From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response
Open accessAbstract
SUMMARY Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data.
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simZFish1.0 successfully replicates key behavioral aspects of zebrafish OMR, partly due to its tuning to match behaviors for limited orthogonal stimuli.
“The first iteration, simZFish1.0, successfully replicates key behavioral aspects of zebrafish OMR, partly due to its tuning to match behaviors for limited orthogonal stimuli (25).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
The Results section, “Identifying Critical Dimensions of Functional Connectivity” (page unavailable), says the circuit-model architecture could accurately predict behavioral data, and the Methods describe fitting predictions to responses under ten stimulus conditions. Our copy does not identify that model as simZFish1.0 or establish that its success was partly due to tuning on limited orthogonal stimuli. (LLM, conf=0.82)
Experimental — accuracy not yet measuredMedial/forward motion-responsive neurons are the most frequent monocular response type in real zebrafish, responding to medial and forward motion.
“Moreover, medial/forward motion-responsive neurons are the most frequent monocular response type in real zebrafish (iMM (25), cf.,’MoNL’ (32)), which respond to medial (nasalward) and forward (translational) motion.”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
In Results, ‘Most Pt Neurons Can Be Classified into a Few Functional Response Types’ (page unavailable), the paper identifies iMM as a monocular class responsive to medial motion with a strong preference for forward motion. It does not establish in the available text that iMM is the most frequent monocular response type; it says only that eight response types occurred at elevated frequency. (LLM, conf=0.84)
Experimental — accuracy not yet measuredCurrent models of zebrafish visuomotor transformations rely on correlation-based neural activity, lack realistic retina or motor representations, omit neural connectivity manipulation, and exclude closed-loop observations of neural activation during behavior.
“Current models of zebrafish visuomotor transformations rely on correlation-based neural activity, lack realistic representations of the retina or motor systems (25, 29), omit the ability to manipulate neural connectivity, and exclude closed-loop observations of neural activation during behavior, which limits the integrative investigation of the system within its sensory and physical environment.”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
The Discussion says the model ignores processing in the retina and spinal cord, and the Methods describe correlation-based neural activity maps. But the Results report both an experimental commissure ablation and its simulation in the model, so the claim that connectivity cannot be manipulated is not supported. The Introduction mentions closed-loop stimulus delivery, while the Methods describe neural imaging in restrained, paralyzed fish; these passages do not establish closed-loop neural observations during behavior. (LLM, conf=0.87)
Experimental — accuracy not yet measuredAlternative neural circuits favoring lower anterior DSGC connectivity could be equally effective but would require downstream visuomotor circuits different from those experimentally observed.
“Although it is plausible that alternative neural circuits favoring lower anterior DSGCs connectivity could be equally effective, they would require downstream visuomotor circuits different from those experimentally observed (25).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
The Results section, “Identifying Critical Dimensions of Functional Connectivity” (page unavailable), says that multiple sets of connections can yield similar behavioral predictions, supporting the possibility of equally effective alternatives. It does not identify alternatives favoring lower anterior DSGC connectivity or say that they would require downstream visuomotor circuits different from those experimentally observed. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe simulations explain why pretectal neurons in real zebrafish preferentially respond to motion in the lower posterior visual field.
“Specifically, our simulations explain why pretectal neurons in real zebrafish preferentially respond to motion in the lower posterior visual field (25, 30, 31), because with laterally positioned eyes, translational, bottom-projected visual stimuli generate opposing rotational optic flow patterns (Fig. 4E).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
The Results section on pretectal activity reports that zebrafish pretectal neurons respond to motion, and the Methods say motion stimuli were presented from below. Neither passage establishes that the neurons preferentially respond to the lower posterior visual field; the paper does not provide that spatial preference as an explanation for the citing authors’ simulations. Page numbers are unavailable in our copy. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Restricting retinal-pretectal connectivity to only one quadrant may confer computational advantages by allowing combined processing of forward/medial and backward/lateral motion, which drive or reduce locomotion, respectively.
“Restricting retinal-pretectal connectivity to only one quadrant, may confer computational advantages, allowing combined processing of forward/medial and backward/lateral motion which drive or reduce locomotion, respectively (25).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
The Results section on eye- and direction-specific motion reports that medial motion drives forward swimming while lateral motion suppresses it. The pretectal-activity Results section also describes integration of monocular motion signals. However, our copy does not describe retinal-pretectal connectivity as restricted to one quadrant or propose a computational advantage from that restriction; the Discussion instead raises possible functional inefficiencies in eye-specific pathways. Page numbers are unavailable in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measuredBrain-scale imaging and causal manipulations via optogenetics in zebrafish are costly and technically challenging, especially during movement.
“Although brain scale imaging (25, 60, 68) and causal manipulations (69) via optogenetics are possible in zebrafish, they are costly and technically challenging, particularly during movement (70).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
The Results section on whole-brain imaging says the fish were restrained during imaging, and the STAR*METHODS imaging section describes immobilization to prevent movement artifacts. This supports the difficulty of imaging during movement, but the paper does not establish that these methods are costly or that optogenetic manipulations face the same difficulty. Page numbers are unavailable in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe open-source simZFish faithfully reproduces the zebrafish OMR using experimentally observed neural activity.
“Benefitting from detailed experimental data (25, 29–34) and recent advances in physics simulation technologies (35), our open-source simZFish faithfully reproduces the zebrafish OMR, utilizing experimentally observed neural activity (25).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
lPTs collectively control movement direction by activating neurons of the anterior hindbrain, which suppresses behavioral oscillation via reciprocal inhibition.
“As suggested by our previous modeling, lPTs collectively control the movement direction by activating neurons of the anterior hindbrain (aHB) (25, 30), which suppresses behavioral oscillation via reciprocal inhibition (Fig. 2E).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
These neurons exist in real zebrafish in at least eight mirror symmetric sets of direction-selective functional response types.
“These neurons exist in real zebrafish in at least eight mirror symmetric sets of direction-selective functional response types (25).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
The artificial neural architecture was synthesized from anatomical, functional, and computational findings, creating an embedded multi-layer network model of the OMR visuomotor pathways consisting of rate-coding artificial neurons.
“To achieve a biorealistic artificial neural architecture, we synthesized anatomical (30, 41), functional (25, 31, 32), and computational findings (25), creating an embedded multi-layer network model of the OMR visuomotor pathways consisting of rate-coding artificial neurons (Fig. 2A).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
Initializing simZFish's circuits with experimentally derived best-fit connection weights and minimal additional tuning achieved functional connectivity with activation patterns similar to zebrafish neurons for direction and eye-specific stimuli.
“By initializing simZFish’s circuits with our experimentally derived, best-fit (25) connection weights (Fig. S3G), minimal additional tuning achieved functional connectivity that demonstrated similar activation patterns to zebrafish neurons to the direction and eye-specific stimuli (Fig. 2F, G).”
From Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors (2025) · cites this paper as [25]
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Zebrafish – The Neurobehavioural Model in Trend
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Modeling sleep and neuropsychiatric disorders in zebrafish
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Collective behavior emerges from genetically controlled simple behavioral motifs in zebrafish
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Dense Circuit Reconstruction to Understand Neuronal Computation: Focus on Zebrafish
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A Neural Representation of Naturalistic Motion-Guided Behavior in the Zebrafish Brain
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Heterogeneity of Hypocretin/Orexin Neurons
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- Authors
- Naumann, E. A., Fitzgerald, J. E., Dunn, T. W., Rihel, J., Sompolinsky, H., & Engert, F.
- Affiliations
- Harvard University (US)
- University College London (GB)
- Corresponding author
- Engert, Florian
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 167
- Issue
- 4
- Pages
- 947-960.e20
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC5111816
- OpenAlex
- W2547071550
- Semantic Scholar
- 85fc104dab138ca2a31f934dc1146b54f5c3cb3a
- Cited by
- 315
- References
- 54
- Citations by year
- 2026: 46 · 2025: 40 · 2024: 22 · 2023: 17 · 2022: 44 · 2021: 40 · 2020: 42 · 2019: 24 · 2018: 25 · 2017: 14
- FWCI
- 14.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- NIH (U01NS090449, DP1 NS082121, R24NS086601)
- Simons Foundation (SCGB#325207)
- European Research Council (282027 ZFISHSLEEP)
- Marie Curie Fellowship (PIIF-GA-2012-328847)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Zebrafish Biomedical Research Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- optomotor response, zebrafish, sensorimotor circuits, visual motion processing, interhemispheric inhibition, functional connectivity, locomotor behavior, orienting
- MeSH terms
- Animals, Brain, Neural Pathways, Neurons, Swimming, Visual Perception, Zebrafish, Feedback, Sensory, Neuroimaging
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