Reviewer #1 (Public review):
Summary:
In this paper, Manley and Vaziri investigate whole-brain neural activity underlying behavioural variability in zebrafish larvae. They combine whole brain (single cell level) calcium imaging during the presentation of visual stimuli, triggering either approach or avoidance, and carry out whole brain population analyses to identify whole brain population patterns responsible for behavioural variability. They show that similar visual inputs can trigger large variability in behavioural responses. Though visual neurons are also variable across trials, they demonstrate that this neural variability does not degrade population stimulus decodability. Instead, they find that the neural variability across trials is in orthogonal population dimensions to stimulus encoding and is correlated with motor output (e.g. tail vigor). They then show that behavioural variability across trials is largely captured by a brain-wide population state prior to the trial beginning, which biases choice - especially on ambiguous stimulus trials. This study suggests that parts of stimulus-driven behaviour can be captured by brain-wide population states that bias choice, independently of stimulus encoding.
Comments on revisions:
The authors have revised their manuscript and provided novel analyses and figures, as well as additions to the text based on our reviewer comments.
As stated in my first review, the strength of the paper principally resides in the whole brain cellular level imaging - using a novel fourier light field microscopy (Flfm) method - in a well-known but variable behaviour.
Many of the authors' answers have provided additional support for their interpretations of results, but the new analysis in Figure 3g - further exploring the orthogonality of e1 and wopt - puts into question the interpretation of a key result: that e1 and wopt are orthogonal in a non-arbitrary way. This needs to be addressed. I have made suggestions below to address this:
Reviewer 3 had correctly highlighted the issue that in high-dimensional data, there is an increasingly high chance of two vectors being orthogonal. The authors address this by shuffling the stimulus labels. They then state (and provide a new panel g in Fig. 3) that the shuffled distribution is wider than the actual distribution, and state that a wilcoxon rank-sum test shows this is significant. Given the centrality of this claim, I would like the authors to clarify what exactly is being done here, as it is not clear to me how this conclusion can be drawn from this analysis:
In lines 449:453 the authors state:<br /> 'While it is possible to observe shuffled vectors which are nearly orthogonal to e1, the shuffled distribution spans a significantly greater range of angles than the observed data (p<0.05, Wilcoxon rank- sum test), demonstrating that this orthogonality is not simply a consequence of analyzing multi-dimensional activity patterns. '<br /> I don't understand how the authors arrive at the p-value using a rank-sum test here. (a) What is the n in this test? Is n the number of shuffles? If so, this violates the assumptions of the test (as n must be the number of independent samples and not the arbitrary number of shuffles). (b) If the shuffling was done once for each animal and compared with actual data with a rank-sum test, how likely is that shuffling result to happen in 10000 shuffle comparisons?<br /> I am highlighting this, as it looks from Figure 3g that the shuffled distribution is substantially overlapping with the actual data (i.e., not outside of the 95 percentile of the shuffled distribution), which would suggest that the angle found between e1 and wept could happen by chance.
I would also suggest the authors instead test whether e1 is consistently aligned with itself when calculated on separate held out data-sets (for example by bootstrapping 50-50 splits of the data). If they can show that there is a close alignment between independently calculated e1's across separate data sets (and do the same for wopt), and then show e1 and wopt are orthogonal, then that supports their statement that e1 and wopt are orthogonal in a meaningful way. Given that e1 captures tail vigor variability (and Wopt appears to not) then I would think this could be the case. But the current answer the authors have given is not supporting their statement.