Economic and Social Modulations of Innate Decision-Making in Mice Exposed to Visual Threats

  1. Zhe Li
  2. Jiahui Wang
  3. Yidan Sun
  4. Jialin Li
  5. Ling-yun Li
  6. Ya-tang Li

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    eLife Assessment

    The authors show that innate defensive behavior in mice is shaped by threat intensity, reward value, and social hierarchy, highlighting how value and social context influence instinctive decisions. The authors provide a valuable characterization of escape behavior which approximates naturalistic conditions. The evidence is incomplete due to indirect measures of vigilance and somewhat misleading characterizations of the looming stimulus.

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Abstract

When confronted by predators, animals make innate decisions with rapid reaction times—a trait shaped by natural selection to maximize survival. However, rapid reactions are effective only when grounded in accurate judgments and appropriate choices, which often require cognitive control. To address how such choices are shaped, we developed a behavioral paradigm to investigate how threat intensity, reward value, and social hierarchy influence decision-making in foraging mice exposed to overhead visual threats. Using a machine learning-based approach, we classified defensive responses into four distinct decision types. We observed rapid habituation to repeated looming threats, with substantial inter-individual variability in the rate of habituation. Across both early and late phases of habituation, threat intensity is the primary determinant of decision-making, strongly driving behavior towards escape. In contrast, the influence of reward is context-dependent and emerges primarily in the late phase: under low-threat conditions, higher rewards suppress defensive responses, consistent with value-based decision theory, whereas under high-threat conditions, higher rewards promote escape, potentially reflecting heightened vigilance. Innate decision-making is further modulated by social hierarchy, with dominant mice showing greater vigilance and a stronger bias towards risk-averse behaviors, while subordinates are more reward-driven. To understand the underlying decision-making process, we developed a drift-diffusion leaky integrator model that successfully captures how threat intensity, reward value, and vigilance are integrated. Together, these findings reveal the economic and social modulation of innate decisions, offering insights into the computational mechanisms underlying the interplay between instinctive reactions and cognitive control.

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  1. Version published to 10.7554/elife.107306.2 on eLife
  2. Version published to 10.7554/elife.107306 on eLife
  3. eLife

    eLife Assessment

    The authors show that innate defensive behavior in mice is shaped by threat intensity, reward value, and social hierarchy, highlighting how value and social context influence instinctive decisions. The authors provide a valuable characterization of escape behavior which approximates naturalistic conditions. The evidence is incomplete due to indirect measures of vigilance and somewhat misleading characterizations of the looming stimulus.

  4. eLife

    Reviewer #1 (Public review):

    This study by Li and colleagues examines how defensive responses to visual threats during foraging are modulated by both reward level and social hierarchy. Using a naturalistic paradigm, the authors test how the availability of water or sucrose, with sucrose being more rewarding than water, shapes escape behavior in mice exposed to looming stimuli of different intensities, which are used to probe perceived threat level and defensive responses. In parallel, the study compares dominant and subordinate animals to assess how social rank biases the trade off between reward seeking and threat avoidance. By combining detailed behavioral analyses with computational modeling, the work addresses how reward level and social context jointly influence escape decisions in an ethologically relevant setting.

    Across the different experimental conditions, perceived threat level is the main determinant of behavior. The authors show that looming stimuli associated with higher threat (contrast) consistently elicit faster and more robust escape responses than lower threat stimuli. This effect is particularly evident during early exposures, when animals are highly vigilant and have not yet habituated to the looming stimulus (learned that it is not dangerous). Later they described that as animals gain experience and habituate, behavior becomes more flexible, and reward level begins to exert a graded modulation of the escape response. Importantly, the authors show that under high threat conditions increasing reward value leads to more frequent and faster escape rather than greater reward pursuit. This finding is particularly relevant, as it suggests that highly valued rewards can heighten vigilance and thereby enhance responsiveness to threat, highlighting that reward does not simply compete with defensive behavior but can also reshape it depending on the perceived level of danger, in contrast to low threat conditions, where threat can be more easily outweighed by reward. Thus, an important conceptual contribution of the study is the introduction of vigilance as a useful framework to interpret these effects. Vigilance is treated as a behavioral state reflecting heightened attention to potential danger. In line with what is known from natural foraging, mice initially maintain high vigilance when confronted with an innate threat. This perspective helps clarify a finding that might otherwise appear counterintuitive. One might expect higher rewards to motivate animals to tolerate risk, explore more, and habituate faster in any scenario. Instead, the data suggest that highly rewarding outcomes can elevate vigilance, making animals more responsive to threat and leading to faster or more frequent escape under high threat conditions. In this sense, reward does not simply compete with threat but can also amplify sensitivity to it, depending on the internal state of the animal.

    The social results are particularly interesting in this context as well. Dominant mice consistently prioritize avoidance over reward, showing stronger escape responses and slower habituation than subordinates. This behavior is well captured by the vigilance framework proposed by the authors: dominant animals appear to maintain higher vigilance, which biases decisions toward threat avoidance. The authors further suggest that stable social relationships sustain high vigilance and slow habituation, framing this as an evolutionarily conserved strategy that may enhance survival. This interpretation provides a valuable perspective on how social structure shapes defensive behavior beyond immediate physical interactions. At the same time, there are important limitations to this interpretation. All experiments were conducted in male mice, and it is possible that the relationship between social hierarchy, vigilance, and defensive behavior would differ substantially in females. In addition, the idea that stable social relationships maintain elevated vigilance does not straightforwardly align with broader views of social stability as protective for mental health and as a buffer against anxiety and stress. These points do not undermine the findings but suggest that the social effects described here should be interpreted with caution and within the specific context of the task and sex studied.

    Another important limitation is that the neural mechanisms underlying these effects remain speculative. The manuscript includes an extensive discussion of candidate circuits, particularly involving the superior colliculus and downstream structures, but this section is necessarily based on prior literature rather than on data presented in the study. Given the complexity of the circuits involved in integrating internal state, reward, social context, and vigilance, the current work should be viewed as providing a strong behavioral and conceptual framework rather than direct insight into underlying neural mechanisms.

    Methodologically, the behavioral paradigm is well suited for studying escape decisions in socially housed animals, and the machine learning based classification of defensive responses is a clear strength. The computational model provides a useful formalization of how threat level, reward level, and vigilance interact and may be valuable for other laboratories studying escape, approach avoidance, or conflict situations, particularly as a way to classify behavioral outcomes after pose estimation. More generally, the work will be of interest to the neuroethology community for its detailed characterization of escape behavior under naturalistic conditions.

    Given the ethological nature of the study and the high inter individual variability reported by the authors, clarity and precision in the methods are especially important for reproducibility. While the revised manuscript addresses many earlier concerns, some aspects remain slightly difficult to follow. For example, the main text states that animals were not water deprived to avoid differences in internal state, whereas parts of the methods describe conditions in which animals were water deprived, suggesting that internal state manipulation may differ across experiments. Clearer separation and explanation of these conditions would further strengthen confidence in the work.

    Overall, this study provides a rich and thoughtful analysis of how reward level and social hierarchy modulate defensive behavior through changes in vigilance. It offers a useful conceptual advance for thinking about escape behavior in naturalistic settings and lays a solid foundation for future work aimed at linking these behavioral states to underlying neural circuits.

  5. eLife

    Reviewer #2 (Public review):

    Zhe Li and colleagues investigate how mice exposed to visual threats and rewards balance their decisions in favour of consuming rewards or engaging in defensive actions. By varying threat intensity and reward value, they first confirm previous findings showing that defensive responses increase with threat intensity and that there is habituation to the threat stimulus. They then find that water-deprived mice have a reduced probability of escaping from low contrast visual looming stimuli when water or sucrose are offered in the environment, but that when the stimulus contrast is high, the presence of sucrose or water increases the probability of escape. By analysing behaviour metrics such as the latency to flee from the threat stimulus, they suggest that this increase in threat sensitivity is due to increased vigilance. Analysis of this behaviour as a function of social hierarchy shows that dominant mice have higher threat sensitivity, which is also interpreted as being due to increased vigilance. These results are captured by a drift diffusion model variant that incorporates threat intensity and reward value.

    The main contribution of this work is quantifying how the presence of water or sucrose in water-deprived mice affects escape behaviour. The differential effects of reward between the low and high contrast conditions are intriguing, but I find the interpretation that vigilance plays a major in this process not supported by the data. The idea that reward value exerts some form of graded modulation of the escape response is also not supported by the data. In addition, there is very limited methodological information, which makes assessing the quality of some of the analyses difficult, and there is no quantification on the quality of the model fits.

    (1) The main measure of vigilance in this work is reaction time. While reaction time can indeed be affected by vigilance, reaction times can vary as a function of many variables, and be different for the same level of vigilance. For example, a primate performing the random dot motion task exhibits differences in reaction times that can be explained entirely by the stimulus strength. Reaction time is therefore not a sound measure of vigilance, and if a goal of this work is to investigate this parameter, then it should be measured. There is some attempt at doing this for a subset of the data in Figure 3H, by looking at differences in the action of monitoring the visual field (presumably a rearing motion, though this is not described) between the first and second trials in the presence of sucrose. I find this an extremely contrived measure. What is the rationale for analysing only the difference between the first and second trials? Also, the results are only statistically significant because the first trial in the sucrose condition happens to have zero up action bouts, in contrast to all other conditions. I am afraid that the statistics are not solid here. When analysing the effects of dominance, a vigilance metric is the time spent in the reward zone. Why is this a measure of vigilance? More generally, measuring vigilance of threats in mice requires monitoring the position of the eyes, which previous work has shown is biased to the upper visual field, consistent with the threat ecology of rodents.

    (2) In both low and high contrast conditions, there are differences in escape behaviour between no reward and water or sucrose presence, but no statistically significant differences between water and sucrose (eg: Figure 3B). I therefore find that statements about reward value are not supported by the data, which only show differences between the presence or absence of reward. Furthermore, there is a confound in these experiments, because according to the methods, mice in the no-reward condition were not water-deprived. It is thus possible that the differences in behaviour arise from differences in the underlying state.

    (3) There is very little methodological information on behavioural quantification. For example, what is hiding latency? Is this the same are reaction time? Time to reach the safe zone? What exactly is distance fled? I don't understand how this can vary between 20 and 100cm. Presumably, the 20cm flights don't reach the safe place, since the threat is roughly at the same location for each trial? How is the end of a flight determined? How is duration measured in reward zone measures, e.g., from when to when? How is fleeing onset determined?

    (4) There is little methodological information on how the model was fit (for example, it is surprising that in the no reward condition, the r parameter is exactly 0. What this constrained in any way), and none of the fit parameters have uncertainty measures so it is not possible to assess whether there are actually any differences in parameters that are statistically significant.

    Comments on the revised manuscript:

    The manuscript has been revised and improved significantly by the addition of methodological details and new analysis. I remain, however, unconvinced by the argument that increased vigilance in the presence of reward leads to heightened escape behaviour.

    In response to my criticism that the work does not measure vigilance directly, the authors have included measures of foraging interval and foraging speed, which they state are "two direct behavioral analyses of vigilance". I disagree - like reaction time, foraging speed and foraging interval can be modulated, for example, by changes in threat sensitivity. Increased threat sensitivity comes with diverse behavioral changes that may well include increased vigilance, but foraging interval and foraging speed can certainly change without the animal expressing increased vigilance behaviors. A bigger issue I still have though, is with the conclusion that the presence of reward increases "direct escape behaviors". Comparing the no reward, water and sucrose groups indeed shows a difference (which is now clear after the split into early and late phases), but the issue is that these are different mice. As the text is written, is sounds like introducing reward will acutely increase escape. But if we look at the raw data show in Figure 2C, what I think is happening is that the presence of reward is decreasing habituation to the stimulus. The data for trials 1 and 10 in the three conditions show this - there is habituation with no reward (reaction times are all shifting to the right), a bit less with water and very little with sucrose. This is interesting in its own right and we can speculate why it might be happening, but I think this is conceptually different from what the authors are proposing.

  6. eLife

    Reviewer #3 (Public review):

    Male mice were tested in a classic behavioral "flee the looming stimulus" paradigm. This is a purely behavioral study; no neural analyses were done. Mice were housed socially, but faced the looming stimulus individually, using an elegant automated tunnel (see videos for clarity).

    The additional changes made to the paper clarify the work done. While there are some limitations (male mice, weird stimulus), the general results are interesting and a valuable addition to the experimental literature. The main claim of the paper is that the different rewards (none, water, sucrose) did not change the escape properties early in learning, but did late, particularly that in the late (already experienced) conditions, reward value (assuming sucrose > water > no reward) interacted with the salience of the looming stimulus (light gray, dark gray). (Panels 3D, 3G, 3K, 3N).

    For readers, I want to note that one of the most interesting results is actually in Figure S2, where they find that a looming stimulus behind the mouse still makes a mouse run to the nest. In these conditions, the mouse runs past the looming stimulus to get to safety! (I also do love the video of the mouse running around the barriers like a snake to get home.)

    I have a few minor clarification questions and a few notes that I think would be useful additions for authors and readers to think about.

    Dominance: What does the mouse social science literature say about the "test tube" test? What can we conclude from this test? This would be useful when trying to understand what is causing the dominance/submissive difference in responses. Figure 4 shows that the dominant mice are more risk-averse than the submissive mice. Is "dominance" in the test-tube actually a measure of risk-seeking? Is the issue that the submissive mice don't think they can get back to the food-site easily, so they are less willing to sacrifice the current (if dangerous) foraging opportunity? Is the issue that the submissive mice can't get back to the nest? As I understand it, the nest was always available to all the mice, so I suspect inability to get to the nest is an unlikely hypotheses. Is the issue that the submissive mice also don't feel safe in the nest?

    Limitations of the study: There is an acknowledged limitation to male mice, and the limitations of the small data sets that are typical of such experiments. In addition, however, it is also worth noting the strangeness of the looming stimulus, which is revealed clearly in the videos. The stimulus is a repeating growing circle, growing in a single location within the environment. The stimulus repeats 10 times, once per second. This is not what an attacking hawk or owl would look like. (I now have this image of an owl diving down, and then teleporting up and diving down again.) Note - I am fine with this stimulus. It produces an interesting experiment and interesting results. I do not think the authors need to change anything in their paper, but readers need to recognize that this is not a "looming predator".

    These "limitations" are better seen as "caveats" when folding these results in with the rest of the literature that has gone before and the literature to come. (Generally, I do not believe that science works by studies making discoveries that change how we think about problems - instead, science works by studies adding to the literature that we integrate in with the rest of the literature.) Thus, these caveats should not be taken as problems with the study or as fixes that need to be done. Instead, they are notes for future researchers to notice if differences are found in any future studies.

    Thus, my only suggestion is that I think authors could write a more careful paper by using the past and subjunctive tense appropriately. Experimental observations should be in past tense, as in "the influence of reward was context-dependent and emerged in the late phase" instead of "the influence of reward is context-dependent and emerges in the late phase" - it emerged in the late phase this once - it might not in future experiments, not due to any fault in this experiment nor due to replicability problems, but rather due to unexpected differences between this and those future experiments. At which point, it will be up to those future experiments to determine the difference. Similarly, large conclusions should be in the subjunctive tense, as in "these data suggest that threat intensity is likely to be the primary determinant of decision making" rather than "threat intensity is the primary determinant of decision making", because those are hypotheses not facts.

  7. eLife

    Author response:

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

    Public Reviews:

    Reviewer #1 (Public review):

    This study by Li and colleagues examines how defensive responses to visual threats during foraging are modulated by both reward level and social hierarchy. Using a naturalistic paradigm, the authors test how the availability of water or sucrose, with sucrose being more rewarding than water, shapes escape behavior in mice exposed to looming stimuli of different intensities, which are used to probe perceived threat level and defensive responses. In parallel, the study compares dominant and subordinate animals to assess how social rank biases the trade off between reward seeking and threat avoidance. By combining detailed behavioral analyses with computational modeling, the work addresses how reward level and social context jointly influence escape decisions in an ethologically relevant setting.

    Across the different experimental conditions, perceived threat level is the main determinant of behavior. The authors show that looming stimuli associated with higher threat (contrast) consistently elicit faster and more robust escape responses than lower threat stimuli. This effect is particularly evident during early exposures, when animals are highly vigilant and have not yet habituated to the looming stimulus (learned that it is not dangerous). Later they described that as animals gain experience and habituate, behavior becomes more flexible, and reward level begins to exert a graded modulation of the escape response. Importantly, the authors show that under high threat conditions increasing reward value leads to more frequent and faster escape rather than greater reward pursuit. This finding is particularly relevant, as it suggests that highly valued rewards can heighten vigilance and thereby enhance responsiveness to threat, highlighting that reward does not simply compete with defensive behavior but can also reshape it depending on the perceived level of danger, in contrast to low threat conditions, where threat can be more easily outweighed by reward. Thus, an important conceptual contribution of the study is the introduction of vigilance as a useful framework to interpret these effects. Vigilance is treated as a behavioral state reflecting heightened attention to potential danger. In line with what is known from natural foraging, mice initially maintain high vigilance when confronted with an innate threat. This perspective helps clarify a finding that might otherwise appear counterintuitive. One might expect higher rewards to motivate animals to tolerate risk, explore more, and habituate faster in any scenario. Instead, the data suggest that highly rewarding outcomes can elevate vigilance, making animals more responsive to threat and leading to faster or more frequent escape under high threat conditions. In this sense, reward does not simply compete with threat but can also amplify sensitivity to it, depending on the internal state of the animal.

    The social results are particularly interesting in this context as well. Dominant mice consistently prioritize avoidance over reward, showing stronger escape responses and slower habituation than subordinates. This behavior is well captured by the vigilance framework proposed by the authors: dominant animals appear to maintain higher vigilance, which biases decisions toward threat avoidance. The authors further suggest that stable social relationships sustain high vigilance and slow habituation, framing this as an evolutionarily conserved strategy that may enhance survival. This interpretation provides a valuable perspective on how social structure shapes defensive behavior beyond immediate physical interactions. At the same time, there are important limitations to this interpretation. All experiments were conducted in male mice, and it is possible that the relationship between social hierarchy, vigilance, and defensive behavior would differ substantially in females. In addition, the idea that stable social relationships maintain elevated vigilance does not straightforwardly align with broader views of social stability as protective for mental health and as a buffer against anxiety and stress. These points do not undermine the findings but suggest that the social effects described here should be interpreted with caution and within the specific context of the task and sex studied.

    We thank the reviewer for raising this important point. In the context of repeated looming exposure, slower habituation reflects more sustained vigilance over time. Compared to individually housed mice, group-housed mice exhibit slower habituation (Lenz et al., 2022), and pair-housed mice showed even slower habituation in our current work. Importantly, this pattern does not indicate that pair-housed mice have higher overall vigilance than individually housed animals. Although individually housed mice habituate more quickly, they display higher initial vigilance, as reflected by their increased probability of escaping in response to looming stimuli (Lenz et al., 2022). Thus, pair-housed mice exhibited reduced defensive responses compared to individually housed animals, consistent with a social buffering effect.

    Furthermore, in a separate study (Rank- and Threat-Dependent Social Modulation of Innate Defensive Behaviors; Li, Gao, Li, 2026, eLife 15:RP109571), we directly compared responses to looming stimuli when mice were tested alone versus in the presence of a social partner and observed clear evidence of social buffering.

    Another important limitation is that the neural mechanisms underlying these effects remain speculative. The manuscript includes an extensive discussion of candidate circuits, particularly involving the superior colliculus and downstream structures, but this section is necessarily based on prior literature rather than on data presented in the study. Given the complexity of the circuits involved in integrating internal state, reward, social context, and vigilance, the current work should be viewed as providing a strong behavioral and conceptual framework rather than direct insight into underlying neural mechanisms.

    We fully agree that the proposed neural mechanisms remain speculative and that the circuits involved in integrating internal state, reward, and social context are likely far more complex. We have revised the manuscript to acknowledge this limitation.

    Methodologically, the behavioral paradigm is well suited for studying escape decisions in socially housed animals, and the machine learning based classification of defensive responses is a clear strength. The computational model provides a useful formalization of how threat level, reward level, and vigilance interact and may be valuable for other laboratories studying escape, approach avoidance, or conflict situations, particularly as a way to classify behavioral outcomes after pose estimation. More generally, the work will be of interest to the neuroethology community for its detailed characterization of escape behavior under naturalistic conditions.

    Given the ethological nature of the study and the high inter individual variability reported by the authors, clarity and precision in the methods are especially important for reproducibility. While the revised manuscript addresses many earlier concerns, some aspects remain slightly difficult to follow. For example, the main text states that animals were not water deprived to avoid differences in internal state, whereas parts of the methods describe conditions in which animals were water deprived, suggesting that internal state manipulation may differ across experiments. Clearer separation and explanation of these conditions would further strengthen confidence in the work.

    To improve clarity, we have revised the Methods section to clearly distinguish between experimental conditions that involved water deprivation and those that did not.

    Overall, this study provides a rich and thoughtful analysis of how reward level and social hierarchy modulate defensive behavior through changes in vigilance. It offers a useful conceptual advance for thinking about escape behavior in naturalistic settings and lays a solid foundation for future work aimed at linking these behavioral states to underlying neural circuits.

    Reviewer #2 (Public review):

    Zhe Li and colleagues investigate how mice exposed to visual threats and rewards balance their decisions in favour of consuming rewards or engaging in defensive actions. By varying threat intensity and reward value, they first confirm previous findings showing that defensive responses increase with threat intensity and that there is habituation to the threat stimulus. They then find that water-deprived mice have a reduced probability of escaping from low contrast visual looming stimuli when water or sucrose are offered in the environment, but that when the stimulus contrast is high, the presence of sucrose or water increases the probability of escape. By analysing behaviour metrics such as the latency to flee from the threat stimulus, they suggest that this increase in threat sensitivity is due to increased vigilance. Analysis of this behaviour as a function of social hierarchy shows that dominant mice have higher threat sensitivity, which is also interpreted as being due to increased vigilance. These results are captured by a drift diffusion model variant that incorporates threat intensity and reward value.

    The main contribution of this work is quantifying how the presence of water or sucrose in water-deprived mice affects escape behaviour. The differential effects of reward between the low and high contrast conditions are intriguing, but I find the interpretation that vigilance plays a major in this process not supported by the data. The idea that reward value exerts some form of graded modulation of the escape response is also not supported by the data. In addition, there is very limited methodological information, which makes assessing the quality of some of the analyses difficult, and there is no quantification on the quality of the model fits.

    (1) The main measure of vigilance in this work is reaction time. While reaction time can indeed be affected by vigilance, reaction times can vary as a function of many variables, and be different for the same level of vigilance. For example, a primate performing the random dot motion task exhibits differences in reaction times that can be explained entirely by the stimulus strength. Reaction time is therefore not a sound measure of vigilance, and if a goal of this work is to investigate this parameter, then it should be measured. There is some attempt at doing this for a subset of the data in Figure 3H, by looking at differences in the action of monitoring the visual field (presumably a rearing motion, though this is not described) between the first and second trials in the presence of sucrose. I find this an extremely contrived measure. What is the rationale for analysing only the difference between the first and second trials? Also, the results are only statistically significant because the first trial in the sucrose condition happens to have zero up action bouts, in contrast to all other conditions. I am afraid that the statistics are not solid here. When analysing the effects of dominance, a vigilance metric is the time spent in the reward zone. Why is this a measure of vigilance? More generally, measuring vigilance of threats in mice requires monitoring the position of the eyes, which previous work has shown is biased to the upper visual field, consistent with the threat ecology of rodents.

    We agree that reaction time can be influenced by multiple factors, including stimulus strength. Consistent with this, reaction times (i.e. latencies to flee) were substantially shorter under high-contrast conditions (Figure 3E). However, even under the same high-contrast condition, reaction times were significantly shorter in the water condition compared to the no-reward condition, suggesting that other factors such as vigilance may contribute.

    Upward-directed attention includes rearing, up-stretching, and upward head orientation, which will be clarified in the Method section. To address concerns about statistical validity, we will quantify these behaviors across the first 10 trials rather than limiting the analysis to the first two.

    As for the dominance-related results, we interpret them as reflecting both enhanced vigilance and reduced reward-seeking behavior. Time spent in the reward zone is not a measure of vigilance but an indicator of reward-seeking motivation. We will clarify this in the revised manuscript.

    (2) In both low and high contrast conditions, there are differences in escape behaviour between no reward and water or sucrose presence, but no statistically significant differences between water and sucrose (eg: Figure 3B). I therefore find that statements about reward value are not supported by the data, which only show differences between the presence or absence of reward. Furthermore, there is a confound in these experiments, because according to the methods, mice in the no-reward condition were not water-deprived. It is thus possible that the differences in behaviour arise from differences in the underlying state.

    In Figure 3B, the difference between water and sucrose conditions did not reach statistical significance (p = 0.08). We plan to collect additional data to determine whether this is due to limited statistical power. It is also possible that some behavioral readouts are more sensitive to the differences between water and sucrose conditions. For example, Figure 3F shows that escape speed was significantly higher in the sucrose than in the water condition under high-contrast stimulation.

    Thank you for pointing this out. To control for the potential confounds related to internal state, mice were not water-deprived under any of the three conditions in Figures 3A-3H. We will clarify this in the main text and Methods. For Figures 3I-3M, which compare decision-making under no-reward and water conditions, we will conduct additional experiments using non-deprived mice in the water condition.

    (3) There is very little methodological information on behavioural quantification. For example, what is hiding latency? Is this the same are reaction time? Time to reach the safe zone? What exactly is distance fled? I don't understand how this can vary between 20 and 100cm. Presumably, the 20cm flights don't reach the safe place, since the threat is roughly at the same location for each trial? How is the end of a flight determined? How is duration measured in reward zone measures, e.g., from when to when? How is fleeing onset determined?

    Hiding latency was defined as the time from stimulus onset to the animal’s arrival at the safe zone. Reaction time was quantified as the latency to flee, measured from stimulus onset to the initiation of the first flight state. The flight state was defined as locomotion exceeding 10 cm at a speed greater than 10 cm/s. Distance fled was defined as the distance covered between stimulus onset and offset for all trials. However, in trials classified as no reaction or freezing, this measure does not accurately reflect escape behavior. We will therefore rename it as distance under threat to better capture its meaning. The reward zone was defined as the region within 15 cm of the reward port at the end of the arena. Duration in the reward zone was measured as the time spent within this region during the 20 seconds following stimulus onset. In Figure 4E, the percentage of time spent in the reward zone was calculated relative to the total time the mouse remained in the arena during the 2-hour social session.

    All definitions and additional details on behavioral quantification will be included in the revised Methods section.

    (4) There is little methodological information on how the model was fit (for example, it is surprising that in the no reward condition, the r parameter is exactly 0. What this constrained in any way), and none of the fit parameters have uncertainty measures so it is not possible to assess whether there are actually any differences in parameters that are statistically significant.

    We appreciate the comment and agree that further clarification is needed. We will provide a more detailed description of the model fitting procedure in the revised Methods section. Specifically, the drift rate parameter (r), which reflects the perceived reward value, was constrained to zero in the no-reward condition. To enable statistical comparison across conditions, we will report uncertainty measures for all fit parameters.

    Comments on the revised manuscript:

    The manuscript has been revised and improved significantly by the addition of methodological details and new analysis. I remain, however, unconvinced by the argument that increased vigilance in the presence of reward leads to heightened escape behaviour.

    In response to my criticism that the work does not measure vigilance directly, the authors have included measures of foraging interval and foraging speed, which they state are "two direct behavioral analyses of vigilance". I disagree - like reaction time, foraging speed and foraging interval can be modulated, for example, by changes in threat sensitivity. Increased threat sensitivity comes with diverse behavioral changes that may well include increased vigilance, but foraging interval and foraging speed can certainly change without the animal expressing increased vigilance behaviors. A bigger issue I still have though, is with the conclusion that the presence of reward increases "direct escape behaviors". Comparing the no reward, water and sucrose groups indeed shows a difference (which is now clear after the split into early and late phases), but the issue is that these are different mice. As the text is written, is sounds like introducing reward will acutely increase escape. But if we look at the raw data show in Figure 2C, what I think is happening is that the presence of reward is decreasing habituation to the stimulus. The data for trials 1 and 10 in the three conditions show this - there is habituation with no reward (reaction times are all shifting to the right), a bit less with water and very little with sucrose. This is interesting in its own right and we can speculate why it might be happening, but I think this is conceptually different from what the authors are proposing.

    We agree that vigilance is not directly observable as a single variable. Our intent was not to claim that foraging speed and foraging interval provide a direct measure of vigilance, but rather to suggest that they may serve as indirect behavioral correlates.

    We also considered an alternative interpretation: these two measures could reflect perceived reward value under high-threat conditions across distinct reward types. If that were the case, animals would be expected to exhibit shorter intervals and faster speeds across no reward, water, and sucrose conditions. However, our data do not support this interpretation (Figures 3L and 3M), suggesting that these measures are more likely correlated with vigilance.

    Furthermore, it is unlikely that changes in foraging interval and speed are driven by altered threat sensitivity, as animals could not see the threat during most of the foraging bout and only encountered it at the end.

    Regarding the conclusion that the presence of reward increases direct escape behaviors, our interpretation is that increased reward value reduces habituation, thereby maintaining higher vigilance during the late phase. This was discussed in the second-to-last paragraph of the "Economic and social modulations of innate decision-making under threat" subsection in the Discussion.

    Reviewer #3 (Public review):

    Male mice were tested in a classic behavioral "flee the looming stimulus" paradigm. This is a purely behavioral study; no neural analyses were done. Mice were housed socially, but faced the looming stimulus individually, using an elegant automated tunnel (see videos for clarity).

    The additional changes made to the paper clarify the work done. While there are some limitations (male mice, weird stimulus), the general results are interesting and a valuable addition to the experimental literature. The main claim of the paper is that the different rewards (none, water, sucrose) did not change the escape properties early in learning, but did late, particularly that in the late (already experienced) conditions, reward value (assuming sucrose > water > no reward) interacted with the salience of the looming stimulus (light gray, dark gray). (Panels 3D, 3G, 3K, 3N).

    For readers, I want to note that one of the most interesting results is actually in Figure S2, where they find that a looming stimulus behind the mouse still makes a mouse run to the nest. In these conditions, the mouse runs past the looming stimulus to get to safety! (I also do love the video of the mouse running around the barriers like a snake to get home.)

    I have a few minor clarification questions and a few notes that I think would be useful additions for authors and readers to think about.

    Dominance: What does the mouse social science literature say about the "test tube" test? What can we conclude from this test? This would be useful when trying to understand what is causing the dominance/submissive difference in responses. Figure 4 shows that the dominant mice are more risk-averse than the submissive mice. Is "dominance" in the test-tube actually a measure of risk-seeking? Is the issue that the submissive mice don't think they can get back to the food-site easily, so they are less willing to sacrifice the current (if dangerous) foraging opportunity? Is the issue that the submissive mice can't get back to the nest? As I understand it, the nest was always available to all the mice, so I suspect inability to get to the nest is an unlikely hypotheses. Is the issue that the submissive mice also don't feel safe in the nest?

    The tube test is a widely used assay in the rodent social behavior literature to assess dominance hierarchies, operationally defined by the ability of one animal to force its opponent to retreat from a narrow tube. Importantly, this assay does not directly measure risk-seeking or anxiety-related traits, but rather competitive outcomes during social conflict. Furthermore, our data indicate that the behavioral responses of subordinate mice to looming stimuli are primarily driven by the visual threat itself rather than by social avoidance. This point was elaborated in the second paragraph of the “Social modulation of innate decision-making” subsection in the Results section.

    Limitations of the study: There is an acknowledged limitation to male mice, and the limitations of the small data sets that are typical of such experiments. In addition, however, it is also worth noting the strangeness of the looming stimulus, which is revealed clearly in the videos. The stimulus is a repeating growing circle, growing in a single location within the environment. The stimulus repeats 10 times, once per second. This is not what an attacking hawk or owl would look like. (I now have this image of an owl diving down, and then teleporting up and diving down again.) Note - I am fine with this stimulus. It produces an interesting experiment and interesting results. I do not think the authors need to change anything in their paper, but readers need to recognize that this is not a "looming predator".

    These "limitations" are better seen as "caveats" when folding these results in with the rest of the literature that has gone before and the literature to come. (Generally, I do not believe that science works by studies making discoveries that change how we think about problems - instead, science works by studies adding to the literature that we integrate in with the rest of the literature.) Thus, these caveats should not be taken as problems with the study or as fixes that need to be done. Instead, they are notes for future researchers to notice if differences are found in any future studies.

    Thus, my only suggestion is that I think authors could write a more careful paper by using the past and subjunctive tense appropriately. Experimental observations should be in past tense, as in "the influence of reward was context-dependent and emerged in the late phase" instead of "the influence of reward is context-dependent and emerges in the late phase" - it emerged in the late phase this once - it might not in future experiments, not due to any fault in this experiment nor due to replicability problems, but rather due to unexpected differences between this and those future experiments. At which point, it will be up to those future experiments to determine the difference. Similarly, large conclusions should be in the subjunctive tense, as in "these data suggest that threat intensity is likely to be the primary determinant of decision making" rather than "threat intensity is the primary determinant of decision making", because those are hypotheses not facts.

    We thank the reviewer for the helpful suggestions and have revised the Abstract accordingly.

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

    Public Reviews:

    Reviewer #1 (Public review):

    Summary:

    This study investigates how mice make defensive decisions when exposed to visual threats and how those decisions are influenced by reward value and social hierarchy. Using a naturalistic foraging setup and looming stimuli, the authors show that higher threat leads to faster escape, while lower threat allows mice to weigh reward value. Dominant mice behave more cautiously, showing higher vigilance. The behavioral findings are further supported by a computational model aimed at capturing how different factors shape decisions.

    Strengths:

    (1) The behavioral paradigm is well-designed and ethologically relevant, capturing instinctive responses in a controlled setting.

    (2) The paper addresses an important question: how defensive behaviors are influenced by social and value-based factors.

    (3) The classification of behavioral responses using machine learning is a solid methodological choice that improves reproducibility.

    Weaknesses:

    (1) Key parts of the methods are hard to follow, especially how trials are selected and whether learning across trials is fully controlled for. For example, it is unclear whether animals are in the nest during the looming stimulus presentations. The main text and methods should clarify whether multiple mice are in the nest simultaneously and whether only one mouse is in the arena during looming exposure. From the description, it seems that all mice may be freely exploring during some phases, but only one is allowed in the arena at a time during stimulus presentation. This point is important for understanding the social context and potential interactions, and should be clearly explained in both the main text and methods.

    We agree that these details are essential and have clarified them in the Methods. When the door system operated normally, only one mouse was allowed in the arena during looming exposure. Specifically, when all mice were in the nest, the nest-tunnel door was open and the tunnel-arena door was closed. Once a single mouse entered the tunnel, as detected by an OpenMV camera, the nest-tunnel door closed and the tunnel-arena opened, ensuring that only that mouse could enter the arena.

    Habituation was conducted over two days. On day 1, five mice were placed together in the nest for 30 minutes with all doors closed. Each mouse was then placed individually in the nest and allowed to freely explore the arena for 10 minutes under normal door operation. Finally, all mice were returned to the nest with all doors open and allowed for free exploration for 2 hours. On day 2, each mouse was placed individually in the nest and given an additional 1 hour of exploration under normal door operation.

    (2) It is often unclear whether the data shown (especially in the main summary figures) come from the first trial or are averages across several exposures. When is the cut-off for trials of each animal? How do we know how many trial presentations were considered, and how learning at different rates between individuals is taken into account when plotting all animals together? This is important because the looming stimulus is learned to be harmless very quickly, so the trial number strongly affects interpretation.

    We observed substantial inter-individual variability in habituation to looming stimuli, with a sharp decline in defensive responses over the first few trials followed by more gradual changes. To account for this, we segmented trials for each animal into two phases: an early rapidhabituation phase and a later stable phase. Analyzing these phases separately revealed that threat intensity dominates behavior in the early phase, whereas both threat and reward significantly influence behavior in the late phase. These results are now presented in revised Figures 2 and 3. Analyses restricted to first trials are included in Figure S5.

    (3) The reward-related effects are difficult to interpret without a clearer separation of learning vs first responses.

    As noted above, we have re-analyzed our data to account for learning effects.

    (4) The model reproduces observed patterns but adds limited explanatory or predictive power. It does not integrate major findings like social hierarchy. Its impact would be greatly improved if the authors used it to predict outcomes under novel or intermediate conditions.

    We have substantially revised the modeling analysis. The model is now fitted to behavioral data from the late phase and used to predict outcomes across additional conditions, including the early phase behavior and rank-dependent behavioral differences. The model successfully captures behavioral patterns across these conditions, supporting its predictive value beyond descriptive fitting.

    (5) Some conclusions (e.g., about vigilance increasing with reward) are counterintuitive and need stronger support or alternative explanations. Regarding the interpretation of social differences in area coverage, it's also possible that the observed behavioral differences reflect access to the nesting space. Dominant mice may control the nest, forcing subordinates to remain in the open arena even during or after looming stimuli. In this case, subordinates may be choosing between the threat of the dominant mouse and the external visual threat. The current data do not distinguish between these possibilities, and the authors do not provide evidence to support one interpretation over the other. Including this alternative explanation or providing data that addresses it would strengthen the conclusions.

    To support the interpretation of increased vigilance with reward under high-threat conditions, we analyzed additional behavioral measures beyond latency to flee. Rewarded mice showed longer foraging interval and slower foraging speed, both consistent with elevated vigilance (Figures 3L and 3M).

    To address the alternative explanation that subordinate mice may remain in the arena due to restricted nest access, we compared arena occupancy before, during, and after looming exposure. Although subordinates spent more time in the arena before looming, this difference disappeared during and after looming exposure (Figures 4C). Moreover, dominant and subordinate mice were

    equally likely to flee to the nest during escape trials. These findings rule out nest access restrictions as an explanation for the observed rank-dependent differences in defensive behaviors.

    (6) While potential neural circuits are mentioned in the discussion, an earlier introduction of candidate brain regions and their relevance to threat and value processing would help ground the study in existing systems neuroscience.

    We have revised the Introduction to incorporate relevant brain regions and neural circuits.

    (7) Some figures are difficult to interpret without clearer trial/mouse labeling, and a few claims in the text are stronger than what the data fully support. Figure 3H is done for low contrast, but the interesting findings will be to do this experiment with high contrast. Figure 4H - I don't understand this part. If the amount of time in the center after the loom changes for subordinate mice, how does this lead to the conclusion that they spend most of their time in the reward zone?. Figure 3A - The example shown does not seem representative of the claim that high contrast stimuli are more likely to trigger escape. In particular, the 10% sucrose condition appears to show more arena visits under low contrast than high contrast, which seems to contradict that interpretation. Also, the plot currently uses trials on the Y-axis, but it would be more informative to show one line per animal, using only the first trial for each. This would help separate initial threat responses from learning effects and clarify individual variability.

    We have substantially revised the figures. Results from trial segmentation based on individual habituation are now explicitly presented in Figures 2 and 3, and analyses using only the first trials are provided in Figure S5 to separate initial responses from learning effects.

    Regarding the original Figure 4H, we are not entirely certain about the concern. In this panel, we measured time spent in the reward zone, which is defined as the region within 10 cm of the reward port at the end of the arena, not the center of the arena, during looming exposure. Subordinate mice spent significantly more time in the reward zone than dominant mice. We have further clarified this in the revised manuscript.

    (8) The analysis does not explore individual variability in behavior, which could be an important source of structure in the data. Without this, it is difficult to know whether social hierarchy alone explains behavioral differences or if other stable traits (e.g., anxiety level, prior experiences) also contribute.

    We observed substantial individual variability in both dominant and subordinate mice, even on the first trial (Figure S7). Paired dominant–subordinate comparisons were used to isolate rankdependent effects.

    (9) The study shows robust looming responses in group-housed animals, which contrasts with other studies that often require single housing to elicit reliable defensive responses. It would be valuable for the authors to discuss why their results differ in this regard and whether housing conditions might interact with social rank or habituation.

    Robust looming-evoked defensive responses have been reported in both group- and singlehoused mice (Yilmaz and Meister, 2013, Lenzi et al., 2022), although single-housed mice habituate more rapidly. We have now discussed the potential interactions between housing conditions, social rank, and habituation in defensive behaviors in the revised manuscript.

    Reviewer #2 (Public review):

    Zhe Li and colleagues investigate how mice exposed to visual threats and rewards balance their decisions in favour of consuming rewards or engaging in defensive actions. By varying threat intensity and reward value, they first confirm previous findings showing that defensive responses increase with threat intensity and that there is habituation to the threat stimulus. They then find that water-deprived mice have a reduced probability of escaping from low contrast visual looming stimuli when water or sucrose are offered in the environment, but that when the stimulus contrast is high, the presence of sucrose or water increases the probability of escape. By analysing behaviour metrics such as the latency to flee from the threat stimulus, they suggest that this increase in threat sensitivity is due to increased vigilance. Analysis of this behaviour as a function of social hierarchy shows that dominant mice have higher threat sensitivity, which is also interpreted as being due to increased vigilance. These results are captured by a drift diffusion model variant that incorporates threat intensity and reward value.

    The main contribution of this work is to quantify how the presence of water or sucrose in waterdeprived mice affects escape behaviour. The differential effects of reward between the low and high contrast conditions are intriguing, but I find the interpretation that vigilance plays a major role in this process is not supported by the data. The idea that reward value exerts some form of graded modulation of the escape response is also not supported by the data. In addition, there is very limited methodological information, which makes assessing the quality of some of the analyses difficult, and there is no quantification of the quality of the model fits.

    (1) The main measure of vigilance in this work is reaction time. While reaction time can indeed be affected by vigilance, reaction times can vary as a function of many variables, and be different for the same level of vigilance. For example, a primate performing the random dot motion task exhibits differences in reaction times that can be explained entirely by the stimulus strength. Reaction time is therefore not a sound measure of vigilance, and if a goal of this work is to investigate this parameter, then it should be measured. There is some attempt at doing this for a subset of the data in Figure 3H, by looking at differences in the action of monitoring the visual field (presumably a rearing motion, though this is not described) between the first and second trials in the presence of sucrose. I find this an extremely contrived measure. What is the rationale for analysing only the difference between the first and second trials? Also, the results are only statistically significant because the first trial in the sucrose condition happens to have zero up action bouts, in contrast to all other conditions. I am afraid that the statistics are not solid here. When analysing the effects of dominance, a vigilance metric is the time spent in the reward zone. Why is this a measure of vigilance? More generally, measuring vigilance of threats in mice requires monitoring the position of the eyes, which previous work has shown is biased to the upper visual field, consistent with the threat ecology of rodents.

    We agree that reaction time can be influenced by multiple factors, including stimulus strength. Consistent with this, reaction times (i.e. latencies to flee) were substantially shorter under highcontrast conditions. However, even under the same high-contrast condition, reaction times were significantly shorter in the reward conditions compared to the no-reward condition, suggesting that other factors such as vigilance may contribute.

    Regarding the measurement of vigilance, in addition to the latency to flee, we analyzed two additional behavioral measures related to vigilance. First, we examined the foraging interval. Our hypothesis was that more vigilant animals would wait longer before re-entering the reward zone following threat exposure. Consistent with this prediction, mice under sucrose and water reward conditions showed significantly longer foraging intervals than those under no-reward conditions (Figure 3L). Second, we analyzed the foraging speed as mice approached the reward. Increased vigilance should lead to more cautious and therefore slower movements. Our results support this, as mice moved more slowly towards the reward under sucrose conditions (Figure 3M). Taken together, these three measures consistently indicate that mice exhibit increased vigilance under sucrose reward in high-threat conditions.

    (2) In both low and high contrast conditions, there are differences in escape behaviour between no reward and water or sucrose presence, but no statistically significant differences between water and sucrose (eg, Figure 3B). I therefore find that statements about reward value are not supported by the data, which only show differences between the presence or absence of reward. Furthermore, there is a confound in these experiments, because according to the methods, mice in the no-reward condition were not water deprived. It is thus possible that the differences in behaviour arise from differences in the underlying state.

    Our new analysis, which segments behavior into an early adaptive phase and a late stable phase, reveals a statistically significant difference between water and sucrose rewards in the late phase (Figure 3H), supporting a graded effect of reward value.

    To control for the potential confounds related to internal state, mice were not water-deprived in all reward conditions. We have clarified this in the revised manuscript.

    (3) There is very little methodological information on behavioural quantification. For example, what is hiding latency? Is this the same are reaction time? Time to reach the safe zone? What exactly is distance fled? I don't understand how this can vary between 20 and 100cm. Presumably, the 20cm flights don't reach the safe place, since the threat is roughly at the same location for each trial? How is the end of a flight determined? How is duration measured in reward zone measures, e.g., from when to when? How is fleeing onset determined?

    Hiding latency was defined as the time from stimulus onset to the animal’s arrival at the safe zone. Reaction time was quantified as the latency to flee, measured from stimulus onset to the initiation of the first flight state. The flight state was defined as locomotion exceeding 10 cm at a speed greater than 10 cm/s. Distance fled was defined as the distance covered between stimulus onset and offset for all trials. However, in trials classified as no reaction or freezing, this measure does not accurately reflect escape behavior. We will therefore rename it as distance under threat to better capture its meaning. The reward zone was defined as the region within 10 cm of the reward port at the end of the arena. Duration in the reward zone was measured as the time spent within this region during the 20 seconds following stimulus onset. In Figure 4E, the percentage of time spent in the reward zone was calculated relative to the total time the mouse remained in the arena during the 2-hour social session.

    All definitions and additional details on behavioral quantification have been included in the revised Methods section.

    (4) There is little methodological information on how the model was fit (for example, it is surprising that in the no reward condition, the r parameter is exactly 0. What this constrained in any way), and none of the fit parameters have uncertainty measures so it is not possible to assess whether there are actually any differences in parameters that are statistically significant.

    We have provided a detailed description of the model fitting procedure in the revised Methods section. Specifically, the reward-value parameter (r) was constrained to zero in the no-reward condition. We have plotted how the overall loss varies with differeent parameters (Figure S9).

    Reviewer #3 (Public review):

    Male mice were tested in a classic behavioral "flee the looming stimulus" paradigm. This is a purely behavioral study; no neural analyses were done. Mice were housed socially, but faced the looming stimulus individually. Drift-diffusion modeling found that reward-level interacted with threat level such that at low-threat levels, reward contrasted with threat as classically expected (high reward overwhelms low threat, low threat overwhelms low reward), but that reward aligned with threat at higher threat levels.

    Note that they define threat level by the darkness of the looming stimulus. I am not sure that darker stimuli are more threatening to mice. But maybe. Figure 3 shows that mice react more quickly to high contrast looming stimuli, but can the authors distinguish between the ability to detect the visual signal from considering it a more dangerous threat? (The fact that vigilance makes a difference in the high contrast condition, not the low contrast condition, actually supports the author's hypotheses here.)

    Regarding the interpretation of stimulus contrast as a proxy for threat level, we agree it is crucial to distinguish improved detection from heightened threat perception. To address this, we examined not only latency to flee but also escape distance and peak escape speed, two measures that reflect the intensity of the defensive response. If contrast only influenced detection, we would expect differences in latency but not in escape distance or speed. All three measures differed significantly across contrast conditions, supporting the interpretation that high-contrast stimuli are perceived as more threatening rather than simply more detectable. Furthermore, manual review of "no response" trials confirmed reliable detection in both conditions, with only three potential "missed" trials out of 117 under low contrast (Figure S3B). We have included this discussion in the revised manuscript.

    The drift-diffusion model (DDM) is fine. I note that the authors included a "leakage rate", which is not a standard DDM parameter (although I like including it). I would have liked to see more about the parameters. What were the distributions? What did the parameters correlate with behaviorally? I would have liked to see distributions of the parameters under the different conditions and different animals. Figure 2C shows the progression of learning. How do the fit parameters change over time as mice shift from choice to choice? How do the parameters change over mice? How do the parameters change over distance to the threat/distance to safety (as per Fanselow and Lester 1988)? They did a supplemental experiment where the threat arrived halfway along the corridor - we could get a lot more detail about that experiment - how did it change the modeling?

    Because our model is fit to the variance of latency distributions, it cannot be applied to singletrial data. Instead, we analyzed how decisions and latencies vary as functions of the fitted threat gain and reward value parameters (Figures 5G and 5H). We have also introduced a simplified deterministic model to further elucidate the decision-making process.

    Regarding the influence of distance to the threat, we conducted additional experiments, presenting the looming stimulus at the end of the arena when the mouse was at different distances from it (Figures S2C–G). We found that as the prey-threat distance increased, mice showed less direct escape behavior, with longer latencies to flee and slower escape speeds. This is consistent with the predatory imminence continuum theory (Fanselow and Lester, 1988), which describes graded defensive behaviors tuned to perceived threat level.

    Regarding the influence of distance to safety, our data indicate that it did not significantly affect defensive responses (Figures S2H and S2I). To test this further, we introduced barriers that lengthened the return path to the safe zone. We found that defensive decisions were not correlated with the distance to the safe zone (Figures S2J and S2K), suggesting that once a threat is detected, animals prioritize escape initiation over evaluating the exact path to safety.

    Overall, this is a reasonable study showing mostly unsurprising results. I think the authors could do more to connect the vigilance question to their results (which seems somewhat new to me).

    We have expanded our analysis of vigilance. In addition to escape latency, we examined the foraging interval and foraging speed. We hypothesized that more vigilant animals would wait longer before re-entering the reward zone following a threat and would approach the reward more slowly. Consistent with this prediction, mice in the sucrose- and water-reward conditions exhibited significantly longer foraging intervals and slower foraging speeds compared to those in the no-reward condition (Figures 3M and 3N). Together, these three measures consistently demonstrate that mice display heightened vigilance under high-threat, high-reward conditions.

    Although the data appear generally fine and the modeling reasonable, the authors do not do the necessary work to set themselves within the extensive literature on decision-making in mice retreating from threats.

    First of all, this is not a new paradigm; variants of this paradigm have been used since at least the 1980s. There is an *extensive* literature on this, including extensive theoretical work on the relation of fear and other motivational factors. I recommend starting with the classic Fanselow and Lester 1988 paper (which they cite, but only in passing), and the reviews by Dean Mobbs and Jeansok Kim, and by Denis Paré and Greg Quirk, which have explicit theoretical proposals that the authors can compare their results to. I would also recommend that the authors look into the "active avoidance" literature. Moreover, to talk about a mouse running from a looming stimulus without addressing the other "flee the predator" tasks is to miss a huge space for understanding their results. Again, I would start with the reviews above, but also strongly urge the authors to look at the Robogator task (work by June-Seek Choi and Jeansok Kim, work by Denis Paré, and others).

    Similarly, in their anatomical review, they do not mention the amygdala. Given the extensive literature on the role of the amygdala in retreating from danger, both in terms of active avoidance and in terms of encoding the danger itself, it would surprise me greatly if this behavior does not involve amygdala processing. (If there is evidence that the amygdala does not play a role here, but that the superior colliculus does, then that would be a *very* important result that needs to be folded into our understanding of decision-making systems and neural computational processing.)

    Second, there is an extensive economic literature on non-human animals in general and on rodents in particular. Again, the authors seem unaware of this work, which would provide them with important data and theories to broaden the impact of their results (by placing them within the literature). First, there are explicit economic literatures in terms of positively-valenced conflicts (e.g., neuroeconomics within the primate literature, sequential foraging and delaydiscounting tasks within the rodent literature), but also there is a long history within the rodent conditioning world, such as the classic work by Len Green and Peter Shizgal. I would strongly urge the authors to explore the motivational conflict literature by people like Gavin McNally, Greg Quirk, and Mark Andermann. Again, putting their results into this literature will increase the impact of their experiment and modeling.

    We have substantially revised the manuscript to contextualize our findings within the extensive literature on defensive behavior and decision-making. The revised Introduction and Discussion now integrate key theoretical frameworks, such as the predatory imminence continuum, and cite relevant work on active avoidance and other "flee the predator" paradigms (e.g., the Robogator task).

    We have also incorporated perspectives from neuroeconomics and motivational conflict, including literature on sequential foraging, delay-discounting tasks, and relevant rodent studies. Furthermore, we now discuss the potential contributions of specific brain regions, including the superior colliculus and the amygdala, to the economic and social modulation of innate defensive decisions in response to visual threats.

    Recommendations for the authors:

    Reviewing Editor Comments:

    These additional recommendations are generally consistent and overlapping across reviewers, particularly Reviewer #1 and 2, so it is advisable to undertake these changes/additions.

    Reviewer #1 (Recommendations for the authors):

    (1) Experimental methods and trial structure need clarification: It is often unclear how many trials were included per condition, per mouse, and whether the key behavioral effects (especially reward-related changes) were observed early in the session or after repeated stimulus exposure. For example, in several reward-related plots (e.g., Figure 3), it is not specified whether results are driven by early or later trials. Since the authors themselves report rapid learning of the looming stimulus (habituation), it is critical to state how many trials were included in each comparison, and to analyze whether effects hold on the first exposure and not the rest. Otherwise, conclusions about value-based behavior are hard to separate from learning effects, which may also differ between individuals. Specifically, the methods section is vague and hard to follow.

    We have substantially expanded the Methods section with additional details to improve clarity.

    To account for individual variability in habituation to the looming stimulus, we segmented trials for each animal into early and late phases. We demonstrate that threat level is the dominant factor driving behavioral responses in the early phase, while both threat level and reward condition shape behavior in the late phase. We have substantially revised Figures 2 and 3 to reflect these changes.

    (2) Add a summary of experimental design: A table or schematic summarizing the trial structure, experimental groups, reward/threat conditions, and the timeline of exposures would greatly improve clarity.

    We have added a schematic to Figure 2 summarizing the trial structure, experimental groups, reward and threat conditions, and the overall timeline.

    (3) Replot key results using only the first trial per mouse: This would allow readers to assess the first (not learned) responses and help control for habituation/suppression.

    We have replotted behavioral results using only the first trial from each mouse and included these analyses in Figure S5. These results confirm that threat level is the dominant factor driving the initial response to looming stimuli.

    (4) The model needs stronger justification and predictive value: As it stands, the model primarily fits the existing data and does not offer new insights beyond what is already evident from the behavioral results.

    Important findings, such as social hierarchy effects and habituation dynamics, are not captured in the model, reducing its relevance to the full dataset.

    The drift-diffusion framework is widely used, and in this implementation appears to have been adjusted post hoc to fit the observed data rather than generating new conceptual advances. No comparison with simpler models is included. Without testing simpler or alternative models, it is not clear whether the added complexity is necessary or justified.

    Use the model to generate and test predictions: to increase the model's contribution, the authors could simulate new conditions. Suggested experiments include:

    a) Predicting escape probability and latency at intermediate threat intensities to test whether behavior shifts gradually or abruptly.

    b) Using the model's habituation parameters to predict changes in escape behavior over repeated exposures.

    c) Adjusting vigilance or threat gain parameters to simulate dominant versus subordinate animals, and comparing model predictions to actual behavioral differences based on social rank.

    We have substantially revised the modeling section to address these concerns. The updated model is now fitted to behavioral data from the late phase of the reward–threat experiments and used to generate predictions for the early phase and for rank-dependent behavioral differences.

    The model accurately captures behavioral patterns across these conditions, demonstrating predictive power beyond descriptive fitting. Accordingly, we have removed the habituation component. Furthermore, we have introduced a simplified deterministic model in the revised manuscript to further understand the decision-making process.

    (5) Clarify housing and arena access conditions: It is unclear from the text whether all mice are in the nest during looming presentations and whether only one mouse is in the arena during the stimulus. This is important for understanding the social context of each trial and should be explained in the main text and methods.

    We have clarified this point in the Methods section. Under normal door operation, only one mouse was allowed in the arena during looming exposure. Specifically, when all mice were in the nest, the nest-tunnel door was open and the tunnel-arena door was closed. Once a single mouse entered the tunnel, as detected by an OpenMV camera, the nest-tunnel door closed and the tunnel-arena opened, ensuring that only that mouse could enter the arena.

    (6) Alternative interpretation of subordinate behavior: differences in area coverage and time in the reward zone may not reflect reduced vigilance, but rather avoidance of dominant mice. Subordinates may remain in the open arena to avoid conflict. The authors do not provide evidence distinguishing between these interpretations, and this should be addressed.

    To address the alternative explanation that subordinate mice may remain in the arena due to restricted nest access, we compared arena occupancy before, during, and after looming exposure (Figure 4C). Before looming exposure, subordinate mice spent significantly more time in the arena, consistent with the idea that they may perceive a social threat from the dominant mouse in the absence of any external threat. However, this difference disappeared during and after looming exposure. This shift suggests that the presence of an external threat alters the social dynamic, reducing the influence of dominance on nest access.

    To further assess whether dominant mice blocked subordinate access to the nest during threatdriven escapes, we analyzed the fraction of escape trials in which mice returned to the nest (Figure 4D). We found no significant difference between dominant and subordinate mice, indicating that dominant mice did not restrict nest access during these trials. Importantly, rank differences in reward-zone occupancy cannot be explained by nest exclusion, as mice do not need to return to the nest when escaping the threat—they can flee directly to the safe zone. Thus, nest access limitations do not account for the observed rank-dependent patterns.

    We agree with the reviewer that reward-zone occupancy should not be interpreted as reduced vigilance in subordinate mice; instead, it likely reflects higher perceived reward value. The manuscript has been revised accordingly.

    (7) Address why robust looming responses were observed in group-housed mice: previous studies often require single housing to elicit strong defensive responses. The authors should explain why their setup yields robust results in group-housed animals and whether housing conditions may interact with dominance or habituation.

    Looming exposure elicits robust defensive behaviors in both group- and single-housed mice (Yilmaz and Meister, 2013, Lenzi et al., 2022), with single-housed animals habituating more quickly to the stimulus (Lenzi et al., 2022). We have now discussed how housing conditions may interact with social rank and habituation to shape defensive behaviors in the revised manuscript.

    For the social-rank experiments, we intentionally co-housed dominant and subordinate mice to maintain a stable hierarchy. This choice was motivated by two considerations. First, our goal was to investigate how social rank modulates defensive responses under ethologically relevant conditions, where mice naturally live in groups. Single housing would remove this social context. Second, singly housing mice can destabilize or eliminate rank relationships, making it difficult to interpret rank-dependent behavioral differences.

    (8) Add analysis of individual variability: trial-by-trial variability or stable behavioral tendencies in individual animals are not explored. This could explain part of the variation currently attributed to social rank.

    We have analyzed individual variability in both dominant and subordinate mice. We observed substantial variability across all behavioral measurements for each group (Figure S7). To attribute the observed behavioral differences to social hierarchy rather than to other individual traits, we conducted paired comparisons between dominant and subordinate mice (Figure 4).

    (9) Improve figure labeling and readability: some plots are ambiguous in terms of whether rows represent trials or animals. Overlapping points obscure the data in several figures, for example, Figure 3H, sucrose is n=4?- consider using jittered scatter plots, boxplots, or individual traces to improve clarity. Also same Figure axis Y is missing an 'e'.

    We have revised figures to improve clarity and corrected the typos.

    (10) Avoid overinterpretation of causal explanations: Statements such as "reward increases vigilance due to evolutionary pressure" or that "subordinates are less vigilant" go beyond what the current data can demonstrate and should be rephrased more cautiously.

    We have revised the manuscript to tone down the statement.

    Reviewer #2 (Recommendations for the authors):

    (1) Provide much more extensive methodological details on analyses and model fitting

    We have thoroughly revised the Methods section to provide extensive detail on both behavioral analyses and computational modeling, as outlined in our responses to points (3) and (4) of the Public Review.

    (2) Perform experiments or analyses that directly measure vigilance, if vigilance is to remain as a key explanation for the data.

    As detailed in our response to point (1) of the Public Review, we have supplemented the escape latency measure with two direct behavioral analyses of vigilance: foraging interval and foraging speed. This multi-metric approach robustly supports the interpretation of heightened vigilance.

    (3) Provide extra evidence for an effect of reward value, as opposed to the presence or absence of reward. Control for differences arising from the water deprivation state by performing the no reward condition experiments in water-deprived mice.

    All behavioral data in the reward–threat experiment were collected on normal (non-deprived) mice (Figures 2 and 3), which have been clarified in the revised manuscript. We have reanalyzed the data by segmenting trials into early and late phases for each animal. In the late phase, under low-threat conditions, the effect of reward value is reflected in significant differences between water and sucrose in terms of escape distance and time spent in the reward zone (Figures 3I and 3J). Under high-threat conditions, the reward value effect is reflected in significant differences in latency to flee and peak escape speed (Figures 3K and 3N).

    (4) Using drift rate to describe the "r" variable is confusing because the drift rate of the drift diffusion process is also determined by terms alpha, beta, and h-terms.

    We have termed “r” as the reward value in the revised manuscript.

    Reviewer #3 (Recommendations for the authors):

    (1) I would tone down some of the extreme statements about the problems of previous experiments (such as that most decision-making is on 2AFC). Lots of people do decision-making in serial foraging, fleeing, and other behavioral tasks. The classic Morris water-maze or Barnesmaze are decision-making tasks that aren't 2AFC. Serial foraging tasks, such as the Restaurant Row task aren't 2AFC. And, actually, lots of mouse behavior tasks are deciding when to stop on a treadmill for a reward. And, for that matter, your task isn't all that "realistic" - mice aren't evolved to flee looming disks, they are evolved to flee hawks and owls. This doesn't invalidate your task at all. I just recommend making it about your work in a positive way rather than others in a negative way.

    We have revised the manuscript to adopt a more positive framing of our work.

    (2) I also don't think there's much use in bringing in crayfish in a mouse task. Spend your time connecting to the other rodent data (mice and rats) instead.

    We agree and have revised the manuscript accordingly, focusing our discussion on relevant rodent literature to provide a more appropriate context for our findings.

    Minor concerns:

    (1) The authors use the term "cognitive control" without making clear what they mean. In general, the authors seem to have a view on decision-making as either being "reflexes" or "cognitive control". This is a very outdated perspective. Modern perspectives include multiple decision-making systems competing, separating these based on their computational properties, such as planning, procedural, instinctual, and, yes, reflexive. Current views on the kinds of behaviors they are discussing generally see fleeing as a transition from reflexive (tonic immobility, freezing) and instinctual responses (freezing, fleeing) to deliberative (anxiety) and procedural (habit). The authors might take a look at the recent Calvin and Redish (2025) paper for some ideas on this.

    We appreciate the reviewer’s insight regarding the term “cognitive control.” In our study, we used this term to emphasize that defensive responses to looming threats are not purely reflexive. Mice exhibit four distinct types of defensive decisions within a short time window, and these decisions are systematically modulated by reward value and social rank. Notably, reward modulation is bidirectional: high reward suppresses defensive responses under low-threat conditions but enhances them under high-threat conditions, indicating that animals integrate multiple sources of information rather than relying solely on instinctive mechanisms.

    We did not observe mid-trajectory aborts in mice, as reported in rats by Calvin & Redish (2025). This difference may reflect species-specific behavior or the nature of the threat: our looming stimulus is purely visual and non-harmful, whereas the robotic predator in their study presents a physical threat. We have revised the Discussion to clarify our use of “cognitive control” and to incorporate these perspectives.

    (2) Only male mice were used. This limits the conclusions that can be drawn.

    We acknowledge the limitation of using only male mice and have discussed this limitation in the revised manuscript.

    (3) Did the authors observe darting behavior? (Gruene...Shansky 2015).

    We did not observe darting behavior, characterized by rapid movement, as reported during inescapable fear conditioning. In our experiment, the mice consistently escaped towards the nest, in most trials, ran directly to the nest without stopping. Occasionally, under low contrast conditions, mice paused once or twice but never moved towards the reward.

    (4) How was only one mouse allowed into the linear arena at a time?

    When all mice were in the nest, the nest-tunnel door was open while the tunnel-arena door remained closed. When a single mouse entered the tunnel, as detected by the RFID and OpenMV camera system, the nest-tunnel door closed and the tunnel-arena door opened, allowing only that mouse to enter the arena. We have clarified this protocol in the Methods section.

    (5) I would like to see more extensive analyses of the animal's responses as a function of distance to the threat (as per Fanselow and Lester 1988).

    As detailed in our response to the public review, we conducted new experiments analyzing behavior as a function of prey–threat distance. The finding that defensive responsiveness decreases with increasing prey–threat distance is now presented in Figures S2C–G and discussed in the context of the predatory imminence continuum.

  8. eLife

    eLife Assessment

    The authors show that innate defensive behavior in mice is shaped by threat intensity, reward value, and social hierarchy, highlighting how value and social context influence instinctive decisions. The authors provide useful behavioural findings supported by strong data, yet the evidence is incomplete due to ambiguities about methodology and the computational model that remains largely descriptive.

  9. eLife

    Reviewer #1 (Public review):

    Summary:

    This study investigates how mice make defensive decisions when exposed to visual threats and how those decisions are influenced by reward value and social hierarchy. Using a naturalistic foraging setup and looming stimuli, the authors show that higher threat leads to faster escape, while lower threat allows mice to weigh reward value. Dominant mice behave more cautiously, showing higher vigilance. The behavioral findings are further supported by a computational model aimed at capturing how different factors shape decisions.

    Strengths:

    (1) The behavioral paradigm is well-designed and ethologically relevant, capturing instinctive responses in a controlled setting.

    (2) The paper addresses an important question: how defensive behaviors are influenced by social and value-based factors.

    (3) The classification of behavioral responses using machine learning is a solid methodological choice that improves reproducibility.

    Weaknesses:

    (1) Key parts of the methods are hard to follow, especially how trials are selected and whether learning across trials is fully controlled for. For example, it is unclear whether animals are in the nest during the looming stimulus presentations. The main text and methods should clarify whether multiple mice are in the nest simultaneously and whether only one mouse is in the arena during looming exposure. From the description, it seems that all mice may be freely exploring during some phases, but only one is allowed in the arena at a time during stimulus presentation. This point is important for understanding the social context and potential interactions, and should be clearly explained in both the main text and methods.

    (2) It is often unclear whether the data shown (especially in the main summary figures) come from the first trial or are averages across several exposures. When is the cut-off for trials of each animal? How do we know how many trial presentations were considered, and how learning at different rates between individuals is taken into account when plotting all animals together? This is important because the looming stimulus is learned to be harmless very quickly, so the trial number strongly affects interpretation.

    (3) The reward-related effects are difficult to interpret without a clearer separation of learning vs first responses.

    (4) The model reproduces observed patterns but adds limited explanatory or predictive power. It does not integrate major findings like social hierarchy. Its impact would be greatly improved if the authors used it to predict outcomes under novel or intermediate conditions.

    (5) Some conclusions (e.g., about vigilance increasing with reward) are counterintuitive and need stronger support or alternative explanations. Regarding the interpretation of social differences in area coverage, it's also possible that the observed behavioral differences reflect access to the nesting space. Dominant mice may control the nest, forcing subordinates to remain in the open arena even during or after looming stimuli. In this case, subordinates may be choosing between the threat of the dominant mouse and the external visual threat. The current data do not distinguish between these possibilities, and the authors do not provide evidence to support one interpretation over the other. Including this alternative explanation or providing data that addresses it would strengthen the conclusions.

    (6) While potential neural circuits are mentioned in the discussion, an earlier introduction of candidate brain regions and their relevance to threat and value processing would help ground the study in existing systems neuroscience.

    (7) Some figures are difficult to interpret without clearer trial/mouse labeling, and a few claims in the text are stronger than what the data fully support. Figure 3H is done for low contrast, but the interesting findings will be to do this experiment with high contrast. Figure 4H - I don't understand this part. If the amount of time in the center after the loom changes for subordinate mice, how does this lead to the conclusion that they spend most of their time in the reward zone?. Figure 3A - The example shown does not seem representative of the claim that high contrast stimuli are more likely to trigger escape. In particular, the 10% sucrose condition appears to show more arena visits under low contrast than high contrast, which seems to contradict that interpretation. Also, the plot currently uses trials on the Y-axis, but it would be more informative to show one line per animal, using only the first trial for each. This would help separate initial threat responses from learning effects and clarify individual variability.

    (8) The analysis does not explore individual variability in behavior, which could be an important source of structure in the data. Without this, it is difficult to know whether social hierarchy alone explains behavioral differences or if other stable traits (e.g., anxiety level, prior experiences) also contribute.

    (9) The study shows robust looming responses in group-housed animals, which contrasts with other studies that often require single housing to elicit reliable defensive responses. It would be valuable for the authors to discuss why their results differ in this regard and whether housing conditions might interact with social rank or habituation.

  10. eLife

    Reviewer #2 (Public review):

    Zhe Li and colleagues investigate how mice exposed to visual threats and rewards balance their decisions in favour of consuming rewards or engaging in defensive actions. By varying threat intensity and reward value, they first confirm previous findings showing that defensive responses increase with threat intensity and that there is habituation to the threat stimulus. They then find that water-deprived mice have a reduced probability of escaping from low contrast visual looming stimuli when water or sucrose are offered in the environment, but that when the stimulus contrast is high, the presence of sucrose or water increases the probability of escape. By analysing behaviour metrics such as the latency to flee from the threat stimulus, they suggest that this increase in threat sensitivity is due to increased vigilance. Analysis of this behaviour as a function of social hierarchy shows that dominant mice have higher threat sensitivity, which is also interpreted as being due to increased vigilance. These results are captured by a drift diffusion model variant that incorporates threat intensity and reward value.

    The main contribution of this work is to quantify how the presence of water or sucrose in water-deprived mice affects escape behaviour. The differential effects of reward between the low and high contrast conditions are intriguing, but I find the interpretation that vigilance plays a major role in this process is not supported by the data. The idea that reward value exerts some form of graded modulation of the escape response is also not supported by the data. In addition, there is very limited methodological information, which makes assessing the quality of some of the analyses difficult, and there is no quantification of the quality of the model fits.

    (1) The main measure of vigilance in this work is reaction time. While reaction time can indeed be affected by vigilance, reaction times can vary as a function of many variables, and be different for the same level of vigilance. For example, a primate performing the random dot motion task exhibits differences in reaction times that can be explained entirely by the stimulus strength. Reaction time is therefore not a sound measure of vigilance, and if a goal of this work is to investigate this parameter, then it should be measured. There is some attempt at doing this for a subset of the data in Figure 3H, by looking at differences in the action of monitoring the visual field (presumably a rearing motion, though this is not described) between the first and second trials in the presence of sucrose. I find this an extremely contrived measure. What is the rationale for analysing only the difference between the first and second trials? Also, the results are only statistically significant because the first trial in the sucrose condition happens to have zero up action bouts, in contrast to all other conditions. I am afraid that the statistics are not solid here. When analysing the effects of dominance, a vigilance metric is the time spent in the reward zone. Why is this a measure of vigilance? More generally, measuring vigilance of threats in mice requires monitoring the position of the eyes, which previous work has shown is biased to the upper visual field, consistent with the threat ecology of rodents.

    (2) In both low and high contrast conditions, there are differences in escape behaviour between no reward and water or sucrose presence, but no statistically significant differences between water and sucrose (eg, Figure 3B). I therefore find that statements about reward value are not supported by the data, which only show differences between the presence or absence of reward. Furthermore, there is a confound in these experiments, because according to the methods, mice in the no-reward condition were not water deprived. It is thus possible that the differences in behaviour arise from differences in the underlying state.

    (3) There is very little methodological information on behavioural quantification. For example, what is hiding latency? Is this the same are reaction time? Time to reach the safe zone? What exactly is distance fled? I don't understand how this can vary between 20 and 100cm. Presumably, the 20cm flights don't reach the safe place, since the threat is roughly at the same location for each trial? How is the end of a flight determined? How is duration measured in reward zone measures, e.g., from when to when? How is fleeing onset determined?

    (4) There is little methodological information on how the model was fit (for example, it is surprising that in the no reward condition, the r parameter is exactly 0. What this constrained in any way), and none of the fit parameters have uncertainty measures so it is not possible to assess whether there are actually any differences in parameters that are statistically significant.

  11. eLife

    Reviewer #3 (Public review):

    Male mice were tested in a classic behavioral "flee the looming stimulus" paradigm. This is a purely behavioral study; no neural analyses were done. Mice were housed socially, but faced the looming stimulus individually. Drift-diffusion modeling found that reward-level interacted with threat level such that at low-threat levels, reward contrasted with threat as classically expected (high reward overwhelms low threat, low threat overwhelms low reward), but that reward aligned with threat at higher threat levels.

    Note that they define threat level by the darkness of the looming stimulus. I am not sure that darker stimuli are more threatening to mice. But maybe. Figure 3 shows that mice react more quickly to high contrast looming stimuli, but can the authors distinguish between the ability to detect the visual signal from considering it a more dangerous threat? (The fact that vigilance makes a difference in the high contrast condition, not the low contrast condition, actually supports the author's hypotheses here.)

    The drift-diffusion model (DDM) is fine. I note that the authors included a "leakage rate", which is not a standard DDM parameter (although I like including it). I would have liked to see more about the parameters. What were the distributions? What did the parameters correlate with behaviorally? I would have liked to see distributions of the parameters under the different conditions and different animals. Figure 2C shows the progression of learning. How do the fit parameters change over time as mice shift from choice to choice? How do the parameters change over mice? How do the parameters change over distance to the threat/distance to safety (as per Fanselow and Lester 1988)? They did a supplemental experiment where the threat arrived halfway along the corridor - we could get a lot more detail about that experiment - how did it change the modeling?

    Overall, this is a reasonable study showing mostly unsurprising results. I think the authors could do more to connect the vigilance question to their results (which seems somewhat new to me).

    Although the data appear generally fine and the modeling reasonable, the authors do not do the necessary work to set themselves within the extensive literature on decision-making in mice retreating from threats.

    First of all, this is not a new paradigm; variants of this paradigm have been used since at least the 1980s. There is an *extensive* literature on this, including extensive theoretical work on the relation of fear and other motivational factors. I recommend starting with the classic Fanselow and Lester 1988 paper (which they cite, but only in passing), and the reviews by Dean Mobbs and Jeansok Kim, and by Denis Paré and Greg Quirk, which have explicit theoretical proposals that the authors can compare their results to. I would also recommend that the authors look into the "active avoidance" literature. Moreover, to talk about a mouse running from a looming stimulus without addressing the other "flee the predator" tasks is to miss a huge space for understanding their results. Again, I would start with the reviews above, but also strongly urge the authors to look at the Robogator task (work by June-Seek Choi and Jeansok Kim, work by Denis Paré, and others).

    Similarly, in their anatomical review, they do not mention the amygdala. Given the extensive literature on the role of the amygdala in retreating from danger, both in terms of active avoidance and in terms of encoding the danger itself, it would surprise me greatly if this behavior does not involve amygdala processing. (If there is evidence that the amygdala does not play a role here, but that the superior colliculus does, then that would be a *very* important result that needs to be folded into our understanding of decision-making systems and neural computational processing.)

    Second, there is an extensive economic literature on non-human animals in general and on rodents in particular. Again, the authors seem unaware of this work, which would provide them with important data and theories to broaden the impact of their results (by placing them within the literature). First, there are explicit economic literatures in terms of positively-valenced conflicts (e.g., neuroeconomics within the primate literature, sequential foraging and delay-discounting tasks within the rodent literature), but also there is a long history within the rodent conditioning world, such as the classic work by Len Green and Peter Shizgal. I would strongly urge the authors to explore the motivational conflict literature by people like Gavin McNally, Greg Quirk, and Mark Andermann. Again, putting their results into this literature will increase the impact of their experiment and modeling.

  12. Version published to 10.7554/elife.107306.1 on eLife
  13. Version published to 10.1101/2025.05.12.653401 on bioRxiv