Divergent spatiotemporal integration of whole-field visual motion in medaka and zebrafish larvae
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eLife Assessment
This important study provides a quantitative comparison of how zebrafish and medaka larvae process visual motion, revealing clear differences in how they integrate information across space and time. The evidence is convincing, combining a broad set of behavioral assays with response decomposition and mechanistic modeling that together support the central conclusions. Some aspects remain incomplete, particularly the link between the spatial and temporal findings, the extent to which the model accounts for the full range of behavioral results, and the framing of broader evolutionary or social interpretations. Overall, the work offers a careful and informative analysis that should be of broad interest to researchers studying visual processing, sensorimotor computation, and comparative neuroscience.
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Abstract
Cross-species comparisons offer leverage for identifying conserved and divergent neural computations underlying innate behavior. Visual motion integration is a fundamental operation that stabilizes position relative to the moving environment and supports object tracking, yet how its underlying algorithms vary across closely related vertebrate brains remains poorly understood. We investigated how zebrafish (Danio rerio) and medaka (Oryzias latipes) larvae implement visual motion integration using distinct spatiotemporal filters that trade speed for persistence through separable control modules. Using controlled whole-field motion stimuli, we found that medaka pool motion signals over visual fields nearly twice as large as those of zebrafish and exhibit enhanced weighting of peripheral inputs, whereas zebrafish rely more strongly on motion signals directly beneath the body. Temporally, zebrafish respond robustly to motion signals with lifetimes as short as 100 ms, whereas medaka require stimulus durations exceeding one second and maintain motion-driven activity for several seconds after stimulus offset. Decomposition of turning behavior revealed separable control modules for large and small corrective maneuvers, with species differences arising primarily from prolonged temporal integration in medaka small-turn control. Together, these differences reveal species-specific tuning of spatial kernels and temporal filters underlying visuomotor control. Our results demonstrate how alterations in basic computational motifs, spatiotemporal pooling, gain, and persistence, can generate divergent visuomotor strategies across closely related vertebrate brains.
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eLife Assessment
This important study provides a quantitative comparison of how zebrafish and medaka larvae process visual motion, revealing clear differences in how they integrate information across space and time. The evidence is convincing, combining a broad set of behavioral assays with response decomposition and mechanistic modeling that together support the central conclusions. Some aspects remain incomplete, particularly the link between the spatial and temporal findings, the extent to which the model accounts for the full range of behavioral results, and the framing of broader evolutionary or social interpretations. Overall, the work offers a careful and informative analysis that should be of broad interest to researchers studying visual processing, sensorimotor computation, and comparative neuroscience.
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Reviewer #1 (Public review):
Summary:
This study investigates how two closely related fish species differ in their processing of visual motion, with a focus on spatial and temporal integration underlying behavior. Using a series of behavioral assays combined with computational modeling, the authors identify clear species-specific differences in how visual information is integrated to guide movement.
Strengths:
A major strength of the work is the systematic and quantitative behavioral analysis, which reveals robust differences between species, including broader spatial integration and longer temporal persistence in medaka compared to zebrafish. The decomposition of behavior into distinct components provides a useful framework for interpreting these differences.
Weaknesses:
The computational modeling captures several key aspects of the …
Reviewer #1 (Public review):
Summary:
This study investigates how two closely related fish species differ in their processing of visual motion, with a focus on spatial and temporal integration underlying behavior. Using a series of behavioral assays combined with computational modeling, the authors identify clear species-specific differences in how visual information is integrated to guide movement.
Strengths:
A major strength of the work is the systematic and quantitative behavioral analysis, which reveals robust differences between species, including broader spatial integration and longer temporal persistence in medaka compared to zebrafish. The decomposition of behavior into distinct components provides a useful framework for interpreting these differences.
Weaknesses:
The computational modeling captures several key aspects of the observed temporal dynamics, particularly differences in response persistence. However, the modeling framework is primarily focused on temporal processing and does not incorporate spatial integration, which is a central finding of the study. In addition, some experimental observations, such as responses to short-duration stimuli and certain frequency-dependent features, are only partially reproduced. These limitations indicate that the link between the model and the full range of behavioral results remains incomplete.
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Reviewer #2 (Public review):
Summary:
This manuscript presents a comparative analysis of optomotor behavior in zebrafish and medaka larvae. Using multiple behavioral paradigms, the authors argue that the two species differ in both the spatial and temporal integration of visual motion. They further decompose turning behavior into large- and small-turn components and use a simple mechanistic model to capture several of the main response features. Overall, the study addresses an interesting question, and the comparative framework gives the work a clear conceptual appeal.
Strengths:
A major strength of the manuscript is the breadth of the behavioral analysis. The authors use several stimulus paradigms to probe spatial extent, temporal persistence, and response dynamics, which makes the cross-species comparison richer and more informative …
Reviewer #2 (Public review):
Summary:
This manuscript presents a comparative analysis of optomotor behavior in zebrafish and medaka larvae. Using multiple behavioral paradigms, the authors argue that the two species differ in both the spatial and temporal integration of visual motion. They further decompose turning behavior into large- and small-turn components and use a simple mechanistic model to capture several of the main response features. Overall, the study addresses an interesting question, and the comparative framework gives the work a clear conceptual appeal.
Strengths:
A major strength of the manuscript is the breadth of the behavioral analysis. The authors use several stimulus paradigms to probe spatial extent, temporal persistence, and response dynamics, which makes the cross-species comparison richer and more informative than a single-assay study. The decomposition into large and small turn components is also a useful feature of the work, as it provides a more structured account of where the species differences may arise. The modeling further helps organize the results and offers a useful framework for interpreting the behavioral differences.
Weaknesses:
The main limitations are in presentation and clarity rather than in the overall motivation or approach. In several places, it is difficult to determine exactly how some quantities are summarized statistically, and some figures and legends would benefit from clearer explanations. In addition, a few of the more specific interpretive claims would be strengthened by more explicit statistical framing and slightly clearer presentation. These issues appear addressable and do not detract from the overall interest of the study.
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Author response:
We appreciate the constructive feedback from the reviewers and are currently working diligently to address all concerns raised in both the public reviews and the recommendations for the authors. Below, we outline the revisions planned for the revised manuscript.
(1) We acknowledge the limitations of the current modeling framework regarding spatial integration, and we agree that the present model does not account for the short lifetime of the dot stimuli.
For spatial integration, our current data suggest a relatively narrow, center-weighted integration function in zebrafish, compared to a broader integration function in medaka. While incorporating such spatial weighting into the model would improve its completeness, we do not expect it to substantially alter our current interpretation of the underlying mechanisms.
Regardi…
Author response:
We appreciate the constructive feedback from the reviewers and are currently working diligently to address all concerns raised in both the public reviews and the recommendations for the authors. Below, we outline the revisions planned for the revised manuscript.
(1) We acknowledge the limitations of the current modeling framework regarding spatial integration, and we agree that the present model does not account for the short lifetime of the dot stimuli.
For spatial integration, our current data suggest a relatively narrow, center-weighted integration function in zebrafish, compared to a broader integration function in medaka. While incorporating such spatial weighting into the model would improve its completeness, we do not expect it to substantially alter our current interpretation of the underlying mechanisms.
Regarding the responses to short-lifetime dot stimuli, we hypothesize that medaka may possess local retinal receptive units that function as low-pass filters, as illustrated schematically in Figure 3e. At present, however, we believe that explicitly modeling this component would remain largely uninformative and would not substantially increase the explanatory power of the model.
In the revised manuscript, we will discuss these limitations and the possible neural implementations more explicitly in the Discussion section.
(2) We appreciate the reviewer’s comments regarding the clarity of data presentation and statistical descriptions.
In the revised manuscript, we will improve the clarity of the figures and legends and provide more explicit explanations of the statistical analyses and summary metrics used throughout the study. We will also revise several sections of the text to improve the framing and interpretation of the results.
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