Individual differences in fear memory expression engage distinct functional brain networks

Reviewer #1 (Public review):

Summary:

This work provides a comprehensive analysis of how adult zebrafish show fear responses to conspecific alarm substances (CAS) and retain their associative memory. It shows that freezing is a more reliable measure of fear response and memory compared to evasive swimming, and that the reactivity and the type of responses depend on the zebrafish strain. It further suggests neuronal substrates of different fear responses based on c-Fos mapping.

Strengths:

The behavioral part is the most comprehensive and detailed yet in the zebrafish field, providing strong support for the authors' claim. The flow from Figure 1 to Figure 4 is very smooth. They provide extremely detailed, yet complementary and necessary, analyses of how different categories of behavior emerge over time during the CAS exposure and memory retrieval. I'm convinced that neuro researchers who study fear/stress responses will always refer to this paper to plan and interpret their future experiments.

Comments on revised version:

The authors successfully addressed my comments, including the addition of Figure S6-2, which gives us some intuition into the relationships between c-Fos levels in individual areas and the behavioral outputs.

Reviewer #2 (Public review):

In this study, Fontana et al. develop a paradigm for associative conditioning by pairing exposure to alarm substance with a novel tank. Exposure to conspecific alarm substance (CAS) in the novel tank triggers freezing and what they characterize as evasive swimming behaviour, which are subsequently seen in a re-exposure to the novel tank without the CAS present. Importantly, these states are identified via automated processes including postural tracking and a random forest classification process, which could be very useful tools for subsequent studies.

In their experiments they focus on the differences in behaviour among strains of zebrafish (both males and females), and among individual zebrafish. For males and females of different strains they find some differences, though the clearest message seems to be that the most robust measure of the behaviour in response to both the CAS and in the memory trials is the freezing behaviour, while evasive behaviour is more variable and not always seen. This may relate to their observation of significant "evasiveness" in vehicle control experiments (discussed further below).

Moving on to individual variation from within this multi-strain male/female dataset, they first examine transition matrices between states, and find this is not dramatically altered by stimulus exposure. They then use clustering to identify 4 different "classes" of zebrafish that differ in their expression (or not) of two types of behaviour: freezing and/or evasive behaviour. They show that over the three exposure epochs of the experiment this classification is somewhat stable in an individual fish, though many fish change their behaviour -- e.g. evading + freezing -> only freezing.

In the final set of experiments they move beyond behavioural analyses and perform whole-brain cFos mapping of these individual zebrafish, and perform analyses aimed at identifying correlations between individual behavioural expression and the number of cFos positive cells in different brain regions. Using partial least squares analysis they find areas associated with two types of behavioural contrasts, which differ in their weighting of different behavioural expression during the Memory trials. Covariation and network structure analysis within different classes of fish also find some differences in covariation among brain areas, providing hypotheses as to underlying network effects that may govern the expression of freezing and/or evasive behavior in the memory trial phases.

Overall, I find this to be an interesting study that employs state of the art methods of behavioural analyses and whole-brain cFos analyses. The revision has clarified the take-home message considerably: the abstract is now more careful about which behavioural groups are memory-associated, and the causal language in the conclusions has been appropriately softened. Two of my three original main concerns have been addressed. The first is not and having looked at the data again I can now be more specific about what concerns me.

Comments on revised version.

(1) My first concern related to the claim that fear memory behaviour falls into four distinct groups, and specifically to the role of evasiveness in defining them. The authors give three reasons for retaining it, but I remain unconvinced.

The first is that variable evasion in response to alarm substance is a long-standing observation (von Frisch; Suboski et al.), and that dissecting this individual variation is the purpose of the paper. I agree with the motivation, and it is a good reason to measure evasion. But it does not establish that evasion on memory day reflects fear memory, and memory day is the only day used for the clustering and neural activity mapping. The manuscript's own results point the other way: relative to pre-exposure, no strain or sex increased evasion on memory day, and relative to vehicle only female TUs did. The temporal profiles show evasion on memory day to be largely similar between vehicle and CAS-treated fish. Historical observations of variable evasion during CAS exposure do not carry over to the memory phase.

The second is that the clustering itself reveals two kinds of freezing fish - one freezing between bouts of normal swimming, the other between bouts of evasion - demonstrating that a subset of fish increase evasion. In absolute terms, this does not match the data. In Figure 4B, evading freezers are below the population mean for absolute evasion, as are freezers. The text describes evading freezers as "high in freezing and evasive behaviors," and I do not think Figure 4B supports this.

What actually separates the two freezing groups is the third measure, evasion as a percentage of active time. And this is where I have difficulty, because that measure is not an independent behavioural readout. The classifier assigns every window to normal, evasive or freezing, and active time is simply non-freezing time, so evasion-as-percent-of-active is fully determined once the other two are known.

This matters for the clustering specifically. Distance-based methods weight each input dimension equally, so a variable that carries no information beyond the other two nonetheless contributes a full third of the distance between any two fish - and it contributes it in a way that counts freezing twice, once directly and once through the denominator of the derived measure. The space is nonetheless described as three-dimensional throughout, including in the Methods and the Figure 4 legend, when there are only two independent behaviours in it.

The consequences fall hardest on exactly the animals at issue. Both freezing groups sit at 65-70% freezing, so there is very little active time to divide by, and small absolute differences in evasion - together with any noise in estimating them from a couple of minutes of non-frozen behaviour - are inflated into large differences on the rescaled measure. In terms of what the fish actually did, the two groups differ by a few percent of trial time. That is the boundary on which much of the rest of the paper rests.

I recognise that evasion as a proportion of active time is in some respects the more biologically meaningful quantity, and the authors are right that a fish freezing 70% of the time has limited opportunity to do anything else. But that is an argument for reporting it as a descriptive measure, not for entering it into the clustering alongside the two variables from which it is computed.

This impression is reinforced by Figure 4A itself. While the freezer group occupies a reasonably distinct region, the non-reactive, evader and evading freezer groups appear as a single continuous distribution with cluster boundaries drawn through it rather than around visible gaps. I appreciate that UMAP is a projection and that visual separation is not required for genuine structure, but this is the figure by which most readers will judge whether four discrete types exist, and it does not obviously support that reading - particularly given that the embedding is built from the same variables, including the rescaled measure, that most favour the separation.

I would suggest that the authors re-run the clustering using only the two directly measured behaviours, percent freezing and percent evasion of total time, and report whether four groups still emerge and, in particular, whether the evading freezer / freezer split survives.

The third is that the two groups have distinct functional networks despite equally high freezing, so the behavioural difference is real and is manifesting in the brain. This is the strongest of the three arguments, and I accept part of it: something about how a frozen fish spends its remaining active time does appear to be neurally meaningful, which is interesting in its own right. But it does not establish that these are two distinct types, nor that the difference has anything to do with the conditioning. Fish taken from either side of a cut through a continuous distribution will differ neurally if that continuum tracks brain state, so the network result is equally compatible with graded variation. More importantly, Figure 5A shows that a substantial proportion of fish are classified as evaders in the vehicle condition and at pre-exposure, before any CAS has been given. This suggests a pre-existing individual tendency toward evasive behaviour that is independent of the alarm substance, and one would expect such a tendency to persist into the memory trial. If so, the distinction the network analysis is drawing between freezers and evading freezers may simply reflect that baseline trait, and its neural correlates would be correlates of the trait rather than of fear memory. I am therefore not convinced that this distinction is related to CAS or to memory.

(2) This concern is fully resolved. I had misread the CAS preparation: it was pooled from eight donors spanning all four strains and both sexes, so every fish received identical material and the strain and sex differences cannot be attributed to donor variability. The clarification now added to the Results will prevent other readers making the same error. The addition of FDR correction to the Figure 2 comparisons also addresses my related concern about multiple testing.

(3) Somewhat resolved. The conclusion no longer states that behavioural variation is "driven by" activity in particular regions, and the added caveat that neural activity was not directly manipulated sets the right expectation for a mapping study. The scatterplots in Figure S6-2 are a useful addition and give a much better intuition for what the PLS contrasts represent. My remaining reservation is the one above: a great deal of the neural story rests on the evading freezer / freezer contrast, and I am not persuaded that this contrast marks a boundary relevant to fear memory.

Reviewer #3 (Public review):

This revised manuscript by Fontana et al. aims to study how animals respond to fearful stimuli, with a specific focus on brain regions involved in predicting animals that passively freeze or those that actively evade the threat. I continue to be enthusiastic about the study. The study addresses an important question regarding individual variation in fear-related behavior and links these behavioral phenotypes to whole-brain activity patterns in adult zebrafish. The combination of a contextual fear conditioning paradigm, strain/sex comparisons, behavioral clustering, and AZBA-based c-Fos mapping makes this a valuable contribution to the field, not just in answering the question posed by the authors, but also in formulating a framework for using adult zebrafish for whole brain analysis of complex behaviors. Overall, I find the authors have responded to my concerns:

(1) I still think that separating memory acquisition and consolidation is an interesting question, and further use of the framework will need to eventually solve that; however, I also appreciate that this may be beyond the scope of the current study, and I appreciate the authors acknowledging this in the manuscript.

(2) Regarding Figure 3, I also agree that this is difficult to present differently, and I appreciate the authors adding text to the body to clarify things. My one request is that the sentence (lines 214-215) that reads: "This increase in evasion in the vehicle group likely represents a response to the water disturbance that occurs when solution is added to the tank." Be changed to: "This increase in evasion in the vehicle group may represent a response to the water disturbance that occurs when solution is added to the tank." While it is entirely possible, there are no concrete data to support that this is "likely."

(3) I appreciate the clarification regarding the PLS-derived contrasts in Figure 6A and in the body.

Overall, this is a really interesting paper that will have a wide-ranging impact. All of my concerns have been addressed.

Author response:

The following is the authors’ response to the original reviews.

We thank the reviewer’s for their thoughtful comments that have significantly strengthened the paper. Below, we have outlined our responses to both the public reviews and recommendations.

In addition to the alterations to the manuscript based on the reviews, during our review of the data analysis we uncovered some small errors that we have now corrected. In looking back over the image registration, we identified three animals whose olfactory bulbs did not register properly and one with poor cell counting in the telencephalon. To account for these issues, we imputed the missing data using an iterative soft-threshold singular value decomposition (described on lines 779-783 of the updated manuscript). This update had little impact on the results. We also identified a small error in how we determined ‘unique’ and ‘overlapping’ edges in the network analysis (Figure 8). In the previous analysis we had incorrectly noted that all ‘unique’ edges did not have an overlapping confidence interval with the two other networks (i.e., the networks for evading freezers, freezers, and non-reactive). Instead, the ‘unique’ edges in the prior version of the manuscript did not have an overlap with at least one other network. We have now updated the analysis so the reader can distinguish between edges that are truly ‘unique’ versus those with ‘1 overlapping confidence interval’ or ‘2 overlapping confidence intervals’ with other networks. As before, this update and change to the analysis does not materially affect the results or conclusions.

Public Reviews:

Reviewer #1 (Public review):

Weaknesses:

The neural analysis part is very comprehensive. Figure 5 and Figure 6 are independent but complement each other very well. They together support that the cerebellar system is the key brain component for a freezing response. Their extreme focus on high-level analyses, however, came at the expense of biological intuitions. I suggest adding some figure panels and result/discussion paragraphs to help with that aspect.

Thank you for the suggestion. We have made extensive edits to the manuscript to include additional discussion and biological intuition. Specifically:

We added a supplemental figure (Figure S6-2) that has scatterplots showing how cfos levels vary with the different behavioral contrasts. Although the PLS analysis is multivariate, this univariate analysis should help give readers a better intuition of how the behavior relates to brain function.

We have also rewritten the results sections for both the PLS analysis (lines 303-361) and network analysis (lines 396-437) to incorporate more of a discussion about the biological context of different regions identified. Thank you for this suggestion, we feel that this significantly strengthens the biological interpretation of the data for the reader.

Reviewer #2 (Public review):

(1) My first concern relates to the claim in the abstract that "We found that fear memory behavior fell into four distinct groups: non-reactive, evaders, evading freezers, and freezers".

In my opinion, the "freezing" aspect is well supported as being both triggered by the CAS and for memory effect upon re-exposure to the tank, but I am less convinced about the "evasive" behaviour. In Figure 2, it appears that "evasiveness" is generally not increased in both the Exposure or Memory phases for many groups, and in Figure 5, it appears that "evasiveness" is expressed by nearly 50% of the fish in the pre-exposure condition before CAS addition and in all phases in the vehicle condition. Therefore, it appears that most of the expression of this behaviour is independent of any memorybased effect.

We thank the reviewer for this suggestion and we agree that this line in the abstract was unintentionally misleading. We have now altered this line in the abstract (lines 34-36) to read:

“We also found that that behavior fell into four distinct groups: non-reactive, evaders, evading freezers, and freezers with the evading freezer and freezer groups most clearly associated with memory formation.”

On the larger point of the inclusion of evasion as part of the fear response, we believe this is warranted for the following reasons: (1) evasive behavior has long been acknowledged as a highly variable aspect of how fish respond to alarm substance where some fish exhibit evasion and others do not. This observation goes back to the original work from Karl von Frisch in minnows (von Frisch, 1938), and others in zebrafish (e.g., Suboski et al, 1990). One goal of our paper (and the work from the lab in general) is to try dissecting out this individual variation that can get lost when only considering population averages. (2) The unsupervised clustering also suggests that there are two distinct types of freezing clusters (Figure 4B) where some fish freeze intermittently with normal swimming and others freeze intermittently with evasive behavior. This suggests that evasion is increased in response to CAS, but only in a subset of fish. (3) The brain networks from the evading freezer and freezer groups are distinct (Figure 8A) despite having equally high levels of freezing behavior (Figures 4B and C). This means the difference we’re able to distinguish behaviorally is also manifesting in the brain, suggesting that it is not anomalous. Thus, while we agree that freezing is definitely the strongest and clearest behavioral response to CAS, we believe the analysis of this large dataset supports the interpretation that, in a subset of fish, increased evasive behavior in response to CAS is also a part of the response.

(2) My second concern relates to the claim in the abstract that "background strain and sex influenced how fish respond to CAS, with males more likely to increase evasive behaviors than females and the TU strain more likely to be non-reactive."

My understanding, based on the introduction and on the methods, is that it is likely important that the CAS be prepared from conspecifics of the same strain and sex, and for this reason, they prepared different CAS specific for each strain and each sex. Therefore, the "CAS" that is applied is necessarily different for each condition, and I am concerned about if the differences observed could relate more to variation in the quality, purity, concentration, etc. of the specific CAS samples for different groups, rather than their reactivity to the substance or their ability to form memories based on such experiences.

The CAS was prepared by mixing extracts from all four strains and both sexes (so 8 fish per batch). Thus, all the fish were exposed to the same CAS mix derived from the same donors. This is described in the methods (lines 626-629). However, to ensure that this is clear to readers, we’ve now included a line indicating this in the results section (lines 123-124).

(3) My third concern relates to the interpretation of the cFos data.

As I mentioned above, I feel as though the behavioural analysis is perhaps more complex than is warranted via the inclusion of evasiveness, and I wonder if the conclusions from the experiments would be simpler if analyzed only from the perspective of freezing.

We agree that the freezing response is driving the majority of the neural cfos response that we are seeing (e.g., Figure 6A-C). However, we feel that the network analysis (Figure 8) justifies the distinction between freezers and evading freezers. This is because the brain networks for these two groups (freezers and evading freezers) are quite distinct, even though these groups both have the same levels of freezing behavior (Figure 4). This stark difference in patterns of neural activity suggests the brain of a freezer and an evading freezer are engaging with the world in two distinct ways that is worth noting. We’ve updated the abstract to make this point clearer (abstract: lines 39-48) and discuss the biological interpretations of patterns of brain activity unique to evasion or evading freezers in more depth (lines 303-361; lines 396-437).

Reviewer #3 (Public review):

(1) The three-day contextual fear paradigm, as implemented - one CAS pairing on day 2 followed by a single recall test on day 3 - inevitably conflates acquisition and long-term memory, making it impossible to know whether strains like TU truly recall the association poorly or simply learn it more slowly. For example, given that TU fish extinguish fear faster than AB or TL strains in extended protocols, they may simply require additional or repeated CAS pairings to achieve the same asymptotic performance. To disentangle learning kinetics from recall strength, the assay could be revised to include multiple acquisition trials (e.g., conditioning on two or more consecutive days) with an immediate post-conditioning probe to assess acquisition independent of consolidation, and continuous measurement of freezing and evasive behaviors across each trial to fit learning curves for each strain. Such refinements - even if on a subset of the strains - would reveal whether "non-reactive" phenotypes reflect genuine recall deficits or merely delayed acquisition.

We thank the reviewer for this thoughtful comment. We agree that it is difficult to disentangle acquisition from consolidation. Indeed, the TU fish do appear to have lower levels of freezing in response to the CAS (Figure 2A), supporting the idea that reduced performance at memory day could be due to some sort of deficit at acquisition. However, pursuing a detailed examination of strain dependent differences in fear memory acquisition versus consolidation is beyond the scope of the current paper where we primarily focus on individual differences in behavior. Nonetheless, we have included this important point in the discussion (lines 470-471).

(2) My second major question is with respect to Figure 3 panel B. This is a complex figure, and I can understand the gist of what the authors are attempting to show, but it is difficult to understand as it is. Can this be represented in a way that is clearer and explained a bit more easily?

We agree that this figure is one of the more complex in the paper. However, we’ve struggled to come up with a better way to present it. We have improved the presentation based on other reviewer comments by making the vehicle and CAS groups more easily distinguishable by using open versus closed circles. We’ve also included additional interpretations of the data in the results, which we hope will help guide readers through this figure better (lines 208-223).

(3) The brain mapping is by far one of the most interesting aspects of this study, and the methods that the group used are interesting. The brain mapping, however, relies on generating "contrasting" groups (Figure 6A), and I was not clear as to how these two groups were formed. Could the authors elaborate a bit?

These contrasting groups (contrast 1, contrast 2) arise analytically from the partial least squares (PLS) analysis; they are not defined by the experimenter. In brief, PLS is a multivariate technique that identifies latent variables that capture axes of maximal covariation between two datasets: behavior and brain activity. As an analogy to a more widely known technique, principal components analysis (PCA) uncovers axes of maximal variance within a single dataset. PLS, in contrast, simultaneously analyzes the covariation in two datasets. The contrast groups in Figure 6A represent the behavioral weights of the latent variables that capture the most covariance, which illustrates how the four behaviors load onto these top two contrasts.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Major points:

(1) The c-Fos analysis in Figure 5 is very comprehensive and convincing, but lacks intuitive presentations. In my understanding, the increase in c-Fos expression in red areas means increased freezing behavior for Contrast 1 for the PLS analysis? Do you have representative c-Fos expression images between different groups of fish?

We decided not to include a representative cfos image because the data is derived from a large number of fish (N=87) and thus it can easily be cherry-picked to choose images that match the narrative. Instead, to more accurately capture the breadth of the data while providing a more intuitive presentation, we have included an additional supplemental figure that includes scatterplots of scaled cfos data against behavioral scores for each of the two contrasts (S6-2). We believe this more fully and accurately captures the relationship between behavior and brain activity. We included six different example brain regions and scatterplots for cfos activity against behavioral scores for contrasts 1 and 2, demonstrating a range of relationships. However, we should note that PLS is a multivariate technique, and so this univariate analysis does not fully capture the subtleties of the PLS analysis. Nonetheless, we think this will help give a more intuitive interpretation of the data to readers. We have also referenced this additional data in the manuscript (lines 307-309). We thank the reviewer for this excellent suggestion that improves the ability of readers to understand the paper.

(2) Also related to Figure 5, the result section only describes the PLS statistics and does not try to describe the biological interpretation. Do the authors think the c-Fos expression directly represents lowlevel behavior, such as swimming, or a high-level behavioral state or learning? Maybe different areas mediate different aspects?

For example, the medullary locomotor areas, which are usually highly correlated with swimming in terms of neural activity, seem to have higher c-Fos expression in freezing fish. I'm not saying this shouldn't be the case. c-Fos expression in this area was not elevated in larval fish during OMR in Shainer et al., 2023, indicating that it doesn't linearly reflect neural activity. But discussing a bit of intuition on the connection between c-Fos expression and biological process, rather than just saying "the cerebellum could regulate emotional states", would help us guide through this highly complex analysis.

We have now added more interpretation of the data in both the PLS and network analysis sections (lines 303-361 and lines 396-437). Again, thank you for this excellent suggestion. This helps make the biological interpretation of the data clearer.

Minor points:

(1) Figure 2B titles: please write "memory" on the right side.

We considered writing ‘memory’ on the right-hand side, but we thought this may add confusion because it would not apply to both graphs in the row. The left-hand graphs are the responses during ‘exposure’ and the right-hand graphs are the responses during the ‘memory’ phase. This is indicated by the titles above the left and right-hand sets of graphs.

(2) Figure 2C: needs legend lines.

We have now moved the legend lines from the top of the graphs to below the graph to make them more visible to readers.

(3) Line 187: "aggregated" data.

This has now been changed to ‘aggregated’ (now line 194).

(4) Line 371: I'm not sure what "Beyond" means.

We have now significantly changed this part of the paper and we no longer use the word ‘beyond’ here.

Reviewer #2 (Recommendations for the authors):

(1) Regarding point (1) in the Public Review:

I would encourage the authors to consider whether this study might be better focused exclusively on the freezing behaviour, which does appear to be reliably expressed during CAS exposure and in the memory phases, and would significantly simplify the subsequent analyses of neural activity, and perhaps may lead to a more coherent conclusion.

As noted in our response to the public review, we appreciate this suggestion, but we have decided to keep the inclusion of the evasive behavior. This is because (1) evasive behavior has long been acknowledged as a highly variable aspect of how fish respond to alarm substance where some fish exhibit evasion and others do not. This observation goes back to the original work from Karl von Frisch in minnows (von Frisch, 1938), and others in zebrafish (e.g., Suboski et al, 1990). One goal of our paper (and the work from the lab in general) is to try dissecting out this individual variation that can get lost when only considering population averages. (2) The unsupervised clustering also suggests that there are two distinct types of freezing clusters (Figure 4B) where some fish freeze intermittently with normal swimming and others freeze intermittently with evasive behavior. This suggests that evasion is increased in response to CAS, but only in a subset of fish. (3) The brain networks from the evading freezer and freezer groups are very distinct (Figure 8A) despite having equally high levels of freezing behavior (Figures 4B and C). This means the difference we’re able to distinguish behaviorally is also manifesting in the brain, suggesting that it is not anomalous. Thus, while we agree that freezing is definitely the strongest and clearest behavioral response to CAS, we believe the analysis of this large dataset supports the interpretation that, in a subset of fish, increased evasive behavior in response to CAS is also a part of the response.

A more minor concern related to the analyses in Figure 2: in the figure legend, it is stated that "*-P < 0.05 compared to vehicle treated fish via t-tests". How are the authors dealing with the multiple comparisons problem? Would something like an ANOVA not be more appropriate?

Thank you for bringing this point up. We did not initially correct for multiple comparisons because we considered each of these experiments across sex and strain separate since we did not compare across strains. However, the way we’ve grouped the data together in figure 2 makes it appear as if they are one large experiment. To alleviate any concern about multiple testing, we have now corrected for multiple comparisons using the false discover rate (FDR) correction. The statistics in the figure and captions have now been updated.

(2) Regarding point (2) in the Public Review:

If the authors agree with my concern regarding potential variability in the CAS samples, I would suggest either testing for differences among strains using the same batch of CAS, or including and explaining this caveat in the text.

As noted in our response to the public review, the CAS was the same for all the fish. Each batch was derived from 8 donor fish, one fish from each strain and sex (described in lines 123-124 of the results and lines 626-629 of the methods).

(3) Regarding point (3) in the Public Review:

I feel like the standard in the field for such conclusions would be after

(a) Direct analyses of the activity states in these areas. I was surprised not to see a direct analysis of the cFos stainings in the cerebellum relative to freezing behaviour, for example, ideally in a different animal cohort.

The PLS analysis does relate activity in the cerebellum (and other brain regions) to specific behaviors via the the behavioral contrasts (Figure 6A). We believe this approach (instead of dividing fish into ‘high and low freezers’) is a more powerful way to leverage the data from all the animals tested (87 fish). However, we appreciate that the interpretation of the PLS analysis is not as intuitive as seeing scatterplots or bar charts comparing neural activity. For this reason (and in response to a comment from reviewer 1), we have included as a supplementary figure (Figure S6-2) scatterplots showing how standardized c-fos activity varies with the behavioral scores from the contrasts identified from the PLS analysis. Given that contrast 1 weights heavily in the positive direction on freezing, these figures can essentially be read as looking at cfos activity as a function of freezing levels. What can clearly be seen is that for regions of the cerebelleum (E.g., the LCa and CC) there is a clear positive relationship between cfos activity and the behavior scores for contrast 1.

(b) Some kind of manipulation of the brain area resulting in the relevant behavioural modification.

We completely agree with the reviewer. However, at the moment, we do not have the tools to do this in adult zebrafish. It is something we’re actively working on.

Of course, I appreciate that such experiments might not be possible or feasible, and in which case I would suggest adjusting the claims accordingly and highlighting the caveats to their interpretations.

We have incorporated the caveat that we have not directly altered neural activity into the discussion (lines 542-543) and adjusted how we discuss our findings in the abstract (lines 39-41) to more accurately represent the type of evidence we provide. Hopefully we’ll be able to do so in the near future!

MINOR CONCERNS:

(1) In Figure 3, how is the end of a behavioural epoch defined? I am surprised to see that you consider transitions between the same behavioural state. How does erratic swimming -> erratic swimming differ from a longer single epoch of erratic swimming? In general, I find this analysis confusing, and I am not sure if it adds significantly to the message of the paper.

Thank you for this question as it prompted us to realize we were missing this in our methods section. We have now updated the methods to include how we calculated the behavioral transitions (lines 644-650). In short, we used a 750 ms behavioral epoch time that corresponds to the size of the sliding window we used for the random forest model.

We have also updated the description of this analysis in the results to indicate the main finding from it (lines 207-223). In brief, the main finding is that exposure to CAS results in longer bouts of evasive behavior without increasing its frequency. Whereas CAS induced freezing arises from both longer bouts and likelihood of occuring. While we agree that this is a relatively minor finding in the paper, one of our goals is to provide as comprehensive analysis of fear behavior as possible to help guide future researchers interested in using fish for understanding different aspects of fear-related behaviors.

(2) In the PLS analyses, two measures of evasion are used: evasion time, and evasion as a percent of active behavior. I don't understand the justification for both of these being used rather than one. Again, my overall recommendation is to reduce the focus on the analysis of evasion behaviour, but if you do not choose to do this, I think the rationale of how both measures are used and why needs explanation.

We chose to incorporate two different measures of evasion throughout the study because the high levels of freezing in some animals results in little opportunity to express other behaviors (like evasion). Thus, to better capture what fish may be doing in the absence of freezing (i.e., when they are active) we also calculate the amount of active time spent performing evasive behaviors (instead of normal swimming). We have now included an explanation for this earlier in the results section when we first use this metric (lines 149-152).

(3) In the methods, I don't understand this: "Animals that were assigned the wrong sex were removed from data analysis, as well as its paired fish (< 2%)".

We determine the sex of fish when we set them up for dual housing. However, we occasionally make errors in sex determination. To ensure we properly sexed the fish, at the end of experiments, we euthanize the fish and check for the presence of eggs. If we incorrectly assigned the sex to a fish, they are removed from the experiment alongside the other fish they were dual housed with. This is because we want to ensure all fish are housed in the same way (i.e., a male fish with a female fish).

(4) How was this determined differently from the first time, resulting in exclusion?

After experiments, fish were euthanized and we checked for the presence of eggs (line 599-601). We’ve now added a line in this other part of the methods referring back to where we describe this (lines 676678).

Reviewer #3 (Recommendations for the authors):

Here are some minor concerns and errors found in the manuscript:

(1) For Figure 2B and Figure 3B, can the group make the lines solid and dotted? The circle or triangle designation is difficult to see, and since the crux of the figure depends on comparing Veh and CAS, it would be easier to see if the lines were altered.

Thank you for this suggestion. Instead of making the lines solid and dotted, we decided to make both the CAS and vehicle group circles and then have open and closed circles. We believe this solves the issue of being able to distinguish these groups and makes the data more readable.

(2) Figure 2C: It appears that the line colors in the legend are missing.

We have moved the line colors below the graphs to make them more obvious.

(3) Figure 8A: Same thing here - could the text be enlarged? It's really difficult to make out each node, and when I zoom the text becomes pixelated. This is an important figure and one that will likely be referenced, and making it clear would be helpful.

This one is difficult. We have made the network images as large as would fit on a page. We have now uploaded vectorized versions of the images so that they do not become pixelated when zooming in. As part of our supplemental materials we also include a cystoscope file that can be explored in greater depth as well.

(4) The paper is really well written: I found a few typos, though:

(a) Line 529: "Institutional Cara and Use Committee" should be "Institutional Animal Care and Use Committee" (Change cara to care and add animal).

(b) Line 274: "hybdridization" should read hybridization.

Thank you for catching these typos. They have now been fixed.