15 Matching Annotations
  1. Jan 2021
    1. Reviewer #1:

      The current study by Ohara et al. describes differences in the connectivity patterns between LVb to LVa. The study builds on the authors previous study (Ohara et al., 2018) where they showed the intrinsic connectivity of LVb neurons in the MEC and LEC. The focus of the current study is the difference the authors observed in the strengths of connectivity between LVb and LVa in the MEC and LEC. The authors suggest that the in MEC Vb neurons do not provide substantial direct input to LVa neurons. The manuscript emphasizes the functional importance of difference as the authors suggest that "...hippocampal -cortex output circuit is present only in LEC, suggesting that episodic systems consolidation predominantly uses LEC-derived information and not allocentric spatial information from MEC." The study uses a newly developed mouse line to investigate connectivity differences, this is a nice technical approach and the experimental data is of high quality. While the data is solid, the authors tend to over-interpret their findings from the functional point of view. While the observed difference is quite interesting, it is unclear what the impact is on information flow in the MEC and LEC and to which degree they differ functionally. The authors assume major differences and their work is framed based on these expected differences, but the manuscript does not provide data that would demonstrate functionally distinct features.

      Major Comments:

      1) Throughout the text the authors treat their findings as if it was 'all-or-none' i.e the LEC has a direct connection between LVb and LVa while the MEC does not. This does not seem to be the case based on their data, the data shows that connectivity in the MEC is less robust but it is definitely there. The difference seems to be quantitative and not qualitative.

      2) Due to this problem, the authors seem to be over-interpreting their data by suggesting that the information flow must be significantly different conceptually in the LEC and the MEC and this would have important implications for memory consolidation. It is impossible to draw these conclusions based on the data presented, as there are no experiments investigating the functional, network level consequences of these connectivity differences.

      3) The electrophysiology experiments provide information about the basic parameters of the investigated cells, but these lack a physiological context that would allow the authors to evaluate the consequences of these differences on information flow and/or processing in the MEC and the LEC.

      4) The study is using a novel transgenic mouse line to differentiate between LVb and LVa neurons, while this is definitely a strength of the study, this strategy allows the authors to visualize ~50% of LEC and ~30% MEC neurons. Since the authors aim to prove a negative (MEC does not have direct connection) the fact that ~70% of the neurons are not labelled could be problematic.

  2. Nov 2020
    1. Reviewer #1:

      The work by Pipitone et al. is a very carefully performed and technically sophisticated elucidation of the establishment of the thylakoid membrane system in Arabidopsis chloroplasts upon first illumination of cotyledons. Its charm is the three-dimensional resolution during a time course that allows it to follow the rapid changes occuring during the short time window in which the greening occurs. In addition, the authors included proteomics and lipidomics approaches complementing the morphological observations by sound molecular data. All together the study provides a very detailed catalogue of the processes that trigger chloroplast biogenesis that is highly useful for the community as it provides important numbers of size and development.


      Actually the work has been performed very carefully and there is not much to improve.

      The introduction could contain more references (e.g. lines 77, 83, 90, 93, 98,, 131, 132)

      SBF-SEM should be spelled out at first mentioning (line 146) and maybe a bit more background about the technology would be helpful for the reader to understand it.

      Line 244: The occurrence of starch granules is of course caused by the continuous illumination. It however may also have an impact on the final size of the plastid. It would be interesting to know whether chloroplasts at the end of a night phase are smaller than at the end of a light phase. This is not mandatory for the current manuscript but an interesting question to follow in future and maybe to be discussed.

      Line 251: The surface area.... please define what is meant since membranes have two sides.

      Lines 256-261: There is another study done in cell culture that has a similar design (Dubreuil et al ), are the two studies compatible with each other in their conclusion and if not, what are the differences?

      Lines 549-551: This sentence is not perfectly clear to me. Maybe the authors can explain this a bit more in detail using examples.

      Lines 564-573: I think it is worth noting that the interactions between PSII complexes located in neighbouring thylakoid membranes trigger the stacking of the grana. It is therefore tempting to speculate that stroma lamellae are established first and that these membranes are then stacked after PSII complexes are inserted into the membrane because they provide the adhesion points between them.

    1. Reviewer #1:

      The study by Lyengar et al describes age- and temperature-dependent changes in the neurophysiology of the giant fiber (GF) system in adult wild type and superoxide dismutase 1 mutant flies (SOD[1]). While the main GF circuit and downstream circuits exhibit little change when flies are reared at 25C, GF inputs and other circuits driving motoneuron activities show age-dependent alterations consistent with earlier studies. Rearing flies at 29C temperatures had no additional effects except that age-dependent progression of defects were accelerated, as it was expected from previous studies. In SOD[1] mutants, which are short lived, changes in the neurophysiology of the GF system were different from those induced by high temperature.

      Overall this technically challenging, and well executed study provides a nice description of the effects of aging, high activity (induced by higher temperature), and loss of SOD function on the neurophysiology of the GF system. However, most of the described effects have been observed in other systems and are thus not entirely novel. Moreover, the study does not provide any insight into the mechanisms underlying the age-dependent alterations of the examined neurons. Thus, the overall significance of the described findings is limited.

    1. Reviewer #1:

      This manuscript compares the effects of a novel versus a classical augmented acoustic environment protocole on partial improvement of congenital hearing loss. The new protocol is based on the idea that temporal structure, and in particular auditory gaps in the augmented environment should improve perception of temporal features in sounds, in particular of auditory gaps.

      Technically sound, the study describes how the encoding of gap in the auditory midbrain (inferior colliculus, IC) of a mouse hearing loss model is affected by the novel temporally enriched paradigm with respect to control mice and to the classical paradigm. The study clearly confirms that augmented acoustic environments improve spectral tuning, and detection of sound features with respect to control animals in IC. IC neurons also appear to show a more robust increase of sensitivity to amplitude changes (onsets and offsets) when the animals have gone through the temporal augmented sound environment, both in the presence and in the absence of background noise, as compared to the classical paradigm, at least if one considers the magnitude of the effects with respect to control. However, only few measures show a significant difference when directly testing between the classical and the temporally enriched paradigm. Thus, there is an overall impact of the temporal paradigm which is worth emphasizing as a small but likely useful increment of the auditory enrichment approach for improving hearing loss. This is a definitely interesting, even if somewhat expected result which could drive further studies on clinical practice. It seems however too specialized for broader readership. A few things in the presentation of the results could be improved, and behavioral data could eventually reinforce the message although it is not mandatory to make these results interesting :

      1) A figure of the auditory enrichment setup would be nice, to better understand how this works. Are mice constantly submitted to the sounds? Are control mice in a more silent environment than normally housed mice?

      2) The lack of behavioral data opens the question whether IC changes have actually an impact on perception. Although it is likely, it would be interesting to measure the magnitude of this impact.

      3) What makes the study interesting is the tendential bias in favor of the temporal paradigm with respect to the classical one. This is however rarely significant in one to one comparisons for each sensitivity measure. To reinforce their point the authors could consider a multivariate statistical analysis (e.g. two way ANOVA) to show that over all their measures there is a significant improvement with temporal against classical.

    1. Reviewer #1:

      This report makes a logical connection between depressive-like behaviors induced in mice following LPS-injection to mimic bacterial infection and the down regulation of phospholipid transporting enzyme, ATP8A2, in the prefrontal cortex. The intermediary is IFN-gamma. The work is quite convincing that LPS down regulates ATP8A2 by upregulating IFN-gamma and that this has some limited effects on behavior. However, the impact of the findings is limited by several factors.

      1) The use of FST and TST as measures of depression is increasingly falling out of favor as there is no face validity to humans. It is understood that these tests have been long in use and were in the past considered the best measures of "depressive-like" behaviors in mice but the field has moved on to much more relevant constructs such as social defeat, anhedonia etc. As it stands the behavioral analysis here is limited and the effects are modest at best.

      2) The use of LPS as a model to induce depression also has limitations. The injection paradigm used is likely to have caused massive inflammation, as evidenced by the increase in cytokines, but what this is modeling is unclear and how the impact would be specific to depression later in life is equally unclear. Indeed, the references the authors cite for the LPS regime they use offer completely different mechanisms and impacts of the inflammation. This is not to say the current findings aren't important, they are, but rather this pathway may be one among many that is invoked following massive inflammation during early development which then has many non-specific effects.

      3) There is no functional connection between down regulation of ATP8A2 developmentally and adult neural activity. Clearly a membrane phospholipid transporting enzyme is important, but exactly how it is important here, meaning what enduring impacts there are on neuronal function, is unknown.

      4) The experiments were designed to test the relationship between IFN-gamma and ATP8A2 but then conclude that the behavioral effects are mediated by this connection. There could be many other effects of IFN-gamma that are not considered here but would be nonetheless blocked by the neutralizing antibody approach used. Thus the main conclusions of the manuscript are not supported in terms of the role of ATP8A2 in LPS-induced depression.

    1. Reviewer #1:

      Mackay et al. present a study on the phenotype of neurons from YAC128 mice, an HD model expressing mHTT with 128 CAG repeats. They show (i) that cultured cortical YAC128 neurons exhibit increased mEPSC rates transiently during development in vitro (i.e. between DIV14-18 but not at DIV7 or DIV21), (ii) that calcium release from ER by low-dose ryanodine increases mEPSC rates only in WT but not in YAC128 cells, and (iii) that blocking SERCA to deplete ER calcium stores reduces mEPSC rates in YAC128 neurons as compared to WT controls. These data are interpreted to indicate that a presynaptic ER calcium leak increases mEPSC rates in YAC128 neurons. Using rSyph-GCaMP imaging, the authors then show (i) an increase in longer-lasting AP-independent calcium signals in synaptic boutons of YAC128 neurons as compared to WT, (ii) less profound increases in calcium signals upon ionomycin-mediated equilibration to 2 mM extracellular calcium, (iii) less profound increases in calcium signals upon caffeine treatment in YAC128 boutons, and (iv) less AP-related calcium events in YAC128 boutons. A final dataset shows that evoked synaptic transmission in YAC128 striatum as assessed by iGluSnFR imaging is inhibited by ryanodine in WT but not in YAC128 mice. The authors conclude that the overexpression of mHTT with 128 CAG repeats in the YAC128 mutant causes aberrant calcium handling (i.e. calcium leak/release from the ER), which leads to increased cytosolic calcium concentrations, increased AP-independent release events, but reduced AP-evoked glutamate release.


      1) I think the authors show convincingly that (presynaptic) calcium handling is perturbed in YAC128 cortical presynaptic boutons. What is conceptually unclear to me at the outset is whether this specific phenomenon is related to HD pathology. The phenomenon is transient during the development of cortical neurons in culture and gone at DIV21. In contrast, the first subtle behavioural defects of YAC128 mice arise at about 3 months of age, overt behavioural defects at 6 months of age, and striatal and cortical degeneration still later.

      2) The issue discussed above (1) could have been addressed in part with the slice experiments, which were conducted with tissue from 2-3 months old mice, but the corresponding data are too cursory at this point. They indicate a small defect in evoked glutamate release in the YAC128 model, but it is unclear whether mEPSC rates are altered. It seems important to test this as the increased mEPSC rates are proposed to be at the basis of the phenotype described in the present study. Indeed, the authors ultimately conclude that the YAC128 mutation causes increased mEPSC rates at the expense of evoked glutamate release. This is generally unlikely to be true as the mEPSC rates in question are very likely overcompensated by the vesicle priming rate.

      3) The phenomenon of altered calcium handling in YAC128 neurons is shown convincingly. However, this finding is not unexpected given that previous studies indicated such increased calcium release from endoplasmic reticulum in HD models in other subcellular compartments, and it remains unclear how this defect is caused by the mutant HTT.

      4) As already outlined above (2) it remains unexplained how the calcium handling defects increase mEPSC rates but decrease evoked transmission. The corresponding part of the discussion reflects this uncertainty. This is aggravated by the fact that several of the drugs used have complex dose-dependent effects that cannot easily be reduced to specific effects on calcium handling by the ER. For instance, it is unclear whether caffeine effects on adenosine receptors or PDEs have to be taken into consideration. In general, the sole reliance on partly 'multispecific' pharmacological tools is a bit worrisome.

      5) There are several other aspects of the paper that are not immediately plausible. For instance, I have difficulties to understand why a calcium transient minutes before ionomycin treatment would affect the calcium signal triggered by ionomycin in the presence of 2 mM extracellular calcium (Figure 4); after all, the example trace shows that the calcium levels return to baseline within seconds. And more generally, in this context: Can differences in calcium buffers and the like be excluded? A direct assessment of absolute cytosolic calcium concentrations would be the ultimate solution.

      Overall, the present paper describes a phenomenon in presynaptic boutons of an HD model, key aspects of which (e.g. increased ER calcium handling defects) have been described in other subcellular compartments of HD models. The connection of this phenomenon to HD is unclear as the developmental timelines of the appearance and disappearance of the cellular phenotype and the disease progression do not match. The opposite phenotypes caused at the level of presynaptic boutons on AP-independent and AP-dependent release remain disconnected. The mechanism by which mutant HTT causes these defects remains unexplored. The pharmacological tools used do not always allow unequivocal conclusions regarding the targets affected. I think some more work is needed to generate a clear picture of what exactly happens presynaptically in YAC128 neurons, and to show how this might relate to HD.

    1. Reviewer #1:

      Deng et al. studied the mechanisms underlying the wide propofol effect-site concentration range associated with loss of responsiveness. Data was acquired from two centers (MRI, Canada; Auditory, Ireland). This is a well conducted study. The results could also explain why older patients (with presumably smaller gray matter volume) are more sensitive to propofol. My major concerns relate to precision in language.

      1) The authors studied mechanisms underlying why patients lose consciousness at a wide range of propofol effect-site concentration. This behavioral phenomenon is known and well described (Iwakiri H, Nishihara N, Nagata O, Matsukawa T, Ozaki M, Sessler DI. Individual effect-site concentrations of propofol are similar at loss of consciousness and at awakening. Anesth Analg. 2005;100:107-10). I would suggest that the. authors position their paper as such. They did not study general anesthesia per se, and the allusions to awareness under anesthesia may not be relevant.

      2) Per comment 1 above. Please reword the intro and discussion section i.e., " Anaesthesia has been used for over 150 years to reversibly abolish consciousness in clinical medicine, but its effect can vary substantially between individuals." What type of anesthesia are you referring to? Anesthetic vapors? Please provide a reference for this statement or make it propofol specific. Awareness under general anesthesia is related to numerous factors, many of which are iatrogenic as detailed in the NAP 5 study "The incidence of awareness rose from 1 out of 135,000 general anaesthetics to 1 out of 8,200 general anaesthetics when neuromuscular blockers were used" (https://pubmed.ncbi.nlm.nih.gov/25204697/). Further, it is unclear when dreaming occurs (during induction which is reasonable to expect/during emergence which is also reasonable to expect versus during the anesthesia). My suggestion is to qualify your statements by stating that this should be further studied in the context of possible genetic predisposition to awareness (Increased risk of intraoperative awareness in patients with a history of awareness. Anesthesiology 2013;119:1275-83).

      3) The term "moderate anaesthesia" is confusing to me, and would be to most clinicians. Please cite the description of what comprises moderate anesthesia. My interpretation is that the study was about sedation. Did you mean moderate sedation? (https://www.asahq.org/standards-and-guidelines/continuum-of-depth-of-sedation-definition-of-general-anesthesia-and-levels-of-sedationanalgesia).

      4) "the antagonistic relationship between the DMN and the DAN/ECN #and# was reduced during moderate anaesthesia, with a stronger and significant result in the narrative condition relative to the resting state." Anticorrelation?

      5) The suggestion that fMRI can be used to improve the accuracy of awareness monitoring is, in my opinion, not necessary and a stretch.

    1. Reviewer #1:

      This article proposes that the assembly of the Sars-CoV-2 capsid is mediated by liquid-liquid phase separation of the N protein and RNA. The strength of the manuscript is a series of in vitro experiments showing that N protein can undergo liquid-liquid phase separation (LLPS) in a manner enhanced by RNA. The authors also identify nilotinib as a compound that alters the morphology of assemblies consisting of RNA and the N protein. The primary weakness of the manuscript is that there is little data connecting the in vitro observations to intracellular events, or viral assembly. Taken together, I find the experiments interesting but, as detailed below, premature.

      Major comments:

      1) A key issue with any in vitro assembly process such as LLPS is a demonstration that same process occurs in the cell. This is an issue since many molecules can undergo LLPS in vitro in a manner unrelated to their biological function. In this work, the authors show that the N protein can undergo LLPS in vitro in a manner a) stimulated by RNA, b) enhanced by the R2 domain, and c) changed in morphology by nilotinib.

      Their argument that this LLPS is relevant to the viral life cycle rests on: a) the observation that over-expressed N protein forms foci in the cytosol, and b) the number of these foci (but not necessarily their morphology as seen in vitro) is somewhat reduced by nilotinib. In my opinion, this is not a very convincing argument for two main reasons.

      First, it is unclear why the N protein is forming foci in cells. Specifically:

      a) Is it being recruited to P-bodies, or some other existing subcellular assembly? (Which could be examined by staining with other markers).

      b) Is it forming a new assembly with RNA as they have proposed? (Which could be addressed by staining for either specific or generic RNAs, or purifying these assemblies and determining if they contain RNA)

      Second, it is unclear that the foci seen in cells are related to the LLPS they observe in vitro or relevant to the viral life cycle. Specifically:

      c) Is the assembly related to the LLPS they have observed in vitro beyond a poorly understood alteration with nilotinib ? (Which could be addressed by examining if the deletions they observe affect LLPS in vitro also affect the formation of N protein foci in cells).

      d) Is the nature of this assembly relevant to the viral life cycle? (Given the difficulty of working with COVID, this is hard. My suggestion here is at a minimum to discuss the issue, and ideally do an experiment with a related coronavirus to test their hypothesis). Frankly, the idea that coronavirus would trigger a LLPS of multiple viral RNAs would seem to be inhibitory to efficient packaging of individual virions. A discussion of how the virus would benefit from such a mechanism, as opposed to a cooperative coating of a viral genome initiated at a high affinity N protein binding site would be important to put the work in context.

      2) The manuscript would be improved by examining the presence of RNA in each LLPS, and the ability of RNA to undergo self-assembly under the conditions examined in the absence of the N protein. As it stands, in some cases, the authors could be studying RNA based self-assembly, that then recruits the N protein to the RNA LLPS by RNA binding (see Van Treeck et al., 2018, PNAS for specific example of this phenomenon). This may be particularly likely for some of the longer viral RNAs that can form more stable base-pairs and thereby promote more "tangled" assemblies (e.g. Tauber et al., 2020, Cell).

      3) I found the CLMS to not fit well in this manuscript for two reasons:

      a) As I understood the methods, the CLMS experiment is looking at cross linking in high and low salt, with some LLPS occurring under low salt. However, since the cross linking was not limited to the dense phase of the low salt condition, a significant fraction (perhaps majority?) of the N proteins will not be in the dense phase. Because of this, the cross linking is essentially mapping interactions that change between high and low salt. If the authors really want to do this experiment, they should separate the phases and examine the crosslinks forming in the dense and dilute phases under the same salt conditions.

      b) A second issue with this cross-linking experiment is that the regions that dominate the changes in cross linking are not ones that appear to be important in driving LLPS in vitro based on their deletion analysis. If the authors want to include this data, it should be related to the deletion experiments and connected to the work in a manner to make it meaningful.

      4) The work would be improved by comparing how alterations that impact LLPS affect specific biochemical interactions of the relevant molecules. In these experiments, the authors are examining assemblies that form through N-N, N-RNA, RNA-RNA interactions. In each case, biochemical assays could be used to examine which of these interactions are altered by deletions or compounds. By understanding the underlying alterations in molecular interactions, a greater understanding of the mechanism of the observed LLPS, and its relevance to the viral life cycle could be revealed.

    1. Reviewer #1:

      This study is based on previous work that exposure to valproic acid (VPA), which is used to model autism spectrum disorders, produces excess local synaptic connectivity, increased seizure susceptibility, abnormal social behavior, and increased MMP-9 mRNA expression in Xenopus tadpoles. VPA is an interesting compound that is also used as an antimanic and mood stabilizing agent in the treatment of bipolar disorder, although the therapeutic targets of VPA for its treatment of mania or as a model of neurodevelopmental disorders have remained elusive. The authors validate that VPA exposed tadpoles have increased MMP9 mRNA expression and then test whether the increased levels of MMP9 mediate the effects of VPA in the tadpole model. The authors report that overexpression of MMP-9 increases spontaneous synaptic activity and network connectivity, whereas pharmacological and genetic inhibition with antisense oligos rescues the VPA induced effects, and then tie the findings to experience dependent synaptic reorganization.

      1) What is the exact nature of "increased connectivity"? Is there an increase in synapse numbers or solely an increase in dendritic complexity coupled with a functional plasticity? The authors should document properties of mEPSCs and mIPSCs recording in TTX to isolate synaptic properties. Coupling this "mini" analysis to quantification of synapse numbers will address whether the changes are solely due to structural plasticity or also due to a functional potentiation of transmission. These experiments should at least be conducted in MMP-9 overexpression, VPA treatment and VPA treatment+MMP-9 loss-of-function cases to validate the basic premise that there is an increased connectivity.

      2) It is unclear why the authors focused on MMP-9 compared to other genes dysregulated by VPA. This point should be further discussed.

      3) How does VPA alter MMP-9 levels? Is this through an HDAC dependent mechanism? Granted VPA has been proposed to work through a variety of mechanisms including HDAC inhibition.

      4) Does SB-3CT rescue the expression levels of MMP-9?

      5) How is increased MMP-9 produces the synaptic and behavioral effects? What is the downstream target (specific receptor?) that would produce the broad changes in synaptic and behavioral phenotypes? Or is this a rather non-specific effect of extracellular matrix? Based on years of data on MMP-9 function its impact on "structural plasticity" in general terms is not surprising but further mechanistic details and specific targets would help move this field forward.

    1. Reviewer #1:

      This manuscript has novelty in it’s approach. The authors use an animal model to abolish the circadian rhythm in mice to study the impact on susceptibility to challenge with LPS. The experimental approach they use involves both wild-type mice subject to sudden stop of the light-dark (LD) cycle and mice knocked-out for the Clock system (KO). I have some points of concern:

      • The investigators show that mice shift from LD to DD become more lethal to LPS. If this is due to abolishment of the circadian rhythm, similar lethality should appear with the challenge of the KO mice. The opposite was found. Please explain.

      • LPS is acting through TLR4 binding. Can the author provide evidence that TLR4 expression is down-regulated in transition from LD to DD? Does the same apply for the expression of SOCS3?

      • TLR4 is a receptor for alarmins with IL-1alpha being one of them. Can the authors comment, based on their IL-1alpha findings, if this may be part of the mechanism?

    1. Reviewer #1:

      This manuscript uses simultaneous fMRI-EEG to understand the haemodynamic correlates of electrophysiological markers of brain network dynamics. The approach is both interesting and innovative. Many different analyses are conducted, but the manuscript is in general quite hard to follow. There are grammatical errors throughout, sentences/paragraphs are long and dense, and they often use vague/imprecise language or rely on (often) undefined jargon. For example, sentences such as the following example are very difficult to decipher and are found throughout the manuscript: "if replicated, an association between high positive BOLD responsiveness and a DAN electrophysiological state, characterized by low amplitude (i.e., desynchronized) activity deviating from energetically optimal spontaneous patterns, would be consistent with prior evidence that the DMN and DAN represent alternate regimes of intrinsic brain function". As a result, the reader has to work very hard to follow what has been done and to understand the key messages of the paper.

      Much is made of a potential power-law scaling of lifetime/interval times as being indicative of critical dynamics. A power-law distribution does not guarantee criticality, and could arise through other properties. Moreover, to accurately determine whether the proposed power-law is indicative of a scale-free system, the empirical property must be assessed over several orders of magnitude. It appears that only the 25-250 ms range was considered here.

      The KS statistic is used to quantify the distance between the empirical and power-law distributions, which is then used as a marker of the degree of criticality. It is unclear that this metric is appropriate, given that transitions in and out of criticality can be highly non-linear. Moreover, the physiological significance of having some networks in a critical state while others are not is unclear. Each network is part of a broader system (i.e., the brain). How should one interpret apparent gradations of criticality in different parts of the system?

      The sample size is small. I appreciate the complexity of the experimental paradigm, but the correlations do not appear to be robust. The scatterplots mask this to some extent by overlaying results from different brain regions, but close inspection suggests that the correlations in Fig 6 are driven by 2-3 observations with negative BOLD responses, the correlations in Fig 7A-B are driven by two subjects with positive WMSA volume, and Fig 7B is driven by 3 or so subjects with negative power-law fit values (indeed, x~0 in this plot is associated with a wide range of recall scores). Some correction for multiple comparisons is also required given the number of tests performed.

      Figure 1 - panel labels would make it much easier to understand what is shown in this figure relative to the caption.

      Figure 2- the aDMN does not look like the DMN at all. It is just the frontal lobe. Similarly, the putative DAN is not the DAN, but the lateral and medial parietal cortex, and cuneus.

      P6, Line 11 - please define "simulation testing"

    1. Reviewer #1:

      Using two behavioral experiments, the authors partially replicate known effects that rotated faces decrease the benefit of visual speech on auditory speech processing.

      As reported by the authors, Experiment 1 suffers from a design flaw considering that a temporal drift occurred in the course of the experiment. This clearly invalidates the reliability of the results and this experiment should be properly calibrated and redone. There is otherwise well-known literature on the topic.

      Experiment 2 should be discussed in the context of divided attention tasks previously reported by researchers so as to better emphasize how and whether this is a novel observation.


      -The question being addressed is narrowly and ill-construed: numerous authoritative statements in the introduction should reference existing work. For instance, seminal models of Bayesian perception (audiovisual speech processing especially) should be attributed to Dominic Massaro. Such statements as "studies fail to distinguish between binding and late integration" are surprising considering that the fields of multisensory integration and audiovisual speech processing have essentially and traditionally consisted in discussing these specific issues. To name a few researchers in the audiovisual speech domain: the work of Ruth Campbell, Ken Grant, and Jean-Luc Schwartz have largely contributed to refine debates on the implication of attentional resources to audiovisual speech processing using behavioral, neuropsychology, and neuroimaging methods. In light of the additional statements of the kind "The importance of temporal coherence for binding has not previously been established for speech", I would highly recommend the authors to do a thorough literature search of their topic (below some possible references as a start).

      -What the authors understand to be "linguistic cues" should be better defined. For instance, the inverted face experiment aimed at dissociating whether visemic processing depends on face recognition (i.e. on holistic processing) or whether it depends on featural processing (and it does constitute a test, as suggested by the authors, of whether viseme recognition is a linguistic process per se).

      Some references:

      -Alsius, A., Möttönen, R., Sams, M. E., Soto-Faraco, S., & Tiippana, K. (2014). Effect of attentional load on audiovisual speech perception: evidence from ERPs. Frontiers in psychology, 5, 727.

      -Chandrasekaran, C., Trubanova, A., Stillittano, S., Caplier, A., & Ghazanfar, A. A. (2009). The natural statistics of audiovisual speech. PLoS Comput Biol, 5(7), e1000436.

      -Jordan, T. R., & Bevan, K. (1997). Seeing and hearing rotated faces: Influences of facial orientation on visual and audiovisual speech recognition. Journal of Experimental Psychology: Human Perception and Performance, 23(2), 388.

      -Grant, K. W., & Seitz, P. F. (2000). The use of visible speech cues for improving auditory detection of spoken sentences. The Journal of the Acoustical Society of America, 108(3), 1197-1208.

      -Grant, K. W., Van Wassenhove, V., & Poeppel, D. (2004). Detection of auditory (cross-spectral) and auditory-visual (cross-modal) synchrony. Speech Communication, 44(1-4), 43-53.

      -Schwartz, J. L., Berthommier, F., & Savariaux, C. (2002). Audio-visual scene analysis: evidence for a" very-early" integration process in audio-visual speech perception. In Seventh International Conference on Spoken Language Processing.

      -Schwartz, J. L., Berthommier, F., & Savariaux, C. (2004). Seeing to hear better: evidence for early audio-visual interactions in speech identification. Cognition, 93(2), B69-B78.

      -Tiippana, Kaisa, T. S. Andersen, and Mikko Sams. (2004) "Visual attention modulates audiovisual speech perception." European Journal of Cognitive Psychology 16.3: 457-472.

      -van Wassenhove, V. (2013). Speech through ears and eyes: interfacing the senses with the supramodal brain. Frontiers in psychology, 4, 388.

      -Van Wassenhove, V., Grant, K. W., & Poeppel, D. (2007). Temporal window of integration in auditory-visual speech perception. Neuropsychologia, 45(3), 598-607.

    1. Reviewer #1:

      This work claims to show that learning of word associations during sleep can impair learning of similar material during wakefulness. The effect of sleep on learning depended on whether slow-wave sleep peaks were present during the presentation of that material during sleep. This is an interesting finding, but I have a lot of questions about the methods that temper my enthusiasm.

      1) The proposed mechanism doesn't make sense to me: "synaptic down-scaling of hippocampal and neocortical language-related neurons, which were then too saturated for further potentiation required for the wake-relearning of the same vocabulary". Also lines 105-122. What is 'synaptic down-scaling'? what are 'language related neurons'? ' How were they 'saturated'? What is 'deficient synaptic renormalization'? How can the authors be sure that there are 'neurons that generated the sleep- and ensuing wake-learning of ... semantic associations'? How can inferences about neuronal mechanisms (ie mechanisms within neurons) be drawn from what is a behavioural study?

      2) On line 54 the authors say "Here, we present additional data from a subset of participants of our previous study in whom we investigated how sleep-formed memories interact with wake-learning." It isn't clear what criteria were used to choose this 'subset of participants'. Were they chosen randomly? Why were only a subset chosen, anyway?

      3) The authors do not appear to have checked whether their nappers had explicit memory of the word pairs that had been presented. Why was this not checked, and couldn't explicit memory explain the implicit memory traces described in lines 66-70 (guessing would be above chance if the participants actually remembered the associations).

    1. Reviewer #1:

      In the present manuscript, Evans and Burgess present a computational model of the entorhinal-hippocampal network that enables self-localization by learning the correspondence between stimulus position in the environment and internal metric system generated by path integration. Their model is composed of two separate modules, observation and transition, which inform about the relationship between environmental features and the internal metric system, and update the internal metric system between two consecutive positions, respectively. The observation module would correspond to projection from hippocampal place cells (PCs) to entorhinal grid cells (GCs), while the transition module would just update the GCs based on animal's movement. The authors suggest that the system can achieve fast and reliable learning by combining online learning (during exploration) and offline learning (when the animal stops or rests). While online learning only updates the observation model, offline learning could update both modules. The authors then test their model on several environmental manipulations. Finally, they discuss how offline learning could correspond to spontaneous replay in the entorhinal-hippocampal network. While the work will certainly be of great interest to the community, the authors should improve the presentation of their manuscript, and make sure they clearly define the key concepts of their study.

      Online learning is clearly explained in the manuscript (e.g. l.101). Both environment structure (PC-PC connections) and the observation models (PC->GC synapses) are learned online, and this leads to stable grid cells. Then, the authors suggest that prediction error between the observation and transition models triggers offline inference that can update both models simultaneously. However, it is hard to figure out what offline learning is exactly. The section "Offline inference: The hippocampus as a probabilistic graph" is quite impossible to follow. Before explicitly defining offline learning the authors introduce a spring model of mutual connection between feature locations, but it is not clearly explained if this network is optimized online or offline.

      The end of this section is particularly difficult to follow (line 180): "In this context, learning the PC-GC weights (modifying the observation model) during online localization corresponds to forming spatial priors over feature locations which anchor the structure, which would otherwise be translation or rotation invariant (since measurements are relative), learned during offline inference to constant locations on the grid-map.".

      What really triggers offline inference is only explained much further in the manuscript, l. 366. Interestingly, this section refers to Fig. 1G for the first time, and should naturally be moved at the beginning of the manuscript (where Fig.1 is described)

      Along the same lines, the role of offline learning should be made much more explicit in Fig. 2.

      The frequent references to the method section too often break the flow of paper and make it difficult to follow. The authors should start their manuscript with a clear and simple definition of the core idea and concepts, almost in lay terms and only introducing a few annotations, using Fig. 1 (perhaps with some modification and focusing especially on panels A and F) as a visual support, and to move mathematical equations such as Eq. 3 to the supplementary information.

      The authors have tested their model on various manipulations that have been previously carried out in freely moving animals, such as change in visual gain and in environmental geometry. These sections are interesting but, again, would be much clearer if presented after a clear explanation of online and offline learning procedures, not in between.

      Finally, the authors discuss the relationship between offline inference and neuronal replay, as observed experimentally in vivo (Figs 6&7). This is interesting but would perhaps benefit from some graphical explanation. It is not immediately obvious to understand the fundamental difference between message passing (Fig. 6A) and simple synaptic propagation of activity among connected PC in CA3. Fig. 7 is actually a nice illustration of the phenomenon and should perhaps be presented before Fig. 6.

    1. Reviewer #1:

      The authors present a workflow based on targeted Nanopore DNA sequencing, in which they amplify and sequence nearly full-length 16S rRNA genes, to analyze surface water samples from the Cam river in Cambridge. They first identify a taxonomic classification tool, out of twelve studied, that performs best with their data. They detect a core microbiome and temporal gradients in their samples and analyze the presence of potential pathogens, obtaining species level resolution and sewage signals. The manuscript is well written and contains sufficient information for others to carry out a similar analysis with a strategy that the authors claim will be more accessible to users around the world, and particularly useful for freshwater surveillance and tracing of potential pathogens.

      The work is sufficiently well-documented and timely in its use of nanopore sequencing to profile environmental microbial communities. However, given that the authors claim to provide a simple, fast and optimized workflow it would be good to mention how this workflow differs or provides faster and better analysis than previous work using amplicon sequencing with a MinION sequencer.

      Many of the June samples failed to provide sufficient sequence information. Could the authors comment on why these samples failed? While some samples did indeed have low yields, this was not the case for all (supp table 2 and supp figure 5) and it could be interesting to know if they think additional water parameters or extraction conditions could have affected yields and subsequent sequencing depth.

      One of the advantages of nanopore sequencing is that you can obtain species-level information. It would therefore be helpful if the authors could include information on how many of their sequenced 16S amplicons provided species-level identification.

      While the overall analysis of microbial communities is well done, it is not entirely clear how the authors define their core microbiome. Are they reporting mainly the most abundant taxa (dominant core microbiome), and would this change if you look at a taxonomic rank below the family level? How does the core compare, for example, with other studies of this same river?