical regions where alpha predominates (which have a different connectivity pattern). GABA uptake from PET studies is used as a control for the specificity of the relationship between beta activity and dopamine uptake. There is much interest in synchronized oscillatory activity as a mechanism of brain function and dysfunction, but the field is short on unifying hypotheses of why particular rhythms predominate in particular regions. This paper contributes nicely to that gap. It is ambitious in generating hypotheses, particularly that modulation of beta activity may be used as a "proxy" for modulating phasic dopamine release.
Weaknesses:
As the authors point out, the use of normative data is excellent for exploring hypotheses but does not address or explore individual variations which could lead to other insights. It is also biased to resting state activity; maps of task-related activity (if they were available) might show different findings.
The figures, results, introduction, and methods are admirably clear and succinct but the discussion could be both shorter and more convincing.
Reviewer #2 (Recommendations For The Authors):
The tone of the discussion is excessively lofty and abstract, and hard to follow in places. Specific examples in comments to authors below.
We thank the reviewer for their positive assessment and their constructive feedback on the discussion. Also in light of the other reviewers we have made a sincere effort to shorten, restructure and improve the discussion. Additionally, we have addressed all the specific comments the reviewer had below. We appended each change to the manuscript where appropriate below and have addressed all comments in the main text. Having that said, we see this paper and discussion to provide our most up-to-date and personal perspective on a correct concept on the interplay of beta oscillations and dopamine that is generalizable. Providing a concept that is so generalizable is very challenging and so far very few authors have even attempted this. One notable exception is the “status quo” concept by Fries & Engel. While we will do our very best to address the comments, we have decided not to deviate from our initial ambition to provide a discussion on a generalizable concept. Naturally such a concept must be very complex and therefore it will be hard to understand in parts. Through the revision, we hope that the readability and comprehensibility has improved, while it provides an in-depth perspective and hypothesis on how beta oscillations, dopamine and their brain circuits may facilitate brain function. Nevertheless, we want to express our honest gratitude for the thoroughness with which the reviewer has read and scrutinized our paper. The review clearly tells that the reviewer had the ambition to follow and understand what we were trying to convey, which can be rare nowadays. We are truly thankful for this.
The first sentence is not quite true, as invasive neurophysiology was not, and cannot be, done in healthy humans. "The present study combined three openly available datasets of invasive neurophysiology, MRI connectomics, and molecular neuroimaging in healthy humans to characterise the spatial distribution of brain regions exhibiting resting beta activity, their shared circuit architecture, and its correlation with molecular markers of dopamine signaling in the human brain."
Changes in manuscript: We have now removed the “healthy” from the respective sentence.
"Our results motivate to conceptualise the capacity to generate.... This is not clear.
Changes in manuscript: “Our results suggest that one common denominator of brain regions that generate beta activity, is their affiliation with beta oscillations as a feature that arises from a largescale global brain network that is modulated by dopamine.”
"Similarly, the robust beta modulation that is elicited by voluntary action in sensorimotor cortex and its correlation with motor symptoms of Parkinson's disease is long known" - the association between movement-related cortical beta desynchronization and Parkinson's motor signs is not well described - could the authors specify and reference this?
We thank the reviewer for pointing out this lack of clarity. We meant that independently beta is known for “movement” and for “movement disorders” and not “movement in movement disorders”. Having that said, there are some studies that suggest that beta ERD is altered in PD (e.g.https://doi.org/10.1093/cercor/bht121), but saying that this is “long known” would be an overstatement and was not our intention. We rephrased this sentence accordingly.
Changes in manuscript: The sentence now reads: “Moreover, the robust beta modulation that is elicited by voluntary action in sensorimotor cortex and its correlation with motor symptoms of Parkinson’s disease is long known.”
"...first fast-cyclic voltammetry experiments that allowed for combined measurement of dopamine release with invasive neurophysiology have provided first evidence that beta band oscillations in healthy non-human primates can differentially link dopamine release, beta oscillations and reward and motor control, depending on the contextual information and striatal domain" - This is not very clear - not sure what "differentially link" signifies.
I think the fact that this is not easy to understand signifies the complexity that we and the authors of the cited paper from Ann Graybiel’s lab aimed to communicate. In fact, we stayed very close to the phrasing used in their paper to try and avoid confusion (Title: Dopamine and beta-band oscillations differentially link to striatal value and motor control” - https://doi.org/10.1126/sciadv.abb9226). The specific results go beyond the scope of the discussion but are very interesting, so I would be happy if our paper would inspire readers to look it up.
Changes in manuscript: We have now adapted the sentence to “In line with this more complex picture, direct measurement of dopamine concentration in non-human primates revealed specific interactions between dopamine release, beta oscillations, reward value and motor control, depending on contextual information and striatal domain. This shows that the relationship of dopamine and beta activity is not solely associated with either reward or movement and depends on where in the striatum beta activity is recorded.”
"In fact, one could argue that it can be contextualised in a recently described framework of neural reinforcement, that serves to orchestrate the re-entrance and refinement of neural population dynamics for the production of neural trajectories" - this is not clear - for example what is a neural trajectory? What is meant by "re-entrance and refinement"?
A neural trajectory refers to the path that the activity of a neural population takes through a high-dimensional space over time. It can be obtained through multivariate analysis of population activity with dimensionality reduction techniques, such as PCA. The concept of low-dimensional representations of high-dimensional neural activity has gained a lot of attention in computational neuroscience ever since high-channel count recordings of neural population activity have become available (an early and prominent example is Churchland et al., 2012 Nature https://doi.org/10.1038/nature11129 , while a more recent example is Safaie et al., Nature 2023 https://doi.org/10.1038/s41586-023-06714-0). The review we refer to by Rui Costa and colleagues (Athalye, V. R., Carmena, J. M. & Costa, R. M. Neural reinforcement: re-entering and refining neural dynamics leading to desirable outcomes. Curr Opin Neurobiol 60, 145–154 (2020) https://doi.org/10.1016/j.conb.2019.11.023) suggests that dopamine may serve to modulate the likelihood of a specific pattern to emerge and re-enter the cortex – basal ganglia loop, for the “reliable production of neural trajectories driving skillful behavior on-demand”. We believe that this concept could be revolutionary in our understanding of dopaminergic modulation and disoroders and together with colleague Alessia Cavallo have written an invited perspective on this topic (https://doi.org/10.1111/ejn.16222), which may help further clarify the topic.
Changes in manuscript: We realize that this aspect may sound a bit unclear or far away from the data in this manuscript. However, given that we have spent more than a decade thinking about beta oscillations and how they can be conceptualized, we would prefer not to entirely change our points and rather bet on the possibility that the concepts become more widely accepted and well-known. Nevertheless, we have now adapted the text to make this a bit more clear:
“We hypothesise that, this “status quo” hypothesis could be equally or maybe even more adequately posed on the neural level. Namely, it could provide insights to what degree a certain activity pattern or synaptic connection is to be strengthened or weakened, in light of neural learning. We propose that this putative function can be contextualised in a recently described framework of neural reinforcement, that serves to orchestrate the re-entrance and refinement of neural population dynamics for the production of neural trajectories.”
"....after which it was quickly translated to first experimental studies using cortical or subcortical beta signals in human patients44." - reference 44 only deals with the use of subcortical beta, not cortical, in adaptive control.
The reviewer is right, in fact there is no study using motor cortex beta for adaptive DBS yet, but different studies have used different markers (especially gamma) since then.
Changes in manuscript: We have rephrased and added citations accordingly: “This approach, also termed adaptive DBS, was first demonstrated based on cortical beta activity that was used to adapt pallidal DBS in the MPTP non-human primate model of PD43. It was quickly translated to first experimental studies using subcortical beta signals in human patients44, followed by further research using more complex cortical and subcortical sensing setups and biomarker combinations45,46.”
The paragraph headed " Implications for neurotechnology" is quite long and should be condensed and focused. It doesn't seem to support the last sentence, "....targeted interventions that can increase and decrease beta activity, as recently shown through phase specific modulation45 could be utilised to mimic phasic dopamine release as a neuroprosthetic approach to alter neural reinforcement38." - I don't quite follow the logic. The authors have clearly shown that beta-related circuits tend to be those linked to dopamine modulation, and may subserve tasks for which reinforcement learning is an important mechanism. However the logic of how modulation of beta activity can "substitute" for modulation of dopamine isn't clear. That would seem to require that the mechanism by which dopamine produces reinforcement, is via an effect on beta oscillation properties (phase, amplitude, frequency). Is there evidence for this? If so it should be better spelled out.
We realize that this is very speculative at this point. Indeed, we believe that subthalamic DBS can mimic dopaminergic control and in the future there may be new treatment avenues, e.g. using neurochemical using neurochemical interfaces for which beta could be informative to mimic dopamine release but ultimately explaining this would be very complex, so we have removed the sentence. With regard to the remaining text in the section, we considered shortening / condensing but felt that this paragraph is highly relevant for the ongoing development of neurotechnology and therefore decided to only remove the first and last sentences.
Changes in manuscript: We have removed the first and last sentences.
"While the abovementioned prospects are promising we should cautiously consider the limitations of our study." - an unnecessary sentence to start a "limitations" section, its clearly a paragraph about limitations. In general, authors should go thru discussion and reduce verbosity; it is not nearly as well edited as the rest of the paper.
Agreed.
Changes in manuscript: We removed the sentence.
Reviewer #3 (Public Review):
Summary:
In this paper, Chikermane et al. leverages a large open dataset of intracranial recordings (sEEG or ECoG) to analyze resting state (eyes closed) oscillatory activity from a variety of human brain areas. The authors identify a dominant proportion of channels in which beta band activity (12-30Hz) is most prominent and subsequently seek to relate this to anatomical connectivity data by using the sEEG/ECoG electrodes as seeds in a large set of MRI data from the human connectome project. This reveals separate regions and white matter tracts for alpha (primarily occipital) and beta (prefrontal cortex and basal ganglia) oscillations. Finally, using a third available dataset of PET imaging, the authors relate the parcellated signals to dopamine signaling as estimated by spatial uptake patterns of dopamine, and reveal a significant correlation between the functional connectivity maps and the dopamine reuptake maps, suggesting a functional relationship between the two.
Strengths:
Overall, I found the paper well justified, focused on an important topic, and interesting. The authors' use of 3 different open datasets was creative and informative, and it significantly adds to our understanding of different oscillatory networks in the human brain, and their more elusive relation with neuromodulator signaling networks by adding to our knowledge of the association between beta oscillations and dopamine signaling. Even my main comments about the lack of a theta network analysis and discussion points are relatively minor, and I believe this paper is valuable and informative.
Weaknesses:
The analyses were adequate, and the authors cleverly leveraged these different datasets to build an interesting story. The main aspect I found missing (in addition to some discussion items, see below) was an examination of the theta network. Theta oscillations have been involved in a number of cognitive processes including spatial navigation and memory, and have been proposed to have different potential originating brain regions, and it would be informative to see how their anatomical networks (e.g. as in Figure 2) look like under the author's analyses.
The authors devote a significant portion of the discussion to relating their findings to a popular hypothesis for the function of beta oscillations, the maintenance of the "status quo", mostly in the context of motor control. As the authors acknowledge, given the static nature of the data and lack of behavior, this interpretation remains largely speculative and I found it a bit too far-reaching given the data shown in the paper. In contrast, I missed a more detailed discussion on the growing literature indicating a role for beta in mood (e.g. in Kirkby et al. 2018), especially given the apparent lack of hippocampal and amygdala involvement in the paper, which was surprising.
We thank the reviewer for their insightful review of our manuscript. One of the aims of our paper was to provide the ground for a circuit-based conceptualization of beta activity, which does not primarily relate to behavior. Practically we have the ambition to provide a generalizable concept that can be applied to all behavioral domains including mood. The reason we focus on the “status quo” hypothesis, is that it is one of the very few if not only generalizable concept of the function of beta oscillations. Through our paper and the discussion, we have to redirect this concept towards a less cognitive/behavioral and more anatomical network based domain, while acknowledging principles that may overlap. We realize that this is very ambitious and this endeavour is necessarily very complex and not easy to communicate. In light of the reviewers comments, we have made an effort to improve the discussion as best we could without trailing too far away from what our initial aim was. We are thankful for the suggested reference, which we have now added to the discussion in the section where we have previously discussed beta as biomarker for mood, also noting the absence of beta dominant channels in amygdala and hippocampus. Here it should be clarified however, that a) only three channels were located in the amygdala of which one exhibited beta activity, we should be cautious to not overinterpret this result and b) most channels exhibited beta and just because beta wasn’t dominant, it doesn’t mean that beta is not present or important in these brain areas. Absence of evidence is not evidence for absence with the way we approached the analysis. We are thankful for the interesting reference, which we have now included our discussion. Notably the study used a complex network analysis, which we could not perform because we did not have parallel recordings from these areas in multiple patients. This is now noted in the limitations.
Changes in manuscript: “For example, it was shown that beta is implicated in working memory28, utilisation of salient sensory cues29, language processing30, motivation31, sleep32, emotion recognition33, mood34 and may even serve as a biomarker for depressive symptom severity in the anterior cingulate cortex35” and “One impactful study reported that beta oscillatory sub-networks of Amygdala and hippocampus could reflect human variations in mood 34. This is interesting, but highlights another relevant limitation of our study, namely that recordings in different areas were stemming from different patients and thus, such sub-network analyses on the oscillatory level could not be conducted.”
Major comment:
• Although the proportion of electrodes with theta-dominant oscillations was lower (~15%) than alpha (~22%) or beta (~57%), it would be very valuable to also see the same analyses the authors carried out in these frequency bands extended to theta oscillations.
We agree with the reviewer and appreciate the interest in other frequency bands; theta, alpha and gamma. Our primary interest was to provide a network concept of beta activity, but anticipated that interest would go beyond that frequency band. However, we also had to limit ourselves to what is communicable and comprehensible. The key aim for us was to provide a data-driven circuit description of beta activity that can lay ground for a generalizable concept of where beta oscillations emerge. Reproducing all analyses for every frequency band would clutter both the results and the discussion. Moreover, the honest truth is that funding and individual career plans of the researchers currently do not allow to allocate time for a reanalysis of all data which would be a significant effort. Therefore, we have decided to just add the topography of theta and gamma channels as a supplement. In case the reviewer is interested on a collaboration on extending this project to other frequency bands and circuits, we would like to invite them to get in touch and perhaps this could be a new collaborative project. Until then, we have extended our limitation that this would be important work for the future.
Changes in manuscript:
We have added and cited the new supplementary figure for the results from theta in the results section, which now reads:
“Further information on the topography of theta channels are shown in supplementary figure 1.”
We would like to add that a sensible interpretation of results from gamma dominant channels is unlikely to be possible given the low count of channels with prominent resting activity in this frequency band. We have added the following text to the limitations section: “The aim of this study was to elucidate the circuit architecture of beta oscillations, which is why insights from this study for other frequency bands are limited. Future research investigating the specific circuits of theta, alpha and gamma oscillations and their relationship with neurotransmitter uptake could yield new important insights on the networks underlying human brain rhythms.“
Reviewer #3 (Recommendations For The Authors):
Minor comments:
• Results: "we performed non-parametric Spearman's correlations between the structural and functional connectivity maps of beta networks with neurotransmitter uptake". This is a significantly complex analysis that requires more detail for the reader to evaluate. There is more detail in the Figure 3 legend but still insufficient. The Methods offer more detail, but I found the description of the parcellation to be vague and I would appreciate a more detailed description.
We thank the reviewer for bringing the insufficient explanation of the methods used to calculate the correlations in analysis to our attention. We have now made an effort to provide more level of detail in the relevant paragraphs.
Changes in manuscript: We have now made changes to both the Results and Methods sections and added the following explanations respectively:
Results: “Next, we resliced the beta network map and the PET images to allow for a meaningful comparison, using a combined parcellation with 476 brain regions that include cortex19, basal ganglia20, and cerebellum21. Here, each parcel – which was a collection of voxels belonging to a particular brain region – from the connectivity map was correlated with the same parcel containing average neurotransmitter uptake from the respective PET scan (see Figure 3A). In this way nonparametric Spearman’s correlations between PET intensity and structural and functional connectivity maps of beta networks were obtained, which indicate to what degree the spatial distribution of connectivity is similar to the distribution of neurotransmitter uptake.“
Methods: “A custom master parcellation in MNI space was created in Matlab using SPM functions by combining three existing parcellations to include cortical regions19, structures of the basal ganglia20 and cerebellar regions21. Regions that were (partially) overlapping between the atlases were only selected once. The final compound parcellation had 476 regions in total. This parcellation was applied to both PET and structural and functional connectivity maps using SPM and custom code. This allowed for the calculation of spatial correlations, providing a statistical measure of spatial similarity of the PET intensity and MRI connectivity distributions. For this, Spearman’s ranked correlations were used to calculate correlations between the PET images, such as the dopamine aggregate map and both functional and structural beta connectivity networks (Figure 3). The analysis was repeated for individual tracers showing similar results Supplementary figure 2. Finally, to validate these results, a control analysis was performed using a GABA PET scan from the same open dataset of neurotransmitter uptake following the same pipeline (Figure 2A, 2B).”
• All of the recordings were taken in an eyes-closed condition. This is likely to affect the power of alpha oscillations; the authors should comment on this.
We agree with the reviewer that this will likely have influenced the results. However, given that the key result of our paper is the abundance and circuit topography of beta oscillations, it is unlikely that increased alpha in some channels will have led to false positive results for beta. If anything, it may have increased the contrast leading to a more conservative estimate of which channels truly show strong beta dominance. On the other hand, we should acknowledge that this limitation can affect the interpretation of the alpha result. Another reason for us to primarily focus on beta in the discussion and results presentation.
Changes in manuscript: We now comment on this in the results:
“It should be noted that that alpha recordings were performed in eyes closed which is known to increase alpha power, which may influence the generalizability of the alpha maps to an eyes open condition. However, given that our primary use of alpha was to act as a control, we believe that this should not affect the interpretability of the key findings of our study.”
• Although the relative proportion of theta and gamma channels is lower, it would be interesting to see the distribution of channels in a SOM figure.
As described above, we have now added supplementary figure 1 that accommodates the topography but not the network analyses.
• Figure legend - typo - "Neither, alpha nor beta" - no comma needed.
Now fixed, thank you for pointing is to this lapse!
• Results: " ere, we aimed to investigate the whole brain circuit representation of beta activity, which is impossible with current neurophysiology approaches" not entirely accurate; suggest rephrasing it to "Here, we aimed to investigate the whole brain circuit representation of beta activity, which is impossible with non-invasive neurophysiology approaches "
Thank you for suggesting the alternative formulation.
Changes in manuscript: The text has been modified as per the suggestion and now reads “Here, we aimed to investigate the whole brain circuit representation of beta activity, which is impossible with non-invasive neurophysiology approaches”.
• Results - typo - "cortical brain areas, that exhibit resting beta activity share a common brain network" - no comma needed.
Thank you for the suggestion, the comma has been removed to better the flow of the sentence structure as suggested.
Check out the website’s technical infrastructure and source code Analysing a website’s source code (which you can see if you hit CTRL+U on Google Chrome) can reveal technical links between different sites that are part of the same disinformation network.
It is a good idea but would would take a lot of time.
<h3> nested inside <h3><p1>, <p2>)\ddd)p1, p2)<br> tags<p1>, <p2> with <p>Fix image URLs
Improve CSS:
Replace inline styling
Clean up code:
<br> with margins/paddingYour content structure shows promise, but needs technical cleanup. Focus first on using valid HTML elements and building a proper CSS structure with IDs and classes.
circleX, circleYcircleRadiusangledrawFirstScreen()drawSecondScreen()drawThirdScreen()push()/pop() usageTrack animation states
Implement variable control:
Reset positions conditionally
Convert to OOP:
Circle classScreen classYour screen management and transformations are great. Converting screens or patterns to classes would make your code more maintainable.
dropX, dropYxSpeed, ySpeedrotleafX, leafYxLoc[]yLoc[]drawClouds() well implementedpush()/pop() usageRaindrop classLeaf classStore instances in arrays
Enhance variable control:
Your sketch is very well-structured with excellent use of arrays, loops, and transformations. To make it perfect, consider converting your raindrops or leaves into classes. This would make your code more maintainable and potentially allow for more complex behaviors.
x, y, xspeed, yspeedrectX, rectYsquareX, squareYmouseX/mouseY usageShape classAdd movement methods
Add iteration:
for loop for multiple shapesStore shapes in array
Create functions:
moveShape()checkBoundaries()drawShape()
Add visual interest:
Use push()/pop()
Make interactive:
Your movement and collision logic is well-implemented. To enhance your sketch, focus on organizing your code into classes and functions, and add more complex features through loops and arrays.
x, yxSpeed, ySpeedx boundary conditionsy boundary conditionsmouseX/mouseY usagefor loop for multiple elementsCreate repeating patterns
Implement storage:
Track multiple elements
Organize code:
Build simple class
Add visual interest:
Implement push()/pop()
Make it interactive:
Your movement and boundary logic is solid. To enhance your sketch, focus on adding more complex elements like loops and transformations. Consider converting your movement code into a class for better organization.
<h1>, <h2> usage<h7>, <h8> tags (HTML only supports h1-h6)<p> tagssrc attribute in <a> tagsobject-fit styling#Moving#Pizza#Mac and Cheese.Driving.Chicago.Pakistanr-gradient (should be linear-gradient)object-fit: ;)<style> blockr-gradient with linear-gradientYour project shows potential but needs technical cleanup. Focus first on using valid HTML elements and fixing broken links. Then work on making your CSS more maintainable by reducing absolute positioning and creating reusable classes.
<a> tag usagetarget="_blank"#intro#ind#iow#pel.div1 across sections.div2 across sections.div1 and .div2</head> closing tag</head> tagExcellent work overall! Your code is clean and well-structured. Making these minor improvements would make it perfect. Your use of classes and IDs is particularly strong, showing good understanding of CSS organization.
<h1> present<h2>, <h3>)</p> closing tags<a"web"</a>)<li> elements#AncientForest#EldersRecess.container used wellbackground-color: #rgb(255, 255, 255)border-color: #red<ul> or <ol> for list items# from RGB valuesYour content and layout ideas are good, but the code needs significant cleanup. Focus on fixing the HTML structure first, then work on simplifying your CSS approach to avoid potential layout issues.
<div> inside <h1> (invalid)<body> tags<a> and <ol><frame> usage (should be <iframe>)<h1> and <h3><p> tag#heading#heading2#p (should be tag selector).container: syntax<body><body> tag<frame> with <iframe><p> tags.container: syntax errorHi Collin, I really enjoyed your projects concept; however, your project needs significant technical improvements to function properly. Focus first on fixing the HTML structure and closing tags, then work on organizing your CSS more efficiently.
<h1> implemented<h2>, <h3>) for sections/images/griptape-2.jpg)#containerone#containertwo#containerthree.container used wellfont-size:100px<h2>, <h3>)<h1> tags<h2> and <h3> for better hierarchy#Content P).container used wellmargin-left:100xtext-align:center declarationsh1 blockmargin-left:100x → margin-left:100px<h2>, <h3>)Your layout and functionality work well. Focus on meeting the technical requirements (IDs and classes) and cleaning up CSS organization to improve your score significantly.
#firstImpression#entertainment#dependency#delusion#acceptance.section.styleOnebackground-color: #blacksize: 50px)#wakeUp, #Lain, #crystal)class=styleOne → class="styleOne"background-color: #black → background-color: blacksize propertyYour structure is good and IDs/classes are well-implemented. Focus on cleaning up syntax and moving styles to your CSS file to make your code more easily updatable.
<a> tag after Giphy embed#containerOne#leftnote#rightnote#color#define#bold#big.notes.smalltable, th, td)<a> tag after GiphyOutstanding work on HTML structure and CSS implementation. Your code is clean, semantic, and well-organized. Minor tweaks to styling organization, but overall nice job.
<h1>) used correctly<p> tags (<p1>, <p2>, <p4>)>)elio2.jpeg) implemented correctly#containerone#containertwo#floatingpup.container used wellopacity: .7.5)<div1>, <p1>, <p2>, <p4>)div1 styling<p1>, <p2>, <p4>) with standard <p> tagsEnjoyed this project overall! Address the technical issues listed here and this will be a solid submission.
<p> tags need content.container class#rain1 ID exists in CSS but not in HTML.container class missing style definitions> in <link> tag<div>p2, h2, #rain1).container stylesOverall I really enjoyed your concept and visuals that reinforced the theme of the page. Focus on cleaning up the technical details and completing the missing style definitions to take this to the next level.
Services Local, State, and U.S. government links $(function () { var widgetContext = "widget_3_1231_1375"; //start VISPP-4466 var useDesignThemFontSizeCss = window.visionOptions.useDesignThemFontSizeCss; var folderPath = useDesignThemFontSizeCss == true ? window.visionOptions.currentDesignFolderPath : window.visionOptions.mainFolderPath; if (!folderPath) folderPath = window.visionOptions.mainFolderPath; var resizeTimer; var resizeFaqTabs = function () { $(".faq_widget").each(function () { var tabheight = $(this).find(".faq_tab_nav").height(); $(this).find(".faqtab_section").attr("style", "min-height: " + (tabheight - 42) + "px"); }); }; var SetFontSize = function (fontsize) { $("#active_font").attr("href", folderPath + fontsize).attr("data-css", fontsize); var url = window.location.origin + visionOptions.virtualApplicationPath + "Shared/ChangeFontSizeCookie"; var cookieValue = fontsize ? fontsize : "small.css"; var cookieInt; switch(cookieValue){ case("xx-small.css"): cookieInt=1; break; case ("x-small.css"): cookieInt = 2; break; case ("small.css"): default: cookieInt = 3; break; case("medium.css"): cookieInt=4; break; case ("large.css"): cookieInt = 5; break; } $.frontendAjax({ url: url, type: 'POST', contentType: 'application/json', data: JSON.stringify({ cookieValue: cookieInt}), success: function (data, textStatus, jqXHR) { if (data && data.success) { $("#active_font").attr("href", window.visionOptions.mainFolderPath + cookieValue).attr("data-css", cookieValue); } } }); if ($(".faq_tab_nav").length > 0) { clearTimeout(resizeTimer); resizeTimer = setTimeout(function () { resizeFaqTabs(); }, 200); } }; $(".font_larger").on("click", function () { switch ($("#active_font").attr("data-css")) { case "medium.css": SetFontSize("large.css"); break; case "small.css": SetFontSize("medium.css"); break; case "x-small.css": SetFontSize("small.css"); break; case "xx-small.css": SetFontSize("x-small.css"); break; } return false; }); $(".font_smaller").on("click", function () { switch ($("#active_font").attr("data-css")) { case "large.css": SetFontSize("medium.css"); break; case "medium.css": SetFontSize("small.css"); break; case "small.css": SetFontSize("x-small.css"); break; case "x-small.css": SetFontSize("xx-small.css"); break; } return false; }); $(".text_size").on("click", function () { SetFontSize("x-small.css"); return false; }); //end VISPP-4466 $("#" + widgetContext + " #share").click(function () { if (!$("#" + widgetContext + " div#share").hasClass("click-active")) $("#" + widgetContext + " div#share").find("ul").show(); else $("#" + widgetContext + " div#share").find("ul").hide(); }); $("div").click(function () { if ($("#" + widgetContext + " div#share").hasClass("click-active")) { $("#" + widgetContext + " div#share").find("ul").hide(); } }); $(document).click(function (e) { if (!$(e.target).closest("#share").length > 0) { $("#" + widgetContext + " div#share").removeClass("click-active"); $("#" + widgetContext + " div#share").find("ul").hide(); } }); var shareContainerTimeout = null; $("#" + widgetContext + " #share").bind('mouseover', function () { //If not relate to click event if (shareContainerTimeout) { clearTimeout(shareContainerTimeout); shareContainerTimeout = null; } shareContainerTimeout = setTimeout(function () { if (!$("#" + widgetContext + " div#share").hasClass("click-active")) $("#" + widgetContext + " div#share").find("ul").show(); }, 100); }); $("#" + widgetContext + " #share").bind('mouseleave', function () { //If not relate to click event if (shareContainerTimeout) { clearTimeout(shareContainerTimeout); shareContainerTimeout = null; } shareContainerTimeout = setTimeout(function () { if (!$("#" + widgetContext + " div#share").hasClass("click-active")) $("#" + widgetContext + " div#share").find("ul").hide(); }, 200); }); $("header#" + widgetContext + " a.feedback_link").click(function () { var windowHeight = 485; if (window.innerWidth <= 648) { windowHeight = 545; } var opts = { title: "Feedback", url: "/Template/GetFeedbackPartial?feedbackUrl=https%3a%2f%2fwww.clarkecounty.gov%2fservices%2flocal-state-and-u-s-government", useFrame: true, height: windowHeight, onClosed: function (result) { if (result != undefined && result.IsOk == true) { $.refreshTempMessage(result.Message); } $("header#" + widgetContext + " a.feedback_link").focus(); }, skin: 'viClientDialog feedback_lightbox', fixed: false }; $.viClientDialog(opts).open(); }); //Safari iOS: No click event $("header#" + widgetContext + " a.send_share_email").bind("click touchstart", function () { var shareEmailTitle = document.itemTitle ? encodeURIComponent(document.itemTitle.trim()).replace(/[!'()*]/g, escape) : "Local%2c+State%2c+and+U.S.+government+links"; var opts = { title: "Click to submit an email online", url: "/Template/GetShareEmailPartial?shareUrl=https%3a%2f%2fwww.clarkecounty.gov%2fservices%2flocal-state-and-u-s-government" + "&shareTitle=" + shareEmailTitle, useFrame: true, height: 485, onClosed: function (result) { if (result != undefined && result.IsOk == true) { $.refreshTempMessage(result.Message); } $("header#" + widgetContext + " a.send_share_email").focus(); }, skin: 'viClientDialog send_share_email_lightbox', fixed: false }; $.viClientDialog(opts).open(); }); }); The external websites listed below are for your convenience. The appearance of a link on this or any other Clarke County government site does not constitute an endorsement, recommendation, or certification, nor should the presence of a link suggest the site has any relationship with Clarke County government. Local Town of Berryville Town of Boyce Clarke Conservation Easement Authority Clarke County Public Schools John H. Enders Fire Company & Rescue Squad Blue Ridge Volunteer Fire & Rescue Co. Boyce Volunteer Fire Company Top of Virginia Regional Chamber includes Clarke County and Town of Berryville Handley Regional Library includes Clarke County Library State Virginia Association of Counties Commonwealth of Virginia official website Virginia Department of Forestry Virginia Department of Motor Vehicles Virginia Department of Transportation VDOT builds, maintains, and operates roads, bridges, and tunnels in the Commonwealth. Virginia Department of Emergency Management VineLink Virginia Victim Information & Notification Everyday (VINE) provides victims of crime timely information about criminal cases and the status of offenders. Water Information from the EPA - Shenandoah Watershed Profile includes water sources, pollutants, stream flows, and more U.S. Census Bureau - American Fact Finder ICC - International Code Council a non-profit association dedicated to building safety Social Security Administration Ready Federal Emergency Management Agency (FEMA)
Playground is here: Build, test, and iterate on RAG apps with intuitive, low-code tools.Read the blog
to - playground is here
logitp[i] <- alpha + beta * voc[i] p[i] <- exp(logitp[i]) / (1 + exp(logitp[i])) observed[i] ~ dbin(p[i], 1)
For next edition, rewrite all JAGS code so that the order/format matches how we write down equations describing our models. E.g.:
response variable ~ statistical distribution(parameters) transformation(parameters) <- linear predictor
Author response:
We thank the editor and reviewers for their feedback. We believe we can address the substantive criticisms in full, first, by providing a more explicit theoretical basis for the method. Then, we believe criticism based on assumptions about phase consistency across time points are not well founded and can be answered. Finally, in response to some reviewer comments, we will improve the surrogate testing of the method.
We will enhance the theoretical justification for the application of higher-order singular value decomposition (SVD) to the problem of irregular sampling of the cortical area. The initial version of the manuscript was written to allow informal access to these ideas (if possible), but the reviewers find a more rigorous account appropriate. We will add an introduction to modern developments in the use of functional SVD in geophysics, meteorology & oceanography (e.g., empirical orthogonal functions) and quantitative fluid dynamics (e.g., dynamic mode decomposition) and computational chemistry. Recently SVD has been used in neuroscience studies (e.g., cortical eigenmodes). To our knowledge, our work is the first time higher-order SVD has been applied to a neuroscience problem. We use it here to solve an otherwise (apparently) intractable problem, i.e., how to estimate the spatial frequency (SF) spectrum on a sparse and highly irregular array with broadband signals.
We will clarify the methodological strategy in more formal terms in the next version of the paper. But essentially SVD allows a change of basis that greatly simplifies quantitative analysis. Here it allows escape from estimating the SF across millions of data-points (triplets of contacts, at each sample), each of which contains multiple overlapping signals plus noise (noise here defined in the context of SF estimation) and are inter-correlated across a variety of known and unknown observational dimensions. Rather than simply average over samples, which would wash out much of the real signal, SVD allows the signals to be decomposed in a lossless manner (up to the choice of number of eigenvectors at which the SVD is truncated). The higher-order SVD we have implemented reduces the size of problem to allow quantification of SF over hundreds of components, each of which is guaranteed certain desirable properties, i.e., they explain known (and largest) amounts of variance of the original data and are orthonormal. This last property allows us to proceed as if the observations are independent. SF estimates are made within this new coordinate system.
We will also more concretely formalise the relation between Fourier analysis and previous observations of eigenvectors of phase that are smooth gradients.
We will very briefly review Fourier methods designed to deal with non-uniform sampling. The problems these methods are designed for fall into the non-uniform part of the spectrum from uniform–non-uniform–irregular–highly-irregular–noise. They are highly suited to, for example, interpolating between EEG electrodes to produce a uniform array for application of the fast Fourier transform (Alamia et al., 2023). However, survey across a range of applied maths fields suggests that no method exists for the degree of irregular sampling found in the sEEG arrays at issue here. In particular, the sparseness of the contact coverage presents an insurmountable hurdle to standard methods. While there exists methods for sparse samples (e.g., Margrave & Fergusen, 1999; Ying 2009), these require well-defined oscillatory behavior, e.g., for seismographic analysis. Given the problems of highly irregular sampling, sparseness of sampling and broadband, nonstationary signals, we have attempted a solution via the novel methods introduced in the current manuscript. We were able to leverage previous observations regarding the relation between eigenvectors of cortical phase and Fourier analysis, as we outline in the manuscript.
We will extend the current 1-dimensional surrogate data to better demonstrate that the method does indeed correctly detect the ordinal relations in power on different parts of the SF spectrum. We will include the effects of a global reference signal. Simulations of cortical activity are an expensive way to achieve this goal. While the first author has published in this area, such simulations are partly a function of the assumptions put into them (i.e., spatial damping, boundary conditions, parameterization of connection fields). We will therefore use surrogate signals derived from real cortical activity to complete this task.
Some more specific issues raised:<br /> (1) Application of the method to general neuroscience problems:<br /> The purpose of the manuscript was to estimate the SF spectrum of phase in the cortex, in the range where it was previously not possible. The purpose was not specifically to introduce a new method of analysis that might be immediately applicable to a wide range of available data-sets. Indeed, the specifics of the method are designed to overcome an otherwise intractable disadvantage of sEEG (irregular spatial sampling) in order to take advantage of its good coverage (compared to ECoG) and low volume conduction compared to extra-cranial methods. On the other hand, the developing field of functional SVD would be of interest to neuroscientists, as a set of methods to solve difficult problems, and therefore of general interest. We will make these points explicit in the next version of the manuscript. In order to make the method more accessible, we will also publish code for the key routines (construction of triplets of contacts, Morlet wavelets, calculation of higher-order SVD, calculation of SF).
(2) Novelty:<br /> We agree with the third reviewer: if our results can convince, then the study will have an impact on the field. While there is work that has been done on phase interactions at a variety of scales, such as from the labs of Fries, Singer, Engels, Nauhaus, Logothetis and others, it does not quantify the relative power of the different spatial scales. Additionally, the research of Freeman et al. has quantified only portions of the SF spectrum of the cortex, or used EEG to estimate low SFs. We would appreciate any pointers to the specific literature the current research contributes to, namely, the SF spectrum of activity in the cortex.
(3) Further analyses:<br /> The main results of the research are relatively simple: monotonically falling SF-power with SF; this effect occurs across the range of temporal frequencies. We provide each individual participant’s curves in the supplementary Figures. By visual inspection, it can be seen that the main result of the example participant is uniformly recapitulated. One is rarely in this position in neuroscience research, and we will make this explicit in the text.
The research stands or falls by the adequacy of the method to estimate the SF curves. For this reason most statistical analyses and figures were reserved for ruling out confounds and exploring the limits of the methods. However, for the sake of completeness, we will now include the SF vs. SF-power correlations and significance in the next version, for each participant at each frequency.
Since the main result was uniform across participants, and since we did not expect that there was anything of special significance about the delayed free recall task, we conclude that more participants or more tasks would not add to the result. As we point out in the manuscript, each participant is a test of the main hypothesis. The result is also consistent with previous attempts to quantify the SF spectrum, using a range of different tasks and measurement modalities (Barrie et al., 1996; Ramon & Holmes 2015; Alexander et al., 2019; Alexander et al., 2016; Freeman et al., 2003; Freeman et al. 2000). The search for those rare sEEG participants with larger coverage than the maximum here is a matter of interest to us, but will be left for a future study.
(4) Sampling of phase and its meaningfulness:<br /> The wavelet methods used in the present study have excellent temporal resolution but poor frequency resolution. We additionally oversample the frequency range to produce visually informative plots (usually in the context of time by frequency plots, see Alexander et al., 2006; 2013; 2019). But it is not correct that the methods for estimating phase assume a narrow frequency band. Rather, the poor frequency resolution of short time-series Morlet wavelets means the methods are robust to the exact shape of the waveforms; the signal need be only approximately sinusoidal; to rise and fall. The reason for using methods that have excellent resolution in the time-domain is that previous work (Alexander et al., 2006; Patten et al. 2012) has shown that traveling wave events can last only one or two cycles, i.e., are not oscillatory in the strict sense but are non-stationary events. So while short time-window Morlet wavelets have a disadvantage in terms of frequency resolution, this means they precisely do not have the problem of assuming narrow-band sinusoidal waveforms in the signal. We strongly disagree that our analysis requires very strong assumptions about oscillations (see last point in this section).
Our hypothesis was about the SF spectrum of the phase. When the measurement of phase is noise-like at some location, frequency and time, then this noise will not substantially contribute to the low SF parts of the spectrum compared to high SFs. Our hypothesis also concerned whether it was reasonable to interpret the existing literature on low SF waves in terms of cortically localised waves or small numbers of localised oscillators. This required us to show that low SFs dominate, and therefore that this signal must dominate any extra-cranial measurements of apparent low SF traveling waves. It does not require us to demonstrate that the various parts of the SF spectrum are meaningful in the sense of functionally significant. This has been shown elsewhere (see references to traveling waves in manuscript, to which we will also add a brief survey of research on phase dynamics).
The calculation of phase can be bypassed altogether to achieve the initial effect described in the introduction to the methods (Fourier-like basis functions from SVD). The observed eigenvectors, increasing in spatial frequency with decreasing eigenvalues, can be reproduced by applying Gaussian windows to the raw time-series (D. Alexander, unpublished observation). For example, undertaking an SVD on the raw time-series windowed over 100ms reproduces much the same spatial eigenvectors (except that they come in pairs, recapitulating the real and imaginary parts of the signal). This reproducibility is in comparison to first estimating the phase at 10Hz using Morlet wavelets, then applying the SVD to the unit-length complex phase values.
(5) Other issues to be addressed and improved:<br /> clarity on which experiments were analyzed (starting in the abstract) discussion of frequencies above 60Hz and caution in interpretation due to spike-waveform artefact or as a potential index of multi-unit spiking discussion of whether the ad hoc, quasi-random sampling achieved by sEEG contacts somehow inflates the low SF estimates
References (new)<br /> Patten TM, Rennie CJ, Robinson PA, Gong P (2012) Human Cortical Traveling Waves: Dynamical Properties and Correlations with Responses. PLoS ONE 7(6): e38392. https://doi.org/10.1371/journal.pone.0038392<br /> Margrave GF, Ferguson RJ (1999) Wavefield extrapolation by nonstationary phase shift, GEOPHYSICS 64:4, 1067-1078<br /> Ying Y (2009) Sparse Fourier Transform via Butterfly Algorithm SIAM Journal on Scientific Computing, 31:3, 1678-1694
Reviewer #1 (Public review):
Summary:
The authors explore a large-scale electrophysiological dataset collected in 10 labs while mice performed the same behavioral task, and aim to establish guidelines to aid reproducibility of results collected across labs. They introduce a series of metrics for quality control of electrophysiological data and show that histological verification of recording sites is important for interpreting findings across labs and should be reported in addition to planned coordinates. Furthermore, the authors suggest that although basic electrophysiology features were comparable across labs, task modulation of single neurons can be variable, particularly for some brain regions. The authors then use a multi-task neural network model to examine how neural dynamics relate to multiple interacting task- and experimenter-related variables, and find that lab-specific differences contribute little to the variance observed. Therefore, analysis approaches that account for correlated behavioral variables are important for establishing reproducible results when working with electrophysiological data from animals performing decision-making tasks. This paper is very well-motivated and needed. However, what is missing is a direct comparison of task modulation of neurons across labs using standard analysis practice in the fields, such as generalized linear model (GLM). This can potentially clarify how much behavioral variance contributes to the neural variance across labs; and more accurately estimate the scale of the issues of reproducibility in behavioral systems neuroscience, where conclusions often depend on these standard analysis methods.
Strength:
(1) This is a well-motivated paper that addresses the critical question of reproducibility in behavioural systems neuroscience. The authors should be commended for their efforts.
(2) A key strength of this study comes from the large dataset collected in collaboration across ten labs. This allows the authors to assess lab-to-lab reproducibility of electrophysiological data in mice performing the same decision-making task.
(3) The authors' attempt to streamline preprocessing pipelines and quality metrics is highly relevant in a field that is collecting increasingly large-scale datasets where automation of these steps is increasingly needed.
(4) Another major strength is the release of code repositories to streamline preprocessing pipelines across labs collecting electrophysiological data.
(5) Finally, the application of MTNN for characterizing functional modulation of neurons, although not yet widely used in systems neuroscience, seems to have several advantages over traditional methods.
Weaknesses:
(1) In several places the assumptions about standard practices in the field, including preprocessing and analyses of electrophysiology data, seem to be inaccurately presented:
a) The estimation of how much the histologically verified recording location differs from the intended recording location is valuable information. Importantly, this paper provides citable evidence for why that is important. However, histological verification of recording sites is standard practice in the field, even if not all studies report them. Although we appreciate the authors' effort to further motivate this practice, the current description in the paper may give readers outside the field a false impression of the level of rigor in the field.
b) When identifying which and how neurons encode particular aspects of stimuli or behaviour in behaving animals (when variables are correlated by the nature of the animals behaviour), it has become the standard in behavioral systems neuroscience to use GLMs - indeed many labs participating in the IBL also has a long history of doing this (e.g., Steinmetz et al., 2019; Musall et al., 2023; Orsolic et al., 2021; Park et al., 2014). The reproducibility of results when using GLMs is never explicitly shown, but the supplementary figures to Figure 7 indicate that results may be reproducible across labs when using GLMs (as it has similar prediction performance to the MTNN). This should be introduced as the first analysis method used in a new dedicated figure (i.e., following Figure 3 and showing results of analyses similar to what was shown for the MTNN in Figure 7). This will help put into perspective the degree of reproducibility issues the field is facing when analyzing with appropriate and common methods. The authors can then go on to show how simpler approaches (currently in Figures 4 and 5) - not accounting for a lot of uncontrolled variabilities when working with behaving animals - may cause reproducibility issues.
When the authors introduce a neural network approach (i.e. MTNN) as an alternative to the analyses in Figures 4 and 5, they suggest: 'generalized linear models (GLMs) are likely too inflexible to capture the nonlinear contributions that many of these variables, including lab identity and spatial positions of neurons, might make to neural activity'). This is despite the comparison between MTNN and GLM prediction performance (Supplement 1 to Figure 7) showing that the MTNN is only slightly better at predicting neural activity compared to standard GLMs. The introduction of new models to capture neural variability is always welcome, but the conclusion that standard analyses in the field are not reproducible can be unfair unless directly compared to GLMs.
In essence, it is really useful to demonstrate how different analysis methods and preprocessing approaches affect reproducibility. But the authors should highlight what is actually standard in the field, and then provide suggestions to improve from there.
(2) The authors attempt to establish a series of new quality control metrics for the inclusion of recordings and single units. This is much needed, with the goal to standardize unit inclusion across labs that bypasses the manual process while keeping the nuances from manual curation. However, the authors should benchmark these metrics to other automated metrics and to manual curation, which is still a gold standard in the field. The authors did this for whole-session assessment but not for individual clusters. If the authors can find metrics that capture agreed-upon manual cluster labels, without the need for manual intervention, that would be extremely helpful for the field.
(3) With the goal of improving reproducibility and providing new guidelines for standard practice for data analysis, the authors should report of n of cells, sessions, and animals used in plots and analyses throughout the paper to aid both understanding of the variability in the plots - but also to set a good example.
Other general comments:
(1) In the discussion (line 383) the authors conclude: 'This is reassuring, but points to the need for large sample sizes of neurons to overcome the inherent variability of single neuron recording'. - Based on what is presented in this paper we would rather say that their results suggest that appropriate analytical choices are needed to ensure reproducibility, rather than large datasets - and they need to show whether using standard GLMs actually allows for reproducible results.
(2) A general assumption in the across-lab reproducibility questions in the paper relies on intralab variability vs across-lab variability. An alternative measure that may better reflect experimental noise is across-researcher variability, as well as the amount of experimenter experience (if the latter is a factor, it could suggest researchers may need more training before collecting data for publication). The authors state in the discussion that this is not possible. But maybe certain measures can be used to assess this (e.g. years of conducting surgeries/ephys recordings etc)?
(3) Figure 3b and c: Are these plots before or after the probe depth has been adjusted based on physiological features such as the LFP power? In other words, is the IBL electrophysiological alignment toolbox used here and is the reliability of location before using physiological criteria or after? Beyond clarification, showing both before and after would help the readers to understand how much the additional alignment based on electrophysiological features adjusts probe location. It would also be informative if they sorted these penetrations by which penetrations were closest to the planned trajectory after histological verification.
(4) In Figures 4 and 6: If the authors use a 0.05 threshold (alpha) and a cell simply has to be significant on 1/6 tests to be considered task modulated, that means that they have a false positive rate of ~30% (0.05*6=0.3). We ran a simple simulation looking for significant units (from random null distribution) from these criteria which shows that out of 100.000 units, 26500 units would come out significant (false error rate: 26.5%). That is very high (and unlikely to be accepted in most papers), and therefore not surprising that the fraction of task-modulated units across labs is highly variable. This high false error rate may also have implications for the investigation of the spatial position of task-modulated units (as effects of the spatial position may drown in falsely labelled 'task-modulated' cells).
(5) The authors state from Figure 5b that the majority of cells could be well described by 2 PCs. The distribution of R2 across neurons is almost uniform, so depending on what R2 value one considers a 'good' description, that is the fraction of 'good' cells. Furthermore, movement onset has now been well-established to be affecting cells widely and in large fractions, so while this analysis may work for something with global influence - like movement - more sparsely encoded variables (as many are in the brain) may not be well approximated with this suggestion. The authors could expand this analysis into other epochs like activity around stimulus presentation, to better understand how this type of analysis reproduces across labs for features that have a less global influence.
(6) Additionally, in Figure 5i: could the finding that one can only distinguish labs when taking cells from all regions, simply be a result of a different number of cells recorded in each region for each lab? It makes more sense to focus on the lab/area pairing as the authors also do, but not to make their main conclusion from it. If the authors wish to do the comparison across regions, they will need to correct for the number of cells recorded in each region for each lab. In general, it was a struggle to fully understand the purpose of Figure 5. While population analysis and dimensionality reduction are commonplace, this seems to be a very unusual use of it.
(7) In the discussion the authors state: "This approach, which exceeds what is done in many experimental labs". Indeed this approach is a more effective and streamlined way of doing it, but it is questionable whether it 'exceeds' what is done in many labs. Classically, scientists trace each probe manually with light microscopy and designate each area based on anatomical landmarks identified with nissl or dapi stains together with gross landmarks. When not automated with 2-PI serial tomography and anatomically aligned to a standard atlas, this is a less effective process, but it is not clear that it is less precise, especially in studies before neuropixels where active electrodes were located in a much smaller area. While more effective, transforming into a common atlas does make additional assumptions about warping the brain into the standard atlas - especially in cases where the brain has been damaged/lesioned. Readers can appreciate the effectiveness and streamlining provided by these new tools without the need to invalidate previous approaches.
(8) What about across-lab population-level representation of task variables, such as in the coding direction for stimulus or choice? Is the general decodability of task variables from the population comparable across labs?
Reviewer #2 (Public review):
Summary:
The authors sought to evaluate whether observations made in separate individual laboratories are reproducible when they use standardized procedures and quality control measures. This is a key question for the field. If ten systems neuroscience labs try very hard to do the exact same experiment and analyses, do they get the same core results? If the answer is no, this is very bad news for everyone else! Fortunately, they were able to reproduce most of their experimental findings across all labs. Despite attempting to target the same brain areas in each recording, variability in electrode targeting was a source of some differences between datasets.
Major Comments:
The paper had two principal goals:<br /> (1) to assess reproducibility between labs on a carefully coordinated experiment<br /> (2) distill the knowledge learned into a set of standards that can be applied across the field.<br /> The manuscript made progress towards both of these goals but leaves room for improvement.
(1) The first goal of the study was to perform exactly the same experiment and analyses across 10 different labs and see if you got the same results. The rationale for doing this was to test how reproducible large-scale rodent systems neuroscience experiments really are. In this, the study did a great job showing that when a consortium of labs went to great lengths to do everything the same, even decoding algorithms could not discern laboratory identity was not clearly from looking at the raw data. However, the amount of coordination between the labs was so great that these findings are hard to generalize to the situation where similar (or conflicting!) results are generated by two labs working independently.
Importantly, the study found that electrode placement (and thus likely also errors inherent to the electrode placement reconstruction pipeline) was a key source of variability between datasets. To remedy this, they implemented a very sophisticated electrode reconstruction pipeline (involving two-photon tomography and multiple blinded data validators) in just one lab-and all brains were sliced and reconstructed in this one location. This is a fantastic approach for ensuring similar results within the IBL collaboration, but makes it unclear how much variance would have been observed if each lab had attempted to reconstruct their probe trajectories themselves using a mix of histology techniques from conventional brain slicing, to light sheet microscopy, to MRI imaging.
This approach also raises a few questions. The use of standard procedures, pipelines, etc. is a great goal, but most labs are trying to do something unique with their setup. Bigger picture, shouldn't highly "significant" biological findings akin to the discovery of place cells or grid cells, be so clear and robust that they can be identified with different recording modalities and analysis pipelines?
Related to this, how many labs outside of the IBL collaboration have implemented the IBL pipeline for their own purposes? In what aspects do these other labs find it challenging to reproduce the approaches presented in the paper? If labs were supposed to perform this same experiment, but without coordinating directly, how much more variance between labs would have been seen? Obviously investigating these topics is beyond the scope of this paper. The current manuscript is well-written and clear as is, and I think it is a valuable contribution to the field. However, some additional discussion of these issues would be helpful.
(2) The second goal of the study was to present a set of data curation standards (RIGOR) that could be applied widely across the field. This is a great idea, but its implementation needs to be improved if adoption outside of the IBL is to be expected. Here are three issues:
(a) The GitHub repo for this project (https://github.com/int-brain-lab/paper-reproducible-ephys/) is nicely documented if the reader's goal is to reproduce the figures in the manuscript. Consequently, the code for producing the RIGOR statistics seems mostly designed for re-computing statistics on the existing IBL-formatted datasets. There doesn't appear to be any clear documentation about how to run it on arbitrary outputs from a spike sorter (i.e. the inputs to Phy).
(b) Other sets of spike sorting metrics that are more easily computed for labs that are not using the IBL pipeline already exist (e.g. "quality_metrics" from the Allen Institute ecephys pipeline [https://github.com/AllenInstitute/ecephys_spike_sorting/blob/main/ecephys_spike_sorting/modules/quality_metrics/README.md] and the similar module in the Spike Interface package [https://spikeinterface.readthedocs.io/en/latest/modules/qualitymetrics.html]). The manuscript does not compare these approaches to those proposed here, but some of the same statistics already exist (amplitude cutoff, median spike amplitude, refractory period violation).
(c) Some of the RIGOR criteria are qualitative and must be visually assessed manually. Conceptually, these features make sense to include as metrics to examine, but would ideally be applied in a standardized way across the field. The manuscript doesn't appear to contain a detailed protocol for how to assess these features. A procedure for how to apply these criteria for curating non-IBL data (or for implementing an automated classifier) would be helpful.
Other Comments:
(1) How did the authors select the metrics they would use to evaluate reproducibility? Was this selection made before doing the study?
(2) Was reproducibility within-lab dependent on experimenter identity?
(3) They note that UCLA and UW datasets tended to miss deeper brain region targets (lines 185-188) - they do not speculate why these labs show systematic differences. Were they not following standardized procedures?
(4) The authors suggest that geometrical variance (difference between planned and final identified probe position acquired from reconstructed histology) in probe placement at the brain surface is driven by inaccuracies in defining the stereotaxic coordinate system, including discrepancies between skull landmarks and the underlying brain structures. In this case, the use of skull landmarks (e.g. bregma) to determine locations of brain structures might be unreliable and provide an error of ~360 microns. While it is known that there is indeed variance in the position between skull landmarks and brain areas in different animals, the quantification of this error is a useful value for the field.
(5) Why are the thalamic recording results particularly hard to reproduce? Does the anatomy of the thalamus simply make it more sensitive to small errors in probe positioning relative to the other recorded areas?
In the code above, def tells Python we want to define a funciton, say_hi is the name we chose for our function, and the empty parentheses () mean that it doesn’t take any parameters. There is then a colon (:) to say what follows is a code block that will be what happens when the function is called.
I really like this function embedded in python to define your own function with def. This function definitely saves time for programmer to not have to create redundant lines of code to repeat the same action that isn't a 'pre-made' function.
One of the things you can do as an individual to better protect yourself against hacking is to enable 2-factor authentication on your accounts.
I've started enabling 2fa on all my accounts but 2fa can be buggy and annoying to use. Some use email, some use texts and others require an app. It gets annoying trying to switch between and find the 2fa code.
Sometimes companies or researchers release datasets that have been “anonymized,” meaning that things like names have been removed, so you can’t directly see who the data is about. But sometimes people can still deduce who the anonymized data is about. This happened when Netflix released anonymized movie ratings data sets, but at least some users’ data could be traced back to them.
I have come across multiple research papers regarding de-identification of personal information and what is so interesting as well as a bit concerning is the idea that any individual can be identified by only 3 pieces of information including zip code, birthday and gender. This discovery did lead to a change in policies regarding privacy research and regulations on various media; however this leads me to think that as privacy protections evolve, so will the methods to breach them.
When we’ve been accessing Reddit through Python and the “PRAW” code library. The praw code library works by sending requests across the internet to Reddit, using what is called an “application programming interface” or API for short. APIs have a set of rules for what requests you can make, what happens when you make the request, and what information you can get back. If you are interested in learning more about what you can do with praw and what information you can get back, you can look at the official documentation for those. But be warned they are not organized in a friendly way for newcomers and take some getting used to to figure out what these documentation pages are talking about. So, if you are interested, you can look at the praw library documentation to find out what the library can do (again, not organized in a beginner-friendly way). You can learn a little more by clicking on the praw models and finding a list of the types of data for each of the models, and a list of functions (i.e., actions) you can do with them.
I believe that API's are very important as they like Reddit’s PRAW library, enable structured access to data. While the PRAW documentation offers deeper insights into its capabilities, it may be challenging to navigate, requiring patience and exploration to master its use to ensure that its full potential and purpose is being utilized.
Code
this adds code tags which could prevent content from being displayed for some Safari users (this is the case when the tags are wrapped around H5P activities)
elif <20:
Der Code funktioniert nicht. Es sollte "elif current_hour <20:" sein.
Then Sean Black, a programmer on TikTok saw this and decided to contribute by creating a bot that would automatically log in and fill out applications with random user info, increasing the rate at which he (and others who used his code) could spam the Kellogg’s job applications:
Sean Black's employment of a bot to automate the spamming process draws attention to the contentious relationship between activism and technology. It also shows how data manipulation and programming may be utilized as a form of protest. The use of fictitious employment applications or other forms of data poisoning highlights how dependent businesses are on reliable, clean data to run efficiently. This gives those who want to upend systems new chances, but it also portends a time in the future when these kinds of strategies might be applied unethically or destructively.
Then Sean Black, a programmer on TikTok saw this and decided to contribute by creating a bot that would automatically log in and fill out applications with random user info, increasing the rate at which he (and others who used his code) could spam the Kellogg’s job applications:
This is a great example of using social media for the right cause and explaining how the context matters. It shows that ethical trolling can be done to get social justice for those who have been wronged, forcing such a big company to act right. It's interesting to see how the company's decision backfired using trolling.
Data can be poisoned intentionally as well. For example, in 2021, workers at Kellogg’s were upset at their working conditions, so they agreed to go on strike, and not work until Kellogg’s agreed to improve their work conditions. Kellogg’s announced that they would hire new workers to replace the striking workers: Kellogg’s proposed pay and benefits cuts while forcing workers to work severe overtime as long as 16-hour-days for seven days a week. Some workers stayed on the job for months without a single day off. The company refuses to meet the union’s proposals for better pay, hours, and benefits, so they went on strike. Earlier this week, the company announced it would permanently replace 1,400 striking workers. People Are Spamming Kellogg’s Job Applications in Solidarity with Striking Workers – Vice MotherBoard People in the antiwork subreddit found the website where Kellogg’s posted their job listing to replace the workers. So those Redditors suggested they spam the site with fake applications, poisoning the job application data, so Kellogg’s wouldn’t be able to figure out which applications were legitimate or not (we could consider this a form of trolling). Then Kellogg’s wouldn’t be able to replace the striking workers, and they would have to agree to better working conditions. Then Sean Black, a programmer on TikTok saw this and decided to contribute by creating a bot that would automatically log in and fill out applications with random user info, increasing the rate at which he (and others who used his code) could spam the Kellogg’s job applications:
The Kellogg's incident, in which the general public used electronic means to interfere with the company's operations, is a fascinating illustration of collective resistance in the digital age. It, in my opinion, represents society's reaction to large businesses abusing their power. But this kind of "data poisoning" begs the moral dilemma of how to define an appropriate mode of dissent. Although flooding the hiring process with phony applications paralyzes it, it may have unintended consequences for other parties, therefore a deeper analysis of the boundaries of technical confrontation is required.
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
Summary:
Previous work demonstrated a strong bias in the percept of an ambiguous Shepard tone as either ascending or descending in pitch, depending on the preceding contextual stimulus. The authors recorded human MEG and ferret A1 single-unit activity during presentation of stimuli identical to those used in the behavioral studies. They used multiple neural decoding methods to test if context-dependent neural responses to ambiguous stimulus replicated the behavioral results. Strikingly, a decoder trained to report stimulus pitch produced biases opposite to the perceptual reports. These biases could be explained robustly by a feed-forward adaptation model. Instead, a decoder that took into account direction selectivity of neurons in the population was able to replicate the change in perceptual bias.
Strengths:
This study explores an interesting and important link between neural activity and sensory percepts, and it demonstrates convincingly that traditional neural decoding models cannot explain percepts. Experimental design and data collection appear to have been executed carefully. Subsequent analysis and modeling appear rigorous. The conclusion that traditional decoding models cannot explain the contextual effects on percepts is quite strong.
Weaknesses:
Beyond the very convincing negative results, it is less clear exactly what the conclusion is or what readers should take away from this study. The presentation of the alternative, "direction aware" models is unclear, making it difficult to determine if they are presented as realistic possibilities or simply novel concepts. Does this study make predictions about how information from auditory cortex must be read out by downstream areas? There are several places where the thinking of the authors should be clarified, in particular, around how this idea of specialized readout of direction-selective neurons should be integrated with a broader understanding of auditory cortex.
While we have not used the term "direction aware", we think the reviewer refers generally to the capability of our model to use a cell's direction selectivity in the decoding. In accordance with the reviewer's interpretation, we did indeed mean that the decoder assumes that a neuron does not only have a preferred frequency, but also a preferred direction of change in frequency (ascending/descending), which is what we use to demonstrate that the decoding in this way aligns with the human percept. We have adapted the text in several places to clarify this, in particular expanding the description in the Methods substantially.
Reviewer #2 (Public Review):
The authors aim to better understand the neural responses to Shepard tones in auditory cortex. This is an interesting question as Shepard tones can evoke an ambiguous pitch that is manipulated by a proceeding adapting stimulus, therefore it nicely disentangles pitch perception from simple stimulus acoustics.
The authors use a combination of computational modelling, ferret A1 recordings of single neurons, and human EEG measurements.
Their results provide new insights into neural correlates of these stimuli. However, the manuscript submitted is poorly organized, to the point where it is near impossible to review. We have provided Major Concerns below. We will only be able to understand and critique the manuscript fully after these issues have been addressed to improve the readability of the manuscript. Therefore, we have not yet reviewed the Discussion section.
Major concerns
Organization/presentation
The manuscript is disorganized and therefore difficult to follow. The biggest issue is that in many figures, the figure subpanels often do not correspond to the legend, the main body, or both. Subpanels described in the text are missing in several cases.
We have gone linearly through the text and checked that all figure subpanels are referred to in the text and the legend. As far as we can tell, this was already the case for all panels, with the exception of two subpanels of Fig. 5.
Many figure axes are unlabelled.
We have carefully checked the axes of all panels and all but two (Fig. 5D) were labeled. As is customary, certain panels inherit the axis label from a neighboring panel, if the label is the same, e.g. subpanels in Fig. 6F or Fig. 5E, which helps to declutter the figure. We hope that with this clarification, the reviewer can understand the labels of each panel.
There is an inconsistent style of in-text citation between figures and the main text. The manuscript contains typos and grammatical errors. My suggestions for edits below therefore should not be taken as an exhaustive list. I ask the authors to consider the following only a "first pass" review, and I will hopefully be able to think more deeply about the science in the second round of revisions after the manuscript is better organized.
While we are puzzled by the severity of issues that R2 indicates (see above, and R3 qualifies it as "well written", and R1 does not comment on the writing negatively), we have carefully gone through all specific issues mentioned by R2 and the other reviewers. We hope that the revised version of the paper with all corrections and clarifications made will resolve any remaining issues.
Frequency and pitch
The terms "frequency" and "pitch" seem to be used interchangeably at times, which can lead to major misconceptions in a manuscript on Shepard tones. It is possible that the authors confuse these concepts themselves at times (e.g. Fig 5), although this would be surprising given their expertise in this field. Please check through every use of "frequency" and "pitch" in this manuscript and make sure you are using the right term in the right place. In many places, "frequency" should actually be "fundamental frequency" to avoid misunderstanding.
Thanks for pointing this out. We have checked every occurrence and modified where necessary.
Insufficient detail or lack of clarity in descriptions
There seems to be insufficient information provided to evaluate parts of these analysis, most critically the final pitch-direction decoder (Fig 6), which is a major finding. Please clarify.
Thanks for pointing this out. We have extended the description of the pitch-direction decoder and highlighted its role for interpreting the results.
Reviewer #3 (Public Review):
Summary:
This is an elegant study investigating possible mechanisms underlying the hysteresis effect in the perception of perceptually ambiguous Shepard tones. The authors make a fairly convincing case that the adaptation of pitch direction sensitive cells in auditory cortex is likely responsible for this phenomenon.
Strengths:
The manuscript is overall well written. My only slight criticism is that, in places, particularly for non-expert readers, it might be helpful to work a little bit more methods detail into the results section, so readers don't have to work quite so hard jumping from results to methods and back.
Following this excellent suggestion, we have added more brief method sketches to the Results section, hopefully addressing this concern.
The methods seem sound and the conclusions warranted and carefully stated. Overall I would rate the quality of this study as very high, and I do not have any major issues to raise.
Thanks for your encouraging evaluation of the work.
Weaknesses:
I think this study is about as good as it can be with the current state of the art. Generally speaking, one has to bear in mind that this is an observational, rather than an interventional study, and therefore only able to identify plausible candidate mechanisms rather than making definitive identifications. However, the study nevertheless represents a significant advance over the current state of knowledge, and about as good as it can be with the techniques that are currently widely available.
Thanks for your encouraging evaluation of our work. The suggestion of an interventional study has also been on our minds, however, this appears rather difficult, as it would require a specific subset of cells to be inhibited. The most suitable approach would likely be 2p imaging with holographic inhibition of a subset of cells (using ArchT for example), that has a preference for one direction of pitch change, which should then bias the percept/behavior in the opposite direction.
Reviewer #1 (Recommendations For The Authors):
MAJOR CONCERNS
(1) What is the timescale used to compute direction selectivity in neural tuning? How does it compare to the timing of the Shepard tones? The basic idea of up versus down pitch is clear, the intuition for the role of direction tuning and its relation to stimulus dynamics could be laid out more clearly. Are the authors proposing that there are two "special" populations of A1 neurons that are treated differently to produce the biased percept? Or is there something specific about the dynamics of the Shepard stimuli and how direction selective neurons respond to them specifically? It would help if the authors could clarify if this result links to broader concepts of dynamic pitch coding in general or if the example reported here is specific (or idiosyncratic) to Shepard tones.
We propose that the findings here are not specific to Shepard tones. To the contrary, only basic properties of auditory cortex neurons, i.e. frequency preference, frequency-direction (i.e. ascending or descending) preference, and local adaptation in the tuning curve, suffice. Each of these properties have been demonstrated many times before and we only verified this in the lead-up to the results in Fig. 6. While the same effects should be observable with pure tones, the lack of ambiguity in the perception of direction of a frequency step for pure tone pairs, would make them less noticeable here. Regarding the time-scale of the directional selectivity, we relied on the sequencing of tones in our paradigm, i.e. 150 ms spacing. The SSTRFs were discretized at 50 ms, and include only the bins during the stimulus, not during the pause. The directional tuning, i.e. differences in the SSTRF above and below the preferred pitchclass for stimuli before the last stimulus, typically extended only one stimulus back in time. We have clarified this in more detail now, in particular in the added Methods section on the directional decoder.
(2) (p. 9) "weighted by each cell's directionality index ... (see Methods for details)" The direction-selective decoder is interesting and appears critical to the study. However, the details of its implementation are difficult to locate. Maybe Fig. 6A contains the key concepts? It would help greatly if the authors could describe it in parallel with the other decoders in the Methods.
We have expanded the description of the decoder in the Methods as the reviewer suggests.
LESSER CONCERNS
p. 1. (L 24) "distances between the pitch representations...." It's not obvious what "distances" means without reading the main paper. Can some other term or extra context be provided?
We have added a brief description here.
p. 2. (L 26) "Shepard tones" Can the authors provide a citation when they first introduce this class of stimuli?
Citation has been added.
p. 3 (L 4) "direction selective cells" Please define or provide context for what has a direction. Selective to pitch changes in time?
Yes, selective to pitch changes in time is what is meant. We have further clarified this in the text.
p. 4 (L 9-19). This paragraph seems like it belongs in the Introduction?
Given the concerns raised by R2 about the organization of the manuscript we prefer to keep this 'road-map' in the manuscript, as a guidance for the reader.
p. 4 (L 32) "majority of cells" One might imagine that the overlap of the bias band and the frequency tuning curve of individual neurons might vary substantially. Was there some criterion about the degree of overlap for including single units in the analysis? Does overlap matter?
We are not certain which analysis the reviewer is referring to. Generally, cells were not excluded based on their overlap between a particular Bias band and their (Shepard) tuning curve. There are several reasons for this: The bias was located in 4 different, overlapping Shepard tone regions, and all sounds were Shepard tones. Therefore, all cells overlapped with their (Shepard) tuning curve with one or multiple of the Biases. For decoding analysis, all cells were included as both a response and lack of a response is contributing to the decoding. If the reviewer is referring only to the analysis of whether a cell adapts, then the same argument applies as above, i.e. this was an average over all Bias sequences, and therefore every responding cell was driven to respond by the Bias, and therefore it was possible to also assess whether it adapted its response for different positions inside the Bias. We acknowledge that the limited randomness of the Bias sequences in combination with the specific tuning of the cells could in a few cases create response patterns over time that are not indicative of the actual behavior for repeated stimulation, however, since the results are rather clear with 91% of cells adapting, we do not think this would significantly change the conclusions.
p. 5 (L 17) "desynchronization ... behaving conditions" The logic here is not clear. Is less desynchronization expected during behavior? Typically, increased attention is associated with greater desynchronization.
Yes, we reformulated the sentence to: While this difference could be partly explained by desynchronization which is typically associated with active behavior or attention [30], general response adaptation to repeated stimuli is also typical in behaving humans [31].
p. 7 (L 5) "separation" is this a separation in time?
Yes, added.
p. 7 (L 33) "local adaptation" The idea of feedforward adaptation biasing encoding has been proposed before, and it might be worth citing previous work. This includes work from Nelken specifically related to SSA. Also, this model seems similar to the one described in Lopez Espejo et al (PLoS CB 2019).
Thanks for pointing this out. We think, however, that neither of these publications suggested this very narrow way of biasing, which we consider biologically implausible. We have therefore not added either of these citations.
p. 11 (L. 17) The cartoon in Fig. 6G may provide some intuition, but it is quite difficult to interpret. Is there a way to indicate which neuron "votes" for which percept?
This is an excellent idea, and we have added now the purported perceptual relation of each cell in the diagram.
p. 12 (L. 8). "classically assumed" This statement could benefit from a citation. Or maybe "classically" is not the right word?
We have changed 'classically' to 'typically', and now cite classical works from Deutsch and Repp. We think this description makes sense, as the whole concept of bistable percepts has been interpreted as being equidistant (in added or subtracted semitone steps) from the first tone, see e.g. Repp 1997, Fig.2.
p. 12 (L. 12) "...previous studies" of Shepard tone percepts? Of physiology?
We have modified it to 'Relation to previous studies of Shepard tone percepts and their underlying physiology", since this section deals with both.
p. 12 (L. 25) "compatible with cellular mechanisms..." This paragraph seems key to the study and to Major Concern 1, above. What are the dynamics of the task stimuli? How do they compare with the dynamics of neural FM tuning and previously reported studies of bias? And can the authors be more explicit in their interpretation - should direction selective neurons respond preferentially to the Shepard tone stimuli themselves? And/or is there a conceptual framework where the same neurons inform downstream percepts of both FM sweeps and both normal (unbiased) and biased Shepard tones?
The reviewer raises a number of different questions, which we address below:
- Dynamics of the task stimuli in relation to previously reported cellular biasing: The timescales tested in the studies mentioned are similar to what we used in our bias, e.g. Ye et al 2010 used FM sweeps that lasted for up to 200ms, which is quite comparable to our SOA of 150ms.
- Preferred responses to Shepard tones: no, we do not think that there should be preferred responses to Shepard tones, but rather that responses to Shepard tones can be thought of as the combined responses to the constituent tones.
- Conceptual framework where the same neurons inform about FM sweeps and both normal (unbiased) and biased Shepard tones: Our perspective on this question is as follows: To our knowledge, the classical approach to population decoding in the auditory system, i.e. weighted based on preferred frequency, has not been directly demonstrated to be read out inside the brain, and certainly not demonstrated to be read out in only this way in all areas of the brain that receive input from the auditory cortex. Rather it has achieved its credibility by being linked directly with animal performance or match with the presented stimuli. However, these approaches were usually geared towards a representation that can be estimated based on constituent frequencies. Additional response properties of neurons, such as directional selectivity have been documented and analyzed before, however, not been used for explaining the percept. We agree that our use of this cellular response preference in the decoding implicitly assumes that the brain could utilize this as well, however, this seems just as likely or unlikely as the use of the preferred frequency of a neuron. Therefore we do not think that this decoding is any more speculative than the classical decoding. In both cases, subsequent neurons would have to implicitly 'know' the preference of the input neuron, and weigh its input correspondingly.
We have added all the above considerations to the discussion in an abbreviated form.
p. 15 (L. 15). Is there a citation for the drive system?
There is no publication, but an old repository, where the files are available, which we cite now: https://code.google.com/archive/p/edds-array-drive/
p. 16 (L. 24) "position in an octave" It is implied but not explicitly stated that the Shepard tones don't contain the fundamental frequency. Can the authors clarify the relationship between the neural tuning band and the bands of the stimulus. Did a single stimulus band typically fall in a neuron's frequency tuning curve? If not 1, how many?
Yes, it is correct that the concept of fundamental frequency does not cleanly apply to Shepard tones, because it is composed of octave spaced pure tones, but the lowest tone is placed outside the hearing range of the animal and amplitude envelope (across frequencies). Therefore one or more constituent tones of the Shepard tone can fall into the tuning curve of a neuron and contribute to driving the neuron (or inhibiting it, if they fall within an inhibitory region of the tuning curve). The number of constituent tones that fall within the tuning curve depends on the tuning width of the neurons. The distribution of tuning widths to Shepard tones is shown in Fig. S1E, which indicated that a lot of neurons had rather narrow tuning (close to the center), but many were also tuned widely, indicated that they would be stimulated by multiple constituent tones of the Shepard tone. As the tuning bandwidth (Q30: 30dB above threshold) of most cortical neurons in the ferret auditory cortex (see e.g. Bizley et al. Cerebral Cortex, 2005, Fig.12) is below 1, this means that typically not more than 1 tone fell into the tuning curve of a neuron. However, we also observed multimodal tuning-curves w.r.t. to Shepard tones, which suggests that some neurons were stimulated by more than 2 or more constituent tones (again consistent with the existence of more broadly tuned neurons (see same citation). We have added this information partly to the manuscript in the caption of Fig. S1E.
p. 17 (L. 32). "Fig 4" Correct figure ref? This figure appears to be a schematic rather than one displaying data.
Thanks for pointing this out, changed to Fig. 5.
p. 18 (L. 25). "assign a pitchclass" Can the authors refer to a figure illustrating this process?
Added.
p. 19 (L. 17). Is mu the correct symbol?
Thanks. We changed it to phi_i, as in the formula above.
p. 19 (L 19). "convolution" in time? Frequency?
Thanks for pointing this out, the term convolution was incorrect in this context. We have replaced it by "weighted average" and also adapted and simplified the formula.
p. 19 (L 25) "SSTRF" this term is introduced before it is defined. Also it appears that "SSTRF" and "STRF" are sometimes interchanged.
Apologies, we have added the definition, and also checked its usage in each location.
p. 23 (Fig 2) There is a mismatch between panel labels in the figure and in the legend. Bottom right panel (B3), what does time refer to here?
Thanks for pointing these out, both fixed.
p. 24 (L 23) "shifts them away" away from what?
We have expanded the sentence to: "After the bias, the decoded pitchclass is shifted from their actual pitchclass away from the biased pitchclass range ... "
p. 25 (L 7) "individual properties" properties of individual subjects?
Thanks for pointing this out, the corresponding sentence has been clarified and citations added.
p. 26 (L 20) What is plotted in panel D? The average for all cells? What is n?
Yes, this is an average over cells, the number of cells has now been added to each panel.
p. 28 (L 3) How to apply the terms "right" "right" "middle" to the panel is not clear. Generally, this figure is quite dense and difficult to interpret.
We have changed the caption of Panel A and replaced the location terms with the symbols, which helps to directly relate them to the figure. We have considered different approaches of adding or removing content from the figure to help make it less dense, but that all did not seem to help. For lack of better options we have left it in its current form.
MINOR/TYPOS
p. 3 (L 1) "Stimulus Specific Adaptation" Capitalization seems unnecessary
Changed.
p. 4 (L 14) "Siple"
Corrected.
p. 9 (L 10) "an quantitatively"
Corrected
p. 9 (L 20) "directional ... direction ... directly ... directional" This is a bit confusing as directseems to mean several different things in its different usages.
We have gone through these sentences, and we think the terms are now more clearly used, especially since the term 'direction' occurs in several different forms, as it relates to different aspects (cells/percept/hypothesis). Unfortunately, some repetition is necessary to maintain clarity.
Reviewer #2 (Recommendations For The Authors):
Detailed critique
Stimuli
It would be very useful if the authors could provide demos of their stimuli on a website. Many readers will not be familiar with Shepard tones and the perceptual result of the acoustical descriptions are not intuitive. I ended up coding the stimuli myself to get some intuition for them.
We have created some sample tones and sequences and uploaded them with the revision as supplementary documents.
Abstract
P1 L27 'pitch and...selective cells' - The authors haven't provided sufficient controls to demonstrate that these are "pitch cells" or "selective" to pitch direction. They have only shown that they are sensitive to these properties in their stimuli. Controls would need to be included to ensure that the cells aren't simply responding to one frequency component in the complex sound, for example. This is not really critical to the overall findings, but the claim about pitch "selectivity" is not accurate.
Fair point. We have removed the word 'selective' in both occurrences.
Introduction
P2 L14-17: I do not follow the phonetic example provided. The authors state that the second syllable of /alga/ and /arda/ are physically identical, but how is this possible that ga = da? The acoustics are clearly different. More explanation is needed, or a correction.
Apologies for the slightly misleading description, it has now been corrected to be in line with the original reference.
P2,L26-27: Should the two uses of "frequency" be "F0" and "pitch" here? The tones are not separated in frequency by half and octave, but "separated in [F0]" by half an octave, correct? Their frequency ranges are largely overlapping. And the second 'frequency', which refers to the percept, should presumably be "pitch".
Indeed. This is now corrected.
P3 L2-6: Unclear at this point in the manuscript what is the difference between the 3 percepts mentioned: perceived pitch-change direction, Shepard tone pitches, and "their respective differences". (It becomes clear later, but clarification is needed here).
We have tried a few reformulations, however, it tends to overload the introduction with details. We believe it is preferable to present the gist of the results here, and present the complete details later in the MS.
P3 L6-7 What does it mean that the MEG and single unit results "align in direction and dynamics"? These are very different signals, so clarification is needed.
We have phrased the corresponding sentence more clearly.
Results
Throughout: Choose one of 'pitch class', 'pitchclass', or 'pitch-class' and use it consistently.
Done.
P4L12 - would be helpful at this point to define 'repulsive effect'
We have added another sentence to clarify this term.
P4, L14 "simple"
Done
P4, L12 - not clear here what "repulsive influence" means
See above.
P4, L17 - alternative to which explanation? Please clarify. In general, this paragraph is difficult to interpret because we do not yet have the details needed to understand the terms used and the results described. In my opinion, it would be better to omit this summary of the results at the very beginning, and instead reveal the findings as they come, when they can be fully explained to the Reader.
We agree, but we also believe that a rather general description here is useful for providing a roadmap to the results. However, we have added a half-sentence to clarify what is meant by alternative.
P4 L30 - text says that cells adapt in their onset, sustained and offset responses, but only data for onset responses are shown (I think - clarification needed for fig 2A2). Supp figure shows only 1 example cell of sustained and offset, and in fact there is no effect of adaptation in the sustained response shown there.
Regarding the effect of adaptation and whether it can be discerned from the supplementary figure: the shown responses are for 10 repetitions of one particular Bias sequence. Since the response of the cell will depend on its tuning and the specific sequence of the Shepard tones in this Bias, it is not possible to assess adaptation for a given cell. We assess the level of adaptation, by averaging all biases (similar to what is shown in Fig. 2A2) per cell, and then fit an exponential to it, separately by response type. The step direction of the exponential, relative to the spontaneous rate is then used to assess the kind of adaptation. The vast majority of cells show adaptation. We have added this information to the Methods of the manuscript.
P4, L32 - please state the statistical test and criterion (alpha) used to determine that 91% of cells decreased their responses throughout the Bias sequence. Was this specifically for onset responses?
Thanks for pointing this out, test and p-value added. Adaptation was observed for onset, sustained and offset responses, in all cases with the vast majority showing an adapting behavior, although the onset responses were adapting the most.
P4 L36 - "response strength is reduced locally". What does "locally" mean here? Nearby frequencies?
We have added a sentence here to clarify this question.
Figure 1 - this appears to be the wrong version of the figure, as it doesn't match the caption or results text. It's not possible to assess this figure until these things are fixed. Figure 1A schematic of definition of f(diff) does not correspond to legend definition.
As far as we can tell, it is all correct, only the resolution of the figure appears to be rather low. This has been improved now.
Fig 2 A2 - is this also onset responses only?
Yes, added to the caption.
Fig 2 A3 - add y-axis label. The authors are comparing a very wide octave band (5.5 octaves) to a much narrower band (0.5 octaves). Could this matter? Is there something special about the cut-off of 2.5 octaves in the 2 bands, or was this an arbitrary choice?
Interesting question.... essentially our stimulus design left us only with this choice, i.e. comparing the internal region of the bias with the boundary region of the bias, i.e. the test tones. The internal region just corresponds to the bias, which is 5 st wide, and therefore the range is here given as 2.5 st relative to its center, while the test tones are at the boundary, as they are 3 st from the center. The axis for the bias was mislabelled, and has now been corrected. The y-axis label is matched with the panel to the left, but has now been added to avoid any confusion.
Fig 2A4 - does not refer to ferret single unit data, as stated in the text (p5L8). Nor does supp Fig2, as stated. Also, the figure caption does not match the figure.
Apologies, this was an error in the code that led to this mislabelling. We have corrected the labels, which also added back the recovery from the Bias sequence in the new Panel A4.
P5 l9 - Figure 3 is not understandable at this point in the text, and should not be referred to here. There is a lot going on in Fig 3, and it isn't clear what you are referring to.
Removed.
P5 L12 - by Fig 2 B1, I assume you mean A4? Also, F2B1 shows only 1 subject, not 2.
Yes, mislabeled by mistake, and corrected now.
Fig2B2 -What is the y-axis?
Same as in the panel to its left, added for clarity.
Stimuli: why are tones presented at a faster rate to ferrets than to humans?
The main reason is that the response analysis in MEG requires more spacing in time than the neuronal analysis in the ferret brain.
P5 L6 - there is no Fig 5 D2? I don't think it is a good idea to get the reader to skip so far ahead in the figures at this stage anyway, even if such a figure existed. It is confusing to jump around the manuscript
Changed to 'see below'
P5 L8 - There is no Figure 2A4, so I don't know whether this time constant is accurate.
This was in reference to a panel that had been removed before, but we have added it back now.
P5 L16: "in humans appears to be more substantial (40%) than for the average single units under awake conditions". One cannot directly compare magnitude of effects in MEG and single unit signals in this way and assume it is due to behavioural state. You are comparing different measures of neural activity, averaged over vastly different numbers of numbers, and recorded from different species listening to different stimuli (presentation rates).
Yes, that's why the next sentence is: "However, comparisons between the level of adaptation in MEG and single neuron firing rates may be misleading, due to the differences in the signal measured and subsequent processing.", and all statements in the preceding sentences are phrased as 'appears' and 'may'. We think we have formulated this comparison with an appropriate level of uncertainty. Further, the main message here is that adaptation is taking place in both active and passive conditions.
P5 L25 -I do not see any evidence regarding tuning widths in Fig s2, as stated in the text.
Corrected to Fig. S1.
P5 l26 - Do not skip ahead to Fig 5 here. We aren't ready to process that yet.
OK, reference removed.
P5 l27 - Do you mean because it could be tuning to pitch chroma, not height?
Yes, that is a possible interpretation, although it could also arise from a combination of excitatory and inhibitory contributions across multiple octaves.
P5 l33 - remove speculation about active vs passive for reasons given above.
Removed.
P6L2-6 'In the present...5 semitone step' - This is an incorrect interpretation of the minimal distance hypothesis in the context of the Shepard tone ambiguity. The percept is ambiguous because the 'true' F0 of the Shepard tones are imperceptibly low. Each constituent frequency of a single tone can therefore be perceived either as a harmonic of some lower fundamental frequency or as an independent tone. The dominant pitch of the second tone in the tritone pair may therefore be biased to be perceived at a lower constituent frequency (when the bias sequence is low) or at a higher constituent frequency (when the bias sequence is high). The text states that the minimal distance hypothesis would predict that an up-bias would make a tritone into a perfect fourth (5 semitones). This is incorrect. The MDH would predict that an up-bias would reduce the distance between the 1st tone in the ambiguous pair and the upper constituent frequency of the 2nd tone in the pair, hence making the upper constituent frequency the dominant pitch percept of the 2nd tone, causing an ascending percept.
The reviewer here refers to a “minimal distance hypothesis”, which without a literature reference,is hard for us to fully interpret. However, some responses are given below:
- "The percept is ambiguous because the 'true' F0 of the Shepard tones are imperceptibly low." This statement appears to be based on some misconception: due to the octave spacing (rather than multiple/harmonics of a lowest frequency), the Shepard tones cannot be interpreted as usual harmonic tones would be. It is correct that the lowest tone in a Shepard tone is not audible, due to the envelope and the fact that it could in principle be arbitrarily small... hence, speaking about an F0 is really not well-defined in the case of a Shepard tone. The closest one could get to it would be to refer to the Shepard tone that is both in the audible range and in the non-zero amplitude envelope. But again, since the envelope is fading out the highest and lowest constituent tones, it is not as easy to refer to the lowest one as F0 (as it might be much quieter than the next higher constituent.
- "The dominant pitch of the second tone in the tritone pair may therefore be biased to be perceived at a lower constituent frequency (when the bias sequence is low) or at a higher constituent frequency (when the bias sequence is high)." This may relate to some known psychophysics, but we are unable to interpret it with certainty.
- "The text states that the minimal distance hypothesis would predict that an up-bias would make a tritone into a perfect fourth (5 semitones). This is incorrect." We are unsure how the reviewer reaches this conclusion.
- "The MDH would predict that an up-bias would reduce the distance between the 1st tone in the ambiguous pair and the upper constituent frequency of the 2nd tone in the pair, hence making the upper constituent frequency the dominant pitch percept of the 2nd tone, causing an ascending percept." Again, in the absence of a reference to the MDH, we are unsure of the implied rationale. We agree that this is a possible interpretation of distance, however, we believe that our interpretation of distance (i.e. distances between constituent tones) is also a possible interpretation.
Fig 4: Given that it comes before Figure 3 in the results text, these should be switched in order in the paper.
Switched.
PCA decoder: The methods (p18) state that the PCA uses the first 3 dimensions, and that pitch classes are calculated from the closest 4 stimuli. The results (P6), however, state that the first 2 principal components are used, and classes are computed from the average of 10 adjacent points. Which is correct, or am I missing something?
Thanks for pointing this out, we have made this more concrete in the Methods to: "The data were projected to the first three dimensions, which represented the pitch class as well as the position in the sequence of stimuli (see Fig. 43A for a schematic). As the position in the Bias sequence was not relevant for the subsequent pitch class decoding, we only focussed on the two dimensions that spanned the pitch circle." Regarding the number of stimuli that were averaged: this might be a slight misunderstanding: Each Shepard tone was decoded/projected without averaging. However, to then assign an estimated pitch class, we first had to establish an axis (here going around the circle), where each position along the axis was associated with a pitch class. This was done by stepping in 0.5 semitone steps, and finding the location in decoded space that corresponded to the median of the Shepard tones within +/- 0.25st. To increase the resolution, this circular 'axis' of 24 points was then linearly interpolated to a resolution of 0.05st. We have updated the text in the Methods accordingly. The mentioning of 10 points for averaging in the Results was correct, as there were 240 tones in all bias stimuli, and 24 bins in the pitch circle. The mentioning of an average over 4 tones in the Methods was a typo.
Fig 3A: axes of pink plane should be PC not PCA
Done.
Fig 3B: the circularity in the distribution of these points is indeed interesting! But what do the authors make of the gap in the circle between semitones 6-7? Is this showing an inherent bias in the way the ambiguous tone is represented?
While we cannot be certain, we think that this represents an inhomogeneous sampling from the overall set of neural tuning preferences, and that if we had recorded more/all neurons, the circle would be complete and uniformly sampled (which it already nearly is, see Fig.4C, which used to be Fig. 3C).
Fig 3B (lesser note): It'd be preferable to replace the tint (bright vs. dark) differentiation of the triangles to be filled vs. unfilled because such a subtle change in tint is not easily differentiable from a change in hue (indicating a different variable in this plot) with this particular colour palette
We have experimented with this suggestion, and it didn't seem to improve the clarity. However, we have changed the outline of the test-pair triangles to white, which now visually separates them better.
P6 l32 - Please indicate if cross-validation was used in this decoder, and if so, what sort. Ideally, the authors would test on a held-out data set, or at least take a leave-one-out approach. Otherwise, the classifier may be overfit to the data, and overfitting would explain the exceptional performance (r=.995) of the classifier.
Cross-validation was not used, as the purpose of the decoder is here to create a standard against which to compare the biased responses in the ambiguous pair, which were not used for training of the decoder. We agree that if we instead used a cross-validated decoder (which would only apply to the local average to establish the pitch class circle) the correlation would be somewhat lower, however, this is less relevant for the main question, i.e. the influence of the Bias sequence on the neural representation of the ambiguous pair. We have added this information to the corresponding section.
Fig 3D: I understood that these pitch classifications shown by the triangles were carried out on the final ambiguous pair of stimuli. I thought these were always presented at the edges of the range of other stimuli, so I do not follow how they have so many different pitchclass values on the x-axis here.
There were 4 Biases, centered at 0,3,6 or 9 semitones, and covering [-2.5,2.5]st relative to this center. Therefore the edges of the bias ranges (3st away from their centers) happen to be the same as the centers, e.g. for the Bias centered at 3, the ambiguous pair would be a 0-6 or 6-0 step. Therefore there are 4 locations for the ambiguous tones on the x-axis of Fig. 4D (previously 3D).
Figure 4: This demonstration of the ambiguity of Shepard pairs may be misleading. The actual musical interval is never ambiguous, as this figure suggests. Only the ascending vs descending percept is ambiguous. Therefore the predictions of the ferret A1 decoding (Fig 3D) and the model in Fig 5 are inconsistent with perception in two ways. One (which the authors mention) is the direction of the bias shift (up vs down). Another (not mentioned here) is that one never experiences a shift in the shepard tone at a fraction of a semitone - the musical note stays the same, and changes only in pitch height, not pitch chroma.
We are unsure of the reviewer’s direction with this question. In particular the second point is not clear to us: "...one (who?) never (in this experiment? in real life?) experiences a bias shift in the Shepard tone at a fraction of a semitone" (why is this relevant in the current experiment?). Pitch chrome would actually be a possible replacement for pitch class, but somehow, the previous Shepard tone literature has referred to it as pitch class.
P7 l12 - omit one 'consequently'
Changed to 'Therefore'.
P7 l24 - I encourage the authors to not use "local" and "global" without making it clear what space they refer to. One tends to automatically think of frequency space in the auditory system, but I think here they mean f0 space? What is a "cell close to the location of the bias"? Cells reside in the brain. The bias is in f0 space. The use of "local" and "global" throughout the manuscript is too vague.
Agreed, the reference here was actually to the cell's preferred pitch class, not its physical location (which one might arguably be able to disambiguate, given the context). We have changed the wording, and also checked the use of global/local throughout the manuscript. The main use of 'global/local' is now in reference to the range of adaptation, and is properly introduced on first mention.
P7 L26 -there is no Fig 5D1. Do you mean the left panel of 5D?
Thanks. Changed.
FigS3 is referred to a lot on p7-8. Should this be moved to the main text?
The main reason why we kept it in the supplement is that it is based on a more static model, which is intended to illustrate the consequences of different encoding schemes. In order to not confuse the reader about these two models, we prefer to keep it in the supplement, which - for an online journal - makes little difference since the reader can just jump ahead to this figure in the same way as any other figure.
Fig 5C, D - label x-axis.
Added.
Fig 5E - axis labels needed. I don't know what is plotted on x and y, and cannot see red and green lines in left plot
Thanks for noticing this, colors corrected, axes labeled.
Page 8 L3-15 - If I follow this correctly, I think the authors are confusing pitch and frequency here in a way that is fundamental to their model. They seem to equate tonotopic frequency tuning to pitch tuning, leading to confused implications of frequency adaptation on the F0 representation of complex sounds like Shepard tones. To my knowledge, the authors do not examine pure tone frequency tuning in their neurons in this study. Please clarify how you propose that frequency tuning like that shown in Fig 5A relates to representation of the F0 of Shepard tones. Or...are the authors suggesting these neural effects have little to do with pitch processing and instead are just the result of frequency tuning for a single harmonic of the Shepard tones?
We agree that it is not trivial to describe this well, while keeping the text uncluttered, in particular, because often tuning properties to stimulus frequency contribute to tuning properties of the same neuron for pitch class, although this can be more or less straightforward: specifically, for some narrowly tuned cells, the Shepard tuning is simply a reflection of their tuning to a single octave range of the constituent tones (see Fig. S1). For more broadly tuned cells, multiple constituent tones will contribute to the overall Shepard tuning, which can be additive, subtractive, or more complex. The assumption in our approach is that we can directly estimate the Shepard tuning to evaluate the consequence for the percept. While this may seem artificial, as Shepard tones do not typically occur in nature, the same argument could be made against pure tones, on which classical tuning curves and associated decodings are often based. Relating the Shepard tuning to the classical tuning would be an interesting study in itself, although arguably relating the tuning of one artificial stimulus to another. Regarding the terminology of pitch, pitch class and frequency: The term pitch class is commonly used in the field of Shepard tones, and - as we indicated in the beginning of the results: "the term pitch is used interchangeably with pitch class as only Shepard tones are considered in this study". We agree that the term pitch, which describes the perceptual convergence/construction of a tone-height from a range of possible physical stimuli, needs to be separated from frequency as one contributor/basis for the perception of a pitch. However, we think that the term pitch can - despite its perceptual origin - also be associated with neuron/neural responses, in order to investigate the neural origin of the pitch percept. At the same time, the present study is not targeted to study pitch encoding per se, as this would require the use of a variety of stimuli leading to consistent pitch percepts. Therefore, pitch (class) is here mainly used as a term to describe the neural responses to Shepard tones, based on the previous literature, and the fact that Shepard tones are composite stimuli that lead to a pitch percept. The last sentence has been added to the manuscript for clarity.
P7-9: I wasn't left with a clear idea of how the model works from this text. I assume you have layers of neurons tuned to frequency or f0 (based on the real data?), which are connected in some way to produce some sort of output when you input a sound? More detail is needed here. How is the dynamic adaptation implemented?
The detailed description of the model can be found in the Methods section. We have gone through the corresponding paragraph and have tried to clarify the description of the model by introducing a high-level description and the reference to the corresponding Figure (Fig. 5A) in the Results.
Fig6A: Figure caption can't be correct. In any case, these equations cannot be understood unless you define the terms in them.
We have clarified the description in the caption.
Fig 6/directionality analysis: Assuming that the "F" in the STRFs here is Shepard tone f0, and not simple frequency?
We have changed the formula in the caption and the axis labels now.
Fig 6C - y-axis values
In the submission, these values were left out on purpose, as the result has an arbitrary scale, but only whether it is larger or smaller than 0 counts for the evaluation of the decoded directionality (at the current level of granularity). An interesting refinement would be to relate the decoded values to animal performance. We have now scaled the values arbitrarily to fit within [-1,1], but we would like to emphasize that only their relative scale matters here, not their absolute scale.
Fig 6E - can't both be abscissa (caption). I might be missing something here, but I don't see the "two stripes" in the data that are described in the caption.
Thank you. The typo is fixed. The stripes are most clearly visible in the right panel of Fig. 6E, red and blue, diagonally from top left to bottom right.
Fig 6G -I have no idea what this figure is illustrating.
This panel is described in the text as follows: "The resulting distribution of activities in their relation to the Bias is, hence, symmetric around the Bias (Fig. 6G). Without prior stimulation, the population of cells is unadapted and thus exhibits balanced activity in response to a stimulus. After a sequence of stimuli, the population is partially adapted (Fig. 6G right), such that a subsequent stimulus now elicits an imbalanced activity. Translated concretely to the present paradigm, the Bias will locally adapt cells. The degree of adaptation will be stronger, if their tuning curve overlaps more with the biased region. Adaptation in this region should therefore most strongly influence a cell’s response. For example, if one considers two directional cells, an up- and a down-selective cell, cocentered in the same frequency location below the Bias, then the Bias will more strongly adapt the up-cell, which has its dominant, recent part of the SSTRF more inside the region of the Bias (Fig. 6G right). Consistent with the percept, this imbalance predicts the tone to be perceived as a descending step relative to the Bias. Conversely, for the second stimulus in the pair, located above the Bias, the down-selective cells will be more adapted, thus predicting an ascending step relative to the previous tone."
I might be just confused or losing steam at this point, but I do not follow what has been done or the results in Fig 6 and the accompanying text very well at all. Can this be explained more clearly? Perhaps the authors could show spike rate responses of an example up-direction and down-direction neuron? Explain how the decoder works, not just the results of it.
We agree that we are presenting something new here. However, it is conceptually not very different from decoding based on preferred frequencies. We have attempted to provide two illustrations of how the decoder works (Fig. 6A) and how it then leads to the percept using prototypical examples of cellular SSTRFs (Fig. 6G). We have added a complete, but accessible description to the Methods section. Showing firing rates of neurons would unfortunately not be very telling, given the usual variability in neural response and the fact that our paradigm did not have a lot of repetitions (but instead a lot of conditions), which would be able to average out the variability on a single neuron level.
Discussion - I do not feel I can adequately critique the author's interpretation of the results until I understand their results and methods better. I will therefore save my critique of the discussion section for the next round of revisions after they have addressed the above issues of disorganization and clarity in the manuscript.
We hope that the updated version of the manuscript provides the reviewer now with this possibility.
Methods
P15L7 - gender of human subjects? Age distribution? Age of ferrets?
We have added this information.
P16L21 - What is the justification for randomizing the phase of the constituent frequencies?
The purpose of the randomization was to prevent idiosyncratic phase relationships for particular Shepard tones, which would depend in an orderly fashion on the included base-frequencies if non-randomized, and could have contributed to shaping the percept for each Shepard tone in a way that was only partly determined by the pitch class of the Shepard tone. Added to the section.
P17L6 - what are the 2 randomizations? What is being randomized?
Pitch classes and position in the Bias sequence. Added to the section.
P16 Shepard Tuning section - What were the durations of the tones and the time between tones within a trial?
Thanks, added!
Equations - several undefined terms in the equations throughout the manuscript.
Thanks. We have gone through the manuscript and all equations and have introduced additional definitions where they had been missing.
Reviewer #3 (Recommendations For The Authors):
P3L10: "passive" and "active" conditions come totally out of the blue. Need introducing first. (Or cut. If adaptation is always seen, why mention the two conditions if the difference is not relevant here?)
We have added an additional sentence in the preceding paragraph, that should clarify this. The reason for mentioning it is that otherwise a possible counter-argument could be made that adaptation does not occur in the active condition, which was not tested in ferrets (but presents an interesting avenue for future research).
P3L14 "siple" typo
Corrected.
P4L1 "behaving humans" you should elaborate just a little here on what sort of behavior the participants engaged in.
Thanks for pointing this out. We have clarified this by adding an additional sentence directly thereafter.
P4 adaptation: I wonder whether it would be useful to describe the Bias condition a bit more here before going into the observations. The reader cannot know what to expect unless they jump ahead to get a sense of what the Bias looks like in the sense of how many stimuli are in it, and how similar they are to each other. Observations such as "the average response strength decreases as a function of the position in the Bias sequence" are entirely expected if the Bias is made up of highly repetitive material, but less expected if it is not. I appreciate that it can be awkward to have Methods after Results, but with a format like that, the broad brushstroke Methods should really be incorporated into the Results and only the tedious details should be reserved for the Methods to avoid readers having to jump back and forth.
Agreed, we have inserted a corresponding description before going into the details of the results.
Related to this (perhaps): Bottom of P4, top of P5: "significantly less reduced (33%, p=0.0011, 2 group t-test) compared to within the bias (Fig. 2 A3, blue vs. red), relative to the first responses of the bias" ... I am at a loss as to what the red and blue symbols in Fig 2 A3 really show, and I wonder whether the "at the edges" to "within the Bias" comparison were to make sense if at this stage I had been told more about the composition of the Bias sequence. Do the ambiguous ('target') tones also occur within the Bias? As I am unclear about what is compared against what I am also not sure how sound that comparison is.
We have added an extended description of the Bias to the beginning of this section of the manuscript. For your reference: the Shepard tones that made up the ambiguous tones were not part of the Bias sequence, as they are located at 3st distance from the center of the Bias (above and below), while the Bias has a range of only +/- 2.5st.
Fig 2: A4 B1 B2 labels should be B1 B2 B3
Corrected.
Fig 2 A2, A3: consider adjusting y-axis range to have less empty space above the data. In A3 in particular, the "interesting bit" is quite compressed.
Done, however, while still matching the axes of A2 and A3 for better comparability.
I am under the strong impression that the human data only made it into Fig 2 and that the data from Fig 3 onwards are animal data only. That is of course fine (MEG may not give responses that are differentiated enough to perform the sort of analyses shown in the later figures. But I do think that somewhere this should be explicitly stated.
Yes, the reviewer's observation is correct. The decoding analyses could not be conducted on the human MEG data and was therefore not further pursued. Its inclusion in the paper has the purpose of demonstrating that even in humans and active conditions, the local adaptation is present, which is a key contributor to the two decoding models. We now state this explicitly when starting the decoding analysis.
P5L2 "bias" not capitalized. Be consistent.
All changed to capitalized.
P5L8 reference to Fig 2 A4: something is amiss here. From legend of Fig 2 it seems clear that panel A4 label is mislabeled B1. Maybe some panels are missing to show recovery rates?
Apologies for this residual text from a previous version of the manuscript. We have gone through all references and corrected them.
P6L7 comma after "decoding".
Changed.
Fig 3, I like this analysis. What would be useful / needed here though is a little bit more information about how the data were preprocessed and pooled over animals. Did you do the PCA separately for each animal, then combine, or pool all units into a big matrix that went into the PCA? What about repeat, presentations? Was every trial a row in the matrix, or was there some averaging over repeats? (In fact, were there repeats??)
Thanks for bringing up these relevant aspects, which were partly insufficiently detailed in the manuscript. Briefly, cells were pooled across animals and we only used cells that could meaningfully contribute to the decoding analysis, i.e. had auditory responses and different responses to different Shepard tones. Regarding the responses, as stated in the Methods, "Each stimulus was repeated 10 times", and we computed average responses across these repetitions. Single trials were not analyzed separately. We have added this information in the Methods, and refer to it in the Results.
Also, there doesn't appear to be a preselection of units. We would not necessarily expect all cortical neurons to have a meaningful "best pitch" as they may be coding for things other than pitch. Intuitively I suspect that, perhaps, the PCA may take care of that by simply not assigning much weight to units that don't contribute much to explained variance? In any event I think it should be possible, and would be of some interest, to pull out of this dataset some descriptive statistics on what proportion of units actually "care about pitch" in that they have a lot (or at least significantly more than zero) of response variance explained by pitch. Would it make sense to show a distribution of %VE by pitch? Would it make sense to only perform the analysis in Fig 3 on units that meet some criterion? Doing so is unlikely to change the conclusion, but I think it may be useful for other scientists who may want to build on this work to get a sense of how much VE_pitch to expect.
We fully agree with the reviewer, which is why this information is already presented in Supplementary Fig.1, which details the tuning properties of the recorded neurons. Overall, we recorded from 1467 neurons across all ferrets, out of which 662 were selected for the decoding analysis based on their driven firing rate (i.e. whether they responded significantly to auditory stimulation) and whether they showed a differential response to different Shepard tones The thresholds for auditory response and tuning to Shepard tones were not very critical: setting the threshold low, led to quantitatively the same result, however, with more noise. Setting the thresholds very high, reduced the set of cells included in the analysis, and eventually that made the results less stable, as the cells did not cover the entire range of preferences to Shepard tones. We agree that the PCA based preprocessing would also automatically exclude many of the cells that were already excluded with the more concrete criteria beforehand. We have added further information on this issue in the Methods section under the heading 'Unit selection'.
P9 "tones This" missing period.
Changed.
P10L17 comma after "analysis"
Changed.
Furthermore, our research demonstrates that the acceptance rate rises over time and is particularly high among less experienced developers, providing them with substantial benefits.
less experienced developers accept more suggeted code (copilot) and benefit relatively versus more experienced developers. Suggesting that the set ways of experienced developers work against fully exploting code generation by genAI.
4 automatically adjust the layout 5 show the figure
Hier ist die Beschriftung des Codes verrückt. Punkt 4 und 5 weisen auf die falschen Zeilen im Code.
may serve as illustrations
The author of this "working definition," Kenneth Stern, has made plain that the legal formalization of IHRA is an "attack on academic freedom and free speech," and that IHRA should never have been adopted as "campus hate speech code."
servo_jp()o Which takes a 1x4 array of joint values in degrees to be sent directly to the actuators andbypasses interpolation● interpolate_jp()o Which takes a 1x4 array of joint values and an interpolation time in ms to get there● measured_js()o Which takes two boolean values, named GETPOS and GETVEL. Only return the results forthe requested data, and set the rest to zero. This will be important because if we want tocollect position data very fast, we will not want to slow the system down by also acquiringunnecessary velocity data.o Which returns a 2x4 array that contains current joint positions in degrees (1st row) and/orcurrent joint velocities (2nd row).● setpoint_js()o Which returns a 1x4 array that contains current joint set point positions in degrees. Ifinterpolation is being used and you request this during motion, it will return the currentintermediate set point.● goal_js()o Which returns a 1x4 array that contains the end-of-motion joint setpoint positions indegrees. Note that this should be stored directly in your robot object (be sure to set it abovewhen making new setpoints), it does not need to be requested from the controller.
These would all be separated into their own code blocks with function requirements and demo instructions in text blocks above
Sign-off #3: Validate that your new code works fine with the robot. Show an SA the functions, themworking, and your Git log.
This sign off was a pain. It would have been easier to check if students made their robot do a little show.
Sign off 3: * Demonstrate servo_jp() by moving between two joint positions * Demonstrate interpolate_jp() by moving between the same two positions over 10 seconds * Interpolate between XXXX and YYYY over 20 seconds while printing out measured_js * Interpolate between YYYY and XXXX over 20 seconds while printing out setpoint_js * Interpolate between XXXX and YYYY over 20 seconds while printing out goal_js
Sign-off #2: Demonstrate to an SA that your Git repository is set up properly and demonstrate that youcan use Git commands in a terminal.
This sign off needs to change a bit. I want this to become a "git practical".
Engagement marker: Student A: Add a comment to lab_1.mlx, and push it to a new branch
Students B&C: Pull student A's code, and show what happens to your file when you switch branches
Sign-off #1: Demonstrate to an SA that your system is configured properly and the MATLAB sample codein lab1_base.m works as expected (the command is sent to the arm and sensor data is received)
This sign off is perfect as is--maybe it's so simple it's not even necessary. Run the provided code, show me that your robot moves in an arc, that's all I need to see.
Honestly I don't even know if there are any comprehension questions I can add that align with the LOs of the course. This is just a logistical step.
Welcome back and in this demo lesson you're going to get the experience of bootstrapping an EC2 instance using user data.
So this is the ability to run a script during the provisioning process for an EC2 instance and automatically add a certain configuration to that instance during the build process.
So this is an alternative to creating a custom AMI.
Earlier in the course you created an Amazon machine image with the WordPress installation and configuration baked in.
Now that's really quick and simple but it does limit your ability to make changes to that configuration.
So the configuration is baked into the AMI and so you're limited as to what you can change during launch time.
With boot strapping you have the ability to perform all the steps in the form of a script during the provisioning process and so it can be a lot more flexible.
Now to get started we need to create the Animals for Life VPC within our general AWS account.
So this is the management account of the organization.
So make sure that you're logged into the IAM admin user of this account and as always make sure you have the Northern Virginia region selected.
Now attached to this lesson is a one-click deployment link so go ahead and open that.
This is going to take you to the quick create stack page and everything should be pre-populated.
The stack name should be bootstrap everything else has appropriate default so just scroll down to the bottom, check the capabilities acknowledgement box and then go ahead and click on create stack.
Now this will create the Animals for Life VPC which contains the public subnets that we'll be launching our instance into and so we're going to need this to be in a create complete state before we move on.
So go ahead and pause the video and once your stack changes from create in progress to create complete then we good to continue.
Okay so now that that stack has moved into a create complete state we good to continue.
Now also attached to this lesson is another link which is the user data that we're going to use for this demo lesson so go ahead and open that link.
This is the user data that we're going to use to bootstrap the EC2 instance so what I want you to do is to download this file to your local machine and then open it in a code editor or alternatively just copy all the text on screen now and paste that into a code editor.
So I've gone ahead and opened that file in my text editor and if you look through all of the different commands contained within this user data .txt file then you should recognize some of them.
These are basically the commands that we ran earlier in the course when we manually installed word press and when we created the Amazon machine image.
So we're essentially installing the MariaDB database server, the Apache web server, Wget and Cowsay.
We're installing PHP and its associated libraries.
We're making sure that both the database and the web server are set to automatically start when the instance reboots and are explicitly started when this script is run.
We're setting the root password of the MariaDB database server.
We're downloading the latest copy of the WordPress installation archive.
We're extracting it and we're moving the files into the correct locations.
Then we're configuring WordPress by copying the sample configuration file into the final and proper file name so wp-config.php and then we're performing a search and replace on those placeholders and replacing them with our actual chosen values for the database name, the database user and the database password.
And then after that we're fixing up the permissions on the web root folder with the WordPress installation files inside so we're making sure that the ownership is correct and then we're fixing up the permissions with a slightly improved version of what we've used previously.
Then we're creating our DB.setup script in the same way that we did when we were manually installing WordPress.
We're logging into the database using the MySQL command line utility, authenticating as the root user with the root password and then running this script and this creates the WordPress database, the user sets the password and gives that user permissions on the database.
And then finally we're configuring the Cowsay utility so we're setting up the message of the day file we're outputting our animals for life custom greeting and then we're forcing a refresh of the login banner.
So these are all of the steps that you've previously done manually so I hope it's still fresh in your memory just how annoying that manual installation was.
Okay so at this point this user data is ready to go and I want to demonstrate to you how you can use this to bootstrap an EC2 instance.
So let's go ahead and move back to the AWS console.
Once we're at the AWS console this CloudFormation 1 click deployment has created the Animals for Life VPC.
So what we're going to do is to click on the services drop down and then move to the EC2 console and go ahead and click on launch instance followed by launch instance again.
So first things first the instance is going to be called a4l for animals for life - manual WordPress so go ahead and enter that in the box at the top then scroll down select Amazon Linux and then make sure Amazon Linux 2023 is selected in the drop down and then make sure that you've got 64-bit x86 selected.
I want you to pick whichever type is free tier eligible within your account and region in my case it's t2.micro but you should pick the one that's free tier eligible.
Under key pair go ahead and pick proceed without a key pair then scroll down to network settings and click on edit and there are a few items on this page that we need to explicitly configure.
The first is we need to select the Animals for Life VPC next to network so select a4l -vpc1 next to subnet I want you to go ahead and pick sn -web -a so that's the web or public subnet within availability zone a then make sure auto assign public IP is set to enable we'll be using an existing security group so check that box and then in the drop down so click the drop down and select the bootstrap -instance security group so bootstrap was the name of the cloud formation stack that we created using the one-click deployment we won't be making any changes to the storage configuration and next we need to scroll down to an option that we've not used before we're going to enter some user data so scroll all the way down and under advanced details expand this if it isn't already and you're looking for the user data box what we're going to do is paste in the user data that you just downloaded so in my case this is the user data.txt which I downloaded so I'm going to go ahead and select all of the information in this user data.txt making sure I get everything including the last line and I'm going to copy that into my clipboard now back at the AWS console we need to paste that in to the user data box now by default EC2 accepts user data as base64 encoded data so we need to provide it with base64 encoded data and we're not we're just giving it a normal text file so in this case the user interface can actually do this conversion for us so if what you're pasting in is not base64 encoded and what we're pasting in isn't then we don't need to do anything else if we're pasting in data which is already base64 encoded we need to check this box below the user data box we don't need to worry about that because we're not pasting in anything with base64 encoding so we can just paste in our user data directly into this box and this will be run during the instance launch process so this is where our automatic configuration comes from this is what will bootstrap the EC2 instance okay so that's everything we need to configure so go ahead and click on launch instance now at this point while this is launching I want you to keep in mind that in the previous demo examples in this course we manually launched an instance and then once the instance was in a running state we had to connect into it download WordPress install WordPress and then configure WordPress along with all of the other associated dependencies that WordPress requires so that was a fairly time-intensive process that was open to errors in the AMI example we followed that same process but at the end we created the Amazon machine image so keep that in mind and compare it to what your experience is in this demo lesson so now we've launched the instance and it's now in a running state and we've provided some user data to this instance so I want you to leave it a couple of minutes after it's showing in a running state just give it a brief while to perform that additional configuration after a few minutes go ahead and right click on that instance and select connect we're going to be using EC2 instance connect so make sure that's selected make sure the user is set to EC2 - user and then just click connect now what you should see if we've given this enough time is our custom animals for life login banner and that means that the bootstrapping process has completed think about this for a minute as part of the launch process EC2 has provisioned us an EC2 instance and it's also run a relatively complex installation and configuration script that we've supplied in the form of user data and that's downloaded and installed WordPress and configured our custom login banner if we go back to EC2 select instances and then if we copy the public IP address into our clipboard so copy the actual IP address do not click on this link because this will open it using HTTPS which we haven't configured if you take that IP address and open that in a new tab you'll see the installation dialogue for WordPress and that's because the bootstrapping process using the user data has done all the configuration process that previously we've had to do manually now if we go back to the instance I want to demonstrate architecturally and operationally exactly how this works what we can do is use the curl utility to review the instance metadata now because we're using Amazon Linux 2023 we need to do this slightly differently we need to use version 2 of the metadata service so first we need to run this command to get a token which we can use to authenticate to the metadata service so run this next we can run this command which gets us the metadata of the instance and this uses the 169254 169254 address or as I like to call it 169.254 repeating now if we use this with meta hyphen data on the end then we get the metadata service but as we know user data is a component of the metadata service so instead of using forward slash latest forward slash metadata we can replace metadata with user data and this will allow us to see the user data supplied to the instance and don't worry all of these commands will be attached to the lesson so you should recognize this this is the user data that we passed into the instance so this is performed a download a configuration and an installation of Apache the database server and WordPress as well as our custom login banner so that's how the user data gets into the EC2 instance and there's a service running on the EC2 instance which takes this data and automatically performs these configuration steps essentially this is run as a script on the operating system now something else we can do is to move into the forward slash VAR forward slash log folder and this is a folder which contains many of the system logs and if we do an LS space hyphen LA we'll see a collection of logs within this folder there are two logs in particular that are really useful for diagnosing bootstrapping related problems these logs are cloud hyphen init dot log and cloud hyphen init hyphen output dot log and both of these are used for slightly different reasons so what I want to do is to output one of these logs and show you the content so we're going to output using shudu first to get admin permissions and then cat and we're going to use the cloud hyphen init hyphen output dot log and I'm going to press enter and that's going to show you the contents of this file and you'll be able to see using this log file exactly what's been executed on this EC2 instance so you'll be able to see all of the actual commands and the output from those commands as they've been executed on this EC2 instance so you'll be able to see all of the WordPress related downloads and copies the replacements of the database usernames and passwords the permissions fix section the database creation user creation and then permissions on that database as well as the command that actually executes those and then right at the bottom is where we configure our custom login banner so this is how you can see exactly what's been run on this EC2 instance and if you ever encounter any issues with any of the demo lessons within this course or any of my courses then you can use this file to determine exactly what's happened on the EC2 instance as part of the bootstrapping process okay so this is the end of part one of this lesson it was getting a little bit on the long side and so I wanted to add a break it's an opportunity just to take a rest or grab a coffee part two will be continuing immediately from the end of part one so go ahead complete the video and when you're ready join me in part two.
AbstractGlobal changes in Cannabis legislation after decades of stringent regulation, and heightened demand for its industrial and medicinal applications have spurred recent genetic and genomics research. An international research community emerged and identified the need for a web portal to host Cannabis-specific datasets that seamlessly integrates multiple data sources and serves omics-type analyses, fostering information sharing.The Tripal platform was used to host public genome assemblies, gene annotations, QTL and genetic maps, gene and protein expression, metabolic profile and their sample attributes. SNPs were called using public resequencing datasets on three genomes. Additional applications, such as SNP-Seek and MapManJS, were embedded into Tripal. A multi-omics data integration web-service API, developed on top of existing Tripal modules, returns generic tables of sample, property, and values. Use-cases demonstrate the API’s utility for various -omics analyses, enabling researchers to perform multi- omics analyses efficiently.
This work has been published in GigaByte Journal under a CC-BY 4.0 license (https://doi.org/10.46471/gigabyte.137). These reviews are as follows.
Reviewer 1. Weiwen Wang
Is the code executable?
Unable to test.
This manuscript is about an online platform, and I am not sure how to test the code.
Is installation/deployment sufficiently outlined in the paper and documentation, and does it proceed as outlined?
Same as above.
Additional Comments:
With the increasing legalization of cannabis in many countries today, exploring this crop has become a hot topic of research. This manuscript by Mansueto et al. introduces a platform built on the Tripal framework, designed to facilitate multi-omics research in Cannabis sativa. The platform integrates genomic, transcriptomic, proteomic, and metabolomic data, providing researchers with a comprehensive resource for data analysis and sharing. Additionally, APIs have been developed, enabling rapid querying. This manuscript detailed information on how to customize Tripal modules and Chado schema for managing biological entities. Finally, this manuscript highlights the importance of standardization in data storage and analysis, proposing community-wide adoption of standardized nomenclature to ensure consistency and traceability of data. Overall, the platform is poised to become a valuable resource for cannabis research and to advance scientific progress in related fields.
While this manuscript was engaging, particularly in the sections on Tripal "re-engineering" and controlled vocabulary, I do have several concerns.
1 Because my registration (using business email) has not been approved, I cannot test the functions requiring ICGRC registration.
2 The authors noted that the Cannabis Genome Browser has not been updated. Do the authors have a plan for updating ICGRC? If so, what is the proposed update frequency?
3 ICGRC currently includes only a few cannabis cultivars, especially when compared to other platforms like Kannapedia and CannabisGDB. Do the authors have plans to add additional cultivars, such as First Light and Jamaican Lions mentioned in this manuscript, in the near future?
4 When I tried to register using Gmail, an error popped up: ‘Domain is not allowed to register for this site’. Perhaps it would be clearer to instruct users to use a business email for registration directly.
5 There is a data submission function in ICGRC, but the exact workings of this feature remain unclear to me. If a user submits a cannabis genome to the ICGRC, whether this data will be visualized within specific modules like synteny search or genetic mapping tools on the platform.
Reviewer 2. Hongyun Shang
Is the code executable?
Unable to test.
Is installation/deployment sufficiently outlined in the paper and documentation, and does it proceed as outlined?
Unable to test.
This is a comprehensive database with many features that improves the shortcomings of cannabis species that had no genome database in the past. It is a good work. Here are some minor suggestions:
Culture as the ‘genetic code’ of the next leap
for - article - The End of Scarcity? From ‘Polycrisis’ to Planetary Phase Shift - Nafeez Ahmed - gene-culture coevolution - adjacency - indyweb dev - individual / collective evolutionary learning - provenance - tracing the evolution of ideas - gene-culture coevolution
adjacency - between - indyweb dev - individual / collective evolutionary learning - provenance - tracing the evolution of ideas - gene-culture coevolution - adjacency relationship - As DNA and epigenetics plays the role of transmitting biological adaptations, language and symmathesy play the role of transmitting cultural adaptations
Overall Assessment (4/5)
Summary: The authors provide a software tool NeuroVar that helps visualizing genetic variations and gene expression profiles of biomarkers in different neurological diseases.
Technical Release criteria
Is the language of sufficient quality? * The language quality of the document is of sufficient quality. I did not notice any major issues.
Is there a clear statement of need explaining what problems the software is designed to solve and who the target audience is? * Yes, authors provide a statement of need. Authors mention that there is the need for a specialized software tool to identify genes from transcriptomic data and genetic variations such as SNPs, specifically for neurological diseases. Perhaps authors could expand on how they chose the diseases. E.g. stroke is not listed among the neurological diseases. Perhaps authors could expand a bit on the diseases they chose in the introduction.
Is the source code available, and has an appropriate Open Source Initiative license been assigned to the code? * Yes the source code is available in github under the following link: https://github.com/omicscodeathon/neurovar. Additionally authors deposited the source code and additional supplementary data in a permanent depository with zenodo under the following DOI: https://zenodo.org/records/13375493. They also provided test data https://zenodo.org/records/13375591. I was able to download and access the complete set of data
As Open Source Software are there guidelines on how to contribute, report issues or seek support on the code? * I did not find any way to contribute, report issues or seek support. I would recommend that the authors add this information to the Github README file.
Is the code executable? * Yes, I could execute the code using Rstudio 4.3.3
Is the documentation provided clear and user friendly? * The documentation is provided and is user friendly. I was able to install, test and run the tool using RStudio. Authors may consider to offer also a simple website link for the RshinyTools if possible. This may enable the access also for scientists that are not familiar with R.Especially, it is great that authors provided a demonstration video. I was able to reproduce the steps. However, I would recommend to add more information into the Youtube video. E.g. reference to the preprint/ paper and Github link would be helpful to connect the data. Perhaps authors could also expand a bit on the possibilities to export data from their software. And provide different formats e.g., PDF / PNG /JPEG. I think this is important for many researchers to export their outputs e.g., from the heatmaps.
Is installation/deployment sufficiently outlined in the paper and documentation, and does it proceed as outlined? * I could follow the installation process, but perhaps authors could add few more details how to download from Github in more detail. As some scientist may have trouble with it. Also perhaps an installation video (additionally to the video demonstration of the Neurovar Shiny App might be helpful.·
Is there a clearly-stated list of dependencies, and is the core functionality of the software documented to a satisfactory level? * Yes, dependencies are listed and are installed automatically. It worked for me with Rstudio version 4.3.3. In the manuscript and in the
Have any claims of performance been sufficiently tested and compared to other commonly-used packages? * not applicable
Are there (ideally real world) examples demonstrating use of the software? * Yes, authors use the example of Epilepsy, focal epilepsy and the gene of interest DEPDC5. I replicated their search and got the same results. However, I find that the label in Figure 1 in the gene’s transcript could be a bit more clear. E.g. it is not clear to me what transcript start and end refers to. It might also be more helpful if authors provide an example dataset for the Expression data that is loaded in the software by default.Furthermore authors use a case study results using RNAseq in ALS patients with mutations in FUS, TARDBP, SOD1, VCP genes.
Is test data available, either included with the submission or openly available via cited third party sources (e.g. accession numbers, data DOIs, etc.)? * Yes the authors provide test data with dois: https://zenodo.org/records/13375591.
Is automated testing used or are there manual steps described so that the functionality of the software can be verified? * Automated testing is not used as far as I can access it.
Overall Recommendation: * Accept with revisions
Reviewer Information: Ruslan Rust is an assistant professor in neuroscience and physiology at University of Southern California working on stem cell therapies on stroke. His lab is particularly interested in working with genomic data and the development of new biomarkers for stroke, AD and other neurological diseases.
Dr. Ruslan Rust's profile on ResearchHub: https://www.researchhub.com/author/4945925
ResearchHub Peer Reviewer Statement: This peer review has been uploaded from ResearchHub as part of a paid peer review initiative. ResearchHub aims to accelerate the pace of scientific research using novel incentive structures.
import streamlit as st
キャプションを入れてほしい
```{code-block} python :caption: app.py
import streamlit ...
```
Welcome back.
This is part two of this lesson.
We're going to continue immediately from the end of part one.
So let's get started.
So this is the folder containing the WordPress installation files.
Now there's one particular file that's really important, and that's the configuration file.
So there's a file called WP-config-sample, and this is actually the file that contains a template of the configuration items for WordPress.
So what we need to do is to take this template and change the file name to be the proper file name, so wp-config.php.
So we're going to create a copy of this file with the correct name.
And to do that, we run this command.
So we're copying the template or the sample file to its real file name, so wp-config.php.
And this is the name that WordPress expects when it initially loads its configuration information.
So run that command, and that now means that we have a live config file.
Now this command isn't in the instructions, but if I just take a moment to open up this file, you don't need to do this.
I'm just demonstrating what's in this file for your benefit.
But if I run a sudo nano, and then wp, and then hyphen-config, and then php, this is how the file looks.
So this has got all the configuration information in.
So it stores the database name, the database user, the database host, and lots of other information.
Now notice how it has some placeholders.
So this is where we would need to replace the placeholders with the actual configuration information.
So the database name itself, the host name, the database username, the database password, all that information would need to be replaced.
Now we're not going to type this in manually, so I'm going to control X to exit out of this, and then clear the screen again to make it easy to see.
We're going to use the Linux utility sed, or S-E-D.
And this is a utility which can perform a search and replace within a text file.
It's actually much more complex and capable than that.
It can perform many different manipulation operations.
But for this demonstration, we're going to use it as a simple search and replace.
Now we're going to do this a number of times.
First, we're going to run this command, which is going to replace this placeholder.
Remember, this is one of the placeholders inside the configuration file that I've just demonstrated, wp-config.
We're going to replace the placeholder here with the contents of the variable name, dbname, that we set at the start of this demo.
So this is going to replace the placeholder with our actual database name.
So I'm going to enter that so you can do the same.
We're going to run the sed command again, but this time it's going to replace the username placeholder with the dbuser variable that we set at the start of this demo.
So use that command as well.
And then lastly, it will do the same for the database password.
So type or copy and paste this command and press enter.
And that now means that this wp-config has the actual configuration information inside.
And just to demonstrate that, you don't need to do this part.
I'll just do it to demonstrate.
If I edit this file again, you'll see that all of these placeholders have actually been replaced with actual values.
So I'm going to control X out of that and then clear the screen.
And that concludes the configuration for the WordPress application.
So now it's ready.
Now it knows how to communicate with the database.
What we need to do to finish off the configuration though is just to make sure that the web server has access to all of the files within this folder.
And to do that, we use this command.
So we're making sure that we use the shown command or chown and set the ownership of all of the files in this folder and any subfolders to be the Apache user and the Apache group.
And the Apache user and Apache group belong to the web server.
So this just makes sure that the web server is able to access and control all of the files in the web root folder.
So run that command and press enter.
And that concludes the installation part of the WordPress application.
There's one final thing that we need to do and that's to create the database that WordPress will use.
So I'm going to clear the screen to make it easy to see.
Now what we're going to do in order to configure the database is we're going to make a database setup script.
We're going to put this script inside the forward slash TMP folder and we're going to call it DB.setup.
So what we need to do is enter the commands into this file that will create the database.
After the database is created, it needs to create a database user and then it needs to grant that user permissions on that database.
Now again, instead of manually entering this, we're going to use those variable names that were created at the start of the demo.
So we're going to run a number of commands.
These are all in the lessons commands document.
The first one is this.
So this echoes this text and because it has a variable name in, this variable name will be replaced by the actual contents of the variable.
Then it's going to take this text with the replacement of the contents of this variable and it's going to enter that into this file.
So forward slash TMP, forward slash DB setup.
So run that and that command is going to create the WordPress database.
Then we're going to use this command and this is the same so it echoes this text but it replaces these variable names with the contents of the variables.
This is going to create our WordPress database user.
It's going to set its password and then it's going to append this text to the DB setup file that we're creating.
Now all of these are actually database commands that we're going to execute within the MariaDB database.
So enter that to add that line to DB.setup.
Then we have another line which uses the same architecture as the ones above it.
It echoes the text.
It replaces these variable names with the contents and then outputs that to this DB.setup file and this command grants our database user permissions to our WordPress database.
And then the last command is this one which just flushes the privileges and again we're going to add this to our DB.setup script.
So now I'm just going to cat the contents of this file so you can just see exactly what it looks like.
So cat and then space forward slash TMP, forward slash DB.setup.
So as you'll see it's replaced all of these variable names with the actual contents.
So this is what the contents of this script actually looks like.
So these are commands which will be run by the MariaDB database platform.
To run those commands we use this.
So this is the MySQL command line interface.
So we're using MySQL to connect to the MariaDB database server.
We're using the username of root.
We're passing in the password and then using the contents of the DB root password variable.
And then once we authenticate the database we're passing in the contents of our DB.setup script.
And so this means that all of the lines of our DB.setup script will be run by the MariaDB database and this will create the WordPress database, the WordPress user and configure all of the required permissions.
So go ahead and press enter.
That command is run by the MariaDB platform and that means that our WordPress database has been successfully configured.
And then lastly just to keep things secure because we don't want to leave files laying around on the file system with authentication information inside.
We're just going to run this command to delete this DB.setup file.
Okay, so that concludes the setup process for WordPress.
It's been a fairly long intensive process but that now means that we have an installation of WordPress on this EC2 instance, a database which has been installed and configured.
So now what we can do is to go back to the AWS console, click on instances.
We need to select the A4L-PublicEC2 and then we need to locate its IP address.
Now make sure that you don't use this open address link because this will attempt to open the IP address using HTTPS and we don't have that configured on this WordPress instance.
Instead, just copy the IP address into your clipboard and then open that in a new tab.
If everything's successful, you should see the WordPress installation dialog and just to verify this is working successfully, let's follow this process through.
So pick English, United States for the language.
For the blog title, just put all the cats and then admin as the username.
You can accept the default strong password.
Just copy that into your clipboard so we can use it to log in in a second and then just go ahead and enter your email.
It doesn't have to be a correct one.
So I normally use test@test.com and then go ahead and click on install WordPress.
You should see a success dialog.
Go ahead and click on login.
Username will be admin, the password that you just copied into your clipboard and then click on login.
And there you go.
We've got a working WordPress installation.
We're not going to configure it in any detail but if you want to just check out that it works properly, go ahead and click on this all the cats at the top and then visit site and you'll be able to see a generic WordPress blog.
And that means you've completed the installation of the WordPress application and the database using a monolithic architecture on a single EC2 instance.
So this has been a slow process.
It's been manual and it's a process which is wide open for mistakes to be made at every point throughout that process.
Can you imagine doing this twice?
What about 10 times?
What about a hundred times?
It gets pretty annoying pretty quickly.
In reality, this is never done manually.
We use automation or infrastructure as code systems such as cloud formation.
And as we move through the course, you're going to get experience of using all of these different methods.
Now that we're close to finishing up the basics of VPC and EC2 within the course, things will start to get much more efficient quickly because I'm going to start showing you how to use many of the automation and infrastructure as code services within AWS.
And these are really awesome to use.
And you'll see just how much power is granted to an architect, a developer, or an engineer by using these services.
For now though, that is the end of this demo lesson.
Now what we're going to do is to clear up our account.
So we need to go ahead and clear all of this infrastructure that we've used throughout this demo lesson.
To do that, just move back to the AWS console.
If you still have the cloud formation tab open and move back to that tab, otherwise click on services and then click on cloud formation.
If you don't see it anywhere, you can use this box to search for it, select the word, press stack, select delete, and then confirm that deletion.
And that will delete the stack, clear up all of the infrastructure that we've used throughout this demo lesson and the account will now be in the same state as it was at the start of this lesson.
So from this point onward in the course, we're going to start using automation.
Now there is a lesson coming up in a little while in this section of the course, where you're going to create an Amazon machine image which is going to contain a pre-baked copy of the WordPress application.
So as part of that lesson, you are going to be required to perform one more manual installation of WordPress, but that's going to be part of automating the installation.
So you'll start to get some experience of how to actually perform automated installations and how to design architectures which have WordPress as a component.
At this point though, that's everything I wanted to cover.
So go ahead, complete this video, and when you're ready, I look forward to you joining me in the next.
We think of the key, each in his prison Thinking of the key, each confirms a prison Only at nightfall, aethereal rumours
While reading this stanza of “What the Thunder Said”, I instantly connected Eliot’s mention of aethereal rumors to “Appearance and Reality” by Francis Herbert Bradley. Bradley’s philosophical essay attempts to examine and explain interactions between souls. In particular, Bradley mentions ether while discussing the possibility of direct communication through souls ( as in soul-to-soul communication without the use of bodies). Bradley explains that this communication would occur by ‘a medium extended in space, and of course, like “ether,” quite material.”. Thus ether, while material, is equated to the direct impressions on one soul from another. With this understand of ether, we can interpret “ethereal rumors” to be ones not concerned with the external environment or human bodies, rather, spiritual messages that transcend the normal methods of bodily communication, such as the voice. However, Bradley seems to doubt the existence of this ethereal communication, and proceeds to worry, stating “If such alterations of our bodies are the sole means which we posses for conveying what is in us, can we be sure that in the end we really have conveyed it?”. Essentially, Bradley shares his fears that humans are unable to fully represent their souls through their bodies. Interestingly, Eliot’s two previous lines seem to evoke a similar notion of distorted communication between souls. Eliot states, “We think of the key, each in his prison// Thinking of the key, each confirms a prison”. In these lines, the people’s thoughts are collective and similar, but each individual has his own prison. When regarding the word “key”, one might think of a physical key to the prison, however, I argue that the word “key”, instead, refers to the ethereal communication between souls discussed by Bradley. A key is defined as “a thing that provides a means of understanding something”, such as “the key to the code”, or “the key to the riddle”. With this understanding of a key, we can interpret Eliot’s prisons as what Bradley would describe as limits of the bodily expression of the soul. These prisons seem to be “affirmed” by the existence of this “key”, which might represent another concern that the bodily methods of communication are only seen as limits due to the yearning for ethereal soul-to-soul communication.
A reduced instruction set computer (RISC) is a type of microprocessor thatrecognizes a relatively limited number of instructions. Until the mid-1980s, thetendency among computer manufacturers was to build increasingly complex CPUsthat had ever larger sets of instructions. At that time, however, a number ofcomputer manufacturers decided to reverse this trend by building CPUs capableof executing only a very limited set of instructions. One advantage of reducedinstruction set computers is that they can execute their instructions very fast becausethe instructions are so simple. Another, perhaps more important advantage, is thatRISC chips require fewer transistors, which makes them cheaper to design andproduce. Since the emergence of RISC computers, conventional computers havebeen referred to as CISCs (complex instruction set computers).6.4.1 HistoryThe first RISC projects came from IBM, Stanford, and UC-Berkeley in the late1970s and early 1980s.
RISC Processors RISC (Reduced Instruction Set Computer) processors are designed to execute a smaller set of simple instructions. Historically, until the 1980s, CPUs were developed to handle complex instruction sets, known as CISC (Complex Instruction Set Computer) processors. RISC reversed this trend by simplifying instructions, which allows for faster execution and reduced hardware complexity.
Key Highlights:
Simplified Instructions: RISC processors handle fewer, simpler instructions than CISC, making execution faster. Lower Transistor Count: Fewer transistors in RISC chips make them cheaper and easier to design.
Insight: While simpler instructions often mean more lines of code for complex tasks, RISC systems are optimized for speed through streamlined execution.
One criticism that applies equally to both proposals is that the semantics of the code now depends on the presence or absence of type information – in particular type annotations, while OCaml programmers are used to consider that they are useful for clarity and debugging purposes only.
Violation of the gradual guarantee. I'm coming around to this being fine but I think that it needs to be declared loudly in a languages design description and possibly alternative syntax for type declarations should be used so it's more obvious it's not just for clarity.
When you are programming, you are writing a control flow diagrams embedded with state transition methods through code.
Acc to structured program theorem, You essentially need three control structures to write any computable program.
1. Sequence
<code>
<code>
<code>
...
2. Selection
if <condition>
| <code_this> # if true
else <code_that> # if false
3. Iteration
<loop>
| <code> # exists for do..while
| if <condition>
| escape # if true
| <code> # exists for while
repeat <loop>
Due to the reliable ubiquity of the first structure, any set of sequenced program statements could be deemed as a code block. Then, control flow structures command the order in which these various code blocks are executed.
There are various control flow methods.
* Conditionals for selection (like if, switch...)
* Loops for iteration (like for, while..)
* Routines for abstraction (like function, class...)
The previous work UniNER (Zhou et al., 2024)distills the strong capability of ChatGPT in openNER into smaller models through IT without anyhuman-annotated data. We follow this line andinvestigate RA-IT under this targeted distillationsetting. Other works of IT for IE like Sainz et al.(2024); Li et al. (2024) using code-style instructiondata, are orthogonal to this work since RA-IT canbe integrated into various instruction styles.
UniNER đã chắt lọc khả năng mạnh mẽ của ChatGPT trong bài toán open NER và truyền các mô hình bé hơn thông qua instruction tuning mà không cần dữ liệu do con người xây dựng. Nghiên cứu này được tiến hành theo hướng tương tự và RA-IT được điều tra theo hướng chắt lọc có mục tiêu (targeted distillation)
To identify the essential code elements needed to com-plete the given infilling method m in a repository, a naivesolution might scan the entire codebase for all accessibleelements, which would introduce excessive noise. Anotherapproach could focus on methods with similar signatures orcontexts; however, these often provide irrelevant elementsthat do not serve m’s functional purpose, leading to redun-dancy and missing critical elements.
problematic methods
use one for work.
the equivalent for Copilot now would be that's for people who don't currently code
ChatGPT 4.0. The newest version of ChatGPT, which is more powerful and accurate than ChatGPT 3.5 but also slower, and it requires a paid account. It also has extended capabilities through plugins that give it the ability to interface with content from websites, perform more sophisticated mathematical functions, and access other services. A new Code I nt erp reter feature gives ChatGPT the ability to analyze data, create charts, solve math problems, edit files, and even develop hypotheses to explain data trends.
Enhanced Capabilities with Plugins: The introduction of plugins allows ChatGPT to interact with online content, perform advanced mathematical functions, and access a variety of external services, broadening its utility.
Code Interpreter Features enable ChatGPT to analyze data, create charts, solve mathematical problems, edit files, and develop hypotheses, making it a powerful tool for data analysis and problem-solving.
To go in a different direction for our last example, let’s look at an example of trolling as a form of protest. In the Black Lives Matters protests of 2020, Dallas Police made an app where they asked people to upload videos of protesters doing anything illegal. In support of the protesters, K-pop fans swarmed the app and uploaded as many K-pop videos as they could eventually leading to the app crashing and becoming unusable, and thus protecting the protesters from this attempt at Police surveillance. Read more at the Verge: K-pop stans overwhelm app after Dallas police ask for videos of protesters For another example of trolling as protests, this one with bots, see: A TikToker said he wrote code to flood Kellogg with bogus job applications after the company announced it would permanently replace striking workers
I feel like this example of trolling is more of a form of digital protest as they leveraged the disruption of this troll to actually support a cause. By using trolling in a way to overwhelm platforms with random content, it helps protestors fight against the surveillance and cooperate actions that social media websites take, and this can be a very effective from of activism.
I long to hear that you have declared an independancy—and by the way in the new Code of Laws which I suppose it will be necessary for you to make I desire you would Remember the Ladies, and be more generous and favourable to them than your ancestors. Do not put such unlimited power into the hands of the Husbands. Remember all Men would be tyrants if they could. If perticuliar care and attention is not paid to the Laidies we are determined to foment a Rebelion, and will not hold ourselves bound by any Laws in which we have no voice, or Representation.
Reflects Abigail's eagerness for Americas independence from British rule. She explicitly asks John to consider women in the legislative process, indicating an early demand for women's inclusion in lawmaking. She also critiques traditional views on marriage and the power held by husbands over their wives. Abagail presents a bold statement about the potential for men to abuse power, highlighting the need for checks and balances Her warning implies that women are ready to rise against oppression, similar to the colonies fight against British rule .The closing assertion is a direct demand for inclusion and rights, emphasizing the importance of representation in governance. Abigail Adams' letter is foundational text in the discourse about women's rights and representation during the American Revolution. The themes highlighted through this annotation process illustrate her advocacy for gender equality ,critique of existing power structures, and demand for women's voices in the political arena. This letter not only reflects the historical context of the time but also resonates with contemporary discussions about gender rights and representation.
http://192.168.1.100:11434 or the docker host machine IP address, e.g., http://172.17.0.1:11434.For local source code deployment, use http://localhost:11434
docker容器间访问ollama localhost要变 ubuntu获取主机ip命令： hostname -I
Author response:
The following is the authors’ response to the original reviews.
Response to reviewers
We thank the Editor and the Reviewers for their constructure review. In the light of this feedback, we have made a number of changes and additions to the manuscript, that we think improved the presentation and hopefully address the majority of the concerns by the reviewers.
Main changes:
• We added a new SI section (B1) with a population dynamics simulation in the high clonal interference regime and without expiring fitness (see R1: (1)).
• We added a new SI section (A9) with the derivation of the equilibrium state of our SIR model in the case of 𝑀 immune groups and in the limit 𝜀 → 0 (see R1: (5)).
• The text of the section Abstraction as “expiring” fitness advantage has been modified.
• We added a new SI section (A4) describing the links between parameters of the “expiring fitness” and SIR models.
All three reviewers had concerns about the relation between our SIR model and the “expiring fitness” model, that we hope will be addressed by the last two items listed above. In particular, we would like to underline the following points:
• The goal of our SIR model is to give a mechanistic explanation of partial sweeps using traditional epidemiological models. While ecological models (e.g. consumer resource) can give rise to the same phenomenology, we believe that in the context of host-pathogen interaction it is relevant to explicitely show that SIR models can result in partial sweeps.
• The expiring fitness model is mainly an effective model: it reproduces some qualitative features of the SIR but does not quantitatively match all aspects of the frequency dynamics in SIR models.
• It is possible to link the parameters of the SIR (𝛼,𝛾,𝑏,𝑓) and expiring fitness (𝑠,𝑥,𝜈) models at the beginning of the invasion of the variant (new SI section A4). However, the two models also differ in significant ways (the SIR model can for example oscillate, while the effective model can not). The correspondence of quantities like the initial invasion rate and the ‘expiration rate’ of fitness effects is thus only expected to hold for some time after the emergence of a novel variant.
Public reviews:
Reviewer 1:
Summary In this work, the authors study the dynamics of fast-adapting pathogens under immune pressure in a host population with prior immunity. In an immunologically diverse population, an antigenically escaping variant can perform a partial sweep, as opposed to a sweep in a homogeneous population. In a certain parameter regime, the frequency dynamics can be mapped onto a random walk with zero mean, which is reminiscent of neutral dynamics, albeit with differences in higher order moments. Next, they develop a simplified effective model of time dependent selection with expiring fitness advantage, and posit that the resulting partial sweep dynamics could explain the behaviour of influenza trajectories empirically found in earlier work (Barrat-Charlaix et al. Molecular Biology and Evolution, 2021). Finally, the authors put forward an interesting hypothesis: the mode of evolution is connected to the age of a lineage since ingression into the human population. A mode of meandering frequency trajectories and delayed fixation has indeed been observed in one of the long-established subtypes of human influenza, albeit so far only over a limited period from 2013 to 2020. The paper is overall interesting and well-written. Some aspects, detailed below, are not yet fully convincing and should be treated in a substantial revision.
We thank the reviewer for their constructive criticism. The deep split in the A/H3N2 HA segment from 2013 to 2020 is indeed the one of the more striking examples of such meandering frequency dynamics in otherwise rapidly adapting populations. But the up and down of H1N1pdm clade 5a.2a.1 in recent years might be a more recent example. We argue that such meandering dynamics might be a common contributor to seasonal influenza dynamics, even if it only spans 3-6 years.
(1) The quasi-neutral behaviour of amino acid changes above a certain frequency (reported in Fig, 3), which is the main overlap between influenza data and the authors’ model, is not a specific property of that model. Rather, it is a generic property of travelling wave models and more broadly, of evolution under clonal interference (Rice et al. Genetics 2015, Schiffels et al. Genetics 2011). The authors should discuss in more detail the relation to this broader class of models with emergent neutrality. Moreover, the authors’ simulations of the model dynamics are performed up to the onset of clonal interference 𝜌/ 𝑠0 \= 1 (see Fig. 4). Additional simulations more deeply in the regime of clonal interference (e.g. 𝜌/ 𝑠0 \= 5) show more clearly the behaviour in this regime.
We agree with the reviewer that we did not discuss in detail the effects of clonal interference on quasi-neutrality and predictability. As suggested, we conducted additional simulations of our population model in the regime of high clonal interference (𝜌/ 𝑠0 ≫ 1) and without expiring fitness effects. The results are shown in a new section of the supplementary information. These simulations show, as expected, that increasing clonal interference tends to decrease predictability: the fixation probability of an adaptive mutation found at frequency 𝑥 moves closer to 𝑥 as 𝜌 increases. However, even in a case of strong interference 𝜌/ 𝑠0 \= 32, 𝑝fix remains significantly different from the neutral expectation. We conclude from this that while it is true that dynamics tend to quasi-neutrality in the case of strong interference, this effect alone is unlikely to explain observations of H3N2 influenza dynamics. In our previous publication (BarratCharlaix et al, MBE, 2021) we have also investigated the effect of epistatic interactions between mutations, along side strong clonal interference. We concluded that, while most of these processes make evolution less predictable and push 𝑝fix towards the diagonal, it is hard to reproduce the empirical observations with realistic parameters. The “expiring fitness” model, however, produces this quite readily.
But there are qualitative differences between quasi-neutrality in traveling wave models and the expiring fitness model. In the traveling wave, a genotype carrying an adaptive mutation is always fitter than if it didn’t carry the mutation. Quasi-neutrality emerges from the accumulation of fitness variation at other loci and the fact that the coalescence time is not much bigger than the inverse selection coefficient of the mutation. In the expiring fitness model, the selective effect of the mutation itself goes away with time. We now discuss the literature on quasi-neutrality and cite Rice et al. 2015 and Schiffels et al. 2011.
In this context, I also note that the modelling results of this paper, in particular the stalling of frequency increase and the decrease in the number of fixations, are very similar to established results obtained from similar dynamical assumptions in the broader context of consumer resource models; see, e.g., Good et al. PNAS 2018. The authors should place their model in this broader context.
We thank the reviewer for pointing out the link between consumer resource models and our work. We further strengthened our discussion of the similarity of the phenomenology to models typically used in ecology and made an effort to highlight the link between consumer-resource models and ours in the introduction and in the part on the SIR model.
(2) The main conceptual problem of this paper is the inference of generic non-predictability from the quasi-neutral behaviour of influenza changes. There is no question that new mutations limit the range of predictions, this problem being most important in lineages with diverse immune groups such as influenza A(H3N2). However, inferring generic non-predictability from quasi-neutrality is logically problematic because predictability refers to individual trajectories, while quasi-neutrality is a property obtained by averaging over many trajectories (Fig. 3). Given an SIR dynamical model for trajectories, as employed here and elsewhere in the literature, the up and down of individual trajectories may be predictable for a while even though allele frequencies do not increase on average. The authors should discuss this point more carefully.
We agree with the reviewer that the deterministic SIR model is of course predictable. Similarly, a partial sweep is predictable. But we argue that expiring fitness makes evolution less predictable in two ways: (i) When a new adaptive mutation emerges and rises in frequency, we typically don’t know how rapidly its fitness effect is ‘expiring’. Thus even if we can measure its instantaneous growth rate accurately, we can’t predict its fate far into the future. (ii) Compared to the situation where fitness effects are not expiring, time to fixation is longer and there are more opportunities for novel mutations to emergence and change the course of the trajectory. We have tried to make this point clearer in the manuscript.
(3) To analyze predictability and population dynamics (section 5), the authors use a Wright-Fisher model with expiring fitness dynamics. While here the two sources of the emerging neutrality are easily tuneable (expiring fitness and clonal interference), the connection of this model to the SIR model needs to be substantiated: what is the starting selection 𝑠0 as a function of the SIR parameters (𝑓,𝑏,𝑀,𝜀), the selection decay 𝜈 = 𝜈(𝑓,𝑏,𝑀,𝜀,𝛾)? This would enable the comparison of the partial sweep timing in both models and corroborate the mapping of the SIR onto the simplified W-F model. In addition, the authors’ point would be strengthened if the SIR partial sweeps in Fig.1 and Fig.2 were obtained for a combination of parameters that results in a realistic timescale of partial sweeps.
We added a new section to the SI (A4) that relates the parameters of the SIR and expiring fitness models. In particular, we compute the initial growth rate 𝑠0 and a proxy for the fitness expiry rate 𝜈 as a function of the SIR parameters 𝛼,𝛾,𝑓,𝑏,𝑀, at the instant where the variant is introduced. The initial growth rate depends primarily on the degree of immune escape 𝑓, while the expiration rate 𝜈 is related to incidence 𝐼wt + 𝐼𝑚. However, as both models have fundamentally different dynamics, these relations are only valid on time scales shorter than potential oscillations of the SIR model. Beyond that, the connection between the models is mostly qualitative: both rely on the fact that growth rate of a strain diminishes when the strain becomes more frequent, and give rise to partial sweeps.
In Figure 1, the time it takes a partial sweep to finish is roughly 100− 200 generations (bottom right panel). If we consider H3N2 influenza and take one generation to be one week, this corresponds to a sweep time of 2 to 4 years, which is slightly slower but roughly in line with observations for selective sweeps. This time is harder to define if oscillatory dynamics takes place (middle right panel), but the time from the introduction of the mutant to the peak frequency is again of about 4 years. The other parameters of the model correspond to a waning time of 200 weeks and immune escape on the order of 20-30% change in susceptibility.
Reviewer 2:
Summary
This work addresses a puzzling finding in the viral forecasting literature: high-frequency viral variants evince signatures of neutral dynamics, despite strong evidence for adaptive antigenic evolution. The authors explicitly model interactions between the dynamics of viral adaptations and of the environment of host immune memory, making a solid theoretical and simulation-based case for the essential role of host-pathogen eco-evolutionary dynamics. While the work does not directly address improved data-driven viral forecasting, it makes a valuable conceptual contribution to the key dynamical ingredients (and perhaps intrinsic limitations) of such efforts.
Strengths
This paper follows up on previous work from these authors and others concerning the problem of predicting future viral variant frequency from variant trajectory (or phylogenetic tree) data, and a model of evolving fitness. This is a problem of high impact: if such predictions are reliable, they empower vaccine design and immunization strategies. A key feature of this previous work is a “traveling fitness wave” picture, in which absolute fitnesses of genotypes degrade at a fixed rate due to an advancing external field, or “degradation of the environment”. The authors have contributed to these modeling efforts, as well as to work that critically evaluates fitness prediction (references 11 and 12). A key point of that prior work was the finding that fitness metrics performed no better than a baseline neutral model estimate (Hamming distance to a consensus nucleotide sequence). Indeed, the apparent good performance of their well-adopted “local branching index” (LBI) was found to be an artifact of its tendency to function as a proxy for the neutral predictor. A commendable strength of this line of work is the scrutiny and critique the authors apply to their own previous projects. The current manuscript follows with a theory and simulation treatment of model elaborations that may explain previous difficulties, as well as point to the intrinsic hardness of the viral forecasting inference problem.
This work abandons the mathematical expedience of traveling fitness waves in favor of explicitly coupled eco-evolutionary dynamics. The authors develop a multi-compartment susceptible/infected model of the host population, with variant cross-immunity parameters, immune waning, and infectious contact among compartments, alongside the viral growth dynamics. Studying the invasion of adaptive variants in this setting, they discover dynamics that differ qualitatively from the fitness wave setting: instead of a succession of adaptive fixations, invading variants have a characteristic “expiring fitness”: as the immune memories of the host population reconfigure in response to an adaptive variant, the fitness advantage transitions to quasi-neutral behavior. Although their minimal model is not designed for inference, the authors have shown how an elaboration of host immunity dynamics can reproduce a transition to neutral dynamics. This is a valuable contribution that clarifies previously puzzling findings and may facilitate future elaborations for fitness inference methods.
The authors provide open access to their modeling and simulation code, facilitating future applications of their ideas or critiques of their conclusions.
We thank the reviewer for their summary, assessement, and constructive critique.
(1) The current modeling work does not make direct contact with data. I was hoping to see a more direct application of the model to a data-driven prediction problem. In the end, although the results are compelling as is, this disconnect leaves me wondering if the proposed model captures the phenomena in detail, beyond the qualitative phenomenology of expiring fitness. I would imagine that some data is available about cross-immunity between strains of influenza and sarscov2, so hopefully some validation of these mechanisms would be possible.
We agree with the reviewer that quantitatively confronting our model with data would be very interesting. Unfortunately, most available serological data for influenza and SARS-CoV-2 is obtained using post-infection sera from previoulsy naive animal models. To test our model, we would require human serology data, ideally demographically resolved, and a way to link serology to transmission dynamics. Furthermore, our model is mostly an explanation for qualitative features of variant dynamics and their apparent lack of predictability. We therefore considered that quantitative validation using data is out of scope of this work.
(2) After developing the SIR model, the authors introduce an effective “expiring fitness” model that avoids the oscillatory behavior of the SIR model. I hoped this could be motivated more directly, perhaps as a limit of the SIR model with many immune groups. As is, the expiring fitness model seems to lose the eco-evolutionary interpretability of the SIR model, retreating to a more phenomenological approach. In particular, it’s not clear how the fitness decay parameter 𝜈 and the initial fitness advantage 𝑠0 relate to the key ecological parameters: the strain cross-immunity and immune group interaction matrices.
The expiring fitness model emerges as a limiting case, at least qualitatively, of the SIR model when growth rate of the new variant is small compared to the waning rate and the SIR model does not oscillate. This can be readily achieved by many immune groups, which reconciles the large effect of many escape mutations and the lack of oscillation by confining the escape to some fraction of the population. Beyond that, the expiring fitness model is mainly an effective model that allows us to study the consequences of partial sweeps on predictability on long timescales. As stated in the “Main changes” section at the start of this reply, we added an SI section which links parameters of the two models. However, we underline the fact that beyond the phenomenon of partial sweeps, the dynamics of the two are different.
Reviewer 3:
Summary
In this work the authors start presenting a multi-strain SIR model in which viruses circulate in an heterogeneous population with different groups characterized by different cross-immunity structures. They argue that this model can be reformulated as a random walk characterized by new variants saturating at intermediate frequencies. Then they recast their microscopic description to an effective formalism in which viral strains lose fitness independently from one another. They study several features of this process numerically and analytically, such as the average variants frequency, the probability of fixation, and the coalescent time. They compare qualitatively the dynamics of this model to variants dynamics in RNA viruses such as flu and SARS-CoV-2.
Strengths
The idea that a vanishing fitness mechanisms that produce partial sweeps may explain important features of flu evolution is very interesting. Its simplicity and potential generality make it a powerful framework. As noted by the authors, this may have important implications for predictability of virus evolution and such a framework may be beneficial when trying to build predictive models for vaccine design. The vanishing fitness model is well analyzed and produces interesting structures in the strains coalescent. Even though the comparison with data is largely qualitative, this formalism would be helpful when developing more accurate microscopic ingredients that could reproduce viral dynamics quantitatively. This general framework has a potential to be more universal than human RNA viruses, in situations where invading mutants would saturate at intermediate frequencies.
We thank the reviewer for their positive remarks and constructive criticism below.
Weaknesses
The authors build the narrative around a multi-strain SIR model in which viruses circulate in an heterogeneous population, but the connection of this model to the rest of the paper is not well supported by the analysis. When presenting the random walk coarse-grained description in section 3 of the Results, there is no quantitative relation between the random walk ingredients importantly 𝑃(𝛽) - and the SIR model, just a qualitative reasoning that strains would initially grow exponentially and saturate at intermediate frequencies. So essentially any other microscopic description with these two features would give rise to the same random walk.
As also highlighted in the response to other reviewers, we now discuss how the parameter of the SIR model are related to the initial growth rate and the ‘expiration’ rate of the effective model. While the phenomenology of the SIR model is of course richer, this correspondence describes its overdamped limit qualitatively well.
Currently it’s unclear whether the specific choices for population heterogeneity and cross-immunity structure in the SIR model matter for the main results of the paper. In section 2, it seems that the main effect of these ingredients are reduced oscillations in variants frequencies and a rescaled initial growth rate. But ultimately a homogeneous population would also produce steady state coexistence between strains, and oscillation amplitude likely depends on parameters choices. Thus a homogeneous population may lead to a similar coarse-grained random walk.
The reviewer is correct that the primary effects of using many immune groups is to slow down the increase of novel variant, which in turn dampens the oscillations. Having multiple immune groups widens the parameter space in which partial sweeps without dramatic oscillations are observed. For slow sweeps, similar dymamics are observed in a homogeneous population.
Similarly, it’s unclear how the SIR model relates to the vanishing fitness framework, other than on a qualitative level given by the fact that both descriptions produce variants saturating at intermediate frequencies. Other microscopic ingredients may lead to a similar description, yet with quantitative differences.
Both of these points were also raised by other reviewers and we agree that it is worth discussing them at greater length. We now discuss how the parameters of the ‘expiring fitness’ model relate to those of the SIR. We also discuss how other models such as ecological models give rise to similar coarse grained models.
At the same time, from the current analysis the reader cannot appreciate the impact of such a mean field approximation where strains lose fitness independently from one another, and under what conditions such assumption may be valid.
In the SIR model, the rate at which strains lose fitness does depend on the precise state of the host population through the quantities 𝑆𝑚 and 𝑆wt , which is apparent in equation (A27) of the new SI section. The fact that a new variant shifts the equilibrium frequencies of previous strains in a proportional way is valid if the “antigenic space” is of very high dimensions, as explained in section Change in frequency when adding subsequent strains of the SI. It would indeed be interesting to explore relaxations of this assumption by considering a larger class of cross immunity matrices 𝐾. However, in the expiring fitness model, the fact that strains lose fitness independently from each ohter is a necessary simplification.
In summary, the central and most thoroughly supported results in this paper refer to a vanishing fitness model for human RNA viruses. The current narrative, built around the SIR model as a general work on host-pathogen eco-evolution in the abstract, introduction, discussion and even title, does not seem to match the key results and may mislead readers. The SIR description rather seems one of the several possible models, featuring a negative frequency dependent selection, that would produce coarse-grained dynamics qualitatively similar to the vanishing fitness description analyzed here.
We have revised the text throughout to make the connections between the different parts of the manuscript, in particular the SIR model and the expiring fitness model, clearer. We agree that the phenomenology of the expiring fitness model is more general than the case of human RNA viruses described by the SIR model, but we think this generality is an attractive feature of the coarse-graining, not a shortcoming. Indeed, other settings with negative frequency dependent selection or eco-systems that adapt on appropriate time scale generate similar dynamics.
Recommendations for the authors:
Reviewer 1:
(4) Line 74: what does fitness mean?
Many population dynamics models, including ones used for viral forecasting, attach a scalar fitness to each strain. The growth rate of each strain is then computed by substracting the average population fitness to the strain’s fitness. In this sentence, fitness is intended in this way.
(5) Fig. 1: The equilibrium frequency in the middle and bottom rows is hardly smaller than the equilibrium frequency in the top row for one immune group. This is surprising since for M=10, the variant escapes in only 1/10th of the population, which naively should impact the equilibrium frequency more strongly. Could the authors comment on this?
This is indeed non-trivial, and a hand-waving argument can be made by considering the extreme case 𝜀 = 0. The variant is then completely neutral for the immune groups 𝑖 > 1, and would be at equilibrium at any frequency in these immune groups. Its equilibrium frequency is then only determined by group 1, which is the only one breaking degeneracy. For 𝜀 > 0 but small, we naturally expect a small deviation from the 𝜀 = 0 case and thus 𝛽 should only change slightly.
A more rigorous argument with a mathematical proof in the case 𝜀 = 0 is now given in section A4 of the supplementary information.
(6) Fig. 1: In the caption, it is stated that the simulations are performed with 𝜀 = 0.99. Is this a typo? It seems that it should be 𝜀 = 0.01, as in and just below equation (7).
This was indeed a typo. It is now fixed.
(7) Fig. 3: The data analysis should be improved. In order to link the average frequency trajectories to standard population genetics of conditional fixation probabilities, the focal time should always be the time where the trajectory crosses the threshold frequency for the first time. Plotting some trajectories from a later time onwards, on their downward path destined to loss, introduces a systematic bias towards negative clonal interference (for these trajectories, the time between the first and the second crossing of the threshold frequency is simply omitted). The focal time of first crossing of the threshold frequency can easily be obtained, e.g., by linear interpolation of the trajectory between subsequent time points of frequency evalution. In light of the modified procedure, the statements on the on the inertia of the trajectories after crossing 𝑥⋆ (line 356) should be re-examined.
The way we process the data is already in line with the suggestions of the reviewer. In particular, we use as focal time the first time at which a trajectory is found in the threshold frequency bin. Trajectories that are never seen in the bin because of limited time-resolution are simply ignored.
In Fig. 3, there are no trajectories that are on their downward path at the focal time and when crossing the threshold frequency. Our other work on predictability of flu Barrat-Charlaix et. al. (2021) has a similar figure, which maybe created confusion.
(8) Fig. 4: authors write 𝛼/ 𝑠0 in the figure, but should be 𝜈/ 𝑠0.
Fixed.
(9) Line 420: authors refer to the blue curve in panel B as the case with strong interference. However, strong interference is for higher 𝜌/ 𝑠0, that is panel D (see point 1).
Fixed.
(10) Line 477: typo “there will a variety of mutations”.
Fixed.
Reviewer 2:
Should 𝛼 be 𝜈 in Figure 4 legends?
Thank you very much for spotting this error. We fixed it.
Equations 4-5 could be further simplified.
We factorised the 𝐼 term in equation 4. In equation 5, we prefered to keep the 1− 𝛿/ 𝛼 term as this quantity appears in different calculations concerning the model. For instance, 𝑆 = 𝛿/ 𝛼 at equilibrium.
The sentence before equation 8 references 𝑃𝛽(𝛽), but this wasn’t previously introduced.
We now introduce 𝑃𝑏𝜂 at the beginning of the section Ultimate fate of the variant.
In the last paragraph of page 12, “monotonously” maybe should be “monotonically”.
Fixed.
For the supplement section B, you might want a more descriptive title than “other”.
We renamed this section to Expiring fitness model and random walk.
Reviewer 3:
To expand on my previous comments, my main concerns regard the connection of section 2 and the SIR model with the rest of the paper.
In the first paragraph of page 9 the authors argue that a stochastic version of the SIR model would lead to different fixation dynamics in homogeneous vs heterogeneous populations due to the oscillations. This paragraph is quite speculative, some numerical simulations would be necessary to quantitatively address to what extent these two scenarios actually differ in a stochastic setting, and how that depends on parameters.
Likewise, the connection between the SIR model, the random walk coarse-grained description and the vanishing fitness model can be investigated through numerical simulations of a stochastic SIR given the chosen population and cross-immunity structures with i.e. 10-20 strains. This would allow for a direct comparison of individual strain dynamics rather than the frequency averages, as well as other scalar properties such as higher moments, coalescent, and fixation probability once reaching a given frequency. It would also be possible to characterize numerically the SIR P(beta) bridging the gap with the random walk description. It’s not obvious to me that the SIR P(beta) would not depend on the population size in the presence of birth-death stochasticity, potentially changing the moments scalings. I appreciate that such simulations may be computationally expensive, but similar numerical studies have been performed in previous phylodynamics works so it shouldn’t be out of reach.
An alternative, the authors should consider re-centering the narrative directly on the random walk of the vanishing fitness model, mentioning the SIR more briefly as a possible qualitative way to get there. Either way the authors should comment on other ways in which this coarse-grained dynamics could arise.
In the vanishing fitness model, where variants fitnesses are independent, is an infinite dimensional antigenic space implicitly assumed? If that’s the case, it should be explained in the main text.
A long simulation of the SIR model would indeed be interesting, but is numerically demanding and our current simulation framework doesn’t scale well for many strains and susceptibilities. We thus refrained from adding extensive simulations.
In Figure 2B of the main text, the simulation with 7 strains illustrates the qualitative match between the expiring fitness and the SIR model. However, it is clearly not long enough to discuss statistical properties of the corresponding random walk. Furthermore, we do not expect the individual strain dynamics of the SIR and expiring fitness models to match. The latter depends on few parameters (𝛼, 𝑠0), while the former depends on the full state of the host population and of the previous variants.
In the sectin linking the parameters of the two models, we now discuss the distribution 𝑃(𝛽) of the SIR model for two strains and a specific choice of distribution for the cross immunity 𝑏 and 𝑓.
Minor comments:
There is some back and forth in the writing. For instance, when introducing the model, 𝐶𝑖𝑗 is first defined as 1/ 𝑀, then a few paragraphs later the authors introduce that in another limit 𝐶𝑖𝑖 is just much higher than any 𝐶𝑖𝑗, and finally they specify that the former is the fast mixing scenario.
Another example is in section 2, in the first paragraph they put forward that heterogeneity and crossimmunity have different impacts on the dynamics, but the meaning attributed to these different ingredients becomes clear only a while later after the homogeneous population analysis. Uniforming the writing would make it easier for the reader to follow the authors’ train of thought.
We removed the paragraph below Equation (1) mentioning the 𝐶𝑖𝑗 \= 1/ 𝑀 case, which we hope will linearize the writing.
When mentioning geographical structure, why would geography affect how immunity sees pairs of viral strains (differences in 𝐾)?
Geographic structure could influence cross-immunity because of exposure histories of hosts. For instance in the case of influenza, different geographical regions do not have the same dominating strains in each season, and hosts from different regions may thus build up different immunity.
In the current narrative there are some speculations about non-scalar fitness, especially in section 2. The heterogeneity in this section does not seem so strong to produce a disordered landscape that defies the notion of scalar fitness in the same way some complex ecological systems do. A more parsimonious explanation for the coexistence dynamics observed here may be a negative frequency dependent selection.
Our language here was not very precise and we agree that the phenomenology we describe is related to that of frequency dependent selection (mediated by via immunity of the host population that integrates past frequencies). Traveling wave models typically use fitness function that are independent of the population distribution and only account for the evolution via an increasing average fitness. We have made discussion more accurate by stating that we consider a case where fitness depends explicitly on present and past population composition, which includes the case of negative frequency dependent selection.
I don’t understand the comparison with genetic drift (typo here, draft) in the last paragraph of section 3 given that there is no stochasticity in growth death dynamics.
We compare the random walk to genetic drift because of the expression of the second moment of the step size. The genetic draft has the same functional form. If one defines the effective population size as in the text, the drift due to random sampling of alleles (neutral drift) and the changes in strain frequency in our model have the same first and second moments. The stochasticity here does not come from the dynamics, which are indeed deterministic, but from the appearance of new mutations (variants) on backgrounds that are randomly sampled in the population. This latter property is shared with genetic draft.
In the vanishing fitness model, I think the reader would benefit from having 𝑃(𝑠) in the main text, and it should be made more clear what simulations assume what different choice of 𝑃(𝑠).
We added the expression of 𝑃(𝑠) in the main text. Simulations use the value 𝑠0 \= 0.03, which we added in the caption of Figure 4.
When comparing the model and data, is the point that COVID is not reproduced due to clonal interference? It seems from the plot that flu has clonal interference as well though. Why is that negligible?
A similar point has been raised by the first reviewer (see R1-(1)). Clonal interference is not negligible, but we find it to be insufficient to explain the observations made for H3N2 influenza, namely the lack of inertia of frequency trajectories or the probability of fixation. This is shown in the new section (B1) of the SI. Both SARS-CoV-2 and H3N2 influenza experience clonal interference, but the former is more predictable than the latter. Our point is that expiring fitness effects should be stronger in influenza because of the higher immune heterogeneity of the host population, making it less predictable than SARS-CoV-2.
Does the fixation probability as a function of frequency threshold match the flu data for some parameters sets?
For H3N2 influenza, the fixation probability is found to be equal to the threshold frequency (see Barrat-Charlaix MBE 2021, also indirectly visible from Fig. 3). In Figure 4, we obtain that either a high expiry rate or intermediate expiry rates and clonal interference regimes match this observation.
It would be instructive to see examples of the individual variant dynamics of the vanishing fitness model compared to the presented data.
We added an extra SI figure (S7) showing 10 randomly selected trajectories of individual variants in the case of H3N2/HA influenza and for the expiring fitness model with different parameter choices.
Figure 4E has no colorbar label. The reader shouldn’t have to look for what that means in the bottom of the SIs. In panels A and B the label should be 𝜈, not 𝛼. Same thing in most equations of page 42.
We added the colorbar label to the figure and also updated the caption: a darker color corresponds to a higher probability of sweeps to overlap. We fixed the 𝜈 – 𝛼 confusion in the SI and in the caption of the figure.
pourquoi pas un logo ce genre de chos mais 100 % en code alors pour ça on va utiliser un outil qui s'appelle revidéo
This tools bridges the gap of having feature files found in your source code and true documentation that your team, product owners and stakeholders can use.
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
Summary:
The authors aimed to elucidate the cytological mechanisms by which conjugated linoleic acids (CLAs) influence intramuscular fat deposition and muscle fiber transformation in pig models. Utilizing single-nucleus RNA sequencing (snRNA-seq), the study explores how CLA supplementation alters cell populations, muscle fiber types, and adipocyte differentiation pathways in pig skeletal muscles.
Thanks!
Strengths:
Innovative approach: The use of snRNA-seq provides a high-resolution insight into the cellular heterogeneity of pig skeletal muscle, enhancing our understanding of the intricate cellular dynamics influenced by nutritional regulation strategy.
Robust validation: The study utilizes multiple pig models, including Heigai and Laiwu pigs, to validate the differentiation trajectories of adipocytes and the effects of CLA on muscle fiber type transformation. The reproducibility of these findings across different (nutritional vs genetic) models enhances the reliability of the results.
Advanced data analysis: The integration of pseudotemporal trajectory analysis and cell-cell communication analysis allows for a comprehensive understanding of the functional implications of the cellular changes observed.
Practical relevance: The findings have significant implications for improving meat quality, which is valuable for both the agricultural and food industry.
Thanks!
Weaknesses:
Model generalizability: While pigs are excellent models for human physiology, the translation of these findings to human health, especially in diverse populations, needs careful consideration.
Thanks!
Reviewer #2 (Public Review):
Summary:
This study comprehensively presents data from single nuclei sequencing of Heigai pig skeletal muscle in response to conjugated linoleic acid supplementation. The authors identify changes in myofiber type and adipocyte subpopulations induced by linoleic acid at depth previously unobserved. The authors show that linoleic acid supplementation decreased the total myofiber count, specifically reducing type II muscle fiber types (IIB), myotendinous junctions, and neuromuscular junctions, whereas type I muscle fibers are increased. Moreover, the authors identify changes in adipocyte pools, specifically in a population marked by SCD1/DGAT2. To validate the skeletal muscle remodeling in response to linoleic acid supplementation, the authors compare transcriptomics data from Laiwu pigs, a model of high intramuscular fat, to Heigai pigs. The results verify changes in adipocyte subpopulations when pigs have higher intramuscular fat, either genetically or diet-induced. Targeted examination using cell-cell communication network analysis revealed associations with high intramuscular fat with fibro-adipogenic progenitors (FAPs). The authors then conclude that conjugated linoleic acid induces FAPs towards adipogenic commitment. Specifically, they show that linoleic acid stimulates FAPs to become SCD1/DGAT2+ adipocytes via JNK signaling. The authors conclude that their findings demonstrate the effects of conjugated linoleic acid on skeletal muscle fat formation in pigs, which could serve as a model for studying human skeletal muscle diseases.
Thanks!
Strengths:
The comprehensive data analysis provides information on conjugated linoleic acid effects on pig skeletal muscle and organ function. The notion that linoleic acid induces skeletal muscle composition and fat accumulation is considered a strength and demonstrates the effect of dietary interactions on organ remodeling. This could have implications for the pig farming industry to promote muscle marbling. Additionally, these data may inform the remodeling of human skeletal muscle under dietary behaviors, such as elimination and supplementation diets and chronic overnutrition of nutrient-poor diets. However, the biggest strength resides in thorough data collection at the single nuclei level, which was extrapolated to other types of Chinese pigs.
Thanks!
Weaknesses:
While the authors generated a sizeable comprehensive dataset, cellular and molecular validation needed to be improved. For example, the single nuclei data suggest changes in myofiber type after linoleic acid supplementation, yet these data are not validated by other methodologies. Similarly, the authors suggest that linoleic acid alters adipocyte populations, FAPs, and preadipocytes; however, no cellular and molecular analysis was performed to reveal if these trajectories indeed apply. Attempts to identify JNK signaling pathways appear superficial and do not delve deeper into mechanistic action or transcriptional regulation. Notably, a variety of single cell studies have been performed on mouse/human skeletal muscle and adipose tissues. Yet, the authors need to discuss how the populations they have identified support the existing literature on cell-type populations in skeletal muscle.Moreover, the authors nicely incorporate the two pig models into their results, but the authors only examine one muscle group. It would be interesting if other muscle groups respond similarly or differently in response to linoleic acid supplementation.Further, it was unclear whether Heigai and Laiwu pigs were both fed conjugated linoleic acid or whether the comparison between Heigai-fed linoleic acid and Laiwu pigs (as a model of high intramuscular fat). With this in mind, the authors do not discuss how their results could be implicated in human and pig nutrition, such as desirability and cost-effectiveness for pig farmers and human diets high in linoleic acid. Notably, while single nuclei data is comprehensive, there needs to be a statement on data deposition and code availability, allowing others access to these datasets. Moreover, the experimental designs do not denote the conjugated linoleic acid supplementation duration. Several immunostainings performed could be quantified to validate statements. This reviewer also found the Nile Red staining hard to interpret visually and did not appear to support the conclusions convincingly. Within Figure 7, several letters (assuming they represent statistical significance) are present on the graphs but are not denoted within the figure legend.
Thanks for your suggestions! We accepted your suggestion to revised our manuscript.
For changes in myofiber type, we performed qPCR to verify the changes of muscle fiber type related gene expression after CLA treatment (Figure 2E); for changes of adipocyte and preadipocyte populations, we also performed immunofluorescence staining, qPCR, and western blotting in LDM tissues and FAPs to verify the alterations of cell types after feeding with CLA (Figure 3D, 3E, 6G, 7C, and 7D). Hence, we think these cellular and molecular results could support our conclusions.
For JNK signaling pathway, we selected this signaling pathway based on snRNA-seq dataset and verified by activator in vitro experiment. However, we did not explore the mechanistic action and the downstream transcriptional regulators need to be further discussed. We have added these in the discussion part (line 443-448).
We have added the comparation between different cell-type populations in skeletal muscles (line 362-368 and 385-390).
For changes in myofiber type of Laiwu pigs, we have discussed in our previous study(Wang et al., 2023). Interestingly, we also found in high IMF content Laiwu pigs, the percentage of type IIa myofibers had an increased tendency (29.37% vs. 23.95%) while the percentage of type IIb myofibers had a decreased tendency (38.56% vs. 43.75%) in this study. We also added this discussion in the discussion part (line 392-395).
We have supplied the information of treatment in the materials and methods part (line 469-478). We also added the discussion about significance of our study for human and pig nutrition in the discussion part (line 375-376 and 446-447).
Our data will be made available on reasonable request (line 574-576).
We have supplied the information of the CLA supplementation duration in the materials and methods part (line 465).
Porcine FAPs have little lipid droplets and we improved the image quality (Figure 7A). In Figure 7, the Nile Red staining could be quantified and we have the quantification of Oil Red O staining (Figure 7B and 7J). We also added the statistical significance in figure legend.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
Suggestions for Improved or Additional Experiments, Data, or Analyses
Cross-species analysis: To strengthen the generalizability of the results, it would be beneficial to include a comparative analysis with other species, such as human, bovine, or rodent models, using publicly available snRNA-seq datasets.
Thanks! Our previous study has compared the conserved and unique signatures in fatty skeletal muscles between different species(Wang, Zhou, Wang, & Shan, 2024). We mainly focused on the regulatory mechanism of CLAs in regulating intramuscular fat deposition. However, there is still a blank in the snRNA-seq or scRNA-seq datasets about the effects of CLAs on regulating fat deposition in muscles across other species, including human, bovine or rodent models. Hence, we only analyze the regulatory mechanisms of CLAs influencing intramuscular fat deposition in pigs.
Functional link: the authors should discuss in the manuscript how the muscles differ in terms of texture, flavor, aroma, etc. before and after CLA administration or between Heigai and Laiwu to provide context and help readers better understand how the observed high-resolution cellular changes relate to these functional properties of meat.
Thanks! We have added these in the introduction part (line 90-98).
Improve figures: some figures, particularly those involving Oil Red O and Nail Red, could be improved by including higher magnification images to assess the organization of lipid droplets of individual adipocytes (Figure 7A, I, and K).
Thanks! Porcine FAPs have little lipid droplets and we improved the image quality (Figure 7A).
Reviewer #2 (Recommendations For The Authors):
All of my comments are above. However, I would recommend improving the writing as several areas throughout the results needed clarity.
Thanks! We have revised our manuscript carefully after accepting your revisions.
Wang, L., Zhao, X., Liu, S., You, W., Huang, Y., Zhou, Y., . . . Shan, T. (2023) Single-nucleus and bulk RNA sequencing reveal cellular and transcriptional mechanisms underlying lipid dynamics in high marbled pork NPJ Sci Food 7: 23. https://doi.org/10.1038/s41538-023-00203-4
Wang, L., Zhou, Y., Wang, Y., & Shan, T. (2024) Integrative cross-species analysis reveals conserved and unique signatures in fatty skeletal muscles Sci Data 11: 290. https://doi.org/10.1038/s41597-024-03114-5
Reviewer #2 (Public review):
Summary:
This study comprehensively presents data from single nuclei sequencing of Heigai pig skeletal muscle in response to conjugated linoleic acid supplementation. The authors identify changes in myofiber type and adipocyte subpopulations induced by linoleic acid at depth previously unobserved. The authors show that linoleic acid supplementation decreased the total myofiber count, specifically reducing type II muscle fiber types (IIB), myotendinous junctions, and neuromuscular junctions, whereas type I muscle fibers are increased. Moreover, the authors identify changes in adipocyte pools, specifically in a population marked by SCD1/DGAT2. To validate the skeletal muscle remodeling in response to linoleic acid supplementation, the authors compare transcriptomics data from Laiwu pigs, a model of high intramuscular fat, to Heigai pigs. The results verify changes in adipocyte subpopulations when pigs have higher intramuscular fat, either genetically or diet-induced. Targeted examination using cell-cell communication network analysis revealed associations with high intramuscular fat with fibro-adipogenic progenitors (FAPs). The authors then conclude that conjugated linoleic acid induces FAPs towards adipogenic commitment. Specifically, they show that linoleic acid stimulates FAPs to become SCD1/DGAT2+ adipocytes via JNK signaling. The authors conclude that their findings demonstrate the effects of conjugated linoleic acid on skeletal muscle fat formation in pigs, which could serve as a model for studying human skeletal muscle diseases.
Strengths:
The comprehensive data analysis provides information on conjugated linoleic acid effects on pig skeletal muscle and organ function. The notion that linoleic acid induces skeletal muscle composition and fat accumulation is considered a strength and demonstrates the effect of dietary interactions on organ remodeling. This could have implications for the pig farming industry to promote muscle marbling. Additionally, these data may inform the remodeling of human skeletal muscle under dietary behaviors, such as elimination and supplementation diets and chronic overnutrition of nutrient-poor diets. However, the biggest strength resides in thorough data collection at the single nuclei level, which was extrapolated to other types of Chinese pigs.
Weaknesses:
Although the authors compiled a substantial and comprehensive dataset, the scope of cellular and molecular-level validation still needs to be expanded. For instance, the single nuclei data suggest changes in myofiber type after linoleic acid supplementation, but these findings need more thorough validation. Further histological and physiological assessments are necessary to address fiber types and oxidative potential. Similarly, the authors propose that linoleic acid alters adipocyte populations, FAPs, and preadipocytes; however, there are limited cellular and molecular analyses to confirm these findings. The identified JNK signaling pathways require additional follow-ups on the molecular mechanism or transcriptional regulation. However, these issues are discussed as potential areas for future exploration. While various individual studies have been conducted on mouse/human skeletal muscle and adipose tissues, these have only been briefly discussed, and further investigation is warranted. Additionally, the authors incorporate two pig models into their results, but they only examine one muscle group. Exploring whether other muscle groups respond similarly or differently to linoleic acid supplementation would be valuable. Furthermore, the authors should discuss how their results translate to human and pig nutrition, such as the desirability and cost-effectiveness for pig farmers and human diets high in linoleic acid. Notably, while the single nuclei data is comprehensive, there needs to be a statement on data deposition and code availability, allowing others access to these datasets.
HazingHazing is any reckless or intentional act, occurring on or off campus, that produces physical, mental, or emotionalpain; discomfort; humiliation; embarrassment; or ridicule directed toward other students or groups (regardless oftheir willingness to participate), that is required or expected of new or current members and which is not related
after learning about all of the horrible effects of hazing I am glad it is talked about in the code of conduct
The CAIC or dean of the college or designee may impose one or more of the following sanctions when a student isfound in violation:a. Any student-faculty meeting sanctions.b. Disciplinary suspension from the University.c. Permanent dismissal from the University.
If a student breaks the code of conduct, it is in writing the punishments. This means the students should know the consequences of their actions before attending.
Faculty members:a. Serve as mentors, advisors, and educators for students.b. Uphold and enforce University rules and guidelines.c. Clarify academic expectations for students
The code of conduct doesn't just apply to students
Persons alleged to have violated the University’s rules and regulations (respondents) within the Code of StudentConduct have the following rights:a. Written/electronic notice of alleged violation(s), account of the conduct resulting in alleged violations, andnotice of the scheduled hearing.b. The right to a hearing.c. The right to a timely student conduct process and decision.d. The right to challenge the admissibility of information.e. The right to appeal.f. The preponderance of the evidence is the default standard or burden of proof used to determine if aviolation has occurred, unless a different standard or burden of proof is set forth by Policy.g. The right to a personal advisor, whose role is to advise the student rather than actively represent.h. The right to participate in the conduct hearing or remain silent.i. The right to present witnesses and a reasonable number of character statements.j. A written decision specifying the violation, outcome, and right of appeal.k. The right to challenge the seating of any hearing officer for good cause.l. The right to have the case heard only on the misconduct for which they have been given notice.m. The right to question all available witnesses.n. The right to request a reasonable postponement of the hearing.o. The right to face their accuser. (Special conditions may be imposed in sensitive cases.)
It's good to have a sense of what your right are. Especially as a student because a lot of us don't know them.
Students:a. Understand and abide by the Code of Student Conduct.b. Take responsibility for personal behavior.c. Actively oppose every instance of academic dishonesty.2. Faculty members:a. Serve as mentors, advisors, and educators for students.b. Uphold and enforce University rules and guidelines.c. Clarify academic expectations for students.3. Administrators and staff:a. Educate the campus and surrounding communities about academic integrity.b. Ensure reasonable and consistent enforcement of standards.
Everyone has a different part in the community. You have to realize that and understand that your role in the campus' community might not be the same as someone else's.
after learning about hazing i'm glad this is a part of the code of conduct
In 2016, when Donald Trump was running a campaign to be the US President, one twitter user pointed out that you could see which of the Tweets on Donald Trump’s Twitter account were posted from an Android phone and which from an iPhone, and that the tone was very different. A data scientist decided to look into it more and found: “My analysis … concludes that the Android and iPhone tweets are clearly from different people, “posting during different times of day and using hashtags, links, and retweets in distinct ways, “What’s more, we can see that the Android tweets are angrier and more negative, while the iPhone tweets tend to be benign announcements and pictures. …. this lets us tell the difference between the campaign’s tweets (iPhone) and Trump’s own (Android).” (Read more in this article from The Guardian) Note: we can no longer run code to check this ourselves because first, Donald Trump’s account was suspended in January 2021 for inciting violence, then when Elon Musk decided to reinstate Donald Trump’s account (using a Twitter poll as an excuse, but how many of the votes were bots?), Elon Musk also decided to remove the ability to look up a tweet’s source.
I believe that the contrast between the 2 different types of tweets, the ones made on Android and Apple truly highlight how the tone and the message can really differ depending on who is managing the account. This difference also shows how data analysis can play a role in finding patterns in tweets and forms of communication. It also can highlight the difference between personal and campaign driven tweets and posts.
he way we present ourselves to others around us (our behavior, social role, etc.) is called our public persona. We also may change how we behave and speak depending on the situation or who we are around, which is called code-switching. While modified behaviors to present a persona or code switch may at first look inauthentic, they can be a way of authentically expressing ourselves in each particular setting. For example: Speaking in a formal manner when giving a presentation or answering questions in a courtroom may be a way of authentically sharing your experiences and emotions, but tailored to the setting Sharing those same experiences and emotions with a close friend may look very different, but still can be authentic Different communities have different expectations and meanings around behavior and presentation. So what is appropriate authentic behavior depends on what group you are from and what group you are interacting with, like this gif of President Obama below:
I believe that code-switching and our public personas allow us to navigate different social contexts and situations that we may be put in while also still being able to express authentic versions of ourselves. Adjusting our behavior to match different social situations reflects our understanding of social expectations and our ability to communicate in different ways.
For example:
Code switching is almost mandatory in public. You can't talk and act the same way around everyone. The way you act to customers and coworkers is going to be different from your friends and family.
While modified behaviors to present a persona or code switch may at first look inauthentic, they can be a way of authentically expressing ourselves in each particular setting. For example: Speaking in a formal manner when giving a presentation or answering questions in a courtroom may be a way of authentically sharing your experiences and emotions, but tailored to the setting Sharing those same experiences and emotions with a close friend may look very different, but still can be authentic Different communities have different expectations and meanings around behavior and presentation. So what is appropriate authentic behavior depends on what group you are from and what group you are interacting with, like this gif of President Obama below:
I feel this is a necessity nowadays. We all have to wear different masks throughout our day in order to adjust and acclimate to our environment. How we behave around close friends verses coworkers' verses strangers. We all adjust to fit in.
The way we present ourselves to others around us (our behavior, social role, etc.) is called our public persona. We also may change how we behave and speak depending on the situation or who we are around, which is called code-switching.
I think this is completely normal because the way you act around your friends and family is different from how you behave at work or school. When you are with friends and family you feel more comfortable around them so you behave like yourself. People can also behave very differently on social media due to them being behind a screen.
Author response:
The following is the authors’ response to the current reviews.
Public Reviews:
Reviewer #2 (Public review):
Weaknesses:
The authors have clarified that the first features available for each patient have been used. However, they have not shown that these features did not occur before the time of post-stroke epilepsy. Explicit clarification of this should be performed.
The data utilized in our analysis were collected during the first examination or test conducted after the patients' admission. We specifically excluded any patients with a history of epilepsy, ensuring that all cases of epilepsy identified in our study occurred after admission. Therefore, the features we analyzed were collected after the patients' admission but prior to the onset of post-stroke epilepsy.
Reviewer #3 (Public review):
Weaknesses:
The writing of the article may be significantly improved.
Although the external validation is appreciated, cross-validation to check robustness of the models would also be welcome.
Thank you for your helpful advice. Performing n-fold cross-validation is a crucial step to ensure the reliability and robustness of the reported results, especially when dealing with the datasets which don't have sufficient quantity. We revised our code and did a 5 fold cross-validation version ,it didn’t have much promote（because our model has reach the auc of 0.99）.Considering that we have sufficient quantity of more than 20000 records, we think split the dataset by 7:3 and train the model is enough for us. We have uploaded the code of 5 fold cross-validation version and ploted the 5 fold test roc on GitHub at https://github.com/conanan/lasso-ml/lasso_ml_cross_validation.ipynb as an external resource. We trained the 5 fold average model and ploted the 5 fold test roc curves, the results show some improvement, but it is not substantial because the best model are still tree models in the end.
External validation results may be biased/overoptimistic, since the authors informed that "The external validation cohort focused more on collecting positive cases 80 to examine the model's ability to identify positive samples", which may result in overoptimistic PPV and Sensitivity estimations. The specificity for the external validation set has not been disclosed.
Thank you for your valuable feedback regarding the external validation results. We appreciate your concerns about potential bias and overoptimism in our estimations of positive predictive value (PPV) and sensitivity.
To clarify, we have uploaded the code for external validation on GitHub at https://github.com/conanan/lasso-ml. The results indicate that the PPV is 0.95 and the specificity is 0.98.
While we focused on collecting more positive cases due to their lower occurrence rate, this approach allows us to better evaluate the model's ability to predict positive samples, which is crucial in clinical settings. We believe that emphasizing positive cases enhances the model's utility for practical applications(So a little overoptimism is acceptable ).
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Weaknesses 1:
The methodology needs further consideration. The Discussion needs extensive rewriting.
Thanks for your advice, we have revised the Discussion
Reviewer #2 (Public Review):
Weaknesses 2:
There are many typos and unclear statements throughout the paper.
There are some issues with SHAP interpretation. SHAP in its default form, does not provide robust statistical guarantees of effect size. There is a claim that "SHAP analysis showed that white blood cell count had the greatest impact among the routine blood test parameters". This is a difficult claim to make.
Thank you for your suggestion that the SHAP analysis is really just a means of interpreting the model. In our research, we compared the SHAP analysis with traditional statistical methods, such as regression analysis. We found the SHAP results to be consistent with the statistical results from the regression for variables like white blood cell count (see Table 1). This alignment leads us to believe the SHAP analysis is providing reliable insights in this context
The Data Collection section is very poorly written, and the methodology is not clear.
Thanks for your advice, we have revised the Data Collection section.
There is no information about hyperparameter selection for models or whether a hyperparameter search was performed. Given this, it is difficult to conclude whether one machine learning model performs better than others on this task.
Thank you for the advices of performing hyperparameter. We used the package of sklearn, xgboost, lightgbm of python 3.10 to construct the model and didn’t change the default settings before. It is not proper and may lead to less certain conclusions. Now we carry out grid search to select and optimize hyperparameters and they make the model better. The best model is still RF.
The inclusion and exclusion criteria are unclear - how many patients were excluded and for what reasons?
The procedure of selection is in figure1. Total there are 42079 records from the stroke database, 24733 patients were diagnosed as ischemic stroke or lacular stoke with new onset. Then we excluded hemorrage stroke(4565),history of stroke(2154), TIA(3570), unclear cause stroke(561) and records who missed important data(6496). Then we excluded patients whose seizure might be attributed to other potential causes (brain tumor, intracranial vascular malformation, traumatic brain injury,etc)(865). Then we exclude patient who had a seizure history(152) or died in hospital (1444). Then we excluded patients who were lost in follow-up (had no outpatient records and can’t contact by phone )or died within 3 months of the stroke incident(813). Finally 21459 cases are involved in this research.
There is no sensitivity analysis of the SMOTE methodology: How many synthetic data points were created, and how does the number of synthetic data points affect classification accuracy?
Thanks for your remind, we have accept these advice and change the SMOTE to SMOTEENN (Synthetic Minority Over-sampling Technique combined with Edited Nearest Neighbors) technique to resample an imbalanced dataset for machine learning. The code is
smoteenn = SMOTEENN(samplingstrategy='auto', randomstate=42)
the SMOTEENN class comes from the imblearn library. The samplingstrategy='auto' parameter tells the algorithm to automatically determine the appropriate sampling strategy based on the class distribution. The randomstate=42 parameter sets a seed for the random number generator, ensuring reproducibility of the results.
Did the authors achieve their aims? Do the results support their conclusions?
Yes, we have achieve some of the aims of predicting PSE while still leave some problem.
The paper does not clarify the features' temporal origins. If some features were not recorded on admission to the hospital but were recorded after PSE occurred, there would be temporal leakage.
The data used in our analysis is from the first examination or test conducted after the patients' admission, retrieved from a PostgreSQL database. First, we extracted the initial admission date for patients admitted due to stroke. Then, we identified the nearest subsequent examination data for each of those patients.
The sql code like follows:
SELECT TO_DATE(condition_start_date, 'DD-MM-YYYY') AS DATE
FROM diagnosis
WHERE person_id ={} and (condition_name like '%梗死%' or condition_name like '%梗塞%') and(condition_name like '%脑%'or condition_name like '%腔隙%'))
order by DATE limit 1
The authors claim that their models can predict PSE. To believe this claim, seeing more information on out-of-distribution generalisation performance would be helpful. There is limited reporting on the external validation cohort relative to the reporting on train and test data.
Thank you for the advice. The external validation is certainly very important, but there have been some difficulties in reaching a perfect solution. We have tried using open-source databases like the MIMIC database, but the data there does not fit our needs as closely as the records from our own hospital. The MIMIC database lacks some of the key features we require, and also lacks the detailed patient follow-up information that is crucial for our analysis. Given these limitations, we have decided to collect newer records from the same hospitals here in Chongqing. We believe this will allow us to build a more comprehensive dataset to support robust external validation. While it may not be a perfect solution, gathering this additional data from our local healthcare system is a pragmatic step forward. Looking ahead, we plan to continue expanding this Chongqing-based dataset and report on the results of the greater external validation in the future. We are committed to overcoming the challenges around data availability to strengthen the validity and generalizability of our research findings.
For greater certainty on all reported results, it would be most appropriate to perform n-fold cross-validation, and report mean scores and confidence intervals across the cross-validation splits
Thank you for your helpful advice. Performing n-fold cross-validation is a crucial step to ensure the reliability and robustness of the reported results, especially when dealing with the datasets which don't have sufficient quantity. While we have sufficient quantity of more than 20000 records, so we think split the dataset by 7:3 and train the model is enough for us. We revised our code and did a 5 fold cross-validation version ,it had little promote（because our model has reach the auc of 0.99）, we may use this great technique in our next study if there is not enough cases.
Additional context that might help readers
The authors show force plots and decision plots from SHAP values. These plots are non-trivial to interpret, and the authors should include an explanation of how to interpret them.
Thank you for your helpful advice. It is a great improve for our draft, we have added the explanation that we use the force plot of the first person to show the influence of different features of the first person, we can see that long APTT time contribute best to PSE, then the AST level and others, the NIHSS score may be low and contribute opposite to the final result. Then the decision plot is a collection of model decisions that show how complex models arrive at their predictions
Reviewer #3 (Public Review):
Weaknesses3:
There are issues with the readability of the paper. Many abbreviations are not introduced properly and sometimes are written inconsistently. A lot of relevant references are omitted. The methodological descriptions are extremely brief and, sometimes, incomplete.
Thanks for your advice, we have revised these flaws.
The dataset is not disclosed, and neither is the code (although the code is made available upon request). For the sake of reproducibility, unless any bioethical concerns impede it, it would be good to have these data disclosed.
Thank you for your recommendations. We have made the code available on GitHub at https://github.com/conanan/lasso-ml. While the data is private and belongs to the hospital. Access can be requested by contacting the corresponding author to apply from the hospitals and specifying the purpose of inquiry.
Although the external validation is appreciated, cross-validation to check the robustness of the models would also be welcome.
Thank you for your valuable advice. Performing n-fold cross-validation is crucial for ensuring the reliability and robustness of results, especially with limited datasets. However, since we have over 20,000 records, we believe that a 70:30 split for training and testing is sufficient.
We revised our code and implemented 5-fold cross-validation, which provided minimal improvement, as our model has already achieved an AUC of 0.99. We plan to use this technique in future studies if we encounter fewer cases.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
My comments include two parts:
(1) Methodology<br /> a-This study was based on multiple clinical indicators to construct a model for predicting the occurrence of PSE. It involved various multi-class indicators such as the affected cortical regions, locations of vascular occlusion, NIHSS scores, etc. Only using the SHAP index to explain the impact of multi-class variables on the dependent variable seems slightly insufficient. It might be worth considering the use of dummy variables to improve the model's accuracy.
Thank you for the detailed feedback on the study methodology. The SHAP analysis is really just a means of interpreting the model, which we compared with the combination of SHAP and traditional statistics, so we think SHAP analysis is reliable in this research. We have used the dummy variables, expecially when dealing with the affected cortical regions, locations of vascular occlusion, for example if frontal region is involved the variable is 1. But they have less impact in the machine learning model
b-The study used Lasso regression to select 20 features to build the model. How was the optimal number of 20 features determined?
Lasso regression is a commonly used feature screening method. Since we extract information from the database and try to include as many features as possible, the cross-verification curve of lasso regression includes 78 features best, but it will lead to too complex model. We select 10,15,20,25,30 features for modeling according to the experiment. When 20 features are found, the model parameters are good and relatively concise. Improve the number of features contribute little to the model effect, decrease the number of features influence the concise of model ,for example the auc of the model with 15 features will drop under 0.95. So we finally select 20 features.
c-The study indicated that the incidence rate of PSE in the enrolled patients is 4.3%, showing a highly imbalanced dataset. If singly using the SMOTE method for oversampling, could this lead to overfitting?
Thanks for your remind, singly using the SMOTE method for oversampling is inproper. Now we have find this improvement and change the SMOTE to SMOTEENN (Synthetic Minority Over-sampling Technique combined with Edited Nearest Neighbors) technique to resample an imbalanced dataset for machine learning. First, oversampling with SMOTE and then undersampling with ENN to remove possible noise and duplicate samples. The code is
smoteenn = SMOTEENN(sampling_strategy='auto', random_state=42)
the SMOTEENN class comes from the imblearn library. The sampling_strategy='auto' parameter tells the algorithm to automatically determine the appropriate sampling strategy based on the class distribution. The random_state=42 parameter sets a seed for the random number generator, ensuring reproducibility of the results.
(2) Clinical aspects:
Line 8, history of ischemic stroke, this is misexpression, could be: diagnosis of ischemic stroke.
Line 8, several hospitals, should be more exact; how many?
Line 74 indicates that the data are from a single centre, this should be clarified.
Line 4 data collection: The criteria read unclear; please clarify further.
Thanks for your remind, we have revised the draft and correct these errors.
Line 110, lab parameters: Why is there no blood glucose?
Because many patients' blood sugar fluctuates greatly and is easily affected by drugs or diet, we finally consider HBA1c as a reference index by asking experts which is more stable.
Line 295, The author indicated that data lost; this should be clarified in the results part, and further, the treatment of missing data should be clarified in the method part.
Thanks for your remind, we have revised the draft and correct these errors.
I hope to see a table of the cohort's baseline characters. The discussion needs extensive rewriting; the author seems to be swinging from the stoke outcome and the seizure, sometimes losing the target.
Figure1 is the procedure of the selection of patients. Table1 contains the cohort's baseline characters
For the swinging from the stoke outcome and the seizure, that is because there are few articles on predicting epilepsy directly by relevant indicators, while there are more articles on prognosis. So we can only take epilepsy as an important factor in prognosis and comprehensively discuss it, or we can't find enough articles and discuss them
Reviewer #2 (Recommendations For The Authors):
There are typos and examples of text that are not clear, including:
"About the nihss score, the higher the nihss score, the more likely to be PSE, nihss score has a third effect just below white blood cell count and D-dimer."
"and only 8 people made incorrect predictions, demonstratijmng a good predictive ability of the model."
"female were prone to PSE"
" Waafi's research"
"One-heat' (should be one-hot)
Thanks for your remind, we have revised the draft and correct these errors.
The Data Collection section is poorly written, and the methodology is not clear. It would be much more appropriate to include a table of all features used and an explanation of what these features involve. It would also be useful to see the mean values of these features to assess whether the feature values are reasonable for the dataset.
Thanks for your remind. All data are from the first examination or test after admission, presented through the postgresql database . First we extract the first date of the patients who was admitted by stroke ,then we extract informations from the nearest examination from the admission. We extract by the SQL code by computer instead of others who may extract data by manual so we get as much data as possible other than only get the features which was reported before .The table of all features used and their mean±std is in table1.
The paper does not clarify the features' temporal origins. If some features were not recorded on admission to the hospital but were recorded after PSE occurred, there would be temporal leakage. I would need this clarified before believing the authors achieved their claims of building a predictive model.
All relevant index results were from the first examination after admission, and the mean standard deviation was listed in the statistical analysis section in table1.
The authors claim that their models can predict PSE. To believe this claim, seeing more information on out-of-distribution generalisation performance would be helpful. There is limited reporting on the external validation cohort relative to the reporting on train and test data.
Thank you for the advice, the external validation is very important but there are some difficulties to reach a perfect one. We have tried some of the open source database like the mimic database ,but these data don't fit our request because they don't have as much features as our hospital and lack of follow-up of the relevant patients. In the end we collected the newer records in the same hospitals in Chongqing and we will collect more and report a greater external validation in the future.
For greater certainty on all reported results, It would be most appropriate to perform n-fold cross-validation, and report mean scores and confidence intervals across the cross-validation splits.
Thank you for your helpful advice. Performing n-fold cross-validation is a crucial step to ensure the reliability and robustness of the reported results, especially when dealing with the datasets which don't have sufficient quantity. While we have sufficient quantity of more than 20000 records, so we think split the dataset by 7:3 and train the model is enough for us. We revised our code and did a 5 fold cross-validation version ,it had little promote, we will use this great technique in our next study.
The authors show force plots and decision plots from SHAP values. These plots are non-trivial to interpret, and the authors should include an explanation of how to interpret them.
It is a great improve for our draft, we have added the explanation we use the force plot of the first person to show the influence of different features of the first person, we can see that long APTT time contribute best to PSE, then the AST level and others, the NIHSS score may be low and contribute lower to the final result. Then the decision plot is a collection of model decisions that show how complex models arrive at their predictions
Reviewer #3 (Recommendations For The Authors):
Abbreviations should not be defined in the abstract )or only in the abstract).
Please explicit what are the purposes of the study you are referring to in "Currently, most studies utilize clinical data to establish statistical models, survival analysis and cox regression."
Authors affirm: "there is still a relative scarcity of research 49 on PSE prediction, with most studies focusing on the analysis of specific or certain risk factors ." This statement is especially curious since the current study uses risk factors as predictors.
It is not clear to me what the authors mean by "No study has proposed or established a more comprehensive and scientifically accurate prediction model." The authors do not summarize the statistical parameters of previously reported model, or other relevant data to assess coverage or validity (maybe including a Table summarizing such information would be appropriate. In any case, I would try to omit statements that imply, to some extent, discrediting previous studies without sufficient foundation.
"antiepileptic drugs" is an outdated name. Please use "antiseizure medications"
Thanks for your remind, we have revised the draft and correct these errors.
The authors say regarding missing data that they "filled the data of the remaining indicators with missing values of more than 1000 cases by random forest algorithm". Please clarify what you mean by "of more than 1000 cases." Also, provide details on the RF model used to fill in missing data.
Thanks for your remind. "of more than 1000 cases" was a wrong sentence and we have corrected it. Here is the procedure, first we counted the values of all laboratory indicators for the first time after stroke admission( everyone who was admitted because of stroke would perform blood routine , liver and kidney function and so on), excluded indicators with missing values of more than 10%, and filled the data of the remaining indicators with missing values by random forest algorithm using the default parameter. First, we go through all the features, starting with the one with the least missing (since the least accurate information is needed to fill in the feature with the least missing). When filling in a feature, replace the missing value of the other feature with 0. Each time a regression prediction is completed, the predicted value is placed in the original feature matrix and the next feature is filled in. After going through all the features, the data filling is complete.
Please specify what do you mean by negative group and positive group, Avoid tacit assumptions.
Thanks for your remind, we have revised the draft and correct these errors.
Please provide more details (and references) on the smote oversampling method. Indicate any relevant parameters/hyperparameters.
Thanks for your remind, we have accept these advice and change the SMOTE to SMOTEENN (Synthetic Minority Over-sampling Technique combined with Edited Nearest Neighbors) technique to resample an imbalanced dataset for machine learning. The code is
smoteenn = SMOTEENN(sampling_strategy='auto', random_state=42)
the SMOTEENN class comes from the imblearn library. The sampling_strategy='auto' parameter tells the algorithm to automatically determine the appropriate sampling strategy based on the class distribution. The random_state=42 parameter sets a seed for the random number generator, ensuring reproducibility of the results.
The methodology is presented in an extremely succinct and non-organic manner (e.g., (Model building) Select the 20 features with the largest absolute value of LASSO." Please try to improve the narrative.
Lasso regression is a commonly used feature screening method. Since we extract information from the database and try to include as many features as possible, the cross-verification curve of lasso regression includes 78 features best, but it will lead to too complex model. We select 10,15,20,25,30 features for modeling according to the experiment. When 20 features are found, the model parameters are good and relatively concise. Improve the number of features contribute little to the model effect, decrease the number of features influence the concise of model ,for example the auc of the model with 15 features will drop under 0.95. So we finally select 20 features.
Many passages of the text need references. For example, those that refer to Levene test, Welch's t-test, Brier score, Youden index, and many others (e.g., NIHSS score). Please revise carefully.
Thanks for your remind, we have revised the draft and correct these errors.
"Statistical details of the clinical characteristics of the patients are provided in the table." Which table? Number?
Thanks for your remind, we have revised the draft and correct these errors， it is in table1.
Many abbreviations are not properly presented and defined in the text, e.g., wbc count, hba1c, crp, tg, ast, alt, bilirubin, bua, aptt, tt, d_dimer, ck. Whereas I can guess the meaning, do not assume everyone will. Avoid assumptions.
ROC is sometimes written "ROC" and others, "roc." The same happens for PPV/ppv, and many other words (SMOTE; NIHSS score, etc.).
Please rephrase "ppv value of random forest is the highest, reaching 0.977, which is more accurate for the identification of positive patients(the most important function of our models).". PPV always refer to positive predictions that are corroborated, so the sentences seem redundant.
Thanks for your remind, we have revised the draft and correct these errors.
What do you mean by "Complex algorithms". Please try to be as explicit as possible. The text looks rather cryptic or vague in many passages.
Thanks for your remind, "Complex algorithms" is corrected by machine learning.
The text needs a thorough English language-focused revision, since the sense of some sentences is really misleading. For instance "only 8 people made incorrect predictions,". I guess the authors try to say that the best algorithm only mispredicted 8 cases since no people are making predictions here. Also, regarding that quote... Are the authors still speaking of the results of the random forest model, which was said to be one of the best performances?
Thanks for your remind, we have revised the draft and correct these errors.
The authors say that they used, as predictors "comprehensive clinical data, imaging data, laboratory test data, and other data from stroke patients". However, the total pool of predictors is not clear to me at this point. Please make it explicit and avoid abbreviations.
Thanks for your remind, we have revised the draft and correct these errors.
Although the authors say that their code is available upon request, I think it would be better to have it published in an appropriate repository.
Thanks for your remind, we showed our code at https://github.com/conanan/lasso-ml.
Reviewer #3 (Public review):
Summary:
The authors report the performance of a series of machine learning models inferred from a large-scale dataset and externally validated with an independent cohort of patients, to predict the risk of post-stroke epilepsy. Some of the reported models have very good explicative performance, and seem to have very good predictive ability.
Strengths:
The models have been derived from real-world large-scale data.
Performances of the best-performing models seem to be very good according to the external validation results.
Early prediction of risk of post-stroke epilepsy would be of high interest to implement early therapeutic interventions that could improve prognosis.
Code is publicly available. The authors also stated that the datasets used are available on request.
Weaknesses:
The writing of the article may be significantly improved.
Although the external validation is appreciated, cross-validation to check robustness of the models would also be welcome.
External validation results may be biased/overoptimistic, since the authors informed that "The external validation cohort focused more on collecting positive cases 80 to examine the model's ability to identify positive samples", which may result in overoptimistic PPV and Sensitivity estimations. The specificity for the external validation set has not been disclosed.
Reviewer #3 (Public review):
Summary:
In this work, the authors aims and efforts point towards evaluating the interaction mechanisms between viral protein integrase (IN) and viral DNA. They develop a multifaceted approach to probe the effect that IN has on the formation and structure of IN-DNA complexes under different environmental conditions to determine the role of IN in early stages of infection. HIV infection is considered a global pandemic with huge challenges in both treatment and prevention. This work presents a step towards understanding the mechanisms in early infection and thus prevention.
The experimental work is carried out using single molecule imaging and force spectroscopy, alongside computational verification using Monte-Carlo simulations. The authors use a range of well-established methods to quantitatively evaluate this, pushing forward the current state of the art.
The paper shows that in the presence of IN, DNA is compacted into a condensate in a biphasic manner, first forming a 'semi-compact' rosette condensate followed by a fully compacted condensate. As HIV DNA must be fully compacted to enter the cell nucleus for infection, this work describes the importance of the role of IN and the conditions required for it to reach a full condensate, and hence provides a new understanding on the early role of IN in infection. Furthermore, the authors show that the semi-compact rosette condensate (i.e. the first phase) is susceptible to IN inhibitors whereas the second compaction phase is insusceptible. This work provides us with information that using inhibitors in the early stages of IN-DNA interaction, infection may be prevented.
Strengths:
The authors present a strong piece of work, using current experimental and computational methods to investigate IN-DNA interactions and to convincingly describe their experimental observations. Firstly the data and analysis shown from AFM and MT experiments convincingly show a two-phase compaction of DNA upon interaction with IN. The authors use Monte-Carlo simulations to model DNA-IN interactions, specifically showing that their experimental results of a two-phase compaction can only be observed via simulations if IN-IN attraction is included.
The authors aim of showing the effect of IN on the compaction of DNA was achieved successfully using AFM and MT. Furthermore, the works show clearly the susceptibility of the partially compacted DNA-IN core to inhibitors. Overall the conclusions in this paper are supported well by their experimental data and it is likely that this paper will not only be used as a model for future experimental work to explore other retroviral nucleoprotein condensation but also to develop a deeper understanding of the role of IN-inhibitors infection prevention.
Finally, the article is written very coherently and is well supported by critical analysis of their findings and appropriate referencing to supplementary figures.
Overall, this article is very worthy and through extensive and detailed work the authors probe difficult questions regarding HIV infection, which currently poses a huge global risk. The work completed by the authors substantially advances our understanding of HIV infection and can be used by those in the future to probe this question further.
Weaknesses:
Important aspects of the methodologies in this paper are not described in detail. For example, force volume curves have been used to evaluate the mechanical properties of the DNA-IN complex. Force-volume measurements are prone to a number of errors, particularly relating to data acquisition and analysis. The methodology presented is not clear on how the data is acquired, whether statically or in amplitude modulation, which affects analysis and interpretation. Although the authors do recognise some of the difficulties with force curve analysis, a more rigorous study could have been provided with citations to additional relevant literature (particularly taking note of the methods).
A minor point is that it is not clear that the AFM imaging is performed in air, in contrast to AFM force spectroscopy in liquid, which could affect the interpretation of the data and therefore comparisons which are drawn between the two. This is made more challenging as the methodology for the compaction measurements is not described in the methods, and the code is not provided. The source code should be made open-access and available to enable the work to be better understood and reproduced.
ANSWER: NO. Schedule II controlled substances are required to be written on an Official Texas Prescription form, which is only available to physicians licensed in Texas. Since Dr. Johnson is only licensed in Oklahoma, she is not able to order Official Prescription Forms, and can not prescribe Schedule II Controlled Substances in Texas.
OUT OF DATE , the answer should be depend, not completely no (a) A Schedule II controlled substance prescription issued by a practitioner in another state may be dispensed if: (1) the practitioner is authorized by the other state to prescribe the substance; (2) the pharmacy has a plan approved by and on file with the board allowing the activity; and (3) the pharmacy processes and submits the prescription according to the reporting requirements approved in the plan. Tex. Admin. Code § 315.9
compile
A compiler and an interpreter are both computer programs that convert high-level programming language code into machine code. However, they differ in how they translate the code and how they run: Compiler Translates the entire source code into machine code before the program runs. This results in faster execution because no translation is required during execution. Compilers are ideal for high-performance applications. Interpreter Translates the code line-by-line as the code runs. Interpreters are well-suited for rapid development, debugging, and situations where there is a need for platform independence.
Author response:
The following is the authors’ response to the current reviews.
Many thanks to the editors for the reviewing of the revised manuscript.
We are very grateful to the Reviewers for their time and for the appreciation of the revision.
We thank the Reviewer 3 for acknowledging the use of sulforhodamine B (SRB) fluorescence as a real-time readout of astrocyte volume dynamics. Experimental data in brain slices were provided to validate this approach.<br /> The incomplete matching of our observation with early reported data in cultured astrocytes (e.g., Solenov et al., AJP-Cell, 2004), might reflect certain of their properties differing from the slice/in vivo counterparts as discussed in the manuscript.<br /> The study (T.R. Murphy et al., Front Cell Neurosci., 2017) showed that AQP4 knockout increased astrocyte swelling extent in response to hypoosmotic solution in brain slices (Fig 9), and discussed '... AQP4 can provide an efficient efflux pathway for water to leave astrocytes.’ Correspondingly, our data suggest that AQP4 mediate astrocyte water efflux in basal conditions.<br /> We have discussed the study (Igarashi et al., NeuroReport 2013); our current data would help to understand the cellular mechanisms underlying the finding of Igarashi et al.
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
Pham and colleagues provide an illuminating investigation of aquaporin-4 water flux in the brain utilizing ex vivo and in vivo techniques. The authors first show in acute brain slices, and in vivo with fiber photometry, SRB-loaded astrocytes swell after inhibition of AQP4 with TGN-020, indicative of tonic water efflux from astrocytes in physiological conditions. Excitingly, they find that TGN-020 increases the ADC in DW-MRI in a region-specific manner, potentially due to AQP4 density. The resolution of the DW-MRI cannot distinguish between intracellular or extracellular compartments, but the data point to an overall accumulation of water in the brain with AQP4 inhibition. These results provide further clarity on water movement through AQP4 in health and disease.
Overall, the data support the main conclusions of the article, with some room for more detailed treatment of the data to extend the findings.
Strengths:
The authors have a thorough investigation of AQP4 inhibition in acute brain slices. The demonstration of tonic water efflux through AQP4 at baseline is novel and important in and of itself. Their further testing of TGN-020 in hyper- and hypo-osmotic solutions shows the expected reduction of swelling/shrinking with AQP4 blockade.
Their experiment with cortical spreading depression further highlights the importance of water efflux from astrocytes via AQP4 and transient water fluxes as a result of osmotic gradients. Inhibition of AQP4 increases the speed of tissue swelling, pointing to a role in the efflux of water from the brain.
The use of DW-MRI provides a non-invasive measure of water flux after TGN-020 treatment.
We thank the reviewer for the insightful comments.
Weaknesses:
The authors specifically use GCaMP6 and light sheet microscopy to image their brain sections in order to identify astrocytic microdomains. However, their presentation of the data neglects a more detailed treatment of the calcium signaling. It would be quite interesting to see whether these calcium events are differentially affected by AQP4 inhibition based on their cellular localization (ie. processes vs. soma vs. vascular end feet which all have different AQP4 expressions).
Following the suggestion, we provide new data on the effect of AQP4 inhibition on spontaneous calcium signals in perivascular astrocyte end-feet. As shown now in Fig.S2, acute application of TGN020 induced Ca2+ oscillations in astrocyte end-feet regions where the GCaMP6 labeling lines the profile of the blood vessel. It is noted that on average, the strength of basal Ca2+ signals in the end-feet is higher than that observed across global astrocyte territories (4.65 ± 0.55 vs. 1.45 ± 0.79, p < 0.01), as does the effect of TGN (8.4 ± 0.62 vs. 6.35 ± 0.97, p < 0.05; Fig S2 vs. Fig 2B). This likely reflects the enrichment of AQP4 in astrocyte end-feet. We describe the data in Fig.S2, and on page 8, line 20 – 23.
We now use the transgenic line GLAST-GCaMP6 for cytosolic GCaMP6 expression in astrocytes. Spontaneous calcium signals, reflected by transient fluorescence rises, occur in discrete micro-domains whereas the basal GCaMP6 fluorescence in the soma is weak. In the present condition, it is difficult to unambiguously discriminate astrocyte soma from the highly intermingled processes.
The authors show the inhibition of AQP4 with TGN-020 shortens the onset time of the swelling associated with cortical spreading depression in brain slices. However, they do not show quantification for many of the other features of CSD swelling, (ie. the duration of swelling, speed of swelling, recovery from swelling).
Regarding the features of the CSD swelling, we have performed new analysis to quantify the duration of swelling, speed of swelling and the recovery time from swelling in control condition and in the presence of TGN-020. The new analysis is now summarized in Fig. S5. Blocking AQP4 with TGN-020 increases the swelling speed, prolongs the duration of swelling and slows down the recovery from swelling, confirming our observation that acute inhibition of AQP4 water efflux facilitates astrocyte swelling while restrains shrinking. We describe the result on page 11, line 19-21.
Significance:
AQP4 is a bidirectional water channel that is constitutively open, thus water flux through it is always regulated by local osmotic gradients. Still, characterizing this water flux has been challenging, as the AQP4 channel is incredibly water-selective. The authors here present important data showing that the application of TGN-020 alone causes astrocytic swelling, indicating that there is constant efflux of water from astrocytes via AQP4 in basal conditions. This has been suggested before, as the authors rightfully highlight in their discussion, but the evidence had previously come from electron microscopy data from genetic knockout mice.
AQP4 expression has been linked with the glymphatic circulation of cerebrospinal fluid through perivascular spaces since its rediscovery in 2012 [1]. Further studies of aging[2], genetic models[3], and physiological circadian variation[4] have revealed it is not simply AQP4 expression but AQP4 polarization to astrocytic vascular endfeet that is imperative for facilitating glymphatic flow. Still, a lingering question in the field is how AQP4 facilitates fluid circulation. This study represents an important step in our understanding of AQP4's function, as the basal efflux of water via AQP4 might promote clearance of interstitial fluid to allow an influx of cerebrospinal fluid into the brain. Beyond glymphatic fluid circulation, clearly, AQP4-dependent volume changes will differentially alter astrocytic calcium signaling and, in turn, neuronal activity.
(1) Iliff, J.J., et al., A Paravascular Pathway Facilitates CSF Flow Through the Brain Parenchyma and the Clearance of Interstitial Solutes, Including Amyloid β. Sci Transl Med, 2012. 4(147): p. 147ra111.
(2) Kress, B.T., et al., Impairment of paravascular clearance pathways in the aging brain. Ann Neurol, 2014. 76(6): p. 845-61.
(3) Mestre, H., et al., Aquaporin-4-dependent Glymphatic Solute Transport in the Rodent Brain. eLife, 2018. 7.
(4) Hablitz, L., et al., Circadian control of brain glymphatic and lymphatic fluid flow. Nature Communications, 2020. 11(1).
We thank the reviewer in acknowledging the significance of our study and the functional implication in brain glymphatic system. We have now highlighted the mentioned studies as well as the potential implication glymphatic fluid circulation (page 4, line 9-10; page 5, line 1-3; and page 19, line 3-10).
Reviewer #2 (Public Review):
Summary:
The paper investigates the role of astrocyte-specific aquaporin-4 (AQP4) water channel in mediating water transport within the mouse brain and the impact of the channel on astrocyte and neuron signaling. Throughout various experiments including epifluorescence and light sheet microscopy in mouse brain slices, and fiber photometry or diffusion-weighted MRI in vivo, the researchers observe that acute inhibition of AQP4 leads to intracellular water accumulation and swelling in astrocytes. This swelling alters astrocyte calcium signaling and affects neighboring neuron populations. Furthermore, the study demonstrates that AQP4 regulates astrocyte volume, influencing mainly the dynamics of water efflux in response to osmotic challenges or associated with cortical spreading depolarization. The findings suggest that AQP4-mediated water efflux plays a crucial role in maintaining brain homeostasis, and indicates the main role of AQP4 in this mechanism. However authors highlight that the report sheds light on the mechanisms by which astrocyte aquaporin contributes to the water environment in the brain parenchyma, the mechanism underlying these effects remains unclear and not investigated. The manuscript requires revision.
Strengths:
The paper elucidates the role of the astrocytic aquaporin-4 (AQP4) channel in brain water transport, its impact on water homeostasis, and signaling in the brain parenchyma. In its idea, the paper follows a set of complimentary experiments combining various ex vivo and in vivo techniques from microscopy to magnetic resonance imaging. The research is valuable, confirms previous findings, and provides novel insights into the effect of acute blockage of the AQP4 channel using TGN-020.
We thank the reviewer for the constructive comments.
Weaknesses:
Despite the employed interdisciplinary approach, the quality of the manuscript provides doubts regarding the significance of the findings and hinders the novelty claimed by the authors. The paper lacks a comprehensive exploration or mention of the underlying molecular mechanisms driving the observed effects of astrocytic aquaporin-4 (AQP4) channel inhibition on brain water transport and brain signaling dynamics. The scientific background is not very well prepared in the introduction and discussion sections. The important or latest reports from the field are missing or incompletely cited and missconcluded. There are several citations to original works missing, which would clarify certain conclusions. This especially refers to the basis of the glymphatic system concept and recently published reports of similar content. The usage of TGN-020, instead of i.e. available AER-270(271) AQP4 blocker, is not explained. While employing various experimental techniques adds depth to the findings, some reasoning behind the employed techniques - especially regarding MRI - is not clear or seemingly inaccurate. Most of the time the number of subjects examined is lacking or mentioned only roughly within the figure captions, and there are lacking or wrongly applied statistical tests, that limit assessment and reproducibility of the results. In some cases, it seems that two different statistical tests were used for the same or linked type of data, so the results are contradictory even though appear as not likely - based on the figures. Addressing these limitations could strengthen the paper's impact and utility within the field of neuroscience, however, it also seems that supplementary experiments are required to improve the report.
The current data hint at a tonic water efflux from astrocyte AQP4 in physiological condition, which helps to understand brain water homeostasis and the functional implication for the glymphatic system. The underlying molecular and cellular mechanisms appear multifaceted and functionally interconnected, as discussed (page 14 line 8 –page 15, line 3). We agree that a comprehensive exploration will further advance our understanding.
The introduction and discussion are now strengthened by incorporating the important advances in glymphatic system while highlighting the relevant studies.
The use of TGN-020 was based on its validation by wide range of ex vivo and in vivo studies including the use of heterologous expression system and the AQP4 KO mice. The validation of AER-270(271, the water soluble prodrug) using AQP4 KO mice is reported recently (Giannetto et al., 2024). AER-271 was noted to impact brain water ADC (apparent diffusion coefficient evaluated by diffusion-weighted MRI) in AQP4 KO mice ~75 min after the drug application (Giannetto et al., 2024). This likely reflects that AER270(271) is also an inhibitor for κΒ nuclear factor (NF-κΒ) whose inhibition could reduce CNS water content independent of AQP4 targeting (Salman et al., 2022). In addition, the inhibition efficiency of AER-270(271) seems lower than TGN-020 (Farr et al., 2019; Giannetto et al., 2024; Huber et al., 2009; Salman et al., 2022). We have now supplemented this information in the manuscript (page 7, line 1-6 and page15, line 7-17).
The description on the DW-MRI is now updated (page 4, line 10-14).
We also performed new experiments and data analysis as described in a point-to-point manner below in the section ‘Recommendations For The Authors’.
Reviewer #3 (Public Review):
Summary:
In this manuscript, the authors propose that astrocytic water channel AQP4 represents the dominant pathway for tonic water efflux without which astrocytes undergo cell swelling. The authors measure changes in astrocytic sulforhodamine fluorescence as the proxy for cell volume dynamics. Using this approach, they perform a technically elegant series of ex vivo and in vivo experiments exploring changes in astrocytic volume in response to AQP4 inhibitor TGN-020 and/or neuronal stimulation. The key finding is that TGN-020 produces an apparent swelling of astrocytes and modifies astrocytic cell volume regulation after spreading depolarizations. Additionally, systemic application of TGN-020 produced changes in diffusion-weighted MRI signal, which the authors interpret as cellular swelling. This study is perceived as potentially significant. However, several technical caveats should be strongly considered and perhaps addressed through additional experiments.
Strengths:
(1) This is a technically elegant study, in which the authors employed a number of complementary ex vivo and in vivo techniques to explore functional outcomes of aquaporin inhibition. The presented data are potentially highly significant (but see below for caveats and questions related to data interpretation).
(2) The authors go beyond measuring cell volume homeostasis and probe for the functional significance of AQP4 inhibition by monitoring Ca2+ signaling in neurons and astrocytes (GCaMP6 assay).
(3) Spreading depolarizations represent a physiologically relevant model of cellular swelling. The authors use ChR2 optogenetics to trigger spreading depolarizations. This is a highly appropriate and much-appreciated approach.
We thank the reviewer for the effort in evaluating our work.
Weaknesses:
(1) The main weakness of this study is that all major conclusions are based on the use of one pharmacological compound. In the opinion of this reviewer, the effects of TGN-020 are not consistent with the current knowledge on water permeability in astrocytes and the relative contribution of AQP4 to this process.
Specifically: Genetic deletion of AQP4 in astrocytes reduces plasmalemmal water permeability by ~two-three-fold (when measured a 37oC, Solenov et al., AJP-Cell, 2004). This is a significant difference, but it is thought to have limited/no impact on water distribution. Astrocytic volume and the degree of anisosmotic swelling/shrinkage are unchanged because the water permeability of the AQP4null astrocytes remains high. This has been discussed at length in many publications (e.g., MacAulay et al., Neuroscience, 2004; MacAulay, Nat Rev Neurosci, 2021) and is acknowledged by Solenov and Verkman (2004).
Keeping this limitation in mind, it is important to validate astrocytic cell volume changes using an independent method of cell volume reconstruction (diameter of sulforhodamine-labeled cell bodies? 3D reconstruction of EGFP-tagged cells? Else?)
Solenov and coll. used the calcein quenching assay and KO mice demonstrating AQP4 as a functional water channel in cultured astrocytes (Solenov et al., 2004). AQP4 deletion reduced both astrocyte water permeability and the absolute amplitude of swelling over comparable time, and also slowed down cell shrinking, which overall parallels our results from acute AQP4 blocking. Yet in Solenovr’s study, the time to swelling plateau was prolonged in AQP4 KO astrocytes, differing from our data from the pharmacological acute blocking. This discrepancy may be due to compensatory mechanisms in chronic AQP4 KO, or reflect the different volume responses in cultured astrocytes from brain slices or in vivo results as suggested previously (Risher et al., 2009).
Soma diameter might be an indicator of cell volume change, yet it is challenging with our current fluorescence imaging method that is diffraction-limited and insufficient to clearly resolve the border of the soma in situ. In addition, the lateral diameter of cell bodies may not faithfully reflect the volume changes that can occur in all three dimensions. Rapid 3D imaging of astrocyte volume dynamics with sufficient high Z-axis resolution appears difficult with our present tools.
We have now accordingly updated the discussion with relevant literatures being cited (page 17 line 14 – page 18, line 3).
(2) TGN-020 produces many effects on the brain, with some but not all of the observed phenomena sensitive to the genetic deletion of AQP4. In the context of this work, it is important to note that TGN020 does not completely inhibit AQP4 (70% maximal inhibition in the original oocyte study by Huber et al., Bioorg Med Chem, 2009). Thus, besides not knowing TGN-020 levels inside the brain, even
"maximal" AQP4 inhibition would not be expected to dramatically affect water permeability in astrocytes.
This caveat may be addressed through experiments using local delivery of structurally unrelated AQP4 blockers, or, preferably, AQP4 KO mice.
It is an important point that TGN-020 partially blocks AQP4, implying the actual functional impact of AQP4 per se might be stronger than what we observed. TGN provides a means to acutely probe AQP4 function in situ, still we agree, its limitation needs be acknowledged. We mention this now on page 15, line 7-9 and 14-17.
We agree that local delivery of an alternative blocker will provide additional information. Meanwhile, local delivery requires the stereotaxic implantation of cannula, which would cause inflammations to surrounding astrocytes (and neurons). The recently introduced AQP4 blocker AER-270(271) has received attention that it influences brain water dynamics (ADC in DW-MRI) in AQP4 KO mice (Giannetto et al., 2024), recalling that AER-270(271) is also an inhibitor for κΒ nuclear factor (NF-κΒ). This pathway can potentially perturb CNS water content and influence brain fluid circulation, in an AQP4independent manner (Salman et al., 2022). The inhibition efficiency on mouse AQP4 of AER-270 (~20%, Farr et al., 2019; Salman et al., 2022) appears lower than TGN-020 (~70%, Huber et al., 2009).
We chose to use the pharmacological compound to achieve acute blocking of AQP4 thereby avoiding the chronic genetics-caused alterations in brain structural, functional and water homeostasis. Multiple lines of evidence including the recent study (Gomolka et al., 2023), have shown that AQP4 KO mice alters brain water content, extracellular space and cellular structures, which raises concerns to use the transgenic mouse to pinpoint the physiological functions of the AQP4 water channel.
We have now mentioned the concerns on AQP4 pharmacology by supplementing additional literatures in the field (page 15, line 8-18).
(3) This reviewer thinks that the ADC signal changes in Figure 5 may be unrelated to cellular swelling. Instead, they may be a result of the previously reported TGN-020-induced hyphemia (e.g., H. Igarashi et al., NeuroReport, 2013) and/or changes in water fluxes across pia matter which is highly enriched in AQP4. To amplify this concern, AQP4 KO brains have increased water mobility due to enlarged interstitial spaces, rather than swollen astrocytes (RS Gomolka, eLife, 2023). Overall, the caveats of interpreting DW-MRI signal deserve strong consideration.
The previous observation show that TGN-020 increases regional cerebral blood flow in wild-type mice but not in AQP4 KO mice (Igarashi et al., 2013). Our current data provide a possible mechanism explanation that TGN-020 blocking of astrocyte AQP4 causes calcium rises that may lead to vasodilation as suggested previously (Cauli and Hamel, 2018). We now add updates to the discussion on page 15, line 3-7.
We are in line with the reviewer regarding the structural deviations observed with the AQP4 KO mice
(Gomolka et al., 2023), now mentioned on page 19, line 3-5. Following the Reviewer’s suggestion, we have also updated the interpretation of the DW-MRI signal and point that in addition to being related to the astrocyte swelling, the ADC signal changes may also be caused by indirect mechanisms, such as the transient upregulation of other water-permeable pathways in compensating AQP4 blocking. We now describe this alternative interpretation and the caveats of the DW-MRI signals (page 20, line 1-8).
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
Private recommendations
My more broad experimental suggestions are in the "weaknesses" section. Some minor points that would improve the manuscript are included below:
(1) A more detailed explanation for why SRB fluorescence reflects the astrocyte volume changes, whereas typical intracellular GFP does not.
As an engineered fluorescence protein, the GFP has been used to tag specific type of cells. Meanwhile, as a relatively big protein (MW, 26.9 kDa), the diffusion rate of EGFP is expected to be much less than SRB, a small chemical dye (MW, 558.7 Da). Also, the IP injection of SRB enables geneticsless labeling of brain astrocytes, so to avoid the influence of protein overexpression on astrocyte volume and water transport responses. We have now stated this point in the manuscript (page 13, line 21 – page 14, line 4).
(2) Figure 1 panel B should have clear labels on the figure and a description in the legend to delineate which part of the panel refers to hyper- or hypo-osmotic treatment.
We have now updated the figure and the legend.
(3) For Figure 2, what is the rationale for analyzing the calcium signaling data between the cell types differently?
We analyzed calcium micro-domains for astrocytes as their spontaneous signals occur mainly in discrete micro-domains (Shigetomi et al., 2013). While for neurons, we performed global analysis by calculating the mean fluorescence of imaging field of view, because calcium signal changes were only observed at global level rather than in micro-domains. This information is now included (page 24, line1820).
(4) For Figure 3, the authors mention that TGN-020 likely caused swelling prior to the hypotonic solution administration. Do they have any measurements from these experiments prior to the TGN-020 application to use as a "true baseline" volume?
The current method detects the relative changes in astrocyte volume (i.e., transmembrane water transport), which nevertheless is blind to the absolute volume value. We have no readout on baseline volumes.
(5) For Figures 3 and 4, did the authors see any evidence for regulatory volume decrease? And is this impaired by TGN-020? It is a well-characterized phenomenon that astrocytes will open mechanosensitive channels to extrude ions during hypo-osmotic induced swelling. This process is dependent on AQP4 and calcium signaling [5]
Mola and coll. provided important results demonstrating the role of AQP4 in astrocyte volume regulation (Mola et al., 2016). In the present study in acute brain slices, when we applied hypotonic solution to induce astrocyte swelling, our protocol did not reveal rapid regulatory volume decrease (e.g., Fig. 3D). When we followed the volume changes of SRB-labeled astrocytes during optogenetically induced CSD, we observed the phase of volume decrease following the transient swelling (Fig. 4F), where the peak amplitude and the degree of recovery were both reduced by inhibiting AQP4 with TGN020. These data imply that regulatory astrocyte volume decrease may occur in specific conditions, which intriguingly has been suggested to be absent in brain slices and in vivo (e.g., Risher et al., 2009). We have not specifically investigated this phenomenon, and now briefly discuss this point on page18 line 6-14.
(6) Figure 5 box plots do not show all data points, could the authors modify to make these plots show all the animals, or edit the legend to clarify what is plotted?
We have now updated the plot and the legend. This plot is from all animals (n = 7 per condition).
(7) pg. 9 line 6, there is a sentence that seems incomplete or otherwise unfinished. "We first followed the evoked water efflux and shrinking induced by hypertonic solution while."
Fixed (now, page 9 line 17-18).
(8) During the discussion on pg 13 line 11, it may be more clear to describe this as the cotransport of water into the cells with ions/metabolites as reviewed by Macaulay 2021 [6].
We agree; the text is modified following this suggestion (now page14, line 12-13).
(1) Iliff, J.J., et al., A Paravascular Pathway Facilitates CSF Flow Through the Brain Parenchyma and the Clearance of Interstitial Solutes, Including Amyloid β. Sci Transl Med, 2012. 4(147): p. 147ra111.
(2) Kress, B.T., et al., Impairment of paravascular clearance pathways in the aging brain. Ann Neurol, 2014. 76(6): p. 845-61.
(3) Mestre, H., et al., Aquaporin-4-dependent Glymphatic Solute Transport in the Rodent Brain. eLife, 2018. 7.
(4) Hablitz, L., et al., Circadian control of brain glymphatic and lymphatic fluid flow. Nature Communications, 2020. 11(1).
(5) Mola, M., et al., The speed of swelling kinetics modulates cell volume regulation and calcium signaling in astrocytes: A different point of view on the role of aquaporins. Glia, 2016. 64(1).
(6) MacAulay, N., Molecular mechanisms of brain water transport. Nat Rev Neurosci, 2021. 22(6): p. 326-344.
We thank the reviewer. These important literatures are now supplemented to the manuscript together with the corresponding revisions.
Reviewer #2 (Recommendations For The Authors):
In its concept, the paper is interesting and provides additional value - however, it requires revision.
Below, I provide the following remarks for the following sections/ pages/lines:
ABSTRACT/page 2 (remarks here refer to the rest of the manuscript, where these sentences are repeated):
- It seems that the 'homeostasis' provides not only physical protection, but also determines the diffusion of chemical molecules...' Please correct the sentence as it is grammatically incorrect.
It is now corrected (page 2, line 1).
- The term 'tonic water' is not clear. I understand, after reading the paper, that it is about tonicity of the solutes injected into the mouse.
We use the term ‘tonic’ to indicate that in basal conditions, a constant water efflux occurs through the APQ4 channel.
- 'tonic aquaporin water efflux maintains volume equilibrium' - I believe it is about maintaining volume and osmotic equilibrium?
This description is now refined (now page 2, line 10).
- It is not clear whether the tonic water outflow refers to the cellular level or outflow from the brain parenchyma (i.e., glymphatic efflux)
It refers to the cellular level.
INTRODUCTION/page 3:
- 'clearance of waste molecules from the brain as described in the glymphatic system' - The original papers describing the phenomena are not cited: Iliff et al. 2012, 2013, Mestre et al. 2018, as well as reviews by Nedergaard et al.
Indeed. We have now cited these key literatures (now page 4, line 10).
- 'brain water diffusion is the basis for diffusion-weighted magnetic resonance imaging (DW-MRI)' - The statement is wrong. it is the mobility of the water protons that DWI is based on, but not the diffusion of molecules in the brain. This should be clarified and based on the DW-MRI principle and the original works by Le Bihan from 1986, 1988, or 2015.
This sentence is now updated (page 4, line10-14).
- Similarly, I suggest correcting or removing the citations and the sentence part regarding the clinical use of DWI, as it has no value here. Instead, it would be worth mentioning what actually ADC reflects as a computational score, and what were the results from previous studies assessing glymphatic systems using DWI. This is especially important when considering the mislocalization of the AQP4 channel.
We now states recent studies using DW-MRI to evaluate glymphatic systems (page 4, line16-17).
- 'In the brain, AQP4 is predominantly expressed in astrocytes'-please review the citations. I suggest reading the work by Nielsen 1997, Nagelhus 2013, Wolburg 2011, and Li and Wang from 2017. To my best knowledge, in the brain AQP4 is exclusively expressed in astrocytes.
Thanks for the reviewer. It is described that while enriched in astrocytes, AQP4 is also expressed in ependymal cells lining the ventricles (e.g., (Mayo et al., 2023; Verkman et al., 2006)). ‘predominantly’ is now removed (page 4, line 21).
- The conclusion: ' Our finding suggests that aquaporin acts as a water export route in astrocytes in physiological conditions, so as to counterbalance the constitutive intracellular water accumulation caused by constant transmitter and ion uptake, as well as the cytoplasmic metabolism processes. This mechanism hence plays a necessary role in maintaining water equilibrium in astrocytes, thereby brain water homeostasis' seems to be slightly beyond the actual findings in the paper. I suggest clarifying according to the described phenomena.
We have now refined the conclusion sticking to the experimental observations (page 5, line16-18).
- The introduction lacks important information on existing AQP4 blockers and their effects, pros and cons on why to use TGN-020. Among others, I would refer to recent work by Giannetto et al 2024, as well as previous work of Mestre et al. 2018 and Gomolka et al. 2023.
We initiated the study by using TGN-020 as an AQP4 blocker because it has been validated by wide range of ex vivo and in vivo studies as documented in the text (page 7, line 1-6). We also update discussions on the recent advances in validating the AQP4 blocker AER-270(271) while citing the relevant studies (page 15, line 7-17).
RESULTS:
- Page 5, lines 19-20: '...transport, we performed fluorescence intensity translated (FIT) imaging.' - this term was never introduced in the methods so it is difficult for the reader to understand it at first sight. -'To this end,' - it is not clear which action refers to 'this'. (is it about previous works or the moment that the brain samples were ready for imaging? Please clarify, as it is only starting to be clear after fully reading the methods.
We now refine the description give the principle of our imaging method first, then explain the technical steps. To avoid ambiguity, the term ‘To this end’ is removed. The updated text is now on page 6, line 1-3.
- From page 6 onwards - all references to Figures lack information to which part of the figure subpanel the information refers (top/middle bottom or left/middle/right).
We apologize. The complementary indication is now added for figure citations when applicable.
- 'whereas water export and astrocyte shrinking upon hyperosmotic manipulation increased astrocyte fluorescence (Figure 1B). Hence, FIT imaging enables real-time recording of astrocyte transmembrane water transport and volume dynamics.' - this part seems to be undescribed or not clear in the methods.
We have now refined this description (page 6, line 19-20).
- Page 6, lines 17-22: TGN-020. In addition to the above, I suggest familiarizing also with the following works by Igarashi 2011. doi: 10.1007/s10072-010-0431-1, and by Sun 2022. doi: 10.3389/fimmu.2022.870029.
These studies are now cited (page 7, line 3-4).
- Page 7: ' AQP4 is a bidirectional channel facilitating... ' - AQP4 water channel is known as the path of least resistance for water transfer, please see Manley, Nature Medicine, 2000 and Papadopoulos, Faseb J, 2004.
This sentence is now updated (page 7, line 12-13).
- ' astrocyte AQP4 by TGN-020 caused a gradual decrease in SRB fluorescence intensity, indicating an intracellular water accumulation' - tissue slice experiment is a very valuable method. However it seems right, the experiment does not comment on the cell swelling that may occur just due to or as a superposition of tissue deterioration and the effect of TGN-020. The AQP4 channel is blocked, and the influx of water into astrocytes should be also blocked. Thus, can swelling be also a part of another mechanism, as it was also observed in the control group? I suggest this should be addressed thoroughly.
We performed this experiment in acute brain slices to well control the pharmacological environment and gain spatial-temporal information. Post slicing, the brain slices recovered > 1hr prior to recording, so that the slices were in a stable state before TGN-020 application as evidenced by the stable baseline. The constant decrease in the control trace is due to photobleaching which did not change its curve tendency in response to vehicle. TGN-020, in contrast, caused a down-ward change suggesting intracellular water accumulation and swelling.
The experiment was performed at basal condition without active water influx; a decrease in SRB fluorescence hints astrocyteintracellular water buildup. This result shows that in basal condition, astrocyte aquaporin mediates a constant (i.e., tonic) water efflux; its blocking causes intracellular water accumulation and swelling.
We have accordingly updated the description of this part (page 7, line 15-20).
- From the Figure 1 legend: Only 4 mice were subjected to the experiment, and only 1 mouse as a control. I suggest expanding the experiment and performing statistics including two-way ANOVA for data in panels B, C, and D, as no results of statistical tests confirm the significance of the findings provided.
The panel B confirms that cytosolic SRB fluorescence displays increasing tendency upon water efflux and volume shrinking, and vice versa. As for the panel C, the number of mice is now indicated. Also, the downward change in the SRB fluorescence was now respectively calculated for the phases prior and post to TGN (and vehicle) application, and this panel is accordingly updated. TGN-020 induced a declining in astrocyte SRB fluorescence, which is validated by t-test performed in MATLAB. To clarify, we now add cross-link lines to indicate statistical significance between the corresponding groups (Fig 1C, middle). As for panel D, we calculated the SRB fluorescence change (decrease) relative to the photobleaching tendency illustrated by the dotted line. The significance was also validated by t-test performed in MATLAB.
- Figure 1: Please correct the figure - pictures in panel A are low quality and do not support the specificity of SRB for astrocytes. Panels B-D are easier to understand if plotted as normal X/Y charts with associated statistical findings. Some drawings are cut or not aligned.
In GFAP-EGFP transgenic, astrocytes are labeled by EGFP. SRB labeling (red fluorescence) shows colocalization with EGFP-positive astrocytes, meanwhile not all EGFP-positive astrocytes are labeled by SRB. The PDF conversion procedure during the submission may also somehow have compromised image quality. We have tried to update and align the figure panels.
- Page 12: ' TGN-020 increased basal water diffusion within multiple regions including the cortex,
hippocampus and the striatum in a heterogeneous manner (Figure 5C).'
This sentence is updated now (page 12, line 12 – page13, line 2). It reads ‘The representative images reveal the enough image quality to calculate the ADC, which allow us to examine the effect of TGN-020 on water diffusion rate in multiple regions (Fig. 5C).’
- The expression of AQP4 within the brain parenchyma is known to be heterogenous. Please familiarize yourself with works by Hubbard 2015, Mestre 2018, and Gomolka 2023. A correlation between ADC score and AQP4 expression ROI-wise would be useful, but it is not substantial to conduct this experiment.
We thank the reviewer. This point is stressed on page 19, line 12-14.
DISCUSSION:
- Most of the issues are commented on above, so I suggest following the changes applied earlier. -Page 16: 'We show by DW-MRI that water transport by astrocyte aquaporin is critical for brain water homeostasis.' This statement is not clear and does not refer to the actual impact of the findings. DWI is allowed only to verify the changes of ADC fter the application of TGN-020. I suggest commenting on the recent report by Giannetto 2024 here.
This sentence is now refined (page 19, line 1-2), followed by the updates commenting on the recent studies employing DW-MRI to evaluate brain fluid transport, including the work of (Giannetto et al., 2024) (page 19, line 3-10).
METHODS:
- Page 18: no total number of mice included in all experiments is provided, as well as no clearly stated number of mice used in each experiment. Please correct.
We have now double checked the number of the mice for the data presented and updated the figure legends accordingly (e.g., updates in legends fig1, fig5, etc).
- Page 18, line 7: 'Axscience' is not a producer of Isoflurane, but a company offering help with scientific manuscript writing. If this company's help was used, it should be stated in the acknowledgments section. Reference to ISOVET should be moved from line 15 to line 7.
We apologize. We did not use external writing help, and now have removed the ‘Axcience’. The Isoflurane was under the mark ‘ISOVET’ from ‘Piramal’. This info is now moved up (page 21, line 11).
- Page 18, line 9: ' modified artificial cerebrospinal fluid (aCSF)'. Additional information on the reason for the modified aCSF would be useful for the reader.
In this modified solution, the concentration of depolarizing ions (Na+, Ca2+) was reduced to lower the potential excitotoxicity during the tissue dissection (i.e., injury to the brain) for preparing the brain slices. Extra sucrose was added to balance the solution osmolarity. This solution has been used previously for the dissection and the slicing steps in adult mice (Jiang et al., 2016). We now add this justification in the text and quote the relevant reference (page 21, line14-16).
- Page 19, line 6: a reasoning for using Tamoxifen would be helpful for the reader.
The Glast-CreERT2 is an inducible conditional mouse line that expresses Cre recombinase selectively in astrocytes upon tamoxifen injection. We now add this information in the text (page 22, line 10-11).
- Line 8 - 'Sigma'
Fixed.
- Line 7/8: It is not clear if ethanol is of 10% solution or if proportions of ethanol+tamoxifen to oil were of 1:9. The reasoning for each performed step is missing.
We have now clarified the procedure (page 22, line 11-15).
- Line 10: '/' means 'or'?
Here, we mean the bigenic mice resulting from the crossing of the heterozygous Cre-dependent GCaMP6f and Glast-CreERT2 mouse lines. We now modify it to ‘Glast-CreERT2::Ai95GCaMP6f//WT’, in consistence with the presentation of other mouse lines in our manuscript (page 22, line 16).
- Lines 22-23: being in-line with legislation was already stated at the beginning of the Methods so I suggest combining for clearance.
Done.
- Page 21, line 4: it is good to mention which printer was used, but it would be worth mentioning the material the chamber was printed from - was it ABS?
Yes. We add this info in the text now (page 24, line 5).
- Line 9 -'PI' requires spelling out.
It is ‘Physik Instrumente’, now added (page 24, line 10).
- Line 11-12: What is the reason for background subtraction - clearer delineation of astrocytes/ increasing SNR in post-processing, or because SRB signal was also visible and changing in the background over time? Was the background removed in each frame independently (how many frames)? How long was the time-lapse and was the F0 frame considered as the first frame acquired? The background signal should be also measured and plotted alongside the astrocytic signal, as a reference (Figure 1). This should be clarified so that steps are to be followed easily.
We sought to follow the temporal changes in SRB fluorescence signal. The acquired fluorescent images contain not only the SRB signals, but also the background signals consisting of for instance the biological tissue autofluorescence, digital camera background noise and the leak light sources from the environments. The value of the background signal was estimated by the mean fluorescence of peripheral cell-free subregions (15 × 15 µm²) and removed from all frames of time-lapse image stack. The traces shown in the figures reflect the full lengths of the time-lapse recordings. F0 was identified as the mean value of the 10 data points immediately preceding the detected fluorescence changes. The text is now updated (page 24 line 21 - page 25 line 5).
- Line 15: Was astrocyte image delineation performed manually or automatically? Where was the center of the region considered in the reference to the astrocyte image? It would be good to see the regions delineated for reference.
Astrocytes labeled by SRB were delineated manually with the soma taken as the center of the region of interest. We now exemplify the delineated region in Fig 1A, bottom.
- Page 22, line 2: 'x4 objective'.
Added (now, page 25, line 16).
- Line 3: 'barrels' - reference to publication or the explanation missing.
The relevant reference is now added on barrel cortex (Erzurumlu and Gaspar, 2020) (page 25, line 19-20).
- Line 19: were the coordinates referred to = bregma?
Yes. This info is now added (page 26, line 12).
- Line 20: was the habituation performed directly at the acquisition date? It is rather difficult to say that it was a habituation, but rather acute imaging. I suggest correcting, that mice were allowed to familiarize themselves with the setup for 30 minutes prior to the imaging start.
In this context, although it is a very nice idea and experiment, the influence of acute stress in animals familiar with the setup only from the day of acquisition is difficult to avoid. It is a major concern, especially when considering norepinephrine as a master driver of neuronal and vascular activity through the brain, and strong activation of the hypothalamic-adrenal axis in response to acute stress. It is well known, that the response of monoamines is reduced in animals subjected to chronic v.s acute stress, but still larger than that if the stressor is absent.
Major remark: The animals should, preferably, be imaged at least after 3 days of habituation based on existing knowledge. I suggest exploring the topic of the importance of habituation. It is difficult though, to objectively review these findings without considering stress and associated changes in vascular dynamics.
Many thanks for the reviewer to help to precise this information. The text is accordingly updated to describe the experiment (now page 26, line 14).
- Page 23, line 17: number of animals included in experiments missing.
The number of animals is added in Methods (page 27, line 12) and indicated in the legend of Figure 5.
- Line 18/19: were the respiratory effects observed after injection of saline or TGN-020? Since DWI was performed, the exclusion of perfusive flow on ADC is impossible.
I suggest an additional experiment in n=3 animals per group, verifying the HR (and if possible BP) response after injection of TGN-020 and saline in mice.
The respiratory rate has been recorded. We added the averaged respiratory rate before and after injection of TGN-020 or saline (now, Fig. S6; page 13, line 5-6).
- Line 22: Please, provide the model of the scanner, the model of the cryoprobe, as well as the model of the gradient coil used, otherwise it is difficult to assess or repeat these experiments.
We have now added the information of MRI system in Methods section (page 27, line17-21).
- Page 24: line 3/4: although the achieved spatial resolution of DWI was good and slightly lower than desired and achievable due to limitations of the method itself as well as cryoprobe, it is acceptable for EPI in mice.
Still, there is no direct explanation provided on the reasoning for using surface instead of volumetric coil, as well as on assuming an anisotropic environment (6 diffusion directions) for DWI measurements. This is especially doubtful if such a long echo-time was used alongside lower-thanpossible spatial resolution. Longer echo time would lower the SNR of the depicted signal but also would favor the depiction of signal from slow-moving protons and larger water pools. On the other hand, only 3 b-values were used, which is the minimum for ADC measurements, while a good research protocol could encompass at least 5 to increase the accuracy of ADC estimation and avoid undersampling between 250 and 1800 b-values. What was the reason for choosing this particular set of b-values and not 50, 600, and 2000? Besides, gradient duration time was optimally chosen, however, I have concerns about the decision for such a long gradient separation times.
If the protocol could have been better optimized, the assessment could have been also performed in respiratory-gated mode, allowing minimization of the effects of one of the glymphatic system driving forces.
Thus, I suggest commenting on these issues.
We chose the cryoprobe to increase the signal-to-noise ratio (SNR) in DW-MRI with long echo-time and high b-value. The volume coil has a more homogeneous SNR in the whole brain rather than the cryoprobe, but SNR should be reduced compared with cryoprobe. We confirmed that, even at the ventral part of the brain, the image quality of DW-MRI images was enough to investigate the ADC with cryoprobe (Fig. 5B-C). This is mentioned now in Methods (page 27, line 17-21).
We performed DW-MRI scanning for 5 min at each time-point using the condition of anisotropic resolution and 3 b-values, to investigate the time-course of ADC change following the injection of TGN020. Because the effect of TGN-020 appears about dozen of minutes post the injection (Igarashi et al., 2011), fast DW-MRI scanning is required. If isotropic DW-MRI with lower echo-time and more direction is used, longer scan time at each time point is required, maybe more than 1h. We agree that three bvalues is minimum to calculate the ADC and more b-values help to increase the accuracy. However, to achieve the temporal resolution so as to better catch the change of water diffusion, we have decided to use the minimum b-values. The previous study also validates the enough accuracy of DW-MRI with three b-values (Ashoor et al., 2019). Furthermore, previous study that used long diffusion time (> 20 ms) and long echo time (40 ms) shows the good mean diffusivity (Aggarwal et al., 2020), supporting that our protocol is enough to investigate the ADC. We have now updated the description (page 28 line 5-9). The reason why we choose the b = 250 and 1800 s/mm² is that 2000 s/mm² seems too high to get the good quality of image. In the previous study, we have optimized that ADC is measurable with b = 0, 250, and 1800 s/mm² (Debacker et al., 2020).
- Page 24, line 7: What was the post-processing applied for images acquired over 70 minutes? Did it consider motion-correction, co-registration, or drift-correction crucial to avoid pitfalls and mismatches in concluding data?
The motion correction and co-registration were explained in Methods (page 28, line 12-14).
Also, were these trace-weighted images or magnitude images acquired since DTI software was used for processing - while ADC fitting could be reliably done in Matlab, Python, or other software. Thus, was DSI software considering all 3 b-values or just used 0 and 1800 for the calculation of mean diffusivity for tractography (as ADC). The details should be explained.
DSIstudio was used with all three b values (b = 0, 250, and 1800 s/mm²) to calculate the ADC. We added the description in Methods (page 28, line 16-18).
To make sure that the results are not affected by the MR hardware, I suggest performing 3 control measurements in a standard water phantom, and presenting the results alongside the main findings.
Thanks for this suggestion. We have performed new experiments and now added the control measurement with three phantoms, that is water, undecane, and dodecane. These new data are summarized now in Fig. S7, showing the stability of ADC throughout the 70 min scanning. We have updated the description on Method part (page 28, line 9-11) and on the Results (page 13, line 6-8).
- Line 13: were the ROI defined manually or just depicted from previously co-registered Allen Brain atlas?
The ROIs of the cortex, the hippocampus, and the striatum were depicted with reference to Allen mouse brain atlas (https://scalablebrainatlas.incf.org/mouse/ABA12). This is explained in Methods (page 28, line 14-16).
- Line 10: why the average from 1st and 2nd ADC was not considered, since it would reduce the influence of noise on the estimation of baseline ADC?
We are sorry that it was a typo. The baseline was the average between 1st and 2nd ADC. We corrected the description (page 28, line 20).
STATISTIC:
Which type of t-test - paired/unpaired/two samples was used and why? Mann-Whitney U-tets are used as a substitution for parametric t-tests when the data are either non-parametric or assuming normal distribution is not possible. In which case Bonferroni's-Holm correction was used? - I couldn't find any mention of any multiple-group analysis followed by multiple comparisons. Each section of the manuscript should have a description of how the quantitative data were treated and in which aim. I suggest carefully correcting all figures accordingly, and following the remarks given to the Figure 1.
We used unpaired t-test for data obtained from samples of different conditions. Indeed, MannWhitney U-test is used when the data are non-parametric deviating from normal distributions. Bonferroni-Holm correction was used for multiple comparisons (e.g., Fig. 4D-E).
Reviewer #3 (Recommendations For The Authors):
I think that the following statement is insufficient: "The authors commit to share data, documentation, and code used in analysis". My understanding is eLife expects that all key data to be provided in a supplement.
We thank the reviewer; we follow the publication guidelines of eLife.
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Author response:
Joint Public Reviews:
Here, the authors compare how different operationalizations of adverse childhood experience exposure related to patterns of skin conductance response during a fear conditioning task. They use a large dataset to definitively understand a phenomenon that, to date, has been addressed using a range of different definitions and methods, typically with insufficient statistical power. Specifically, the authors compared the following operationalizations: dichotomization of the sample into "exposed" and "non-exposed" categories, cumulative adversity exposure, specificity of adversity exposure, and dimensional (threat versus deprivation) adversity exposure. The paper is thoughtfully framed and provides clear descriptions and rationale for procedures, as well as package version information and code. The authors' overall aim of translating theoretical models of adversity into statistical models, and comparing the explanatory power of each model, respectively, is an important and helpful addition to the literature. However, the analysis would be strengthened by employing more sophisticated modelling techniques that account for between-subjects covariates and the presentation of the data needs to be streamlined to make it clearer for the broad audience for which it is intended.
Strengths
Several outstanding strengths of this paper are the large sample size and its primary aim of statistically comparing leading theoretical models of adversity exposure in the context of skin conductance response. This paper also helpfully reports Cohen's d effect sizes, which aid in interpreting the magnitude of the findings. The methods and results are generally thorough.
Weaknesses
Weakness 1: The largest concern is that the paper primarily relies on ANOVAs and pairwise testing for its analyses and does not include between-subjects covariates. Employing mixedeffects models instead of ANOVAs would allow more sophisticated control over sources of random variance in the sample (especially important for samples from multi-site studies such as the present study), and further allow the inclusion of potentially relevant between-subjects covariates such as age (e.g. Eisenstein et al., 1990) and gender identity or sex assigned at birth (e.g. Kopacz II & Smith, 1971) (perhaps especially relevant due to possible to gender or sex-related differences in ACE exposure; e.g. Kendler et al., 2001). Also, proxies for socioeconomic status (e.g. income, education) can be linked with ACE exposure (e.g. Maholmes & King, 2012) and warrant consideration as covariates, especially if they differ across adversity-exposed and unexposed groups.
We appreciate the reviewer's suggestion and recognize the value of using (more) sophisticated statistical methods. However, we think that considerations which methods to employ should not only be guided by perceived complexity and think that the chosen ANOVA -based approach provides reliable and valid data. In our revision, we address the reviewer's suggestion by demonstrating that employing mixed models leaves the reported results unchanged (a). We would also like to refer the reviewer to the robustness analyses provided in the initial supplementary material (b).
a) Re-running analyses using mixed models
Based on the reviewers' suggestion, we repeated our main analyses (association between exposure to childhood adversity and SCRs, arousal, valence, and contingency ratings during fear acquisition and generalization) using linear mixed models, including age, sex, educational attainment, and childhood adversity as fixed effects, and site as a random effect. These analyses produced results similar to those in our manuscript, demonstrating a significant effect of childhood adversity on SCRs, as assessed by CS discrimination during both acquisition training and the generalization phase, and on general reactivity, but not on linear deviation scores (LDS). For the different rating types, we did not observe any significant effects of childhood adversity.
We would prefer to retain our main analyses as they are and report the linear mixed model results as additional results in the supplement. However, if the reviewer and editor have strong preferences otherwise, we are open to presenting the mixed models in the main manuscript and moving our previous analyses to the supplement.
We added the following paragraph to the main manuscript (page 25-26):
“At the request of a reviewer, we repeated our main analyses by using linear mixed models including age, sex, school degree (i.e., to approximate socioeconomic status), and exposure to childhood adversity as mixed effects as well as site as random effect. These analyses yielded comparable results demonstrating a significant effect of childhood adversity on CS discrimination during acquisition training and the generalization phase as well as on general reactivity, but not on the generalization gradients in SCRs (see Supplementary Table 2 A). Consistent with the results of the main analyses reported in our manuscript, we did not observe any significant effects of childhood adversity on the different types of ratings when using mixed models (see Supplementary Table 2 B-D). Some of the mixed model analyses showed significantly lower CS discrimination during acquisition training and generalization, and lower general reactivity in males compared to females (see Supplementary Table 2 for details).”
b) Additional robustness tests for the main analyses (already provided in the initial submission as supplementary material)
We would also like to refer the reviewer to the robustness analyses in the initial supplement to account for possible site effects. Adding site to the analyses affected the pvalue in only one instance: entering site as covariate in analyses of CS discrimination during acquisition training attenuated the p-value of the ACQ exposure effect from p = 0.020 to p = 0.089.
Further robustness checks involved repeating our main analyses while excluding (a) physiological non-responders (participants with only SCRs = 0) and (b) extreme outliers (data points ± 3 SDs from the mean) to ensure generalizable results. These repetitions of the analyses did not lead to any changes in the results.
We did not include age in our primary analyses due to the homogeneity of our sample and the lack of related hypotheses. Additionally, socio-economic status was assessed only crudely via the highest education level attained, rendering it of limited use.
Weakness 2: On a related methodological note, the authors mention that scores representing threat and deprivation were not problematically collinear due to VIFs being <10; however, some sources indicate that VIFs should be <5 (e.g. Akinwande et al., 2015).
We thank the reviewer for bringing different cut-offs to our attention. We have revised this section to highlight the arbitrary nature of their interpretation (page 33):
“Within the dimensional model framework, the issue of multicollinearity among predictors (i.e., different childhood adversity types) is frequently discussed (McLaughlin et al., 2021; Smith & Pollak, 2021). If we apply the rule of thumb of a variance inflation factor (VIF) > 10, which is often used in the literature to indicate concerning multicollinearity (e.g., Hair, Anderson, Tatham, & Black, 1995; Mason, Gunst, & Hess, 1989; Neter, Wasserman, & Kutner, 1989), we can assume that that multicollinearity was not a concern in our study (abuse: VIF = 8.64; neglect: VIF = 7.93). However, some authors state that VIFs should not exceed a value of 5 (e.g., Akinwande, Dikko, and Samson (2015)), while others suggest that these rules of thumb are rather arbitrary (O’brien, 2007).”
Weakness 3: Additionally, the paper reports that higher trait anxiety and depression symptoms were observed in individuals exposed to ACEs, but it would be helpful to report whether patterns of SCR were in turn associated with these symptom measures and whether the different operationalizations of ACE exposure displayed differential associations with symptoms.
We thank the reviewer for highlighting these relevant points. We have included additional analyses in the supplementary material in response to this comment. Figures and the corresponding text are also copied below for your convenience.
We added the following paragraphs to the main manuscript: Methods (page 21):
“Analyses of trait anxiety and depression symptoms
To further characterize our sample, we compared individuals being unexposed compared to exposed to childhood adversity on trait anxiety and depression scores by using Welch tests due to unequal variances.
On the request of a reviewer, we additionally investigated the association of childhood adversity as operationalized by the different models used in our explanatory analyses (i.e., cumulative risk, specificity, and dimensional model) and trait anxiety as well as depression scores (see Supplementary Figure 7). By using STAI-T and ADS-K scores as independent variable, we calculated a) a comparison of conditioned responding of the four severity groups (i.e., no, low, moderate, severe exposure to childhood adversity) using one-way ANVOAs and the association with the number of sub-scales exceeding an at least moderate cut-off in simple linear regression models for the implementation of the cumulative risk model, and b) the association with the CTQ abuse and neglect composite scores in separate linear regression models for the implementation of the specificity/dimensional models. On request of the reviewer, we also calculated the Pearson correlation between trait anxiety (i.e., STAI-T scores), depression scores (i.e., ADS-K scores) and conditioned responding in SCRs (see Supplementary Table 8).”
Results (page 38):
“Analyses of trait anxiety and depression symptoms
As expected, participants exposed to childhood adversity reported significantly higher trait anxiety and depression levels than unexposed participants (all p’s < 0.001; see Table 1 and Supplementary Figure 6). This pattern remained unchanged when childhood adversity was operationalized differently - following the cumulative risk approach, the specificity, and dimensional model (see methods). These additional analyses all indicated a significant positive relationship between exposure to childhood adversity and trait anxiety as well as depression scores irrespective of the specific operationalization of “exposure” (see Supplementary Figure 7).
CS discrimination during acquisition training and the generalization phase, generalization gradients, and general reactivity in SCRs were unrelated to trait anxiety and depression scores in this sample with the exception of a significant association between depression scores and CS discrimination during fear acquisition training (see Supplementary Table 8). More precisely, a very small but significant negative correlation was observed indicating that high levels of depression were associated with reduced levels of CS discrimination (r = -0.057, p =0.033). The correlation between trait anxiety levels and CS discrimination during fear acquisition training was not statistically significant but on a descriptive level, high anxiety scores were also linked to lower CS discrimination scores (r = -0.05, p = 0.06) although we highlight that this should not be overinterpreted in light of the large sample. However, both correlations (i.e., CS-discrimination during fear acquisition training and trait anxiety as well as depression, respectively) did not statistically differ from each other (z = 0.303, p = 0.762, Dunn & Clark, 1969). Interestingly, and consistent with our results showing that the relationship between childhood adversity and CS discrimination was mainly driven by significantly lower CS+ responses in exposed individuals, trait anxiety and depression scores were significantly associated with SCRs to the CS+, but not to the CS- during acquisition training (see Supplementary Table 8).”
Weakness 4: Given the paper's framing of SCR as a potential mechanistic link between adversity and mental health problems, reporting these associations would be a helpful addition. These results could also have implications for the resilience interpretation in the discussion (lines 481-485), which is a particularly important and interesting interpretation.
We have added a paragraph on this to the discussion (page 41):
“Interestingly, in our study, trait anxiety and depression scores were mostly unrelated to SCRs, defined by CS discrimination and generalization gradients based on SCRs as well as general SCR reactivity, with the exception of a significant - albeit minute - relationship between CS discrimination during acquisition training and depression scores (see above). Although reported associations in the literature are heterogeneous (Lonsdorf et al., 2017), we may speculate that they may be mediated by childhood adversity. We conducted additional mediation analyses (data not shown) which, however, did not support this hypothesis. As the potential links between reduced CS discrimination in individuals exposed to childhood adversity and the developmental trajectories of psychopathological symptoms are still not fully understood, future work should investigate these further in - ideally - prospective studies.”
Weakness 5: Given that the manuscript criticizes the different operationalizations of childhood adversity, there should be greater justification of the rationale for choosing the model for the main analyses. Why not the 'cumulative risk' or 'specificity' model? Related to this, there should also be a stronger justification for selecting the 'moderate' approach for the main analysis. Why choose to cut off at moderate? Why not severe, or low? Related to this, why did they choose to cut off at all? Surely one could address this with the continuous variable, as they criticize cut-offs in Table 2.
We thank the reviewers and editors for bringing to our attention that our reasoning for choosing the main model was not clear. As outlined in the manuscript, we chose the approach for the main analyses from the literature as a recent review on this topic (Ruge et al., 2023) has shown the moderate CTQ cut-off to be the most abundantly employed in the field of research on associations between childhood adversity and threat learning. We have made this rationale more explicit in our revised manuscript (page 15/21):
“Operationalization of "exposure"
We implemented different approaches to operationalize exposure to childhood adversity in the main analyses and exploratory analyses (see Table 2). In the main analyses, we followed the approach most commonly employed in the field of research on childhood adversity and threat learning - using the moderate exposure cut-off of the CTQ (for a recent review see Ruge et al. (2024)). In addition, the heterogeneous operationalizations of classifying individuals into exposed and unexposed to childhood adversity in the literature (Koppold, Kastrinogiannis, Kuhn, & Lonsdorf, 2023; Ruge et al., 2024) hampers comparison across studies and hence cumulative knowledge generation. Therefore, we also provide exploratory analyses (see below) in which we employ different operationalizations of childhood adversity exposure.”
“Exploratory analyses
Additionally, the different ways of classifying individuals as exposed or unexposed to childhood adversity in the literature (Koppold et al., 2023; for discussion see Ruge et al., 2024) hinder comparison across studies and hence cumulative knowledge generation. Therefore, we also conducted exploratory analyses using different approaches to operationalize exposure to childhood adversity (see Table 2 for details).”
Furthermore, as correctly noted, we fully agree that employing the moderate cut-off (or any cut-off in fact) is in principle an arbitrary decision - despite being guided by and derived from the literature in the field. However, we would like to draw the reviewers’ attention to Figure 5 in the initial submission (please see also below): Although the differences in SCR between severity groups were not significant, the overall pattern suggests at a descriptive level that the decline in CS discrimination, LDS and general reactivity in SCR occurs mainly when childhood adversity exceeds a moderate level. Thus, while we used the moderate cut-off as it was recently shown to be the most widely used approach in the literature (see Ruge et al., 2023), our exploratory analyses also seem to suggest on a descriptive level, that this cut-off may indeed “make sense”. We also refer to this in the results section (page 31-32) and discussion (page 43-44):
Results:
“However, on a descriptive level (see Figure 5), it seems that indeed exposure to at least a moderate cut-off level may induce behavioral and physiological changes (see main analysis, Bernstein & Fink, 1998). This might suggest that the cut-off for exposure commonly applied in the literature (see Ruge et al., 2024) may indeed represent a reasonable approach.”
Discussion:
“It is noteworthy, however, that this cut-off appears to map rather well onto psychophysiological response patterns observed here (see Figure 5). More precisely, our exploratory results of applying different exposure cut-offs (low, moderate, severe, no exposure) seem to indicate that indeed a moderate exposure level is “required” for the manifestation of physiological differences, suggesting that childhood adversity exposure may not have a linear or cumulative effect.”
Weakness 6: In the Introduction, the authors predict less discrimination between signals of danger (CS+) and safety (CS-) in trauma-exposed individuals driven by reduced responses to the CS+. Given the potential impact of their findings for a larger audience, it is important to give greater theoretical context as to why CS discrimination is relevant here, and especially what a reduction in response specifically to danger cues would mean (e.g. in comparison to anxiety, where safety learning is impacted).
We thank the reviewer for highlighting that this was not sufficiently clear. We revised the paragraph in the introduction as follows (page 7-8):
“Fear acquisition as well as extinction are considered as experimental models of the development and exposure-based treatment of anxiety- and stress-related disorders. Fear generalization is in principle adaptive in ensuring survival (“better safe than sorry”), but broad overgeneralization can become burdensome for patients. Accordingly, maintaining the ability to distinguish between signals of danger (i.e., CS+) and safety (i.e., CS-) under aversive circumstances is crucial, as it is assumed to be beneficial for healthy functioning (Hölzel et al., 2016) and predicts resilience to life stress (Craske et al., 2012), while reduced discrimination between the CS+ and CS- has been linked to pathological anxiety (Duits et al., 2015; Lissek et al., 2005): Meta-analyses suggest that patients suffering from anxiety- and stress-related disorders show enhanced responding to the safe CS- during fear acquisition (Duits et al., 2015). During extinction, patients exhibit stronger defensive responses to the CS+ and a trend toward increased discrimination between the CS+ and CS- compared to controls, which may indicate delayed and/or reduced extinction (Duits et al., 2015). Furthermore, meta-analytic evidence also suggests stronger generalization to cues similar to the CS+ in patients and more linear generalization gradients (Cooper, van Dis, et al., 2022; Dymond, Dunsmoor, Vervliet, Roche, & Hermans, 2015; Fraunfelter, Gerdes, & Alpers, 2022). Hence, aberrant fear acquisition, extinction, and generalization processes may provide clear and potentially modifiable targets for intervention and prevention programs for stress-related psychopathology (McLaughlin & Sheridan, 2016).”
Recommendations for the authors:
Abstract:
Comment 1:
(a) It does not succinctly describe the background rationale well (i.e. it tries to say too much). It should be streamlined. There is a lot of 'jargon', which muddies the results, and too many concepts are introduced at each part and assume knowledge from the reader.
We thank the reviewer for providing constructive guidance for revisions. We have revised our abstract according to these suggestions.
(b) Multiple terms for childhood trauma are used: ACEs, early adversity, childhood trauma, and childhood maltreatment. Choose one term and stick to it to enhance clarity. Why not just use childhood adversity, as in the title? Related to this, the use of ACEs sets up an expectation that ACE questionnaire was used, so readers are then surprised to find they used the childhood trauma questionnaire.
We thank the reviewer for bringing this to our attention. As suggested by the reviewer, we use the term “childhood adversity” in our revised manuscript.
Introduction:
Comment 2:
The phrasing seems to 'exaggerate' the trauma problem and is too broad in the first paragraph - e.g., "two-thirds of people experience one or more traumatic events..." It is important to clarify that not all of these people will go on to develop behavioral, somatic, and psychopathological conditions. Could break this down more into how many people have low, moderate, or severe for clarity, as 1 childhood adversity is different to 5+, and the type.
We thank the reviewer for bringing this to our attention and have revised the first paragraph accordingly (page 6). Please note, however, that in the literature typically a specific cut-off (e.g. moderate) is used and the number of individuals that would meet different cut-offs (e.g., low and high) are not specifically reported.
“Exposure to childhood adversity is rather common, with nearly two thirds of individuals experiencing one or more traumatic events prior to their 18th birthday (McLaughlin et al., 2013). While not all trauma-exposed individuals develop psychopathological conditions, there is some evidence of a dose-response relationship (Danese et al., 2009; Smith & Pollak, 2021; Young et al., 2019). As this potential relationship is not yet fully clear, understanding the mechanisms by which childhood adversity becomes biologically embedded and contributes to the pathogenesis of stress-related somatic and mental disorders is central to the development of targeted intervention and prevention programmes.”
Comment 3:
The published cut-offs for exposed/unexposed should be indicated here.
We have included the published cut-offs as suggested (page 10):
We operationalize childhood adversity exposure through different approaches: Our main analyses employ the approach adopted by most publications in the field (see Ruge et al., 2024 for a review) - dichotomization of the sample into exposed vs. unexposed based on published cut-offs for the Childhood Trauma Questionnaire [CTQ; Bernstein et al. (2003); Wingenfeld et al. (2010)]. Individuals were classified as exposed to childhood adversity if at least one CTQ subscale met the published cut-off (Bernstein & Fink, 1998; Häuser, Schmutzer, & Glaesmer, 2011) for at least moderate exposure (i.e., emotional abuse 13, physical abuse 10, sexual abuse 8, emotional neglect 15, physical neglect 10).
Comment 4:
Please check for overly complex sentences, and reduce the complexity. For example: "In addition, we provide exploratory analyses that attempt to translate dominant (verbal) theoretical accounts (McLaughlin et al., 2021; Pollak & Smith, 2021) on the impact of exposure to ACEs into statistical tests while acknowledging that such a translation is not unambiguous and these exploratory analyses should be considered as showcasing a set of plausible solutions."
We have revised this section and carefully proofread our manuscript by paying attention to this (page 10):
“In addition, we provide exploratory analyses that attempt to translate dominant (verbal) theoretical accounts (McLaughlin et al., 2021; Pollak & Smith, 2021) on the impact of exposure to childhood adversity into statistical tests. At the same time, we acknowledge that such a translation is not unambiguous and these exploratory analyses should be considered as showcasing a set of plausible solutions”
Here is another example of reducing the complexity of our sentences (page 6):
“Learning is a core mechanism through which environmental inputs shape emotional and cognitive processes and ultimately behavior. Thus, learning mechanisms are key candidates potentially underlying the biological embedding of exposure to childhood adversity and their impact on development and risk for psychopathology (McLaughlin & Sheridan, 2016).”
Methods:
Comment 5:
Is this study part of a larger project? These outcomes were probably not the primary outcomes of this multicenter project. The readers need to understand how this (crosssectional?) analysis was nested in this larger trial.
We thank the reviewers and editor for bringing to our attention that this was not sufficiently clear. Thus far, we included the information that we used the participants recruited for large multicentric study in the main manuscript, but point to the inclusion of more information in the supplement (page 11):
“In total, 1678 healthy participants (age_M_ = 25.26 years, age_SD_ = 5.58 years, female = 60.10%, male = 39.30%) were recruited in a multi-centric study at the Universities of Münster, Würzburg, and Hamburg, Germany (SFB TRR58). Data from parts of the Würzburg sample have been reported previously (Herzog et al., 2021; Imholze et al., 2023; Schiele, Reinhard, et al., 2016; Schiele, Ziegler, et al., 2016; Stegmann et al., 2019). These previous reports, also those focusing on experimental fear conditioning (Schiele, Reinhard, et al., 2016; Stegmann et al., 2019), addressed, however, research questions different from the ones investigated here (see also Supplementary Material for details).”
Moreover, we have included additional information on the larger trial in our revised supplement (page 2):
“Participants of this study were recruited in a multi-centric collaborative research center “Fear, anxiety, anxiety disorders” joining forces between the Universities of Hamburg,
Würzburg, and Münster, Germany (SFB TRR58). During the second funding period of (20132016), all three sites recruited a large sample (N ~500) in the context of the Z project. All participants underwent the cross-sectional experimental paradigm reported here and were additionally extensively characterized to allow specific subprojects to recruit target subpopulations serving different aims with a focus on molecular genetic, epigenetic, or other research questions (see Herzog et al. (2021); Imholze et al. (2023); Schiele, Reinhard, et al. (2016); Schiele, Ziegler, et al. (2016); Stegmann et al. (2019)). The question on the association of exposure to childhood adversity and recent adversity was part of the primary research question of one subproject led by the senior author of this work (B07, TBL) and was hence a research question of primary interest also for this multicentric project.”
Comment 6:
Table 1 does not include percentages (a reader must calculate them: for example, 15% exposed?). These numbers belong in the results (i.e., it is confusing to read about the exposed/non-exposed before we know how it has been calculated).
We have added the percentages as suggested and have included information on how exposed and unexposed was calculated as a table caption. We have considered moving the table to the results section but find it more suitable here.
Comment 7:
A procedure figure could be useful.
We thank the reviewer for this advice and have included a procedure figure in the supplementary material.
Comment 8:
Physiological data recordings and processing paragraph: The reasoning as to why the authors chose log transformation over square root transformation, or an approach that does not require transformation is not clear.
We thank the reviewer for notifying us that we did not make this point clear enough. We opted for a log-transformation and range-correction of the SCR data because we use these transformations consistently in our laboratory (e.g., Ehlers et al., 2020; Kuhn et al., 2016; Scharfenort & Lonsdorf, 2016; Sjouwerman et al., 2015; Sjouwerman et al. 2020). In addition, log-transformed and range-corrected data are assumed to be closer to a normal distribution, to have a lower error variance resulting in larger effect sizes (Lykken & Venables, 1971; Lykken, 1972; Sjouwerman et al., 2022), and appear to have - at least descriptively - higher reliability compared to raw data (Klingelhöfer-Jens et al., 2022). We added a sentence on this to the methods section (page 14):
Note that previous work using this sample (Schiele, Reinhard, et al., 2016; Stegmann et al., 2019) had used square-root transformations but we decided to employ a log-transformation and range-correction (i.e., dividing each SCR by the maximum SCR per participant). We used log-transformation and range-correction for SCR data because these transformations are standard practice in our laboratory and we strive for methodological consistency across different projects (e.g., Ehlers, Nold, Kuhn, Klingelhöfer-Jens, & Lonsdorf, 2020; Kuhn, Mertens, & Lonsdorf, 2016; Scharfenort, Menz, & Lonsdorf, 2016; Sjouwerman & Lonsdorf, 2020; Sjouwerman, Niehaus, & Lonsdorf, 2015). Additionally, log-transformed and rangecorrected data are generally assumed to approximate a normal distribution more closely and exhibit lower error variance, which leads to larger effect sizes (Lykken, 1972; Lykken & Venables, 1971; Sjouwerman, Illius, Kuhn, & Lonsdorf, 2022). Additionally, on a descriptive level, this combination of transformations appear to offer greater reliability compared to using raw data alone (Klingelhöfer-Jens, Ehlers, Kuhn, Keyaniyan, & Lonsdorf, 2022).
Ehlers, M. R., Nold, J., Kuhn, M., Klingelhöfer-Jens, M., & Lonsdorf, T. B. (2020). Revisiting potential associations between brain morphology, fear acquisition and extinction through new data and a literature review. Scientific Reports, 10(1), 19894. https://doi.org/10.1038/s41598-020-76683-1
Kuhn, M., Mertens, G., & Lonsdorf, T. B. (2016). State anxiety modulates the return of fear. International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 110, 194–199. https://doi.org/10.1016/j.ijpsycho.2016.08.001
Scharfenort, R., & Lonsdorf, T. B. (2016). Neural correlates of and processes underlying generalized and differential return of fear. Social Cognitive and Affective Neuroscience, 11(4), 612–620. https://doi.org/10.1093/scan/nsv142
Sjouwerman, R., Niehaus, J., & Lonsdorf, T. B. (2015). Contextual Change After Fear Acquisition Affects Conditioned Responding and the Time Course of Extinction Learning—Implications for Renewal Research. Frontiers in Behavioral Neuroscience, 9. https://doi.org/10.3389/fnbeh.2015.00337
Sjouwerman, R., Scharfenort, R., & Lonsdorf, T. B. (2020). Individual differences in fear acquisition: Multivariate analyses of different emotional negativity scales, physiological responding, subjective measures, and neural activation. Scientific Reports, 10(1), 15283. https://doi.org/10.1038/s41598-020-72007-5
Comment 9:
There are 24 lines of text of R packages. I do not think this is necessary for the manuscript document and could be moved to the Supplement.
We thank the reviewer for this comment and understand that it may take a considerable amount of space to list all the references of the R packages. However, we think it is important to prominently credit the respective authors of the R packages. Yet, if this is an important concern of the reviewer and editor, we will reconsider this point.
Comment 10:
It is not clear why the authors chose to analyze summary scores across trials rather than including a time factor for the acquisition phase.
We would like to thank the reviewer for highlighting that the factor time may be interesting as well. However, we think that in our case the time factor is less interesting, as the acquisition effect itself is rather strong. Nevertheless, we have included a figure in the supplement that shows the time course of the SCR by displaying trial-by-trial data across the acquisition and generalization phase for transparency. This figure (Supplementary figure 4) shows that the trajectories appear to barely differ between individuals who were unexposed vs. exposed to moderate childhood adversity. Hence, we think that the analysis approach we have chosen is unlikely to overshadow central time-depending effects. However, if the reviewer and editor has strong feelings about this point, we will consider integrating additional analyses including the time factor in the supplement.
Results:
Comment 11:
The caption of Figure 3 does not match the figure. Please check this.
We thank the reviewers and editor for attentive reading and have revised this part.
References:
Comment 12:
The Ruge et al paper that is cited many times throughout does not have a valid DOI in the References section. Additionally, the author list on the preprint server is substantially different from that listed in the manuscript. Please correct this reference.
We thank the reviewers and editor for attentive reading and have corrected this reference. The provided doi was functioning at our end and we hope that this now also applies to the reviewers.
Reviewer #2 (Public review):
Summary:
This important study uses convincing evidence to compare how different operationalizations of adverse childhood experience exposure related to patterns of skin conductance response during a fear conditioning task in a large sample of adults. Specifically, the authors compared the following operationalizations: dichotomization of the sample into "exposed" and "non-exposed" categories, cumulative adversity exposure, specificity of adversity exposure, and dimensional (threat versus deprivation) adversity exposure. The paper is thoughtfully framed and provides clear descriptions and rationale for procedures, as well as package version information and code. The authors' overall aim of translating theoretical models of adversity into statistical models, and comparing the explanatory power of each model, respectively, is an important and helpful addition to the literature.
Several outstanding strengths of this paper are the large sample size and its primary aim of statistically comparing leading theoretical models of adversity exposure in the context of skin conductance response. This paper also helpfully reports Cohen's d effect sizes, which aid in interpreting the magnitude of the findings. The methods and results are thorough and well-described.
Author Response:
Reviewer #1 (Public Review):
This work makes several contributions: (1) a method for the self-supervised segmentation of cells in 3D microscopy images, (2) an cell-segmented dataset comprising six volumes from a mesoSPIM sample of a mouse brain, and (3) a napari plugin to apply and train the proposed method.
First, thanks for acknowledging our contributions of a new tool, new dataset, and new software.
(1) Method
This work presents itself as a generalizable method contribution with a wide scope: self-supervised 3D cell segmentation in microscopy images. My main critique is that there is almost no evidence for the proposed method to have that wide of a scope. Instead, the paper is more akin to a case report that shows that a particular self-supervised method is good enough to segment cells in two datasets with specific properties.
First, thanks for acknowledging our contributions of a new tool, new dataset, and new software. We agree we focus on lightsheet microscopy data, therefore to narrow the scope we have changed the title to “CellSeg3D: self-supervised 3D cell segmentation for light-sheet microscopy”.
To support the claim that their method "address[es] the inherent complexity of quantifying cells in 3D volumes", the method should be evaluated in a comprehensive study including different kinds of light and electron microscopy images, different markers, and resolutions to cover the diversity of microscopy images that both title and abstract are alluding to. The main dataset used here (a mesoSPIM dataset of a whole mouse brain) features well-isolated cells that are easily distinguishable from the background. Otsu thresholding followed by a connected component analysis already segments most of those cells correctly.
You have selectively dropped the last part of that sentence that is key: “.... 3D volumes, often in cleared neural tissue” – which is what we tackle. The next sentence goes on to say: “We offer a new 3D mesoSPIM dataset and show that CellSeg3D can match state-of-the-art supervised methods.” Thus, we literally make it clear our claims are on MesoSPIM and cleared data.
The proposed method relies on an intensity-based segmentation method (a soft version of a normalized cut) and has at least five free parameters (radius, intensity, and spatial sigma for SoftNCut, as well as a morphological closing radius, and a merge threshold for touching cells in the post-processing). Given the benefit of tweaking parameters (like thresholds, morphological operation radii, and expected object sizes), it would be illuminating to know how other non-learning-based methods will compare on this dataset, especially if given the same treatment of segmentation post-processing that the proposed method receives. After inspecting the WNet3D predictions (using the napari plugin) on the used datasets I find them almost identical to the raw intensity values, casting doubt as to whether the high segmentation accuracy is really due to the self-supervised learning or instead a function of the post-processing pipeline after thresholding.
First, thanks for testing our tool, and glad it works for you. The deep learning methods we use cannot “solve” this dataset, and we also have a F1-Score (dice) of ~0.8 with our self-supervised method. We don’t see the value in applying non-learning methods; this is unnecessary and beyond the scope of this work.
I suggest the following baselines be included to better understand how much of the segmentation accuracy is due to parameter tweaking on the considered datasets versus a novel method contribution:<br /> * comparison to thresholding (with the same post-processing as the proposed method)<br /> * comparison to a normalized cut segmentation (with the same post-processing as the proposed method)<br /> * comparison to references 8 and 9.
Ref 8 and 9 don’t have readily usable (https://github.com/LiangHann/USAR) or even shared code (https://github.com/Kaiseem/AD-GAN), so re-implementing this work is well beyond the bounds of this paper. We benchmarked Cellpose, StartDist, SegResNets, and a transformer – SwinURNet. Moreover, models in the MONAI package can be used. Note, to our knowledge the transformer results also are a new contribution that the Reviewer does not acknowledge.
I further strongly encourage the authors to discuss the limitations of their method. From what I understand, the proposed method works only on well-separated objects (due to the semantic segmentation bottleneck), is based on contrastive FG/BG intensity values (due to the SoftNCut loss), and requires tuning of a few parameters (which might be challenging if no ground-truth is available).
We added text on limitations. Thanks for this suggestion.
(2) Dataset
I commend the authors for providing ground-truth labels for more than 2500 cells. I would appreciate it if the Methods section could mention how exactly the cells were labelled. I found a good overlap between the ground truth and Otsu thresholding of the intensity images. Was the ground truth generated by proofreading an initial automatic segmentation, or entirely done by hand? If the former, which method was used to generate the initial segmentation, and are there any concerns that the ground truth might be biased towards a given segmentation method?
In the already submitted version, we have a 5-page DataSet card that fully answers your questions. They are ALL labeled by hand, without any semi-automatic process.
In our main text we even stated “Using whole-brain data from mice we cropped small regions and human annotated in 3D 2,632 neurons that were endogenously labeled by TPH2-tdTomato” - clearly mentioning it is human-annotated.
(3) Napari plugin
The plugin is well-documented and works by following the installation instructions.
Great, thanks for the positive feedback.
However, I was not able to recreate the segmentations reported in the paper with the default settings for the pre-trained WNet3D: segments are generally too large and there are a lot of false positives. Both the prediction and the final instance segmentation also show substantial border artifacts, possibly due to a block-wise processing scheme.
Your review here does not match your comments above; above you said it was working well, such that you doubt the GT is real and the data is too easy as it was perfectly easy to threshold with non-learning methods.
You would need to share more details on what you tried. We suggest following our code; namely, we provide the full experimental code and processing for every figure, as was noted in our original submission: https://github.com/C-Achard/cellseg3d-figures.
Reviewer #2 (Public Review):
Summary:
The authors propose a new method for self-supervised learning of 3d semantic segmentation for fluorescence microscopy. It is based on a WNet architecture (Encoder / Decoder using a UNet for each of these components) that reconstructs the image data after binarization in the bottleneck with a soft n-cuts clustering. They annotate a new dataset for nucleus segmentation in mesoSPIM imaging and train their model on this dataset. They create a napari plugin that provides access to this model and provides additional functionality for training of own models (both supervised and self-supervised), data labeling, and instance segmentation via post-processing of the semantic model predictions. This plugin also provides access to models trained on the contributed dataset in a supervised fashion.
Strengths:
(1) The idea behind the self-supervised learning loss is interesting.
(2) The paper addresses an important challenge. Data annotation is very time-consuming for 3d microscopy data, so a self-supervised method that yields similar results to supervised segmentation would provide massive benefits.
Thank you for highlighting the strengths of our work and new contributions.
Weaknesses:
The experiments presented by the authors do not adequately support the claims made in the paper. There are several shortcomings in the design of the experiment and presentation of the results. Further, it is unclear if results of similar quality as reported can be achieved within the GUI by non-expert users.
Major weaknesses:
(1) The main experiments are conducted on the new mesoSPIM dataset, which contains quite small and well separated nuclei. It is unclear if the good performance of the novel self-supervised learning method compared to CellPose and StarDist would hold for dataset with other characteristics, such as larger nuclei with a more complex morphology or crowded nuclei.
StarDist is not pretrained, we trained it from scratch as we did for WNet3D. We retrained Cellpose and reported the results both with their pretrained model and our best-retrained model. This is documented in Figure 1 and Suppl. Figure 1. We also want to push back and say that they both work very well on this data. In fact, our main claim is not that we beat them, it is that we can match them with a self-supervised method.
Further, additional preprocessing of the mesoSPIM images may improve results for StarDist and CellPose (see the first point in minor weaknesses). Note: having a method that works better for small nuclei would be an important contribution. But I am uncertain the claims hold for larger and/or more crowded nuclei as the current version of the paper implies.
Figure 2 benchmarks our method on larger and denser nuclei, but we do not intend to claim this is a universal tool. It was specifically designed for light-sheet (brain) data, and we have adjusted the title to be more clear. But we also show in Figure 2 it works well on more dense and noisy samples, hinting that it could be a promising approach. But we agree, as-is, it’s unlikely to be good for extremely dense samples like in electron microscopy, which we never claim it would be.
With regards to preprocessing, we respectfully disagree. We trained StarDist (and asked the main developer of StarDist, Martin Weigert, to check our work and he is acknowledged in the paper) and it does very well. Cellpose we also retrained and optimized and we show it works as-well-as leading transformer and CNN-based approaches. Again, we only claimed we can be as good as these methods with an unsupervised approach.
The contribution of the paper would be stronger if a comparison with StarDist / CellPose was also done on the additional datasets from Figure 2.
We appreciate that more datasets would be ideal, but we always feel it’s best for the authors of tools to benchmark their own tools on data. We only compared others in Figure 1 to the new dataset we provide so people get a sense of the quality of the data too; there we did extensive searches for best parameters for those tools. So while we think it would be nice, we will leave it to those authors to be most fair. We also narrowed the scope of our claims to mesoSPIM data (added light-sheet to the title), which none of the other examples in Figure 2 are.
(2) The experimental setup for the additional datasets seems to be unrealistic. In general, the description of these experiments is quite short and so the exact strategy is unclear from the text. However, you write the following: "The channel containing the foreground was then thresholded and the Voronoi-Otsu algorithm used to generate instance labels (for Platynereis data), with hyperparameters based on the Dice metric with the ground truth." I.e., the hyperparameters for the post-processing are found based on the ground truth. From the description it is unclear whether this is done a) on the part of the data that is then also used to compute metrics or b) on a separate validation split that is not used to compute metrics. If a): this is not a valid experimental setup and amounts to training on your test set. If b): this is ok from an experimental point of view, but likely still significantly overestimates the quality of predictions that can be achieved by manual tuning of these hyperparameters by a user that is not themselves a developer of this plugin or an absolute expert in classical image analysis, see also 3. Note that the paper provides notebooks to reproduce the experimental results. This is very laudable, but I believe that a more extended description of the experiments in the text would still be very helpful to understand the set-up for the reader. Further, from inspection of these notebooks it becomes clear that hyper-parameters where indeed found on the testset (a), so the results are not valid in the current form.
We apologize for this confusion; we have now expanded the methods to clarify the setup is now b; you can see what we exactly did as well in the figure notebook: https://c-achard.github.io/cellseg3d-figures/fig2-b-c-extra-datasets/self-supervised-extra.html#threshold-predictions. For clarity, we additionally link each individual notebook now in the Methods.
(3) I cannot obtain similar results to the ones reported in the manuscript using the plugin. I tried to obtain some of the results from the paper qualitatively: First I downloaded one of the volumes from the mesoSPIM dataset (c5image) and applied the WNet3D to it. The prediction looks ok, however the value range is quite narrow (Average BG intensity ~0.4, FG intensity 0.6-0.7). I try to apply the instance segmentation using "Convert to instance labels" from "Utilities". Using "Voronoi-Otsu" does not work due to an error in pyClesperanto ("clGetPlatformIDs failed: PLATFORM_NOT_FOUND_KHR"). Segmentation via "Connected Components" and "Watershed" requires extensive manual tuning to get a somewhat decent result, which is still far from perfect.
We are sorry to hear of the installation issue; pyClesperanto is a dependency that would be required to reproduce the images (sounds like you had this issue; https://forum.image.sc/t/pyclesperanto-prototype-doesnt-work/45724 ) We added to our docs now explicitly the fix: https://github.com/AdaptiveMotorControlLab/CellSeg3D/pull/90. We recommend checking the reproduction notebooks (which were linked in initial submission): https://c-achard.github.io/cellseg3d-figures/intro.html.
Then I tried to obtain the results for the Mouse Skull Nuclei Dataset from EmbedSeg. The results look like a denoised version of the input image, not a semantic segmentation. I was skeptical from the beginning that the method would transfer without retraining, due to the very different morphology of nuclei (much larger and elongated). None of the available segmentation methods yield a good result, the best I can achieve is a strong over-segmentation with watersheds.
- We are surprised to hear this; did you follow the following notebook which directly produces the steps to create this figure? (This was linked in preprint): https://c-achard.github.io/cellseg3d-figures/fig2-c-extra-datasets/self-supervised-extra .html
- We have made a video demo for you such that any step that might be unclear is also more clear to a user: (https://youtu.be/U2a9IbiO7nE).
- We also expanded the methods to include the exact values from the notebook into the text.
Minor weaknesses:
(1) CellPose can work better if images are resized so that the median object size in new images matches the training data. For CellPose the cyto2 model should do this automatically. It would be important to report if this was done, and if not would be advisable to check if this can improve results.
We reported this value in Figure 1 and found it to work poorly, that is why we retrained Cellpose and found good performance results (also reported in Figure 1). Resizing GB to TB volumes for mesoSPIM data is otherwise not practical, so simply retraining seems the preferable option, which is what we did.
(2) It is a bit confusing that F1-Score and Dice Score are used interchangeably to evaluate results. The dice score only evaluates semantic predictions, whereas F1-Score evaluates the actual instance segmentation results. I would advise to only use F1-Score, which is the more appropriate metric. For Figure 1f either the mean F1 score over thresholds or F1 @ 0.5 could be reported. Furthermore, I would advise adopting the recommendations on metric reporting from https://www.nature.com/articles/s41592-023-01942-8.
We are using the common metrics in the field for instance and semantic segmentation, and report them in the methods. In Figure 2f we actually report the “Dice” as defined in StarDist (as we stated in the Methods). Note, their implementation is functionally equivalent to F1-Score of an IoU >= 0, so we simply changed this label in the figure now for clarity. We agree this clarifies for the expert readers what was done, and we expanded the methods to be more clear about metrics. We added a link to the paper you mention as well.
(3) A more conceptual limitation is that the (self-supervised) method is limited to intensity-based segmentation, and so will not be able to work for cases where structures cannot be distinguished based on intensity only. It is further unclear how well it can separate crowded nuclei. While some object separation can be achieved by morphological operations this is generally limited for crowded segmentation tasks and the main motivation behind the segmentation objective used in StarDist, CellPose, and other instance segmentation methods. This limitation is only superficially acknowledged in "Note that WNet3D uses brightness to detect objects [...]" but should be discussed in more depth.
Note: this limitation does not mean at all that the underlying contribution is not significant, but I think it is important to address this in more detail so that potential users know where the method is applicable and where it isn't.
We agree, and we added a new section specifically on limitations. Thanks for raising this good point. Thus, while self-supervision comes at the saving of hundreds of manual labor, it comes at the cost of more limited regimes it can work on. Hence why we don’t claim this should replace excellent methods like Cellpose or Stardist, but rather complement them and can be used on mesoSPIM samples, as we show here.
Author Response:
We thank the reviewers for their thoughtful comments on our manuscript. In this provisional response, we aim to address the major concerns raised and outline a plan for a revised version of the manuscript. A more detailed point-by-point response will follow with the revision.
The reviewers appreciated our efforts to combine computational modelling with experimental work. However, they also expressed the need for more clarity in explaining how the model was set up, what was simulated, and what the insights and limitations are. In the revision, we plan to improve the discussion section to clarify all of these points.
The reviewers also highlighted the need for more transparency regarding the code and the mathematical formulas used in this study. We agree that this is an important issue. While we have already made the software and code for our computational model, along with instructions on how to run it, available in Zenodo (see Ref. 1), and have extensively described the original computational model and formulas in a 13-page supplementary file in our previous study (see Ref. 2), we recognize from the reviewers’ comments that additional transparency is needed. To address this, we will provide an appendix in the revision that includes a full model description, covering the incorporation of cell differentiation and death, a list of parameters, and details on how parameter values were chosen.
Additionally, in the revised manuscript, we will add a paragraph to more thoroughly discuss the limitations of our approach, as well as avenues for future studies. We hope this will clarify both capabilities and limitations of our model in a way that is more accessible to readers of eLife.
References:
1. Virtual Thymus Model (version 2.0). Published: Jun 14, 2024. doi:10.5281/zenodo.11656320
2. Aghaallaei, Narges, et al. "αβ/γδ T cell lineage outcome is regulated by intrathymic cell localization and environmental signals." Science Advances 7.29 (2021): eabg3613.
Reviewer #2 (Public review):
Summary:
This manuscript investigates the role of Hox genes in the specification of forelimb position. The central conclusions are that Hox paralogy group (PG) 6/7 genes are both necessary and sufficient to induce forelimb buds. In addition, the authors argue that HoxPG4/5 genes are necessary, but, by contrast to Hox PG6/7 genes, Hox PG4/5 genes are not sufficient to induce forelimb budding. To test the roles of Hox4-7 genes in limb development, the authors use both gain-of-function (GOF) and loss-of-function (LOF) approaches in chick embryos.
In LOF experiments, they produced dominant negative forms of Hoxa4, Hoxa5, Hoxa6, and Hoxa7, which lack the DNA-binding domain, and they electroporated these constructs into the prospective wing field of the lateral plate mesoderm (LPM) in pre-limb bud stage (HH12) chick embryos. All 4 constructs resulted in down-regulation of Tbx5 (an early marker of forelimb development), and of its target gene, Fgf10, which is required for the initiation of limb budding, in the lateral plate mesoderm. The dominant negative experiments also caused down-regulation of Fgf8 in the overlying limb ectoderm and a marked reduction in the size of the early wing bud. Based on the LOF results, the authors conclude that each of the Hoxa4-7 genes is required for the specification of the forelimb field and for the establishment of the Fgf10-Fgf8 feedback loop in wing bud mesenchyme and overlying epithelium.
The authors then use a GOF strategy to investigate whether the same genes are sufficient to induce forelimb budding. They test this hypothesis using the neck, a region that is known to be incompetent to form limbs in response to Fgf signaling. Overexpression of full-length Hoxa6 and Hoxa7 in the neck region caused ectopic expression of Tbx5 in the neck region, which fits with "posteriorization" of cells at neck level, as Tbx5 typically marks the forelimb and flank (interlimb) region of the lateral plate mesoderm. Consistent with a posterior transformation of positional identity (neck to forelimb), overexpression of Hoxa6 or Hoxa7 leads to activation of Fgf10 expression and development of an ectopic forelimb bud from (or extension of the normal forelimb bud into) the neck region). By contrast, overexpression of either Hoxa4 or Hoxa5 in the neck region is not sufficient to induce ectopic forelimb budding. Curiously, the ectopic forelimb buds do not express Fgf8 in the overlying ectoderm or develop beyond the bud stage. The latter finding is consistent with previous work showing that neck ectoderm is not competent to support outgrowth of transplanted limb bud mesenchyme. The authors investigate the mechanistic basis of this early arrest of outgrowth by comparing the transcriptomes of ectopic limb buds, normal forelimb buds, and normal neck cells.
The RNA sequencing analysis shows that while some limb development genes (e.g., Lmx1b, Hoxa9, Hoxd9, Hoxa10, Hoxd10) are activated in the ectopic limb bud, other key components of the circuit (e.g., Shh, Fgf8, Hox12/13 paralogs) are not established, leading them to conclude that failure of neck ectoderm to form an AER underlies the arrested outgrowth of ectopic limb buds.
Strengths:
This study provides the first evidence that altering the Hox code in neck lateral plate mesoderm (LPM) is sufficient to induce ectopic development of forelimb buds at the neck level. For more than 30 years, developmental biologists have speculated and provided indirect evidence that Hox genes are involved in the specification of forelimb position, but to my knowledge, no study has shown that altering Hox gene expression alone can induce limb development outside of the normal limb field. The finding that Hox6/7 paralogs are sufficient for forelimb bud development, whereas Hox4/5 paralogs are not, suggests that specification of forelimb identity requires instructive signaling that is a specific property of Hox6/7 paralogs. The GOF experiments significantly extend the knowledge of limb specification beyond that which has come from Hox gene manipulations in mice.
Weaknesses:
(1) By contrast to the GOF experiments that induce ectopic limb budding, the LOF experiments, which use dominant negative forms of Hoxa4, Hoxa5, Hoxa6, and Hoxa7, are more challenging to interpret due to the absence of data on the specificity of the dominant negative constructs. Absent such controls, one cannot be certain that effects on limb development are due to disruption of the specific Hox proteins that are being targeted.
(2) A test of their central hypothesis regarding the necessity and sufficiency of the Hox genes under investigation would be to co-transfect the neck with full-length Hoxa6/a7 AND the dnHoxA4/a5. If their hypothesis is correct, then the dn constructs should block the limb-inducing ability of Hoxa6/a7 overexpression (again, validation of specificity of the DN constructs is important here).
(3) The paper could be strengthened by providing some additional data, which should already exist in their RNA-Seq dataset, such as supplementary material that shows the actual gene expression data that are represented in the Venn diagram, heatmap, and GO analysis in Figure 3.
(4) The results of these experiments in chick embryos are rather unexpected based on previous knockout experiments in mice, and this needs to be discussed.
Generative AI (gen AI) is revolutionizing the banking industry as financial institutions use the technology to supercharge customer-facing chatbots, prevent fraud, and speed up time-consuming tasks such as developing code, preparing drafts of pitch books, and summarizing regulatory reports.
It seems to already having a positive affect on the banking community
2024913_PHYS545_JCCBAB_AFM_T020200122Si16
not needed in the report; again in the notebook, but in the report those details are "hidden" in the code portion.
GPT-4 can be trained on a dataset of known malware signatures, malicious and benign code snippets, and their behavior patterns.
As technology evolves, ChatGPT can recognize and understand behavior patterns of malware
Attackers use the generative power of GenAI tools to create a convincing social engineering attack, phishing attack, attack payload, and different kinds of malicious code snippets that can be compiled into an executable malware file [19], [20].
Ways GenAI could use to incite a cyberattack
defense techniques and uses GenAI tools to improve security measures, including cyber defense automation, reporting, threat intelligence, secure code generation and detection, attack identification, developing ethical guidelines, incidence response plans, and malware detection.
Perspective of the defense side of GenAI
es of data on social media platforms are organized as lists, such as lists of friends or followers lists of posts lists of photos in a post lists of people who liked a post etc.
This made m think about how a person would like to get there followers up on instagram and how easy it is to just follow a bunch of people, but not think about how much coding/programming there is to follow a single person. It really makes me think how complicated programming is because one single follow equals to be one line of code and imagine that for 10s of thousands of follows.
Now, let’s say we have a list of users who liked our latest social media post: users_who_liked_our_post = ["@pretend_user_1", "@pretend_user_2", "@pretend_user_3"] Copy to clipboard What if we wanted to follow all of them? If our list was long, it would take a lot of code to pull out each one and try to follow them. But Python gives us an easy way to perform actions on all the items in a list, by using for loops.
This passage really resonates with me because it highlights the fun and flexibility of programming. Seeing how a simple for loop can help follow a bunch of users makes everything feel so much more manageable.
The comedy website Something Awful was created in 1999, and it included web forums where many popular memes of the day originated. While the Something Awful forums had edgy content, one 15-year-old member of the Something Awful forum called “Anime Death Tentacle Rape Whorehouse” was frustrated by content restrictions on Something Awful, and created his own new site with less restrictions: 4Chan. 5.5.2. 4Chan# 4Chan was created in 2003 by copying the code from a Japanese image-sharing bulletin board called Futaba or 2chan.
Its funny how even on a site named "Something awful" a person still felt restricted. But I cant say im mad about it because i feel like i heard a couple useful stories from 4chan due to the lack of restrictions.
Author response:
The following is the authors’ response to the original reviews.
Reviewer #1 (Public Review):
Weaknesses:
There are some minor weaknesses.
Comment 1:Notably, there are not a lot of new insights coming from this paper. The structural comparisons between MCC and PCC have already been described in the literature and there were not a lot of significant changes (outside of the exo- to endo- transition) in the presence vs. absence of substrate analogues.
We agree that the structures of the human MCC and PCC holoenzymes are similar to their bacterial homologs. That is due to the conserved sequences and functions of MCC and PCC across different species.
Comment 2: There is not a great deal of depth of analysis in the discussion. For example, no new insights were gained with respect to the factors contributing to substrate selectivity (the factors contributing to selectivity for propionyl-CoA vs. acetyl-CoA in PCC). The authors state that the longer acyl group in propionyl-CoA may mediate stronger hydrophobic interactions that stabilize the alpha carbon of the acyl group at the proper position. This is not a particularly deep analysis and doesn't really require a cryo-EM structure to invoke. The authors did not take the opportunity to describe the specific interactions that may be responsible for the stronger hydrophobic interaction nor do they offer any plausible explanation for how these might account for an astounding difference in the selectivity for propionyl-CoA vs. acetyl-CoA. This suggests, perhaps, that these structures do not yet fully capture the proper conformational states.
We appreciate this comment. Unfortunately, in the cryo-EM maps of the PCC holoenzymes, the acyl groups were not resolved (fig. S6), so we were unable to analyze the specific interactions between the acyl-CoAs and PCC. We have revised the manuscript and acknowledged this limitation in the second paragraph of the discussion section:
“In the cryo-EM maps of the PCC holoenzymes, the acyl groups of acetyl-CoA and propionylCoA were not resolved (fig. S6), limiting the analysis of the interactions between the acyl groups and PCC. Nevertheless, the PCC-PCO and PCC-ACO structures determined in our study demonstrate that the conformations of the acyl-CoA binding pockets in the two structures are almost identical (Fig. 3F, fig. S7, B and C). In addition, the well resolved CoA groups of propionyl-CoA and acetyl-CoA bind at the same position in human PCC holoenzyme (Fig. 3F). These findings indicate that propionyl-CoA and acetyl-CoA bind to PCC with a similar binding mode.”
Comment 3: The authors also need to be careful with their over-interpretation of structure to invoke mechanisms of conformational change. A snapshot of the starting state (apo) and final state (ligand-bound) is insufficient to conclude *how* the enzyme transitioned between conformational states. I am constantly frustrated by structural reports in the biotin-dependent enzymes that invoke "induced conformational changes" with absolutely no experimental evidence to support such statements. Conformational changes that accompany ligand binding may occur through an induced conformational change or through conformational selection and structural snapshots of the starting point and the end point cannot offer any valid insight into which of these mechanisms is at play.
Point accepted. We have revised our manuscript to use conformational differences instead of conformational changes to describe the differences between the apo and ligand-bound states (see the last paragraph of the introduction section and the third paragraph of the discussion section).
Reviewer #2 (Public Review):
Comments and questions to the manuscripts:
Comment 1: I'm quite impressed with the protein purification and structure determination, but I think some functional characterization of the purified proteins should be included in the manuscript. The activity of enzymes should be the foundation of all structures and other speculations based on structures.
We appreciate this comment. However, since we purified the endogenous BDCs and the sample we obtained was a mixture of four BDCs, the enzymatic activity of this mixture cannot accurately reflect the catalytic activity of PCC or MCC holoenzyme. We have revised the manuscript and acknowledged this limitation in the first paragraph of the results section:
“We did not characterize the enzyme activities of the mixed BDCs because the current methods used to evaluate the carboxylase activities of BDCs, such as measuring the ATP hydrolysis or incorporation of radio-labeled CO2, are unable to differentiate the specific carboxylase activity of each BDC.”
Comment 2: In Figure 1B, the structure of MCC is shown as two layers of beta units and two layers of alpha units, while there is only one layer of alpha units resolved in the density maps. I suggest the authors show the structures resolved based on the density maps and show the complete structure with the docked layer in the supplementary figure.
We appreciate this comment. We have shown the cryo-EM maps of the PCC and MCC holoenzymes in fig. S8 to indicate the unresolved regions in these structures. The BC domains in one layer of MCCα in the MCC-apo structure were not resolved. However, we think it would be better to show a complete structure in Fig. 1 to provide an overall view of the MCC holoenzyme. We have revised Fig. 1B and the figure legend to clearly point out which domains were not resolved in the cryo-EM map and were built in the structure through docking. We have also revised the main text to clearly describe which parts of the holoenzymes were not resolved in the cryo-EM maps and how the complete structures were built.
Comment 3: In the introduction, I suggest the author provide more information about the previous studies about the structure and reaction mechanisms of BDCs, what is the knowledge gap, and what problem you will resolve with a higher resolution structure. For example, you mentioned in line 52 that G437 and A438 are catalytic residues, are these residues reported as catalytic residues or this is based on your structures? Has the catalytic mechanism been reported before? Has the role of biotin in catalytic reactions revealed in previous studies?
Point accepted. It was reported that G419 and A420 in Streptomyces coelicolor PCC, corresponding to G437 and A438 in human PCCβ, were the catalytic residues for the secondstep carboxylation reaction (PMID: 15518551). The same study also reported the catalytic mechanism of the carboxyl transfer reaction. The role of biotin in the BDC-catalyzed carboxylation reactions has been extensively studied (PMIDs: 22869039, 28683917). We have revised the manuscript to introduce the catalytic mechanisms of BDCs elucidated through the investigation of prokaryotic BDCs in the fourth paragraph of the introduction section.
Comment 4: In the discussion, the authors indicate that the movement of biotin could be related to the recognition of acyl-CoA in BDCs, however, they didn't observe a change in the propionyl-CoA bound MCC structure, which is contradictory to their speculation. What could be the explanation for the exception in the MCC structure?
We appreciate this comment. We do not have a good explanation for why we did not observe a change in the propionyl-CoA bound MCC structure. It is noteworthy that neither acetyl-CoA nor propionyl-CoA is the natural substrate of MCC. Recently, a cryo-EM structure of the human MCC holoenzyme in complex with its natural substrate, 3-methylcrotonyl-CoA, has been resolved (PDB code: 8J4Z). In this structure, the binding site of biotin and the conformation of the CT domain closely resemble that in our acetyl-CoA-bound MCC structure. Therefore, the movement of biotin induced by acetyl-CoA binding mimics that induced by the binding of MCC's natural substrate, 3-methylcrotonyl-CoA, indicating that in comparison with propionylCoA, acetyl-CoA is closer to 3-methylcrotonyl-CoA regarding its ability to bind to MCC. We have discussed this possibility in the last paragraph of the discussion section. We have also added a supplementary figure (fig. S11) to compare the structures of human MCC holoenzyme in complex with acetyl-CoA and 3-methylcrotonyl-CoA.
Comment 5: In the discussion, the authors indicate that the selectivity of PCC to different acyl-CoA is determined by the recognition of the acyl chain. However, there are no figures or descriptions about the recognition of the acyl chain by PCC and MCC. It will be more informative if they can show more details about substrate recognition in Figures 3 and 4.
We appreciate this comment. Unfortunately, in the cryo-EM maps of the PCC holoenzymes, the acyl groups were not resolved (fig. S6), so we were unable to analyze the specific interactions between the acyl-CoAs and PCC. We have revised the manuscript and acknowledged this limitation in the second paragraph of the discussion section:
“In the cryo-EM maps of the PCC holoenzymes, the acyl groups of acetyl-CoA and propionylCoA were not resolved (fig. S6), limiting the analysis of the interactions between the acyl groups and PCC. Nevertheless, the PCC-PCO and PCC-ACO structures determined in our study demonstrate that the conformations of the acyl-CoA binding pockets in the two structures are almost identical (Fig. 3F, fig. S7, B and C). In addition, the well resolved CoA groups of propionyl-CoA and acetyl-CoA bind at the same position in human PCC holoenzyme (Fig. 3F). These findings indicate that propionyl-CoA and acetyl-CoA bind to PCC with a similar binding mode.”
Comment 6: How are the solved structures compared with the latest Alphafold3 prediction?
Since AlphaFold3 was not released when our manuscript was submitted, we did not compare the solved structures with the AlphaFold3 predictions. We have now carried out the predictions using Alphafold3. Due to the token limitation of the AlphaFold3 server, we can only include two α and six β subunits of human PCC or MCC in the prediction. The overall assembly patterns of the Alphafold3-predicted structures are similar to that of the cryo-EM structures. The RMSDs between PCCα, PCCβ, MCCα, and MCCβ in the apo cryo-EM structures and those in the AlphaFold3-predicted structures are 7.490 Å, 0.857 Å, 7.869 Å, and 1.845 Å, respectively. The PCCα and MCCα subunits adopt an open conformation in the cryo-EM structures but adopt a closed conformation in the AlphaFold-3 predicted structures, resulting in large RMSDs.
Reviewer #1 (Public review):
Summary:
DMS-MaP is a sequencing-based method for assessing RNA folding by detecting methyl adducts on unpaired A and C residues created by treatment with dimethylsulfate (DMS). DMS also creates methyl adducts on the N7 position of G, which could be sensitive to tertiary interactions with that atom, but N7-methyl adducts cannot be detected directly by sequencing. In this work, the authors adopt a previously developed method for converting N7-methyl-G to an abasic site to make it detectable by sequencing and then show that the ability of DMS to form an N7-methyl-G adduct is sensitive to RNA structural context. In particular, they look at the G-quadruplex structure motif, which is dense with N7-G interactions, is biologically important, and lacks conclusive methods for in-cell structural analysis.
Strengths:
- The authors clearly show that established methods for detecting N7-methyl-G adducts can be used to detect those adducts from DMS and that the formation of those adducts is sensitive to structural context, particularly G-quadruplexes.
- The authors assess the N7-methyl-G signal through a wide range of useful probing analyses, including standard folding, adduct correlations, mutate-and-map, and single-read clustering.
- The authors show encouraging preliminary results toward the detection of G-quadruplexes in cells using their method. Reliable detection of RNA G-quadruplexes in cells is a major limitation for the field and this result could lead to a significant advance.
- Overall, the work shows convincingly that N7-methyl-G adducts from DMS provide valuable structural information and that established data analyses can be adapted to incorporate the information.
Weaknesses:
- Most of the validation work is done on the spinach aptamer and it and polyUG RNA are the only RNAs tested that have a known 3D structure. Although it is a useful model for validating this method, it does not provide a comprehensive view of what results to expect across varied RNA structures.
- It's not clear from this work what the predictive power of BASH-MaP would be when trying to identify G-quadruplexes in RNA sequences of unknown structure. Although clusters of G's with low reactivity and correlated mutations seem to be a strong signal for G-quadruplexes, no effort was made to test a range of G-rich sequences that are known to form G-quadruplexes or not. Having this information would be critical for assessing the ability of BASH-MaP to identify G-quadruplexes in cells.
- Although the authors present interesting results from various types of analysis, the code currently available on Github lacks the documentation and examples necessary to be useful to the broader community.
- There are aspects of the DAGGER analysis that could limit its robustness or utility for different RNAs:
(1) Folding of the RNA based on individual reads does not represent single-molecule folding since each read contains only a small fraction of the possible adducts that could have formed on that molecule. As a result, each fold will largely be driven by the naive folding algorithm. The DANCE-MaP algorithm that was also used by the authors addresses this concern.<br /> (2) G residues in a loop will have a different impact on RNA folding than those in a G-quadruplex. This difference could reduce the accuracy of CONTRAfold predictions when forcing G-quadruplex residues to be unpaired. That said, predicting secondary structure around G-quadruplexes is a challenge for folding algorithms.<br /> (3) Incorporation of the G mutations requires prior knowledge of the RNA 3D structure, limiting the utility of the method to predicting alternative conformations in structures that are already well characterized.
We can use a similar approach to look at the nationalities of authors whose works are represented on the list. Focusing on the AUTHOR_NATIONALITY column, we can count how many times each country code appears, and see that over 80% of the novels were written by authors from the U.S. or the U.K.
The researchers primarily speak and read english which will greatly influence what are considered "classic" books. The data is influenced by the creator's language as that is what they have known the whole time. They wouldnt know about classics from Spanish speaking contries or French speaking countries unless they have actively been pushed in english translated versions.
STAT3-mediated allelic imbalance of novel genetic variant rs1047643 and B cell specific super-enhancer in association with systemic lupus erythematosus
Click Here for full report
Summary of datasets and Open Science materials associated with article: - 17 Dataset(s) - 1 Code
14 Genetic Data Dataset(s) - 9 "High-Throughput Nucleotide Sequencing" - 2 "Sequence Alignment" - 2 "Single Nucleotide Polymorphism" - 1 "Real-Time Polymerase Chain Reaction"
3 Tabular Data Dataset(s) - 1 "Subject Data Table" - 1 "Assay" - 1 "Immunoassay"
stargazer(fat_mod1, fat_mod2, fat_mod3, fat_mod4, fat_mod5, fat_mod6, fat_mod7, digits = 3, header = FALSE, type = "latex", se = rob_se, title = "Linear Panel Regression Models of Traffic Fatalities due to Drunk Driving", model.numbers = FALSE, column.labels = c("(1)", "(2)", "(3)", "(4)", "(5)", "(6)", "(7)"))
With R version 4.2.2 or greater and Stargazer version 5.2.3, this code doesn't work. You have to put all the models in a list first and use the list as the first argument of the stargazer command. all_models <- list(fat_mod1,fat_mod2,fat_mod3,fat_mod4,fat_mod5,fat_mod6,fat_mod7)
stargazer(all_models, digits = 3, header = FALSE, type = "text", se = rob_se, title = "Linear Panel Regression Models of Traffic Fatalities due to Drunk Driving", model.numbers = FALSE, column.labels = c("(1)", "(2)", "(3)", "(4)", "(5)", "(6)", "(7)"))
ll Iwant is a case just like mine fromGeorgia!” She left in a huff, thor-oughly convinced that I did not wantto help her and half-believing that Iwas secretly in league with the insur-ance company against her,
Here, we see some of the frustration that the public has with our legal system. People who aren't trained attorneys often don't understand the "whys" of the law: Why is it so hard to find a similar case? Why did a judge rule in a way that seems to contradict common sense? Why is this city code so hard to read? I think a lawyer who works with everyday people (i.e. a local defense attorney or a lawyer who writes wills for your average Joe) must empathize with these frustrations and be patient if they want to be effective.
Loop through the list of submissions# The variable submissions_list now has a list of Reddit submissions. So we can use a for loop to go through each submission, and then use . to access info from each tweet (other pieces of information would need [" "] to access). For each of the tweets, we will use print to display information about the tweet
This reminds me of Lab 1, where I was so excited after successfully using code to post an article on Reddit. However, it also left me feeling a bit anxious when I considered the broader implications. It made me realize that so much content on the internet can be generated through code, and a single individual has the power to shape public opinion or even spark controversies with just a few lines of code. It's both empowering and a little daunting to think about how easily information can spread and influence people.
dictionaries
Dictionaries are very useful when working with social media data. Especially when we need to organize multiple pieces of user information (such as username, avatar, watch list, etc.) to edit code, it provides a flexible way to quickly access and manage this data.
opensource science
"Open-source" science is code language for conservative efforts to undermine the work of scientists and the role of science in the regulatory process. It is the most recent variation on calls for "sound science," which was a talking point for EPA Administrator Scott Pruitt at the start of the Trump administration. Calls for "open source" or "sound science" seek to limit the kinds of scientific research that can be used in regulatory decisionmaking. In particular, they seek to eliminate any studies that draw upon sensitive healthcare records. https://fivethirtyeight.com/features/the-easiest-way-to-dismiss-good-science-demand-sound-science/
This "open-source science" agenda would exclude from regulatory considerations practically all the burgeoning science done over the past two decades centering on actual people who are exposed to toxic pollutants, including what are considered by scientists to be the best and most conclusive studies in epidemiology. That's because all these studies involve confidential medical records the laws like HIPA make impossible to fully release to the public without violating patients' privacy. https://nyuelj.org/2021/06/transparency-in-regulatory-science-for-whom/
eLife Assessment
The authors describe a model for tracking time-varying functional connectivity between neurons from multi-electrode spike recordings. This is an interesting and potentially useful approach to an open problem in neural data analysis, and could be an essential tool for investigating the neural code from large-scale in-vivo recordings of spiking activity. However, the evidence is incomplete: systematic comparisons with existing methods and/or demonstration of its utility relative to conventional methods are essential to demonstrate the usefulness of the method.
Author response:
The following is the authors’ response to the original reviews.
We thank the reviewers for the constructive criticism and detailed assessment of our work which helped us to significantly improve our manuscript. We made significant changes to the text to better clarify our goals and approaches. To make our main goal of extracting the network dynamics clearer and to highlight the main advantage of our method in comparison with prior work we incorporated Videos 1-4 into the main text. We hope that these changes, together with the rest of our responses, convincingly demonstrate the utility of our method in producing results that are typically omitted from analysis by other methods and can provide important novel insights on the dynamics of the brain circuits.
Reviewer #1 (Public Review):
(1) “First, this paper attempts to show the superiority of DyNetCP by comparing the performance of synaptic connectivity inference with GLMCC (Figure 2).”
We believe that the goals of our work were not adequately formulated in the original manuscript that generated this apparent misunderstanding. As opposed to most of the prior work focused on reconstruction of static connectivity from spiking data (including GLMCC), our ultimate goal is to learn the dynamic connectivity structure, i.e. to extract time-dependent strength of the directed connectivity in the network. Since this formulation is fundamentally different from most of the prior work, therefore the goal here is not to show the “improvement” or “superiority” over prior methods that mostly focused on inference of static connectivity, but rather to thoroughly validate our approach and to show its usefulness for the dynamic analysis of experimental data.
(2) “This paper also compares the proposed method with standard statistical methods, such as jitter-corrected CCG (Figure 3) and JPSTH (Figure 4). It only shows that the results obtained by the proposed method are consistent with those obtained by the existing methods (CCG or JPSTH), which does not show the superiority of the proposed method.”
The major problem for designing such a dynamic model is the virtual absence of ground-truth data either as verified experimental datasets or synthetic data with known time-varying connectivity. In this situation optimization of the model hyper-parameters and model verification is largely becoming a “shot in the dark”. Therefore, to resolve this problem and make the model generalizable, here we adopted a two-stage approach, where in the first step we learn static connections followed in the next step by inference of temporally varying dynamic connectivity. Dividing the problem into two stages enables us to separately compare the results of both stages to traditional descriptive statistical approaches. Static connectivity results of the model obtained in stage 1 are compared to classical pairwise CCG (Fig.2A,B) and GLMCC (Fig.2 C,D,E), while dynamic connectivity obtained in step 2 are compared to pairwise JPSTH (Fig.4D,E).
Importantly, the goal here therefore is not to “outperform” the classical descriptive statistical or any other approaches, but rather to have a solid guidance for designing the model architecture and optimization of hyper-parameters. For example, to produce static weight results in Fig.2A,B that are statistically indistinguishable from the results of classical CCG, the procedure for the selection of weights which contribute to averaging is designed as shown in Fig.9 and discussed in details in the Methods. Optimization of the L2 regularization parameter is illustrated in Fig.4 – figure supplement 1 that enables to produce dynamic weights very close to cJPSTH as evidenced by Pearson coefficient and TOST statistical tests. These comparisons demonstrate that indeed the results of CCG and JPSTH are faithfully reproduced by our model that, we conclude, is sufficient justification to apply the model to analyze experimental results.
(3) “However, the improvement in the synaptic connectivity inference does not seem to be convincing.”
We are grateful for the reviewer to point out to this issue that we believe, as mentioned above, results from the deficiency of the original manuscript to clarify the major motivation for this comparison. Comparison of static connectivity inferred by stage 1 of our model to the results of GLMCC in Fig.2C,D,E is aimed at optimization of yet another two important parameters - the pair spike threshold and the peak height threshold. Here, in Fig. 2D we show that when the peak height threshold is reduced from rigorous 7 standard deviations (SD) to just 5 SD, our model recovers 74% of the ground truth connections that in fact is better than 69% produced by GLMCC for a comparable pair spike threshold of 80. As explained above, we do not intend to emphasize here that our model is “superior” since it was not our goal, but rather use this comparison to illustrate the approach for optimization of thresholds for units and pairs filtering as described in detail in Fig. 11 and corresponding section in Methods.
To address these misunderstandings and better clarify the goal of our work we changed the text in the Introductory section accordingly. We also incorporated Videos 1-4 from the Supplementary Materials into the main text as Video 1, Video 2, Video 3, and Video 4. In fact, these videos represent the main advantage (or “superiority”) of our model with respect to prior art that enables to infer the time-dependent dynamics of network connectivity as opposed to static connections.
(4) “While this paper compares the performance of DyNetCP with a state-of-the-art method (GLMCC), there are several problems with the comparison. For example:
(a) This paper focused only on excitatory connections (i.e., ignoring inhibitory neurons).
(b) This paper does not compare with existing neural network-based methods (e.g., CoNNECT: Endo et al. Sci. Rep. 2021; Deep learning: Donner et al. bioRxiv, 2024).
(c) Only a population of neurons generated from the Hodgkin-Huxley model was evaluated.”
(a) In general, the model of Eq.1 is agnostic to excitatory or inhibitory connections it can recover. In fact, Fig. 5 and Fig.6 illustrate inferred dynamic weights for both excitatory (red arrows) and inhibitory (blue arrows) connections between excitatory (red triangles) and inhibitory (blue circles) neurons. Similarly, inhibitory and excitatory dynamic interactions between connections are represented in Fig. 7 for the larger network across all visual cortices.
(b) As stated above, the goal for the comparison of the static connectivity results of stage 1 of our model to other approaches is to guide the choice of thresholds and optimization of hyperparameters rather than claiming “superiority” of our model. Therefore, comparison with “static” CNN-based model of Endo et al. or ANN-based static model of Donner et al. (submitted to bioRxiv several months after our submission to eLife) is beyond the scope of this work.
(c) We have chosen exactly the same sub-population of neurons from the synthetic HH dataset of Ref. 26 that is used in Fig.6 of Ref. 26 that provides direct comparison of connections reconstructed by GLMCC in the original Ref.26 and the results of our model.
(5) “In summary, although DyNetCP has the potential to infer synaptic connections more accurately than existing methods, the paper does not provide sufficient analysis to make this claim. It is also unclear whether the proposed method is superior to the existing methods for estimating functional connectivity, such as jitter-corrected CCG and JPSTH. Thus, the strength of DyNetCP is unclear.”
As we explained above, we have no intention to claim that our model is more accurate than existing static approaches. In fact, it is not feasible to have better estimation of connectivity than direct descriptive statistical methods as CCG or JPSTH. Instead, comparison with static (CCG and GLMCC) and temporal (JPSTH) approaches are used here to guide the choice of the model thresholds and to inform the optimization of hyper-parameters to make the prediction of the dynamic network connectivity reliable. The main strength of DyNetCP is inference of dynamic connectivity as illustrated in Videos 1-4. We demonstrated the utility of the method on the largest in-vivo experimental dataset available today and extracted the dynamics of cortical connectivity in local and global visual networks. This information is unattainable with any other contemporary methods we are aware of.
Reviewer #1 (Recommendations for the Authors):
(6) “First, the authors should clarify the goal of the analysis, i.e., to extract either the functional connectivity or the synaptic connectivity. While this paper assumes that they are the same, it should be noted that functional connectivity can be different from synaptic connectivity (see Steavenson IH, Neurons Behav. Data Anal. Theory 2023).”
The goal of our analysis is to extract dynamics of the spiking correlations. In this paper we intentionally avoided assigning a biological interpretation to the inferred dynamic weights. Our goal was to demonstrate that a trough of additional information on neural coding is hidden in the dynamics of neural correlations. The information that is typically omitted from the analysis of neuroscience data.
Biological interpretation of the extracted dynamic weights can follow the terminology of the shortterm plasticity between synaptically connected neurons (Refs 25, 33-37) or spike transmission strength (Refs 30-32,46). Alternatively, temporal changes in connection weights can be interpreted in terms of dynamically reconfigurable functional interactions of cortical networks (Refs 8-11,13,47) through which the information is flowing. We could not also exclude interpretation that combines both ideas. In any event our goal here is to extract these signals for a pair (video1, Fig.4), a cortical local circuit (Video 2, Fig.5), and for the whole visual cortical network (Videos 3, 4 and Fig.7).
To clarify this statement, we included a paragraph in the discussion section of the revised paper.
(7) “Finally, it would be valuable if the authors could also demonstrate the superiority of DyNetCP qualitatively. Can DyNetCP discover something interesting for neuroscientists from the large-scale in vivo dataset that the existing method cannot?”
The model discovers dynamic time-varying changes in neuron synchronous spiking (Videos 1-4) that more traditional methods like CCG or GLMCC are not able to detect. The revealed dynamics is happening at the very short time scales of the order of just a few ms during the stimulus presentation. Calculations of the intrinsic dimensionality of the spiking manifold (Fig. 8) reveal that up to 25 additional dimensions of the neural code can be recovered using our approach. These dimensions are typically omitted from the analysis of the neural circuits using traditional methods.
Reviewer #2 (Public Review):
(1) “Simulation for dynamic connectivity. It certainly seems doable to simulate a recurrent spiking network whose weights change over time, and I think this would be a worthwhile validation for this DyNetCP model. In particular, I think it would be valuable to understand how much the model overfits, and how accurately it can track known changes in coupling strength.”
We are very grateful to the reviewer for this insight. Verification of the model on synthetic data with known time-varying connectivity would indeed be very useful. We did generate a synthetic dataset to test some of the model performance metrics - i.e. testing its ability to distinguish True Positive (TP) from False Positive (FP) “serial” or “common input” connections (Fig.10A,B). Comparison of dynamic and static weights might indeed help to distinguish TP connections from an artifactual FP connections.
Generating a large synthetic dataset with known dynamic connections that mimics interactions in cortical networks is, however, a separate and not very trivial task that is beyond the scope of this work. Instead, we designed a model with an architecture where overfitting can be tested in two consecutive stages by comparison with descriptive statistical approaches – CCG and JPSTH. Static stage 1 of the model predicts correlations that are statistically indistinguishable from the CCG results (Fig.2A,B). The dynamic stage 2 of the model produce dynamic weight matrices that faithfully reproduce the cJPSTH (Fig.4D,E). Calculated Pearson correlation coefficients and TOST testing enable optimizing the L2 regularization parameter as shown in Fig.4 – supplement 1 and described in detail in the Methods section. The ability to test results of both stages separately to descriptive statistical results is the main advantage of the chosen model architecture that allow to verify that the model does not overfit and can predict changes in coupling strength at least as good as descriptive statistical approaches (see also our answer above to the Reviewer #1 questions).
(2) “If the only goal is "smoothing" time-varying CCGs, there are much easier statistical methods to do this (c.f. McKenzie et al. Neuron, 2021. Ren, Wei, Ghanbari, Stevenson. J Neurosci, 2022), and simulations could be useful to illustrate what the model adds beyond smoothing.”
We are grateful to the reviewer for bringing up these very interesting and relevant references that we added to the discussion section in the paper. Especially of interest is the second one, that is calculating the time-varying CCG weight (“efficacy” in the paper terms) on the same Allen Institute Visual dataset as our work is using. It is indeed an elegant way to extract time-variable coupling strength that is similar to what our model is generating. The major difference of our model from that of Ren et al., as well as from GLMCC and any statistical approaches is that the DyNetCP learns connections of an entire network jointly in one pass, rather than calculating coupling separately for each pair in the dataset without considering the relative influence of other pairs in the network. Hence, our model can infer connections beyond pairwise (see Fig. 11 and corresponding discussion in Methods) while performing the inferences with computational efficiency.
(3) “Stimulus vs noise correlations. For studying correlations between neurons in sensory systems that are strongly driven by stimuli, it's common to use shuffling over trials to distinguish between stimulus correlations and "noise" correlations or putative synaptic connections. This would be a valuable comparison for Figure 5 to show if these are dynamic stimulus correlations or noise correlations. I would also suggest just plotting the CCGs calculated with a moving window to better illustrate how (and if) the dynamic weights differ from the data.”
Thank you for this suggestion. Note that for all weight calculations in our model a standard jitter correction procedure of Ref. 33 Harrison et al., Neural Com 2009 is first implemented to mitigate the influences of correlated slow fluctuations (slow “noise”). Please also note that to obtain the results in Fig. 5 we split the 440 total experimental trials for this session (when animal is running, see Table 1) randomly into 352 training and 88 validation trials by selecting 44 training trials from each configuration of contrast or grating angle and 11 for validation. We checked that this random selection, if changed, produced the very same results as shown in Fig.5.
Comparison of descriptive statistical results of pairwise cJPSTH and the model are shown in Fig. 4D,E. The difference between the two is characterized in Fig.4 – supplement 1 in detail as evidenced by Pearson coefficient and TOST statistical tests.
Reviewer #2 (Recommendations for the Authors):
(4) “The method is described as "unsupervised" in the abstract, but most researchers would probably call this "supervised" (the static model, for instance, is logistic regression).”
The model architecture is composed of two stages to make parameter optimization grounded. While the first stage is regression, the second and the most important stage is not. Therefore, we believe the term “unsupervised” is justified.
(5) “Introduction - it may be useful to mention that there have been some previous attempts to describe time-varying connectivity from spikes both with probabilistic models: Stevenson and Kording, Neurips (2011), Linderman, Stock, and Adams, Neurips (2014), Robinson, Berger, and Song, Neural Computation (2016), Wei and Stevenson, Neural Comp (2021) ... and with descriptive statistics: Fujisawa et al. Nat Neuroscience (2008), English et al. Neuron (2017), McKenzie et al. Neuron (2021).”
We are very grateful to both reviewers for bringing up these very interesting and relevant references that we gladly included in the discussions within the Introduction and Discussion sections.
(6) “In the section "Static connectivity inferred by the DyNetCP from in-vivo recordings is biologically interpretable"... I may have missed it, but how is the "functional delay" calculated? And am I understanding right that for the DyNetCP you are just using [w_i\toj, w_j\toi] in place of the CCG?”
The functional delay is calculated as a time lag of the maximum (or minimum) in the CCG (or static weight matrix). The static weight that the model is extracting is indeed the wiwj product. We changed the text in this section to better clarify these definitions.
(7) “P14 typo "sparce spiking" sparse”
Fixed. Thank you.
(8) “Suggest rewarding "Extra-laminar interactions reveal formation of neuronal ensembles with both feedforward (e.g., layer 4 to layer 5), and feedback (e.g., layer 5 to layer 4) drives." I'm not sure this method can truly distinguish common input from directed, recurrent cortical effects. Just as an example in Figure 5, it looks like 2->4, 0->4, and 3>2 are 0 lag effects. If you wanted to add the "functional delay" analysis to this laminar result that could support some stronger claims about directionality, though.”
The time lags for the results of Fig. 5 are indeed small, but, however, quantifiable. Left panel Fig. 5A shows static results with the correlation peaks shifted by 1ms from zero lag.
(9) “Methods - I think it would be useful to mention how many parameters the full DyNetCP model has.”
Overall, after the architecture of Fig.1C is established, dynamic weight averaging procedure is selected (Fig.9), and Fourier features are introduced (Fig.10), there is just a few parameters to optimize including L2 regularization (Fig.4 – supplement 1) and loss coefficient (Fig.1 – figure supplement 1A). Other variables, common for all statistical approaches, include bin sizes in the lag time and in the trial time. Decreasing the bin size will improve time resolution while decreasing the number of spikes in each bin for reliable inference. Therefore, number of spikes threshold and other related thresholds α𝑠 , α𝑤 , α𝑝 as well as λ𝑖λ𝑗, need to be adjusted accordingly (Fig.11) as discussed in detail in the Methods, Section 4. We included this sentence in the text.
(10) “It may be useful to also mention recent results in mice (Senzai et al. Neuron, 2019) and monkeys (Trepka...Moore. eLife, 2022) that are assessing similar laminar structures with CCGs.”
Thank you for pointing out these very interesting references. We added a paragraph in “Dynamic connectivity in VISp primary visual area” section comparing our results with these findings. In short, we observed that connections are distributed across the cortical depth with nearly the same maximum weights (Fig.7A) that is inconsistent with observed in Trepka et al, 2022 greatly diminished static connection efficacy within <200µm from the source. It is consistent, however, with the work of Senzai et al, 2019 that reveals much stronger long-distance correlations between layer 2/3 and layer 5 during waking in comparison to sleep states. In both cases these observations represent static connections averaged over a trial time, while the results presented in Video 3 and Fig.7A show strong temporal modulation of the connection strength between all the layers during the stimulus presentation. Therefore, our results demonstrate that tracking dynamic connectivity patterns in local cortical networks can be invaluable in assessing circuitlevel dynamic network organization.
Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public Review):
Summary:
In this work, the authors utilize recurrent neural networks (RNNs) to explore the question of when and how neural dynamics and the network's output are related from a geometrical point of view. The authors found that RNNs operate between two extremes: an 'aligned' regime in which the weights and the largest PCs are strongly correlated and an 'oblique' regime where the output weights and the largest PCs are poorly correlated. Large output weights led to oblique dynamics, and small output weights to aligned dynamics. This feature impacts whether networks are robust to perturbation along output directions. Results were linked to experimental data by showing that these different regimes can be identified in neural recordings from several experiments.
Strengths:
A diverse set of relevant tasks.
A well-chosen similarity measure.
Exploration of various hyperparameter settings.
Weaknesses:
One of the major connections found BCI data with neural variance aligned to the outputs.
Maybe I was confused about something, but doesn't this have to be the case based on the design of the experiment? The outputs of the BCI are chosen to align with the largest principal components of the data.
The reviewer is correct. We indeed expected the BCI experiments to yield aligned dynamics. Our goal was to use this as a comparison for other, non-BCI recordings in which the correlation is smaller, i.e. dynamics closer to the oblique regime. We adjusted our wording accordingly and added a small discussion at the end of the experimental results, Section 2.6.
Proposed experiments may have already been done (new neural activity patterns emerge with long-term learning, Oby et al. 2019). My understanding of these results is that activity moved to be aligned as the manifold changed, but more analyses could be done to more fully understand the relationship between those experiments and this work.
The on- vs. off-manifold experiments are indeed very close to our work. On-manifold initializations, as stated above, are expected to yield aligned solutions. Off-manifold initializations allow, in principle, for both aligned and oblique solutions and are thus closer to our RNN simulations. If, during learning, the top PCs (dominant activity) rotate such that they align with the pre-defined output weights, then the system has reached an aligned solution. If the top PCs hardly change, and yet the behavior is still good, this is an oblique solution. There is some indication of an intermediate result (Figure 4C in Oby et al.), but the existing analysis there did not fully characterize these properties. Furthermore, our work suggests that systematically manipulating the norm of readout weights in off-manifold experiments can yield new insights. We thus view these as relevant results but suggest both further analysis and experiments. We rewrote the corresponding section in the discussion to include these points.
Analysis of networks was thorough, but connections to neural data were weak. I am thoroughly convinced of the reported effect of large or small output weights in networks. I also think this framing could aid in future studies of interactions between brain regions.
This is an interesting framing to consider the relationship between upstream activity and downstream outputs. As more labs record from several brain regions simultaneously, this work will provide an important theoretical framework for thinking about the relative geometries of neural representations between brain regions.
It will be interesting to compare the relationship between geometries of representations and neural dynamics across connected different brain areas that are closer to the periphery vs. more central.
It is exciting to think about the versatility of the oblique regime for shared representations and network dynamics across different computations.
The versatility of the oblique regime could lead to differences between subjects in neural data.
Thank you for the suggestions. Indeed, this is precisely why relative measures of the regime are valuable, even in the absence of absolute thresholds for regimes. We included your suggestions in the discussion.
Reviewer #2 (Public Review):
Summary:
This paper tackles the problem of understanding when the dynamics of neural population activity do and do not align with some target output, such as an arm movement. The authors develop a theoretical framework based on RNNs showing that an alignment of neural dynamics to output can be simply controlled by the magnitude of the read-out weight vector while the RNN is being trained. Small magnitude vectors result in aligned dynamics, where low-dimensional neural activity recapitulates the target; large magnitude vectors result in "oblique" dynamics, where encoding is spread across many dimensions. The paper further explores how the aligned and oblique regimes differ, in particular, that the oblique regime allows degenerate solutions for the same target output.
Strengths:
- A really interesting new idea that different dynamics of neural circuits can arise simply from the initial magnitude of the output weight vector: once written out (Eq 3) it becomes obvious, which I take as the mark of a genuinely insightful idea.
- The offered framework potentially unifies a collection of separate experimental results and ideas, largely from studies of the motor cortex in primates: the idea that much of the ongoing dynamics do not encode movement parameters; the existence of the "null space" of preparatory activity; and that ongoing dynamics of the motor cortex can rotate in the same direction even when the arm movement is rotating in opposite directions.
- The main text is well written, with a wide-ranging set of key results synthesised and illustrated well and concisely.
- The study shows that the occurrence of the aligned and oblique regimes generalises across a range of simulated behavioural tasks.
- A deep analytical investigation of when the regimes occur and how they evolve over training.
- The study shows where the oblique regime may be advantageous: allows multiple solutions to the same problem; and differs in sensitivity to perturbation and noise.
- An insightful corollary result that noise in training is needed to obtain the oblique regime.
- Tests whether the aligned and oblique regimes can be seen in neural recordings from primate cortex in a range of motor control tasks.
Weaknesses:
- The magnitude of the output weights is initially discussed as being fixed, and as far as I can tell all analytical results (sections 4.6-4.9) also assume this. But in all trained models that make up the bulk of the results (Figures 3-6) all three weight vectors/matrices (input, recurrent, and output) are trained by gradient descent. It would be good to see an explanation or results offered in the main text as to why the training always ends up in the same mapping (small->aligned; large->oblique) when it could, for example, optimise the output weights instead, which is the usual target (e.g. Sussillo & Abbott 2009 Neuron).
We understand the reviewer’s surprise. We chose a typical setting (training all weights of an RNN with Adam) to show that we don’t have to fine-tune the setting (e.g. by fixing the output weights) to see the two regimes. However, other scenarios in which the output weights do change are possible, depending on the algorithm and details in the way the network is parameterized. Understanding why some settings lead to our scenario (no change in scale) and others don’t is not a simple question. A short explanation here, nonetheless:
- Small changes to the internal weights are sufficient to solve the tasks.
- Different versions of gradient descent and different ways of parametrizing the network lead to different results in which parts of the weights get trained. This goes in particular for how weight scales are introduced, e.g. [Jacot et al. 2018 Neurips], [Geiger et al. 2020 Journal of Statistical Mechanics], or [Yang, Hu 2020, arXiv, Feature learning in infinite-width networks]. One insight from these works is that plain gradient descent (GD) with small output weights leads to learning only at the output (and often divergence or unsuccessful learning). For this reason, plain GD (or stochastic GD) is not suitable for small output weights (the aligned regime). Other variants of GD, such as Adam or RMSprop, don’t have this problem because they shift the emphasis of learning to the hidden layers (here the recurrent weights). This is due to the normalization of the gradients.
- FORCE learning [Sussillo & Abbott 2009] is somewhat special in that the output weights are simultaneously also used as feedback weights. That is, not only the output weights but also an additional low-rank feedback loop through these output weights is trained. As a side note: By construction, such a learning algorithm thus links the output directly to the internal dynamics, so that one would only expect aligned solutions – and the output weights remain correspondingly small in these algorithms [Mastrogiuseppe, Ostojic, 2019, Neural Comp].
- In our setting, the output is not fed back to the network, so training the output alone would usually not suffice. Indeed, optimizing just the output weights is similar to what happens in the lazy training regime. These solutions, however, are not robust to noise, and we show that adding noise during the training does away with these solutions.
To address this issue in the manuscript, we added the following sentence to section 2.2: “While explaining this observation is beyond the scope of this work, we note that (1) changing the internal weights suffices to solve the task, and that (2) the extent to which the output weights change during learning depends on the algorithm and specific parametrization [21, 27, 85].”
- It is unclear what it means for neural activity to be "aligned" for target outputs that are not continuous time-series, such as the 1D or 2D oscillations used to illustrate most points here.
Two of the modeled tasks have binary outputs; one has a 3-element binary vector.
For any dynamics and output, we compare the alignment between the vector of output weights and the main PCs (the leading component of the dynamics). In the extreme of binary internal dynamics, i.e., two points {x_1, x_2}, there would only be one leading PC (the line connecting the two points, i.e. the choice decoder).
- It is unclear what criteria are used to assign the analysed neural data to the oblique or aligned regimes of dynamics.
Such an assignment is indeed difficult to achieve. The RNN models we showed were at the extremes of the two regimes, and these regimes are well characterized in the case of large networks (as described in the methods section). For the neural data, we find different levels of alignment for different experiments. These differences may not be strong enough to assign different regimes. Instead, our measures (correlation and relative fitting dimension) allow us to order the datasets. Here, the BCI data is more aligned than non-BCI data – perhaps unsurprisingly, given the experimental design of the prior and the previous findings for the rotation task [Russo et al, 2018]. We changed the manuscript accordingly, now focusing on the relative measure of alignment, even in the absence of absolute thresholds. We are curious whether future studies with more data, different tasks, or other brain regions might reveal stronger differentiation towards either extreme.
Recommendations for the authors:
Reviewer #1 (Recommendations For The Authors):
There's so much interesting content in the supplement - it seemed like a whole other paper! It is interesting to read about the dynamics over the course of learning. Maybe you want to put this somewhere else so that more people read it?
We are glad the reviewer appreciated this content. We think developing these analysis methods is essential for a more complete understanding of the oblique regime and how it arises, and that it should therefore be part of the current paper.
Nice schematic in Figure 1.
There were some statements in the text highlighting co-rotation in the top 2 PCs for oblique networks. Figure 4a looks like aligned networks might also co-rotate in a particular subspace that is not highlighted. I could be wrong, but the authors should look into this and correct it if so. If both aligned and oblique networks have co-rotation within the top 5 or so PCs, some text should be updated to reflect this.
This is indeed the case, thanks for pointing this out! For one example, there is co-rotation for the aligned network already in the subspace spanned by PCs 1 and 3, see the figure below. We added a sentence indicating that co-rotation can take place at low-variance PCs for the aligned regime and pointed to this figure, which we added to the appendix (Fig. 17).
While these observations are an important addition, we don’t think they qualitatively alter our results, particularly the stronger dissociation between output and internal dynamics for oblique than aligned dynamics.
Figure 4 color labels were 'dark' and 'light'. I wasn't sure if this was a typo or if it was designed for colorblind readers? Either way, it wasn't too confusing, but adding more description might be useful.
Fixed to red and yellow.
Typo "Aligned networks have a ratio much large than one"
Typo "just started to be explored" Typo "hence allowing to test"
Fixed all typos.
Reviewer #2 (Recommendations For The Authors):
- Explain/discuss in the main text why the initial output weights reliably result in the required internal RNN dynamics (small->aligned; large->oblique) after training. The magnitude of the output weights is initially discussed as being fixed, and as far as I can tell all analytical results (sections 4.6-4.9) also assume this. But in all trained models that make up the bulk of the results (Figures 3-6) all three weight vectors/matrices (input, recurrent, and output) are trained by gradient descent. It would be good to see an explanation or results offered in the main text as to why the training always ends up in the same mapping (small->aligned; large->oblique) when it could, for example, just optimise the output weights instead.
See the answer to a similar comment by Reviewer #1 above.
- Page 6: explain the 5 tasks.
We added a link to methods where the tasks are described.
- Page 6/Fig 3 & Methods: explain assumptions used to compute a reconstruction R^2 between RNN PCs and a binary or vector target output.
We added a new methods section, 4.4, where we explain the fitting process in Fig. 3. For all tasks, the target output was a time series with P specified target values in N_out dimensions. We thus always applied regression and did not differentiate between binary and non-binary tasks.
- Page 8: methods and predictions are muddled up: paragraph ending "along different directions" should be followed by paragraph starting "Our intuition...". The intervening paragraph ("We apply perturbations...") should start after the first sentence of the paragraph "To test this,...".
Right, these sentences were muddled up indeed. We put them in the correct order.
- Page 10: what are the implications of the differences in noise alignment between the aligned and oblique regimes?
The noise suppression in the oblique regime is a slow learning process that gradually renders the solution more stable. With a large readout, learning separates into two phases. An early phase, in which a “lazy” solution is learned quickly. This solution is not robust to noise. In a second, slower phase, learning gradually leads to a more robust solution: the oblique solution. The main text emphasizes the result of this process (noise suppression). In the methods, we closely follow this process. This process is possibly related to other slow learning process fine-tuning solutions, e.g., [Blanc et al. 2020, Li et al. 2021, Yang et al. 2023]. Furthermore, it would be interesting to see whether such fine-tuning happens in animals [Ratzon et al. 2024]. We added corresponding sentences to the discussion.
- Neural data analysis:
(i) Page 11 & Fig 7: the assignment of "aligned" or "oblique" to each neural dataset is based on the ratio of D_fit/D_x. But in all cases this ratio is less than 1, indicating fewer dimensions are needed for reconstruction than for explaining variance. Given the example in Figure 2 suggests this is an aligned regime, why assign any of them as "oblique"?
We weakened the wording in the corresponding section, and now only state that BCI data leans more towards aligned, non-BCI data more towards oblique. This is consistent with the intuition that BCI is by construction aligned (decoder along largest PCs) and non-BCI data already showed signs of oblique dynamics (co-rotating leading PCs in the cycling task, Russo et al. 2018).
We agree that Fig 2 (and Fig 3) could suggest distinguishing the regimes at a threshold D_fit/D_x = 1, although we hadn’t considered such a formal criterion.
(ii) Figure 23 and main text page 11: discuss which outputs for NLB and BCI datasets were used in Figure 7 & and main text; the NLB results vary widely by output type - discuss in the main text; D_fit for NLB-maze-accuracy is missing from panel D; as the criterion is D_fit/D_x, plot this too.
We now discuss which outputs were used in Fig. 7 in its caption: the velocity of the task-relevant entity (hand/finger/cursor). This was done to have one quantity across studies. We added a sentence to the main text, p. 11, which points to Fig 22 (which used to be Fig 23) and states that results are qualitatively similar for other decoded outputs, despite some fluctuations in numerical values and decodability.
Regarding Fig 22: D_fit for NLB-maze-accuracy was beyond the manually set y-limit (for visibility of the other data points). We also extended the figure to include D_fit/D_x. We also discovered a small bug in the analysis code which required us to rerun the analysis and reproduce the plots. This also changed some of the numbers in the main text.
- Discussion:
"They do not explain why it [the "irrelevant activity"] is necessary", implies that the following sentence(s) will explain this, but do not. Instead, they go on to say:
"Here, we showed that merely ensuring stability of neural dynamics can lead to the oblique regime": this does not explain why it is necessary, merely that it exists; and it is unclear what results "stability of neural dynamics" is referring to.
We agree this was not a very clear formulation. We replaced these last three sentences with the following:
“Our study systematically explains this phenomenon: generating task-related output in the presence of large, task-unrelated dynamics requires large readout weights. Conversely, in the presence of large output weights, resistance to noise or perturbations requires large, potentially task-unrelated neural dynamics (the oblique regime).”
- The need for all 27 figures was unclear, especially as some seemed not to be referenced or were referenced out of order. Please check and clarify.
Fig 16 (Details for network dynamics in cycling tasks) and Fig 21 (loss over learning time for the different tasks) were not referenced, and are now removed.
We also reordered the figures in the appendix so that they would appear in the order they are referenced. Note that we added another figure (now Fig. 17) following a question from Reviewer #1.
stargazer(TSMA_mod1, TSMA_mod2, TSMA_mod3, TSMA_mod4, TSMA_mod5, TSMA_mod6, title = "Regressions Using Massachusetts Test Score Data", type = "latex", digits = 3, header = FALSE, se = rob_se, object.names = TRUE, model.numbers = FALSE, column.labels = c("(I)", "(II)", "(III)", "(IV)", "(V)", "(VI)"))
Got an error message when running this code. The code below worked for me:
stargazer(TSMA_mod1, TSMA_mod2, TSMA_mod3, TSMA_mod4, TSMA_mod5, TSMA_mod6, title = "Regressions Using Massachusetts Test Score Data", type = "text", digits = 3, se = rob_se, dep.var.caption = "Dependent Variable: Test Score", column.labels = c("(I)", "(II)", "(III)", "(IV)", "(V)", "(VI)"))
delimiter
A delimiter is a character or symbol that separates data, words, phrases, lines, or code snippets.
Résumé de la vidéo [00:00:00][^1^][1] - [00:23:09][^2^][2]:
Cette vidéo explore le rôle de l'éducation dans la construction de la citoyenneté et la préservation de la République en France, en mettant l'accent sur l'importance de la laïcité et de l'unité nationale.
Temps forts: + [00:00:00][^3^][3] Introduction et citoyenneté * Importance de la citoyenneté dans la République * Citoyenneté comme consentement et volonté de vivre ensemble * Rôle de l'éducation dans la construction de la citoyenneté + [00:01:59][^4^][4] Histoire de l'éducation en France * Éducation comme instrument de régénération pendant la Révolution française * Contribution de l'éducation à la République sous la 3ème République * Éducation comme moyen d'affermir les principes républicains + [00:03:02][^5^][5] Indivisibilité de la République * Indivisibilité comme principe fondamental de la nation * Unité du pouvoir normatif et unicité du souverain * Rôle du Conseil constitutionnel dans la protection de l'indivisibilité + [00:08:01][^6^][6] Langue française et laïcité * Importance de la langue française dans l'unité nationale * Laïcité comme condition de l'indépendance de l'État * École comme sanctuaire protégé de toute immixtion religieuse + [00:13:00][^7^][7] Crise de la citoyenneté * Crise de confiance entre les citoyens et le système politique * Fragmentation de la citoyenneté et montée des revendications identitaires * Défis liés à la laïcité et à la reconnaissance des spécificités locales
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Cette partie de la vidéo traite de l'enseignement des langues régionales en France, en particulier de l'enseignement bilingue et immersif, et de ses implications constitutionnelles et légales.
Highlights: + [00:23:11][^3^][3] Enseignement bilingue et indivisibilité * Enseignement facultatif * Volume horaire inférieur au français * Jugé constitutionnel + [00:24:03][^4^][4] Réglementation des langues régionales * Code général des collectivités territoriales * Régions et territoires ultramarins concernés * Enseignement bilingue autorisé + [00:24:50][^5^][5] Enseignement immersif * Pas interdit mais régulé * Volume horaire limité * Non obligatoire + [00:27:02][^6^][6] Communication en français * Langue de communication avec les parents * Respect des principes de base du français * Enseignement privé sous contrat soumis aux mêmes obligations + [00:28:06][^7^][7] Instruction en famille * Changement depuis 2021 * Motifs d'autorisation limités * Enseignement des langues régionales en famille
Now, there are many reasons one might be suspicious about utilitarianism as a cheat code for acting morally, but let’s assume for a moment that utilitarianism is the best way to go. When you undertake your utility calculus, you are, in essence, gathering and responding to data about the projected outcomes of a situation. This means that how you gather your data will affect what data you come up with. If you have really comprehensive data about potential outcomes, then your utility calculus will be more complicated, but will also be more realistic. On the other hand, if you have only partial data, the results of your utility calculus may become skewed. If you think about the potential impact of a set of actions on all the people you know and like, but fail to consider the impact on people you do not happen to know, then you might think those actions would lead to a huge gain in utility, or happiness.
This reminds me most of measuring value of life in systems such as trolley problems or AI car decision making. Is a doctor more worthy of being saved than a musician? Or a depressed person? Or a felon? Where do you draw the line? If you draw a line, how many "felon lives" equals one doctor life? Utilitarianism to me isn't a morality system itself but a coping mechanism to allow humans to rationalize tough decisions. But when humans put the same logic in computers, it's not a coping strategy for a computer's feelings, but just a flawed series of priorities.
Now, there are many reasons one might be suspicious about utilitarianism as a cheat code for acting morally, but let’s assume for a moment that utilitarianism is the best way to go. When you undertake your utility calculus, you are, in essence, gathering and responding to data about the projected outcomes of a situation. This means that how you gather your data will affect what data you come up with. If you have really comprehensive data about potential outcomes, then your utility calculus will be more complicated, but will also be more realistic. On the other hand, if you have only partial data, the results of your utility calculus may become skewed. If you think about the potential impact of a set of actions on all the people you know and like, but fail to consider the impact on people you do not happen to know, then you might think those actions would lead to a huge gain in utility, or happiness.
This text points out the impact utilitarianism may have on moral decision-making. In other words, utilitarianism has certain limitations. In detail, if the data is not complete in the process of data collection, then its final result will have a certain bias. For example, only considering the impact of people you know and like on yourself, and ignoring the impact of people you don't know on yourself, then the results of the experiment are not comprehensive enough.
Address
For address, you may want to use test as datatype and put it into a string with age, name and relationship status. These data should be considered as metadata. For constraint, limited format of address: street, city, state, country, zip code. Limited length of zip code and street number. Create a list of exist countries and relevant states.
git add ., git commit -m “Your commit message.” Replace “Your commit message”
als code block, ich habe einen Befehl übersehen
Reviewer #1 (Public review):
Summary:
This paper examines plasticity in early cortical (V1-V3) areas in an impressively large number of rod monochromats (individuals with achromatopia). The paper examines three things:
(1) Cortical thickness. It is now well established that early complete blindness leads to increases in cortical thickness. This paper shows increased thickness confined to the foveal projection zone within achromats. This paper replicates the work by Molz (2022) and Lowndes (2021), but the detailed mapping of cortical thickness as a function of eccentricity and the inclusion of higher visual areas is particularly elegant.
(2) Failure to show largescale reorganization of early visual areas using retinotopic mapping. This is a replication of a very recent study by Molz et al. but I believe, given anatomical variability (and the very large n in this study) and how susceptible pRF findings are to small changes in procedure, this replication is also of interest.
(3) Connective field modelling, examining the connections between V3-V1. The paper finds changes in the pattern of connections, and smaller connective fields in individuals with achromatopsia than normally sighted controls, and suggests that these reflect compensatory plasticity, with V3 compensating for the lower resolution V1 signal in individuals with achromatopsia.
Strengths:
This is a carefully done study (both in terms of data collection and analysis) that is an impressive amount of work. I have a number of methodological comments but I hope they will be considered as constructive engagement - this work is highly technical with a large number of factors to consider.
Weaknesses:
(1) Effects of eye-movements
I have some concerns with how the effects of eye-movements are being examined. There are two main reasons the authors give for excluding eye-movements as a factor in their results. Both explanations have limitations.
a) The first is that R2 values are similar across groups in the foveal confluence. This is fine as far as it goes, but R2 values are going to be low in that region. So this shows that eye-movements don't affect coverage (the number of voxels that generate a reliable pRF), but doesn't show that eye-movements aren't impacting their other measures.
b) The authors don't see a clear relationship between coverage and fixation stability. This seems to rest on a few ad hoc examples. (What happens if one plots mean fixation deviation vs. coverage (and sets the individuals who could not be calibrated as the highest value of calibrated fixation deviation. Does a relationship then emerge?).
In any case, I wouldn't expect coverage to be particularly susceptible to eye-movements. If a voxel in the cortex entirely projects to the scotoma then it should be robustly silent. The effects of eye-movements will be to distort the size and eccentricity estimates of voxels that are not entirely silent.
There are many places in the paper where eye-movements might be playing an important role.
Examples include the larger pRF sizes observed in achromats. Are those related to fixation instability? Given that fixation instability is expected to increase pRF size by a fixed amount, that would explain why ratios are close to 1 in V3 (Figure 4).
(2) Topography
The claim of no change in topography is a little confusing given that you do see a change in eccentricity mapping in achromats.
Either this result is real, in which case there *is* a change in topography, albeit subtle, or it's an artifact.
Perhaps these results need a little bit of additional scrutiny.
One reason for concern is that you see different functions relating eccentricity to V1 segments depending on the stimulus. That almost certainly reflects biases in the modelling, not reorganization - the curves of Figure 2D are exactly what Binda et al. predict.
Another reason for concern is that I'm very surprised that you see so little effect of including/not including the scotoma - the differences seem more like what I'd expect from simply repeating the same code twice. (The quickest sanity check is just to increase the size of the estimated scotoma to be even bigger?).
I'd also look at voxels that pass an R2>0.2 threshold for both the non-selective and selective stimulus. Are the pRF sizes the same for both stimuli? Are the eccentricity estimates? If not, that's another clear warning sign.
(3) Connective field modelling
Let's imagine a voxel on the edge of the scotoma. It will tend to have a connective field that borders the scotoma, and will be reduced in size (since it will likely exclude the cortical region of V1 that is solely driven by resting state activity). This predicts your rod monochromat data. The interesting question is why this doesn't happen for controls. One possibility is that there is top-down 'predictive' activity that smooths out the border of the scotoma (there's some hint of that in the data), e.g., Masuda and Wandell.
One thing that concerns me is that the smaller connective fields don't make sense intuitively. When there is a visual stimulus, connective fields are predominantly driven by the visual signal. In achromats, there is a large swath of cortex (between 1-2.5 degrees) which shows relatively flat tuning as regards eccentricity. The curves for controls are much steeper, See Figure 2b. This predicts that visually driven connective fields should be larger for achromats. So, what's going on? The beta parameter is not described (and I believe it can alter connective field sizes). Similarly, it's possible to get very small connective fields, but there wasn't a minimum size described in the thresholding. I might be missing something obvious, but I'm just deeply confused as to how the visual maps and the connectome maps can provide contradictory results given that the connectome maps are predominantly determined by the visual signal. Some intuition would be helpful.
Some analyses might also help provide the reader with insight. For example, doing analyses separately on V3 voxels that project entirely to scotoma regions, project entirely to stimulus-driven regions, and V3 voxels that project to 'mixed' regions.
The finding that pRF sizes are larger in achromats by a constant factor as a function of eccentricity is what differences in eye-movements would predict. It would be worth examining the relationship between pRF sizes and fixation stability.
Reviewer #2 (Public review):
Summary:
Ziółkowska et al. characterize the synaptic mechanisms at the basis of the REdCA1 contribution to the consolidation of fear memory extinction. In particular, they describe a layer specific modulation of RE-dCA1 excitatory synapses modulation associated to contextual fear extinction which is impaired by transient chemogenetic inhibition of this pathway. These results indicate that RE activity-mediated modulation of synaptic morphology contributes to the consolidation of contextual fear extinction
Strengths:
The manuscript is well conceived, the statistical analysis is solid and methodology appropriate. The strength of this work is that it nicely builds up on existing literature and provides new molecular insight on a thalamo-hippocampal circuit previously known for its role in fear extinction. In addition, the quantification of pre- and post-synapses is particularly thorough.
Weaknesses:
The findings in this paper are well supported by the data more detailed description of the methods is needed.
(1) In the paragraph Analysis of dCA1 synapses after contextual fear extinction (CFE), more experimental and methodological data should be given in the text: -how was PSD95 used for the analysis, what was the difference between RE. Even if Thy1-GFP mice were used in Fig.2, it appears they were not used for bouton size analysis. To improve clarity, I suggest moving panel 2C to Figure 3. It is not clear whether all RE axons were indiscriminately analysed in Fig. 2 or if only the ones displaying colocalization with both PSD95 and GFP were analysed. If GFP was not taken into account here, analysed boutons could reflect synapses onto inhibitory neurons and this potential scenario should be discussed<br /> (2) in the methods: The volume of intra-hippocampal CNO injections should be indicated. The concentration of 3 uM seems pretty low in comparison with previous studies. More details of what software/algorithm was used to score freezing should be included. CNO source is missing. Antibody dilutions for IHC should be indicated. Secondary antibody incubation time should be indicated
No statement about code and data availability is present.
Author response:
Public Reviews:
Reviewer #1 (Public review):
The findings of Ziolkowska and colleagues show that a specific projection from the nucleus reuniens of the thalamus (RE) to dorsal hippocampal CA1 neurons plays an important role in fear extinction learning in male and female mice. In and of itself, this is not a particularly new finding, although the authors' identification of structural alterations from within dorsal CA1 stratum lacunosum moleculare (SLM) as a candidate mechanism for the learning-related plasticity is potentially novel and exciting. The authors use a range of anatomical and functional approaches to demonstrate structural synaptic changes in dorsal CA1 that parallel the necessary role of RE inputs in modulating extinction learning. Yet, the significance of these findings is substantially limited by several technical shortcomings in the experimental design, and the authors' central interpretation. Otherwise, there remain several strengths in the design and interpretation that offset some of these concerns.
Given that much is already known about the role of RE and hippocampus in modulating fear learning and extinction, it remains unclear whether addressing these concerns would substantially increase the impact of this study beyond the specific area of speciality. Below, several major weaknesses will be highlighted, followed by several miscellaneous comments.
Methodological:
(1) One major methodological weakness in the experimental design involves the widespread misapplication of Ns used for the statistical analyses. Much of the anatomical analyses of structural synaptic changes in the RE-CA1 pathway use N = number of axons (Figs. 1, 2), N = number of dendrites (Figs. 3, 4), and N = number of sections (Fig. 7; note that there are 7 figures in total). In every instance, N = animal number should be used. It is unclear which of these results would remain significant if N = animal number were used in each or how many more animals would be required. This is problematic since these data comprise the main evidence for the authors' central conclusion that specific structural synaptic changes are associated with fear extinction learning.
We do agree with the reviewer that N = animal number is the preferred way to present data in most of our experiments. However, in some experimental groups we observed a very low number of entries. For example, in the 5US group we found RE+/+ spines only in 3 out of 6 analyzed animals. We believe that this observation is not due to technical problems as mCherry virus transduction required to find RE+/+ spines is similar in all experimental groups and we analyzed similar volumes of tissue. While this result still allows the calculation of density of RE+/+ spines per animal it generates no entries for spine area and PSD95 mean gray value if N = animal number. Hence, we decided to use N=animals to calculate spines and boutons densities, and N=dendritic spines/boutons to calculate other spine/bouton parameters.
(2) There is a lack of specific information regarding what constitutes learning with respect to behavioral freezing. It is never clearly stated what specific intervals are used over which freezing is measured during acquisition, extinction, and in extinction retrieval tests. Additionally, assessment of freezing during retrieval at 5- and 30-min time points doesn't lay to rest the possibility that there were differences in the decay rate over the 30-min period (also see below).
We added a detailed description of how learning was assessed.
ln 125-134: For assessment of learning we used percent of time spent by animals freezing (% freezing). Freezing behavior was defined as complete lack of movement, except respiration. To assess within-session learning (working memory) we compared pre- and post-US freezing frequency (the first 148 sec vs last 30 sec) during the CFC session (day 1). To assess formation of long-term contextual fear memory, we compared pre-US freezing (day 1) and the first 5 minutes of the Extinction session (day 2). To assess within session contextual fear extinction we ran 2-way ANOVA to assess the effect of time and manipulation on freezing frequency. Freezing data were analyzed in 5-minute bins. To assess formation of long-term contextual fear extinction memory we compared the first 5 minutes of the Extinction session (day 2) and Test session (day 3).
As suggested by the reviewer, we also added data for all six 5-minut bins of Extinction sessions.
(3) A minor-to-moderate methodological weakness concerns the authors' decision to utilize saline injected groups as controls for the chemogenetics experiments (Figs. 5, 6). The correct design is to have a CNO-only group with the same viral procedure sans hM4Di. This concern is partly mitigated by the inclusion of a CNO vs. saline injection control experiment (Fig. 6).
Figure 5 does not describe a chemogenetic experiment.
We added new groups with control virus (CNO vs saline) to Figure 6 (now Fig. 6D and H).
The chemogenetic experiment shown on Figure 7 has all 4 experimental groups (Control vs hM4Di and saline vs CNO).
(4) In the electron microscopic analyses of dendritic spines (Fig. 5), comparison of only the fear acquisition versus extinction training, and the lack of inclusion of a naïve control group, makes it difficult to understand how these structural synaptic changes are occurring relative to baseline. It is noteworthy that the authors utilize the tripartite design in other anatomical analyses (Fig. 2-4).
We added data for the Naive mice to Figure 5.
(5) Interpretation:
The main interpretive weakness in the study is the authors' claim that their data shows a role for the RE-CA1 pathway in memory consolidation (i.e., see Abstract). This claim is based on the premise that, although RE-CA1 pathway inactivation with CNO treatment 30 min prior to contextual fear extinction did not affect freezing at 5- and 30-min time points relative to saline controls, these rats showed greater freezing when tested on extinction retrieval 24 h thereafter. First, the data do not rule out possible differences in the decay rate of freezing during extinction training due to CNO administration. Next, the fact that CNO is given prior to training still leaves open the possibility that acquisition was affected, even if there were not any frank differences in freezing. Support for this latter possibility derives from the fact that mice tested for extinction retrieval as early as 5 min after extinction training (Fig. 6C) showed the same impairments as mice tested 24 h later (Figs. 6A). Further, all the structural synaptic changes argued to underlie consolidation were based on analysis at a time point immediately following extinction training, which is too early to allow for any long-term changes that would underlie memory consolidation, but instead would confer changes associated with the extinction training event.
We do agree with the reviewer that our data do not allow us to conclude whether RE-CA1 pathway is involved in acquisition or consolidation of CFE memory. Therefore, we avoid those terms in the manuscript. We just conclude that RE→CA1 participates in the CFE.
Reviewer #2 (Public review):
Summary:
Ziółkowska et al. characterize the synaptic mechanisms at the basis of the REdCA1 contribution to the consolidation of fear memory extinction. In particular, they describe a layer specific modulation of RE-dCA1 excitatory synapses modulation associated to contextual fear extinction which is impaired by transient chemogenetic inhibition of this pathway. These results indicate that RE activity-mediated modulation of synaptic morphology contributes to the consolidation of contextual fear extinction
Strengths:
The manuscript is well conceived, the statistical analysis is solid and methodology appropriate. The strength of this work is that it nicely builds up on existing literature and provides new molecular insight on a thalamo-hippocampal circuit previously known for its role in fear extinction. In addition, the quantification of pre- and post-synapses is particularly thorough.
Weaknesses:
The findings in this paper are well supported by the data more detailed description of the methods is needed.
(1) In the paragraph Analysis of dCA1 synapses after contextual fear extinction (CFE), more experimental and methodological data should be given in the text:
- how was PSD95 used for the analysis, what was the difference between RE. Even if Thy1-GFP mice were used in Fig.2, it appears they were not used for bouton size analysis. To improve clarity, I suggest moving panel 2C to Figure 3. It is not clear whether all RE axons were indiscriminately analysed in Fig. 2 or if only the ones displaying colocalization with both PSD95 and GFP were analysed. If GFP was not taken into account here, analysed boutons could reflect synapses onto inhibitory neurons and this potential scenario should be discussed.
PSD-95 immunostaining in close apposition to boutons was used to identify RE buttons innervating CA1 (Fig 1 and 2). In these cases PSD-95 signal was not quantified. PSD-95 in close apposition to dendritic spines was used as a proxy of PSDs in CA1 (Figure 3, 4 and 7). In these cases we assessed the integrated mean gray value of PSD-95 signal per dendritic spine (Figure 3, 4) or per ROI (Figure 7). This is explained in detail in the section Confocal microscopy and image quantification (ln 149-172).
GFP signal was not taken into account during boutons analysis. This is explained in the materials and methods section Confocal microscopy and image quantification (ln 149-172).
We indicate that PSD-95 is a marker of excitatory synapses located both on excitatory and inhibitory neurons.
Ln 258: RE boutons were identified in SO and SLM as axonal thickenings in close apposition to PSD-95-positive puncta (a synaptic scaffold used as a marker of excitatory synapses located both on excitatory and inhibitory neurons (Kornau et al., 1995; El-Husseini et al., 2000; Chen et al., 2011; Dharmasri et al., 2024).
We also cite literature demonstrating that RE projects to the hippocampal formation and forms asymmetric synapses with dendritic spines and dendrites, suggesting innervation of excitatory synapses on both excitatory and aspiny inhibitory neurons (ln 673).
As advised by the reviewer the Figure 2C panel was moved to Figure 3 (now it is Fig 3A).
(2) in the methods: The volume of intra-hippocampal CNO injections should be indicated. The concentration of 3 uM seems pretty low in comparison with previous studies. CNO source is missing.
This section has been rewritten to be more clear. The concentration of CNO was chosen based on the previous studies (Stachniak et al., 2014).
ln 103: Cannula placement. Mice were anesthetized by inhalation of 3–5% isoflurane (IsoFlo; Abbott Animal Health) in oxygen and positioned in a stereotaxic frame (51503, Stoelting, Wood Dale, IL, USA). Two holes were drilled in the skull, and a double guide cannulae (2 mm apart and 2 mm long; 26GA, Plastics One) was lowered into the holes such that the cannula tip was located over dorsal CA1 area (2 mm posterior to bregma, ±1 mm lateral, and −1.3 mm vertical). Cannulae were kept patent by using 33-gauge internal dummy cannulae (Plastics One). The animals were used in contextual fear conditioning 21 days after the cannulation. Animals received bilateral CNO (3 μM, 0.2 μl per side for 1 min; Tocris Bioscience, Cat. No. 4936) (Stachniak et al., 2014) or saline injections (0.2 μl per side) 30 minutes before Extinction session via intrahippocampal injection cannulae (33-gauge). After the infusion, the cannula was left in place for 30 seconds. The cannula placement was verified by histology, and only data from animals with correct cannula implants were included in statistical analyses.”
(3) More details of what software/algorithm was used to score freezing should be included.
Freezing was automatically scored with VideoFreeze™ Software (Med Associates Inc.).
(4) Antibody dilutions for IHC should be indicated. Secondary antibody incubation time should be indicated.
The missing information is added.
ln 144: Next, sections were incubated in 4°C overnight with primary antibodies directed against PSD-95 (1:500, Millipore, MAB 1598), washed three times in 0.3% Triton X-100 in PBS and incubated in room temperature for 90 minutes with a secondary antibody bound with Alexa Fluor 647 (1:500, Invitrogen, A31571).
(5) No statement about code and data availability is present.
The statements are added.
ln 785: Row data and the code used for analysis of confocal data is available at OSF (https://osf.io/bnkpx/).
Reviewer #3 (Public review):
Summary:
This paper examined the role of nucleus reuniens (RE) projections to dorsal CA1 neurons in context fear extinction learning. First, they show that RE neurons send excitatory projections to the stratum oriens (SO) and the stratum lacunosum moleculare (SLM), but not the stratum radiatum (SR). After context fear conditioning, the synaptic connections between RE and dCA1 neurons in the SLM (but not the SO) are weakened (reduced bouton and spine density) after mice undergo context fear conditioning. This weakening is reversed by extinction learning, which leads to enhanced synaptic connectivity between RE inputs and dendrites in the SLM. Control experiments demonstrate that the observed changes are due to extinction and not caused by simple exposure to the context. Extinction learning also induced increases in the size (volume and surface area) of the post-synaptic density (PSD) in SLM. To establish the functional role of RE inputs to dCA1, the researchers used an inhibitory DREADD to silence this pathway during extinction learning. They observe that extinction memory (measured 2-hours or 24-hours later) is impaired by this inhibition. Control experiments show that the extinction memory deficit is not simply due to increased freezing caused by inactivation of the pathway or injections of CNO. Inhibiting the RO projection during extinction learning also reduced the levels of PSD-95 protein levels in the spines of dCA1 neurons.
Strengths:
Based on their results, the authors conclude that, "the RE→SLM pathway participates in the updating of fearful context value by actively regulating CFE-induced molecular and structural synaptic plasticity in the SLM.". I believe the data are generally consistent with this hypothesis, although there is an important control condition missing from the behavioral experiments.
Weaknesses:
(1) A defining feature of extinction learning is that it is context specific (Bouton, 2004). It is expressed where it was learned, but not in other environments. Similarly, it has been shown that internal contexts (or states) also modulate the expression of extinction (Bouton, 1990). For example, if a drug is administered during extinction learning, it can induce a specific internal state. If this state is not present during subsequent testing, the expression of extinction is impaired just as it is when the physical context is altered (Bouton, 2004). It is possible that something similar is happening in Figure 6. In these experiments, CNO is administered to inactivate the RE-dCA1 projection during extinction learning. The authors observe that this manipulation impairs the expression of extinction the next day (or 2-hours later). However, the drug is not given again during the test. Therefore, it is possible that CNO (and/or inactivation of the RE-dCA1 pathway) induces a state change during extinction that is not present during subsequent testing. Based on the literature cited above, this would be expected to disrupt fear extinction as the authors observed. To determine if this alternative explanation is correct, the researchers need to add groups that receive CNO during extinction training and subsequent extinction testing. If the deficits in extinction expression reported in Figure 6 result from a state change, then these groups should not exhibit an impairment. In contrast, if the authors' account is correct, then the expression of extinction should still be disrupted in mice that receive CNO during training and testing.
We do agree with the reviewer that such an experiment would be interesting. However, it could be also confusing as we could not distinguish whether the possible behavioral effects are related to the state-dependent aspects of CFE or impaired recall of CFE. Importantly, previous studies showed that RE is crucial for extinction recall (Totty et al., 2023). We also show that CFE memory is impaired not only when the animals recall CFE without CNO (day 3) but also with CNO (day 4) (Figure 6C). Moreover, we do not see the effects of CNO on CFE in the control groups (Figure 6D and H). So we believe that it is unlikely that CNO results in state-dependent CFE.
(2) In their analysis of dCA1 synapses after contextual fear extinction (CFE) (Figure 4), the authors should have compared Ctx and Ctx-Ctx animals against naïve animals (as they did in Figure 3) when comparing 5US and Ext with naïve animals. Otherwise, the authors cannot make the following conclusion; "since changes of SLM synapses were not observed in the animals exposed to the familiar context that was not associated with the USs, our data support the role of the described structural plasticity at the RE→SLM synapses in CFE, rather than in processing contextual information in general.".
We assume that the key experimental groups to conclude about synaptic plasticity related to particular behavior are the groups that differ just by one factor/experience. For CFE that would be mice sacrificed immediately before and after CFE session (Figure 2 & 3); on the other hand to conclude about the effects of the re-exposure to the neutral context mice sacrificed before and after second exposure to the neutral context are needed (Figure 4). The naive group, as it differs by at least two manipulations from the Ext and Ctx-Ctx groups, is interesting but not crucial in both cases. This group would be necessary if we focused on the memories of FC or novel context. However, these topics are not the main focus of the current manuscript. Still, the naive group is shown on Figures 2 & 3 to check if CFE brings spine parameters to the levels observed in mice with low freezing.
We have re-written the cited paragraph to be more precise in our conclusions.
"Overall, our data demonstrate that synapses in all dCA1 strata undergo structural or molecular changes relevant to CFC and/or CFE. However, only in SLM CFE-induced synaptic changes are likely to be directly regulated by RE inputs as they appear on RE+ dendrites and spines. Since such changes of SLM synapses were not observed in the animals re-exposed to the neutral context, our data support the role of the described structural plasticity at the RE→SLM synapses in CFE, rather than in processing contextual information in general."
(3) In the materials and methods section, the description of cannula placements is confusing and needs to be rewritten.
This section has been rewritten.
ln 103: Cannula placement. Mice were anesthetized by inhalation of 3–5% isoflurane (IsoFlo; Abbott Animal Health) in oxygen and positioned in a stereotaxic frame (51503, Stoelting, Wood Dale, IL, USA). Two holes were drilled in the skull, and a double guide cannulae (2 mm apart and 2 mm long; 26GA, Plastics One) was lowered into the holes such that the cannula tip was located over dorsal CA1 area (2 mm posterior to bregma, ±1 mm lateral, and −1.3 mm vertical). Cannulae were kept patent by using 33-gauge internal dummy cannulae (Plastics One). The animals were used in contextual fear conditioning 21 days after the cannulation. Animals received bilateral CNO (3 μM, 0.2 μl per side for 1 min; Tocris Bioscience, Cat. No. 4936) (Stachniak et al., 2014) or saline injections (0.2 μl per side) 30 minutes before Extinction session via intrahippocampal injection cannulae (33-gauge). After the infusion, the cannula was left in place for 30 seconds. The cannula placement was verified by histology, and only data from animals with correct cannula implants were included in statistical analyses.”
Reviewer #2 (Public review):
Summary:
This study evaluated the aperiodic component in the medial prefrontal cortex (mPFC) using resting-state EEG recordings from 149 individuals with chronic pain and 115 healthy participants. The findings showed no significant differences in the aperiodic component of the mPFC between the two groups, nor was there any correlation between the aperiodic component and pain intensity. These results were consistent across various chronic pain subtypes and were corroborated by whole-brain analyses. The study's robustness was further reinforced by preregistration and multiverse analyses, which accounted for a wide range of methodological choices.
Strengths:
This study was rigorously conducted, yielding clear and conclusive results. Furthermore, it adhered to stringent open and reproducible science practices, including preregistration, blinded data analysis, and Bayesian hypothesis testing. All data and code have been made openly available, underscoring the study's commitment to transparency and reproducibility.
Weaknesses:
The aperiodic exponent of the EEG power spectrum is often regarded as an indicator of the excitatory/inhibitory (E/I) balance. However, this measure may not be the most accurate or optimal for quantifying E/I balance, a limitation that the authors might consider addressing in the future.
Jackson Laboratory strain code 007914
DOI: 10.1038/s41596-024-01048-1
Resource: (IMSR Cat# JAX_007914,RRID:IMSR_JAX:007914)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:007914
Jackson Laboratory strain code 008538
DOI: 10.1038/s41596-024-01048-1
Resource: (IMSR Cat# JAX_008538,RRID:IMSR_JAX:008538)
Curator: @dhovakimyan1
SciCrunch record: RRID:IMSR_JAX:008538
Exploring notational design in computer science - Episode 17 delved into philosophical aspects, while this episode focuses on practical applications. - Addressing the need for operational semantics and elegance in reasoning and design, alongside listener questions.
Work environment and shift in focus - The department was initially conducive for mathematically oriented work and founded by three mathematicians. - The focus shifted over time and became less favorable for the speaker.
Elegance is about concise expressibility - Definition of elegance involves simplicity and mathematics we already know - Elegance does not mean familiarity or subjectivity, opposite to what is commonly perceived
Mathematics values concise expressions and reusability. - Mathematicians value expressing things concisely in core mathematic field. - Abstract algebra is a pragmatic tool derived from the need for reusability in mathematics.
Capitalism promotes short-term value work - Values of capitalism lead to focusing on immediate results without considering long-term impact. - Precise simplicity is essential for understanding complexity and elegance in theories.
MIT shifted from teaching Scheme to Python due to industry demand - Python is favored by companies for hiring programmers. - MIT's switch to Python reflects the influence of capitalism over academic values.
Courage to go beyond easy solutions - Being uncomfortable with proposed solutions but lacking a better one - Importance of speaking up and listening in decision-making processes
Choosing personal responsibility and honesty in values - Choosing not to prioritize promotions and raises by avoiding rocking the boat - Recognizing the brief window of opportunity to make an impact in the world
Scientific method emphasizes experimentation and progress towards truth - Experimentation measures theories against reality and guides where to look and what to test for - Capitalism focuses on short-term value, individuals must prioritize work of lasting value by making strategic choices and being skeptical of established norms and technologies.
Choosing work of lasting value over short-term gain requires sacrifice and dedication - Prioritizing meaningful work over maximizing bonuses and raises can be challenging but rewarding - Agreeing with Dan on valuing elegance in science and using objective criteria for progress
Complex questions must be formally checked for trustworthiness. - Complicated questions are likely false and can fool most people. - Questions that cannot be formally checked must be approached with simplicity and pragmatism.
Elegance is a duality of simplicity and cost - Simplicity requires mental effort and is difficult to find - Complexity results in usage cost for the user and creation cost for the creator
Elegance and easily formalizable values discussed - Dan and the speaker share similar values on elegance - Elegance should be easily formalizable and objective to avoid self-deception
Occasionally compelling theories may be disproven by measurements - Mistakes in measurements can lead to disagreement with theories - Compelling theories may prompt reevaluation and remeasurement to verify accuracy
Proof prevents self-dilution and ensures arrival at truth - Proof tells us if we haven't finished the proof or if we have truly reached the truth, unlike informal arguments - The cost of proof is the cost of knowing we are right, which outweighs the detraction from performance
Proof is essential for optimizing performance in software engineering. - Without proof, optimization can lead to self-defeating results and shaky correctness. - Engineers prioritize reliability and efficiency, with energy efficiency being a key aspect in modern software development.
Proper documentation in proof states reveals and corrects mistakes. - Proof not only confirms correctness but also helps constructively identify and correct mistakes. - Would you rather appear right or become right? Proof is key to becoming right and challenges the idea of already being right.
Code documentation must include proofs for understanding - The statement of the theorem represents the functionality of the software - The proof ensures the implementation details are correct
Elegance is key for simplicity and value in theorems and proofs - Simple and precise theorems provide more value to users than complex specifications, leading to practical benefits. - Striving for elegance in proofs reduces unnecessary complexity and effort, ensuring a better outcome.
Creating high value and cost-effective solutions with efficiency and sustainability - Balancing high value with cost-effectiveness and efficiency to create sustainable solutions. - Emphasizing the importance of simplicity, correctness, and elegance in delivering value to end users.
Analogy between compositional semantics and homomorphic design. - The essence is the same but in a more specific form. - Computers are analog, made out of nature, and cannot run at Nature's Own rate.
Nature's discreetness is impossible to achieve in this universe. - The discreetness of nature at the plank level is interesting but impractical in software or hardware implementation. - Even hardware built in this universe cannot achieve the required sampling rate set by nature.
Digital abstraction is about bits and bit patterns. - Digital abstraction involves interpreting data as bits and patterns, not numbers, trees, or graphs. - Using precise and truthful analogies, such as homomorphism in mathematics, is essential for accurate representation.
Groups and their relation in engineering - Groups like real numbers and symmetry groups serve as a basis in engineering. - Monoids, such as natural numbers and strings, are also used in programming.
Logarithms provide precise analogies between multiplication and addition - Log of a product is the sum of the logs (log a + log b) - Logarithms allow computation by turning multiplication into addition
Creating an implementation to add natural numbers using machine - Describing the need for dependable and efficient implementation - Resolving the challenge of using a machine that deals with bits, not numbers
Understanding the three-step process of converting numbers to binary and interpreting output - First step involves converting a number to binary before interpretation - Second step includes interpreting the binary using a mathematical function to get the number output
Denotational design ensures consistent results from input to output. - Correctness in denotational design means getting the same result from different paths. - Denotational design aims for a beautiful and elegant formulation of implementations and correctness proofs.
Implementing homomorphic data representations using different mathematical structures. - Utilizing the same vocabulary for data representations to maintain homomorphism. - Exploring various mathematical structures like monoids, groups, rings, and vector spaces in relation to machine learning and linear algebra.
Linear algebra deals with vector spaces over a ring with scalars. - Scalars form a ring, which can also be a commutative ring or a field. - Vectors can be added and scaled by scalars, forming the basis of linear algebra.
Matrices encode linear maps - Using currying, matrices represent functions from vectors to vectors - Matrices describe linear functions, making it easier to prove properties
Matrix multiplication is associative - Matrix multiplication involves matching up rows and columns, multiplying corresponding elements, and adding them up. - Associativity in matrix multiplication means the order of multiplication doesn't affect the result.
Understanding the purpose of a matrix as denoting a linear transformation - A matrix represents the mapping from a matrix to a linear function - Linear algebra is about functions that are linear, not about matrices
Matrices are a more efficient representation of linear functions. - Matrix multiplication follows a completely systematic denotational design. - Choosing the right representation, such as matrices, is crucial for success.
Matrix multiplication must be a perfect analogy to function composition. - Linear Maps and matrices speak the same language. - Composition is the main motivation for matrix multiplication in linear algebra.
Matrix composition is equivalent to interpreting matrices as linear maps and then composing them. - Correct matrix multiplication is necessarily associative. - Defining equality for matrices and linear functions is crucial for consistency.
Proving algebraic properties is not necessary for understanding concepts. - Algebraic properties are symptoms of superficial understanding. - Properties can be assumed to hold without explicit proof, as they follow from discipline.
Clear interpretation of linear maps and matrices is crucial for correct implementation. - Linear algebra is not about computers but using them as tools for visualization. - It is essential to understand the analogy between linear maps and matrices for accurate implementation.
Specification drives towards simplicity, implementation towards efficiency. - Using functions for linear maps is simpler than matrices to avoid errors in interpretation. - Introducing denotation helps reconcile different interpretations of matrices, ensuring correctness.
Specifications and implementations should be pulled in opposite directions - Specifications should be simple and free of detail, while implementations should be full of clever tricks and optimized for the specific hardware - The flaw in operational semantics is that it tries to put specifications and implementations together, rather than allowing them to be different
Correctness proofs emphasize simplicity for valuable theorems - Denotation simplifies theorem proof by removing operational complexities - Efficient implementation requires consideration of modern processing elements like GPU, ASIC
Understanding function composition and associative properties. - Importance of both formal and informal reasoning in relation to function composition. - Distinguishing between operational implementations for better performance and theoretical theorems for proofs.
Identifying linear operations and their presence in algebra - Linear operations include left and right projection of a pair, and appending zero to the pair - Exploring the existence of these operations within an algebraic structure, such as vector spaces and categories
Denotational design and linear maps in category theory - Linear maps and building blocks of denotational design - Understanding the mathematical realm and implementing the linear transformations
Showing type safety through operational semantics - Operational semantics used to demonstrate correctness of a computable language - Type safety proven through strong normalization and proper type relations
Operational semantics is a means to an end, not the goal. - Using operational semantics to solve problems definable outside of technology. - Creating a language with a type system to implement mathematical concepts in computing.
Designing programming interfaces vs. languages - I don't design languages, I design programming interfaces and implementations. - Programming languages have two parts: descriptions and gluing things together.
Choose one host language and embed domain-specific vocabularies to avoid constant language creation. - Peter Landin suggests embedding all vocabularies in a host language, distinguishing between domain-independent and domain-specific components. - This approach leads to pragmatic benefits and helps in avoiding the constant reinvention of programming languages.
Don't design languages - Existing imperative languages like C, C++, JavaScript are not conducive to adding new features easily. - Functional languages, particularly non-strict function languages, and dependently typed languages are better at hosting other vocabularies.
Operational and denotational semantics in language designing - Choosing between operational and denotational semantics for libraries - Challenges in separating operational and denotational semantics in some cases
Understanding denotational design in mathematical manipulation - Differentiating essential hard work from inessential hard work in math proofs - Exploring representations and operations in linear algebra and polynomial manipulation
Automatic differentiation is about functions that are differentiable - Definition and importance of differentiable functions in automatic differentiation - The connection between automatic differentiation and denotational design
Discussion on full abstraction and notational semantics - The conversation revolves around the impressive notational semantics and its relation to full abstraction. - The discussion also involves a comparison between concrete models and the challenges in achieving full abstraction in sequential and parallel computation.
Full abstraction is a key concept for equivalence - Observable operational equivalence means matching in all contexts - Many current languages lack full abstraction, which is historically accidental
Exploring the concept of parallelism in computational functions - It involves understanding PCF partial computable functions and Lambda calculus - The implementation challenge arises from deciding the evaluation order when dealing with false arguments
Differentiating between operational and denotational semantics in defining discourse - Operational semantics should not dictate denotational semantics - We should question and challenge the legitimacy of paradigms defining discourse
Imperative knowledge crucial for realistic 21st-century program implementation. - Declarative programs in high-level languages still need to meet the machine for practical interest. - Care about implementation involves proof, specification, correctness, and elegance.
Emphasizing the importance of proof in efficient specifications - Discussion on the necessity of detailed proofs for efficiency - Highlighting the comparison between operational and denotational approaches in linear algebra
Prevention through higher-level language and rich type systems - Higher-level language with a simple denotational model is expressive and aids in preventing errors - Focus on a small subset of machine behaviors that reflect correct execution of simple programming notions
Handling errors and exceptions in programming - Errors are things that cannot be captured in the semantic domain, leading to exceptions - A failure of the type system can result in errors, showing a need for a better system like in C or Pascal
Dependent types provide equivalent reasoning to foundations of mathematics and logic. - Dependent types offer a general solution for proofs and encoding in a self-consistent logical framework. - The entry barrier for learning advanced concepts like dependent types can be intimidating but crucial for ecosystem development.
Bridging familiarity and elegance in programming paradigms - Discussing the balance between familiarity and elegance in programming paradigms - Emphasizing the importance of making small tweaks to familiar paradigms for easier adoption
Challenging existing paradigms in computation - Exploring fundamental weaknesses in current computational paradigms - Adapting to the deceleration of Moore's Law and the need for innovation
Contributing to existing paradigms may bring short-term popularity but leads to dead ends - Choosing to contribute to existing paradigms may result in short-term popularity, kudos, and raises. - However, it also involves expending life energy, a non-renewable and precious resource, into something that is a dead end.
Learning negotiation and mediation from Roger Carl - Reflecting the other person's point of view to their satisfaction - Listening deeply and connecting with the other person's perspective
Facilitating heart-to-heart communication. - The facilitator observes and guides the process. - The dialogue creates a deeper connection and understanding between the individuals involved.
Belief clings but Faith lets go - Belief is the insistence that the truth is what one would wish it to be - Faith is an unreserved opening of the mind to the truth, without preconceptions
rustworthy. I
VISUAL ANNOTATIONS
(3:55) Code Carbon helps to provide a visual for the emissions produced in a certain time period. Much like the nutrition information on the outside of a cereal box, though it is helpful to know how many calories or grams of sugar are contained in one serving, that information would be useless without knowing what a serving size is. Even more so if we are unaware of how many calories we should consume in a given time frame. This information allows us to make informed decisions about what we should consume.
(5:04) This visual of the photos that are generated when she inputs her own information provides a bit of shock factor to the audience. Not only are most of those images of someone who is not her, but they are quite illicit photos of someone who is not her. Taken out of context and unknown to be AI generated, photos such as these could be detrimental to someone's career or personal life.
Methods
Would you be willing to provide the code you used for this project as a GitHub repo or a gist?
Callback functions
What: A callback function in JavaScript is a function passed as an argument to another function, which is then executed after the completion of that function.
Why: Asynchronous Operations: JavaScript uses callbacks to handle asynchronous tasks like API calls, timers, or file reading. Code Modularity: Callbacks allow for cleaner, reusable, and more maintainable code by delegating operations to specific functions. How: You define a callback function and pass it as a parameter:
javascript Copy code function greet(name, callback) { console.log('Hello, ' + name); callback(); }
function sayGoodbye() { console.log('Goodbye!'); }
greet('Alice', sayGoodbye); Here, sayGoodbye is passed as a callback to greet, and gets executed after the greeting.
You said: output ChatGPT said: ChatGPT The output of the provided code would be:
Copy code Hello, Alice Goodbye! Explanation: The greet function is called with "Alice" and the sayGoodbye function as arguments. Inside greet, it first logs "Hello, Alice". After that, it calls callback(), which refers to sayGoodbye, and the sayGoodbye function logs "Goodbye!".
if ((gup_flags & (FOLL_PIN | FOLL_LONGTERM)) != (FOLL_PIN | FOLL_LONGTERM)) return true;
most likely part of a policy code that includes flag based decision making
We often think of game development as a technical discipline, but so much of a video game has nothing to do with code or technology
fenomenalno!!!!!
It’s time for policymakers to elevate family authority, formation, and cohesion as their top priority and even use government power, including through the tax code, to restore the American family.
A theme of American conservatism especially since its political alliance with conservative Evangelicals and Catholics starting in the 1970s. "Restore the American family" implies a stable definition of "family" that stands outside of history. Scholars have argued, instead, that the concept of "family" is constantly changing and in recent decades has become highly politicized. See, for instance, https://us.macmillan.com/books/9780809026746/allinthefamil, https://press.princeton.edu/books/paperback/9781935408345/family-values?srsltid=AfmBOorOO6MeT5oyZNB-hky3yAl_vnpYYFkV8m2vGEd-R9p7oqyZtTkx, and https://www.dukeupress.edu/the-world-turned.
A chief goal of that earlier merger of politically engaged Evangelicals and conservative Catholics, overturning Roe v. Wade, has now been achieved. Hence, advocates of this agenda, in pushing state-level abortion bans as well as newers targets, have sought ever more active exercise of governmental authority over both sexual relations and gender identify.
multithreaded code.
Multithreaded code is code that allows multiple threads (smaller units of a process) to run concurrently. In a multithreaded program, different threads can execute code simultaneously, allowing tasks to be performed in parallel, which can improve performance, especially in multi-core systems.
Welcome back and in this lesson I want to talk about hashing, what it is and why we need it.
Now we do have a lot to cover so let's jump in and get started straight away.
What's simply hashing is a process where an algorithm is used to turn this or any other piece of data into this, a fixed length representation of that data.
Hashing is at the core of many critical services that you use today, such as passwords, digital signatures, SSL certificates, data searches, and even some antivirus or anti-malware solutions rely on hashes so they can store definitions of malicious files without having to store every single huge file.
We even have some forms of digital money such as Bitcoin which use hashing.
Now to understand why hashing is so important we need to step through how it works, what benefits it provides and some of the terminology used.
So let's go ahead and do that.
Hashing starts with a hash function and think of this as a piece of code and algorithm.
Now there are many different ones which are used or have been used over the years.
An example include MD5 and SHA-2 256.
The core principle of hashing is that you take some large variable sized data and you put that data through a hashing function and receive a fixed size hash of that data.
So whether the data is a text file, an image or a huge database file, the hash you receive will be tiny and fixed length based on the hashing function type.
Now also critically if you take some other data and again put it through the same hashing function you will get a different hash, a unique hash value.
Even if the data differs by only one byte, one character or one pixel it will result in a different hash.
The aim with hash functions is that any change no matter how minor will result in a different hash value.
Another critical part of hashing is that while getting a hash from some data is trivial what you cannot do is take a hash value and get the original data back.
There's no way to do this.
Let's say that you had a hash of an image.
Well you couldn't take the hash and derive the image.
You could if you had infinite processing power and infinite time brute force every image in existence to try and link back to the hash.
But this would require hashing every single image until you found the correct one.
You should view it as impossible with any modern hashing algorithm to derive the original data from a hash.
Without some vulnerability in the hashing function or without infinite time and processing power the hashing is one way only.
Data through to hash.
Now lastly another fundamental part of hashing is that given the same data you're always going to get the same hash value if you use the same hashing function.
So for one piece of data you get one hash value, for a different piece of data you get a different hash value and hashing is one way only.
And you should never get the same hash value for different data.
There are more on this in a second.
Let's look at an example of where hashing can be used which should be pretty familiar.
Imagine you're using an online service and they have a single server.
And when you create an account on that service you create a username and password and both of those are stored on that server.
When you log in you send your username and password to the server and an automated process checks the password that you send with the one that's stored and if they match you can log in.
Now even if you encrypt your password in transit and even if the password is encrypted when stored on the server your password still exists on that server.
And it means if the server is ever exploited then a bad actor will have access but worst to your password and at best an encrypted version of your password.
Assuming a full data dump or a long term exploit is pretty trivial to get the plain text version of your password in this way.
If you use that password on all the services those services are also at risk.
But what about if we use hashes?
Well with this architecture instead of sending a password to the server when signing up or signing in we send a hash of the password.
This means the server instead of having our actual password it only stores the hash of our password.
All the server needs to do is check that the hash that you send matches the one in its database and it can confirm the password was entered correctly on the local client.
Because given the same data in this case password and the same hashing algorithm you'll end up with the same hash value.
So by comparing the hash value it stores to the hash value that you deliver by the hash of your password it can check you're entering the correct password without ever storing a copy of your password.
Now in this example I've used the MD5 hashing algorithm but as you're going to say in a second this isn't super secure anymore so you'd likely need to use another hashing algorithm.
I'm going to use MD5 as an example to demonstrate a weakness of some algorithms.
So to stress you wouldn't generally use MD5 for production password systems you'd use something a lot more secure.
Now if this server was ever exploited when using password hashes this would be much safer because the hashes are one way you can't derive the password from a hash.
Nothing stops the attacker though from getting over and over again trying every possible word and phrase combination with the hashing algorithm used until it gets us right.
And then it has confirmed the password that you used and it can try and exploit all the services which you also make use of.
And this is why it's really important to use a modern secure hashing algorithm.
Now there are two things with hashing which are really bad.
One is if we were ever able to take a hash and derive the original data but as I mentioned earlier that's basically impossible to have a critical vulnerability in how hashing works.
Another major problem would be a collision.
An example of a collision is that if we take this image of a plane and if we hash this image and then if we take another image say this image of a shipwreck and we also hash this image we should have two different hash values.
If we do awesome.
If not if the hash of A on the left equals the hash of B on the right then bad things happen because we can no longer trust the hash function i.e. the hash algorithm.
And this is one of the reasons that MD5 has hashing algorithm is less trusted because collisions can happen.
We can actually show how they can be created, how data can be manipulated to cause collisions.
Now I've attached some links to this video with the research project showing how we can create those collisions.
But as a quick example I want to switch to my terminal and demonstrate how this works with these two images.
So in this folder on my local machine I have two images plane.jpg and ship.jpg and those represent the two images that you've just seen on your screen moments ago.
I'm going to go ahead and generate a hash value of one of these files and I'm going to use the MD5 hashing algorithm.
So I'm going to put MD5 space and then plane.jpg.
Go ahead and focus on the hashing value that's been generated so this hashing value in theory should uniquely represent the image plane.jpg.
So plane.jpg should always generate this hash value and if I repeat this command I get the same hash value.
But what should happen is if I generate a hash of another piece of data I should get a different hash value.
So I'm going to run MD5 again this time on ship.jpg.
Watch what happens in this case it's the same hash value and this is an example of a collision where two different pieces of data generate the same hash value.
And this is a weakness of MD5.
We can create this collision.
We can adjust the data in order to generate this collision and this is a bad thing.
This shouldn't happen.
Now I'm not to follow the same process but using a more secure hashing algorithm.
So this time I'm going to use the SHA-2 256 algorithm on the same file plane.jpg.
Now watch what happens now.
The hash value is longer because this is a different hashing algorithm but we confirm that this hash value is for plane.jpg.
Now I'm going to run the same hashing algorithm on ship.jpg.
This time note how it's a different hash value.
This is a much more secure hashing algorithm.
SHA-2-256 is much better at protecting against these collisions.
It's a more modern and more well trusted hashing algorithm.
Now just like any other form of security such as encryption it's important that you always use the latest and most secure protocols and architectures.
So if you're using hashing in production you should generally use something like SHA-2-256 because if you want to guarantee that one-to-one link between a piece of data and a hash so that any other piece of data generates a different hash you need to make sure you're using a well respected hashing algorithm such as SHA-2-256.
Now the likelihood of this happening in normal usage is nearly possible because these two images have actually been artificially adjusted to cause this collision but it does represent theoretical vulnerability in the MD5 hashing algorithm.
I've included links attached to this video which detail the search project and some examples of how you can implement this as a personal project if you want.
But at this point I'm going to go ahead and return to the remainder of this video.
Now just to summarise with hashing you take some data plus a hashing function and you generate a hash value.
Now you can't get the original data from a hash it is a one-way process and the same data should always generate the same hash.
Different data should always generate a different hash.
Now just demonstrated how you can artificially cause a collision using older hashing algorithms but in the real world even older algorithms should generate a different hash for different data and any modern hashing algorithm is protected against even this artificial process.
Now hashing can be used to verify downloaded data.
If you're making some data available to download you can have the download in one location and the hash of that download stored on a different system.
It means that you can download the data you can hash it and generate your own hash value.
If the hash value is matched then the downloaded data hasn't been altered.
If they differ then it means that what you have is not the same data as what was made available by the original author.
And this is a process that's very often used to verify sensitive applications.
So if you're downloading any form of application which stores sensitive data or operates on sensitive networks then you'll generally find that a hash will be made available by the author of that application and it can be used to verify that that download has not been adjusted.
Now in these type of security sensitive situations or if you're a security professional you also need to be sure that the hash itself hasn't been altered.
It's also whether the hash itself was generated by the person who claims to have generated that hash.
So if I make some software available to you and you download it you need to first check that the download hasn't been altered by hashing it yourself and comparing your hash to the hash that I publish.
But you also need to be sure that it was me publishing that hash and that the hash that you download hasn't been altered in some way.
And a way that this can be done is using digital signing or digital signatures and this is something that I cover in another video.
But at this point that's everything I wanted to cover in this video so go ahead and complete the video and be ready.
I'll look forward to you joining me in the next.
Welcome to this lesson where I want to provide a quick foundation into encryption.
Now I want to keep foundation lessons as short as possible so let's jump in and get started.
Before we get started though, I just want to cover the topics that we're going to go through in this lesson.
I'll be starting by talking about the different approaches to encryption, so encryption at rest and encryption in transit.
I'll follow up by talking about the different concepts, so the different components and how those fit together.
I'll cover symmetric encryption, asymmetric encryption, including the differences between those two, and I'll finish up the lesson talking about signing and then steganography.
Now I'll get started by talking about the different approaches to encryption, so we'll do that first.
There are two main approaches to encryption that you will see used within AWS and the real world in general.
Each of these is aimed at solving a very different problem.
First we've got encryption at rest and second encryption in transit.
Encryption at rest is designed to protect against physical theft and physical tampering, and a common example of this is a user with an encrypted laptop.
So Nat's using her laptop as she would with any other device, but her laptop is busy encrypting or scrambling any data that it writes to the internal storage, and then decrypting that data when it reads it from the same storage into memory.
Now there's a special piece of data that's used to encrypt and decrypt that data, and it's only known to Nat.
Now the proper word for this is secret.
Now with laptop encryption, this is either the password for the user logging into the laptop, or a piece of data that's derived from that, but in other types of encryption, it's more complex than that.
What this means though, is that if Nat's laptop is stolen or tampered with, the data is encrypted at rest without the information required to decrypt it.
It's useless to an attacker.
If somebody steals a laptop without the passcode that Nat uses, all they have is a laptop with encrypted or scrambled data, which is useless.
Encryption at rest is also used fairly commonly within cloud environments.
Your data is stored on shared hardware, and it's done so in an encrypted form.
Even if somebody else could find and access the base storage device that you were using, they couldn't access your data.
Encryption at rest is generally used where only one party is in this case, Nat, and that party is the only person who knows the encryption and encryption team.
The other approach to encryption is known as encryption in transit, and this is aimed at protecting data while it's being transferred between two places.
So when Nat is using her encryption data, the data is encrypted before it exits Nat's laptop, and decrypted by the bank when it arrives, and the same process is followed in reverse.
So the bank encrypts any data that's destined for Nat's laptop, and Nat's laptop performs the decryption process.
What you're essentially doing with encryption in transit is to apply an encryption wrapper, a tunnel, around the raw data, and anyone looking from the outside would just see a stream of scrambled data.
Encryption in transit is generally used when multiple individuals or systems are involved.
So let's move on and talk about encryption concepts.
In this part of the lesson, I want to introduce some encryption terms.
Not all of these are immediately intuitive, and so if you haven't heard of these before, I want to confirm your understanding because I'll be using them throughout the course.
Now we'll start with plaintext, and this is a horrible term to use for this thing, because the name gives you the impression that it's text data, and it isn't always.
Plaintext is unencrypted data.
It can be text, but it doesn't have to be.
It can also be images or even applications.
Plaintext is data that you can load into an application and use, or you can load and immediately read that data.
The next term is an algorithm, and an algorithm is a piece of code, or more specifically a piece of maths which takes plaintext and an encryption key, which I'll talk about shortly, and it generates encrypted data.
Now common examples of algorithms are Blowfish, AES, RC4, DES, RC5, and RC6.
When an algorithm is being used, it needs the plaintext, and it needs a key.
And a key is the next term I want to talk about.
A key at its simplest is a password, but it can be much more complex.
When an algorithm takes plaintext and a key, the output that it generates is ciphertext.
Now just like plaintext, ciphertext isn't always text data.
Ciphertext is just encrypted data.
So the relationship between all these things is that encryption, it takes plaintext, it uses an algorithm and a key, and it uses those things to create ciphertext.
Decryption is just the reverse.
It takes ciphertext, it takes a key, and it generates plaintext.
Now this is not all that complex at a high level, but like most things in tech, there are some details which you need to understand.
First I want to focus on the encryption key for the next part of the lesson.
The type of key influences how encryption is used.
So let's look at the different types of keys and different types of encryption.
The first type of encryption key that I want to talk about is a symmetric key.
Symmetric keys are used as part of a symmetric encryption process.
Now it's far easier to show you an example visually rather than just explain it.
So here goes.
Now as everybody knows at this point I'm a fan of animals, specifically cats.
What you might not know is I'm also a fan of robots.
And everybody knows that cats want to achieve world domination, and robots are working towards the robot apocalypse.
In this example, they've allied.
They created a plan for world domination.
So on the left we've got the cat supreme ruler, and on the right we've got the robot general.
Both leaders want to exchange data, their battle plans, and they want to do that without humans being able to read them in a plaintext form.
They need to ensure that the battle plans are only ever exchanged using ciphertext, so the humans never see the plaintext battle plans.
So step one is they agree on an algorithm to use, in this case AES 256.
And they set to work preparing to send the plaintext battle plans.
Now the cat ruler, because he's the party sending the data, he needs to generate a symmetric encryption key, so he needs to create that and keep it safe.
A symmetric encryption algorithm is used, and this accepts the key and the plaintext battle plans.
And once it's accepted both of those, it performs encryption and it outputs ciphertext, the encrypted battle plans.
The encrypted battle plans are now secure, because they're ciphertext and nobody can decipher them without the key.
They can be sent over any transmission method, even an insecure way to the robot general.
The encryption removes the risk of transmitting this data in the open, so even if we handed the ciphertext over to an untrustable party and asked for him to deliver that to the robot general, that would still be safe because the ciphertext is un-desyferable without the key.
But this is where the problem starts for our rulers.
The robot general doesn't have the key which was used to encrypt the data.
With symmetric encryption, the same key is used for both the encryption and the encryption processors.
So we need to find a way to get the robot general a copy of the key that was used to encrypt the data.
So how do we do that?
Well, we could transfer it electronically, but that's a bad idea because if the humans get the key, it's all over.
They can also decrypt the data.
We could arrange an in-person meetup, but for anything which is really sensitive, this is less than ideal because the people meeting to exchange the key could be intercepted on their way.
We could encrypt the encryption key and then transfer that key.
Now, that would be safe because the encryption key would be protected, but we'd still need to find a safe way of transferring the key that was used to encrypt the encryption key, and that gets really complex really quickly.
This is why symmetric encryption is great for things like local file encryption or disk encryption or lac-box, but not so useful for situations where the data needs to be transferred between two remote parties, because arranging the transit of the key is the problem, and generally we need to do that in advance so there is no delay in decrypting the data.
If the data that we're transferring is time-sensitive, the transit of the encryption key needs to happen in advance, and that's the most complex part of this method of encryption.
Now, if we did have a way to transfer the key securely, then the same algorithm would decrypt the data using the key and the ciphertext, and then we'd return the original plaintext battle plans.
But there's another way of doing it, and that's to use asymmetric encryption, and this addresses some of the problems that our rulers are facing.
It makes it much easier to exchange keys because the keys used in asymmetric encryption are themselves asymmetric.
Now, let's look at exactly what this means.
To use asymmetric encryption, the first stage is for the cap ruler and the robot channel to agree an asymmetric algorithm to use, and then create encryption keys for the algorithm, which logically enough will be asymmetric encryption keys.
Asymmetric encryption keys are formed of two parts, a public key and a private key.
For both sides to be able to send and receive to each other, then both sides would need to make both public and private keys.
To keep the diagram simple, we're going to use the example of where the cap ruler will be sending the battle plans to the robot channel, so only the robot channel in this scenario will need to generate any keys.
Now, a public key can be used to generate ciphertext, which can only be decrypted by the corresponding private key.
The public key cannot decrypt data that it was used to encrypt, only the private key can decrypt that data.
This means the private key needs to be guarded really carefully because it's what's used to decrypt data.
If it leaks, the battle plans could be compromised.
The public key, it's just used to encrypt, and so the robot general uploads his public key to his cloud storage so that anyone can access it.
The worst thing that could happen to anyone who obtains the robot general's public key is that he or she could use it to encrypt plaintext into ciphertext that only the robot general could decrypt.
So there's no downside to anyone getting hold of the robot general's public key.
So with asymmetric encryption, there's no requirement to exchange keys in advance.
As long as the robot general uploaded his public key to somewhere that was accessible to the world, then the first step would be for the cap ruler to download the robot general's public key.
Remember, this isn't sensitive.
Anyone can use it to encrypt data for the robot general, and that's it.
That's the only thing that the public key can do in this scenario.
So using the general's public key and the plaintext battle plans, the asymmetric algorithm would generate some ciphertext.
The ciphertext can then be transmitted to the robot general, and once received, only the robot general could decrypt that data.
This time, though, there's no key exchange required because the rulers are using asymmetric encryption.
The general already has his private key, and so he provides that private key and the ciphertext to the algorithm, which decrypts the ciphertext back into plaintext, and then the robot general has a copy of plaintext battle plans.
Asymmetric encryption is generally used where two or more parties are involved, and generally when those parties have never physically met before.
Issues by PTP, popular email and file encryption system.
Issues by SSL or TLS, which is a system for encrypting browser communications.
And issues by SSH, a popular method to securely access servers using key-based authentication.
Now, asymmetric encryption is computationally much more difficult to do than symmetric, and so many processors use asymmetric encryption to initially agree and communicate symmetric key, and then the symmetric key is used for communication between those two parties from that point onward.
Okay, so this is the end of part one of this lesson.
It was getting a little bit on the long side, and so I wanted to add a break.
It's an opportunity just to take a rest or grab a coffee.
Part two will be continuing immediately from the end of part one.
So go ahead, complete video, and when you're ready, join me in part two.
creates or contains “machine code”
the Python interpreter
if (s->flags & __CMPXCHG_DOUBLE) { ret = __update_freelist_fast(slab, freelist_old, counters_old, freelist_new, counters_new); } else { ret = __update_freelist_slow(slab, freelist_old, counters_old, freelist_new, counters_new); }
This policy is very similar to annotated code below. The description is reproduced here:
This policy determines if the system has support for compare and exchange. If so, it will use the "__update_freelist_fast()" function, which uses a compare and exchange internally. Otherwise, it will use "__update_freelist_slow()", which uses a lock (specifically a bit-based spinlock) internally.
this is why software is a conversation before you go and code it have that deep conversation
software is a conversation with a purpose and intent
/* * The baseline for the badness score is the proportion of RAM that each * task's rss, pagetable and swap space use. */ points = get_mm_rss(p->mm) + get_mm_counter(p->mm, MM_SWAPENTS) + mm_pgtables_bytes(p->mm) / PAGE_SIZE; task_unlock(p); /* Normalize to oom_score_adj units */ adj *= totalpages / 1000; points += adj;
The kernel calls out of memory when the RAM passes full utilization limit. This code calculates a predicate for choosing the maximal "bad" process to reap to fix the out of memory issue. This code defines the predicate as a heuristic calculation; it calculates "badness" as the proportion of RAM that the sum of the task's RSS, pagetable, and swap space use.
#ifdef CONFIG_VM_EVENT_COUNTERS DEFINE_PER_CPU(struct vm_event_state, vm_event_states) = {{0}}; EXPORT_PER_CPU_SYMBOL(vm_event_states); static void sum_vm_events(unsigned long *ret) { int cpu; int i; memset(ret, 0, NR_VM_EVENT_ITEMS * sizeof(unsigned long)); for_each_online_cpu(cpu) { struct vm_event_state *this = &per_cpu(vm_event_states, cpu); for (i = 0; i < NR_VM_EVENT_ITEMS; i++) ret[i] += this->event[i]; } } /* * Accumulate the vm event counters across all CPUs. * The result is unavoidably approximate - it can change * during and after execution of this function. */ void all_vm_events(unsigned long *ret) { cpus_read_lock(); sum_vm_events(ret); cpus_read_unlock(); } EXPORT_SYMBOL_GPL(all_vm_events); /* * Fold the foreign cpu events into our own. * * This is adding to the events on one processor * but keeps the global counts constant. */ void vm_events_fold_cpu(int cpu) { struct vm_event_state *fold_state = &per_cpu(vm_event_states, cpu); int i; for (i = 0; i < NR_VM_EVENT_ITEMS; i++) { count_vm_events(i, fold_state->event[i]); fold_state->event[i] = 0; } } #endif /* CONFIG_VM_EVENT_COUNTERS */
When CONFIG_VM_EVENT_COUNTERS is enabled, the kernel compiles the code that collects and manages virtual memory (vm) event counters. These counters track events like page faults, page allocations, and swap operations. The functions sum_vm_events, all_vm_events, and vm_events_fold_cpu are responsble for accumulating these statistics across all CPUs.
If CONFIG_VM_EVENT_COUNTERS is not enabled, this code is excluded from the build. This means the kernel won't collect these detailed VM statistics, reducing memory usage and avoiding the overhead associated with tracking them.
#ifdef CONFIG_NUMA int sysctl_vm_numa_stat = ENABLE_NUMA_STAT; /* zero numa counters within a zone */ static void zero_zone_numa_counters(struct zone *zone) { int item, cpu; for (item = 0; item < NR_VM_NUMA_EVENT_ITEMS; item++) { atomic_long_set(&zone->vm_numa_event[item], 0); for_each_online_cpu(cpu) { per_cpu_ptr(zone->per_cpu_zonestats, cpu)->vm_numa_event[item] = 0; } } } /* zero numa counters of all the populated zones */ static void zero_zones_numa_counters(void) { struct zone *zone; for_each_populated_zone(zone) zero_zone_numa_counters(zone); } /* zero global numa counters */ static void zero_global_numa_counters(void) { int item; for (item = 0; item < NR_VM_NUMA_EVENT_ITEMS; item++) atomic_long_set(&vm_numa_event[item], 0); } static void invalid_numa_statistics(void) { zero_zones_numa_counters(); zero_global_numa_counters(); } static DEFINE_MUTEX(vm_numa_stat_lock); int sysctl_vm_numa_stat_handler(struct ctl_table *table, int write, void *buffer, size_t *length, loff_t *ppos) { int ret, oldval; mutex_lock(&vm_numa_stat_lock); if (write) oldval = sysctl_vm_numa_stat; ret = proc_dointvec_minmax(table, write, buffer, length, ppos); if (ret || !write) goto out; if (oldval == sysctl_vm_numa_stat) goto out; else if (sysctl_vm_numa_stat == ENABLE_NUMA_STAT) { static_branch_enable(&vm_numa_stat_key); pr_info("enable numa statistics\n"); } else { static_branch_disable(&vm_numa_stat_key); invalid_numa_statistics(); pr_info("disable numa statistics, and clear numa counters\n"); } out: mutex_unlock(&vm_numa_stat_lock); return ret; } #endif
This conditionally includes the NUMA-specific code based on whether the CONFIG_NUMA option is enabled during kernel compilation. Within this conditional block, the sysctl_vm_numa_stat_handler function provides a runtime configuration mechanism through the sysctl_vm_numa_stat variable. This function allows system administrators to enable or disable the collection of NUMA statistics at runtime. When the value of sysctl_vm_numa_stat changes, the function changes the vm_numa_stat_key to start or stop the statistics collection and clears the NUMA counters if disabled.
if (behavior == MADV_SOFT_OFFLINE) { pr_info("Soft offlining pfn %#lx at process virtual address %#lx\n", pfn, start); ret = soft_offline_page(pfn, MF_COUNT_INCREASED); }
This is algorithmic policy. If this particular madvise behavior is MADV_SOFT_OFFLINE, the code decides to performs soft offlining of a page by marking it as unavailable for future use without reclaiming it.
if (folio_test_large(folio)) { int err; if (folio_estimated_sharers(folio) != 1) break; if (!folio_trylock(folio)) break; folio_get(folio); arch_leave_lazy_mmu_mode(); pte_unmap_unlock(start_pte, ptl); start_pte = NULL; err = split_folio(folio); folio_unlock(folio); folio_put(folio); if (err) break; start_pte = pte = pte_offset_map_lock(mm, pmd, addr, &ptl); if (!start_pte) break; arch_enter_lazy_mmu_mode(); pte--; addr -= PAGE_SIZE; continue; }
This is algorithmic policy. This code handles the splitting of large folio pages. It checks if the folio can be safely split, attempts to split it into smaller folios, and then appropriately updates the relevant PTEs and MMU state.
if (pending != flushed) { arch_flush_tlb_batched_pending(mm);
This is an algorithmic policy. This code decides whether to perform a TLB flush based on whether there are pending flushes that haven't been completed.
if (!dst->anon_vma && src->anon_vma && anon_vma->num_children < 2 && anon_vma->num_active_vmas == 0) dst->anon_vma = anon_vma;
This is an algorithmic policy. This code checks if dst currently does not have an anonymous VMA and if src does. It checks that the anon VMA being considered has fewer than two children and no active VMAs. If all conditions are met, it reuses the existing anonymous VMA rather than allocating a new one.
if (should_proactive_compact_node(pgdat)) { unsigned int prev_score, score; prev_score = fragmentation_score_node(pgdat); proactive_compact_node(pgdat); score = fragmentation_score_node(pgdat); /* * Defer proactive compaction if the fragmentation * score did not go down i.e. no progress made. */ if (unlikely(score >= prev_score)) timeout = default_timeout << COMPACT_MAX_DEFER_SHIFT; }
This part of the code checks whether proactive compaction should be triggered using the should_proactive_compact_node(pgdat) predicate. If proactive compaction is necessary, it stores the node's fragmentation score (prev_score), performs proactive compaction (proactive_compact_node(pgdat)), and then checks the new fragmentation score (score). If the score does not decrease after compaction (indicating no progress), the system defers further proactive compaction by increasing the timeout (timeout = default_timeout << COMPACT_MAX_DEFER_SHIFT). This helps avoid repeated compaction attempts without progress.
if (err) { putback_movable_pages(&cc->migratepages); /* * migrate_pages() may return -ENOMEM when scanners meet * and we want compact_finished() to detect it */ if (err == -ENOMEM && !compact_scanners_met(cc)) { ret = COMPACT_CONTENDED; goto out; } /* * If an ASYNC or SYNC_LIGHT fails to migrate a page * within the pageblock_order-aligned block and * fast_find_migrateblock may be used then scan the * remainder of the pageblock. This will mark the * pageblock "skip" to avoid rescanning in the near * future. This will isolate more pages than necessary * for the request but avoid loops due to * fast_find_migrateblock revisiting blocks that were * recently partially scanned. */ if (!pageblock_aligned(cc->migrate_pfn) && !cc->ignore_skip_hint && !cc->finish_pageblock && (cc->mode < MIGRATE_SYNC)) { cc->finish_pageblock = true; /* * Draining pcplists does not help THP if * any page failed to migrate. Even after * drain, the pageblock will not be free. */ if (cc->order == COMPACTION_HPAGE_ORDER) last_migrated_pfn = 0; goto rescan; } }
This block of code handles errors during page migration by first resetting the state to prevent inconsistencies. If a migration error occurs, the kernel puts back the movable pages. If the error is due to memory shortage (-ENOMEM), the process checks if the migration and free page scanners have met. If not, compaction is terminated early with COMPACT_CONTENDED. For ASYNC or SYNC_LIGHT modes, if the migration fails within an unaligned pageblock, the kernel marks the block for skipping to avoid unnecessary rescanning. Thus, improving efficiency by isolating more pages than required and preventing revisits to partially scanned blocks. For transparent huge pages (THP), it ensures the failed pageblocks are not reused.