{"id":2634,"date":"2021-08-02T08:13:36","date_gmt":"2021-08-02T05:13:36","guid":{"rendered":"https:\/\/elsc.huji.ac.il\/?post_type=faculty-members&p=2634"},"modified":"2026-03-17T09:43:59","modified_gmt":"2026-03-17T07:43:59","slug":"lilach-avitan","status":"publish","type":"faculty-members","link":"https:\/\/elsc.huji.ac.il\/he\/people-directory\/faculty-members\/lilach-avitan\/","title":{"rendered":"Lilach Avitan"},"content":{"rendered":"

Or lab studies how neural circuits develop and give rise to behavior. We combine computational and experimental approaches to understand how the brain encodes and processes sensory information, and how these neural codes change during development.<\/p>\n

Using the zebrafish as a model system, we investigate the principles governing spontaneous and evoked neural activity patterns in the developing brain. Our work bridges neuroscience, computational modeling, and behavioral analysis to uncover the rules that shape functional neural circuits.<\/p>\n

Lab Website:\u00a0https:\/\/avitanlab.com\/<\/a><\/p>\n

Our sensation, perception and behavior arise from the activity of millions of interconnected neurons in the brain.\u00a0 We are interested in how this network of neurons processes information and converts it into an appropriate behavior.\u00a0 To address this question we use the zebrafish as a model system.\u00a0Zebrafish larvae display a range complex behaviors, and are transparent allowing whole-brain imaging of neural activity at the single cell resolution.\u00a0\u00a0In conjunction with these experiments, we use computational, statistical and mathematical tools to analyse the data and uncover the neural mechanism driving behavior.<\/p>\n

How does the brain encode social interaction?<\/p>\n

This project maps whole-brain neural activity at cellular resolution during real-time social interactions in zebrafish, capturing dynamic and distributed activity patterns. We identify a robust neural signature that predicts an upcoming approach toward a conspecific, distinct from the dynamics preceding non-social movements. This signature also accounts for inter-individual variability. Our approach enables the study of the developmental trajectory of social coding and its disruption in models of social impairment. The movie below displays raw two-photon recordings from eight selected imaging planes during social interaction with a conspecific.<\/p>\n

Distinct brain-wide neural dynamics predict social approach behavior<\/em><\/strong>
\nShai Tishby Tamari, Yoav Rubinstein, Netta Livneh, Maayan Moshkovitz, Abeer Karmi, Lilach Avitan
\nhttps:\/\/doi.org\/10.1101\/2025.07.20.665717<\/a><\/p>\n

Hot or cold, the hunt stays on<\/strong><\/h3>\n

We show that larval zebrafish preserve precise hunting performance across a 10\u00b0 C temperature range, despite temperature-dependent compression of behavioral timescales. Spatial movement parameters remain stable through coordinated adjustments in tail dynamics, specifically, increased tail beat frequency and reduced bout duration. Brain-wide calcium imaging revealed parallel temporal scaling in neural activity, and a simple rate model demonstrated that changes in a single neural parameter, the time constant, can account for the observed compensation. These findings suggest that neural temporal scaling enables behavioral stability under global thermal fluctuations without requiring active regulation.<\/p>\n

It's about time: neural temporal scaling accounts for robust hunting behavior across temperatures<\/strong><\/em>
\nYoav Rubinstein, Maayan Moshkovitz, Itay Ottenheimer, Sapir Shapira, Stas Tiomkin, Lilach Avitan
\nhttps:\/\/www.cell.com\/iscience\/fulltext\/S2589-0042(25)00474-2<\/a><\/p>\n

Where can a fish land\u2014and why does it matter?<\/strong><\/h3>\n

Like moves in a board game, each tail flick of a hunting zebrafish follows rules that shape strategy. We mapped the fish\u2019s movement repertoire and discovered a hidden principle: each movement constrains where the fish can be and how it can face next. Position and heading are coupled, carving a low-dimensional set of future options. By modeling this manifold, we reveal how simple movement rules enable strategic prey pursuit.<\/p>\n

A detailed quantification of larval zebrafish behavioral repertoire uncovers principles of hunting behavior
\n<\/strong><\/em>Yoav Rubinstein, Maayan Moshkovitz, Itay Ottenheimer, Sapir Shapira, Stas Tiomkin, Lilach Avitan
\nhttps:\/\/www.cell.com\/iscience\/fulltext\/S2589-0042(25)00474-2<\/a><\/p>\n

The Making of a Hunter: Developmental Tuning of Brain and Behavior<\/strong><\/h3>\n

As zebrafish mature, their hunting becomes faster, more precise, and more efficient. This project investigates how experience and development shape goal-directed behavior, asking what fish learn about the sensory world, and how neural circuits adapt to support improved targeting, decision-making, and motor control. By linking behavior to brain dynamics, we uncover how developmental refinement of neural coding enables more effective hunting.<\/p>\n

<\/h3>\n

How does the fish control its movements?\u200b<\/strong><\/h3>\n

We developed a unified dynamical model that reconstructs the full spatio-temporal structure of zebrafish tail movements from a low-dimensional control space. By feeding low-dimensional controls, the model captures the continuous nature of movement space. This sparse control framework allows precise reconstruction of entire tail movement and offers a window into the neural structure of motor commands, linking movement generation to neural dynamics.<\/p>\n

Our sensation, perception and behavior arise from the activity of millions of interconnected neurons in the brain.\u00a0 We are interested in how this network of neurons processes information and converts it into an appropriate behavior.\u00a0 To address this question we use the zebrafish as a model system.\u00a0Zebrafish larvae display a range complex behaviors, and are transparent allowing whole-brain imaging of neural activity at the single cell resolution.\u00a0\u00a0In conjunction with these experiments, we use computational, statistical and mathematical tools to analyse the data and uncover the neural mechanism driving behavior.<\/p>\n

How does the brain encode social interaction?<\/strong><\/p>\n

Distinct brain-wide neural dynamics predict social approach behavior
\nImri Lifshitz, Netta Livneh, Maayan Moshkovitz, Abeer Karmi, Lilach Avitan
\nbioRxiv 2025.07.09.663340; doi:
\nhttps:\/\/doi.org\/10.1101\/2025.07.09.663340<\/a><\/p>\n

This project maps whole-brain neural activity at cellular resolution during real-time social interactions in zebrafish, capturing dynamic and distributed activity patterns. We identify a robust neural signature that predicts an upcoming approach toward a conspecific, distinct from the dynamics preceding non-social movements. This signature also accounts for inter-individual variability. Our approach enables the study of the developmental trajectory of social coding and its disruption in models of social impairment. The movie below displays raw two-photon recordings from eight selected imaging planes during social interaction with a conspecific.<\/p>\n

Hot or cold, the hunt stays on<\/strong><\/p>\n

<\/b>It's about time: neural temporal scaling accounts for robust hunting behavior across temperatures
\nShai Tishby Tamari, Yoav Rubinstein, Netta Livneh, Maayan Moshkovitz, Abeer Karmi, Lilach Avitan
\nbioRxiv 2025.07.20.665717; doi:
\nhttps:\/\/doi.org\/10.1101\/2025.07.20.665717<\/a><\/p>\n

We show that larval zebrafish preserve precise hunting performance across a 10\u00b0 C temperature range, despite temperature-dependent compression of behavioral timescales. Spatial movement parameters remain stable through coordinated adjustments in tail dynamics, specifically, increased tail beat frequency and reduced bout duration. Brain-wide calcium imaging revealed parallel temporal scaling in neural activity, and a simple rate model demonstrated that changes in a single neural parameter, the time constant, can account for the observed compensation. These findings suggest that neural temporal scaling enables behavioral stability under global thermal fluctuations without requiring active regulation.<\/p>\n

Where can a fish land\u2014and why does it matter?<\/strong><\/p>\n

Yoav Rubinstein, Maayan Moshkovitz, Itay Ottenheimer, Sapir Shapira, Stas Tiomkin, Lilach Avitan
\nhttps:\/\/www.cell.com\/iscience\/fulltext\/S2589-0042(25)00474-2<\/a><\/p>\n

Like moves in a board game, each tail flick of a hunting zebrafish follows rules that shape strategy. We mapped the fish\u2019s movement repertoire and discovered a hidden principle: each movement constrains where the fish can be and how it can face next. Position and heading are coupled, carving a low-dimensional set of future options. By modeling this manifold, we reveal how simple movement rules enable strategic prey pursuit.<\/p>\n

The Making of a Hunter: Developmental Tuning of Brain and Behavior<\/strong>
\nAs zebrafish mature, their hunting becomes faster, more precise, and more efficient. This project investigates how experience and development shape goal-directed behavior, asking what fish learn about the sensory world, and how neural circuits adapt to support improved targeting, decision-making, and motor control. By linking behavior to brain dynamics, we uncover how developmental refinement of neural coding enables more effective hunting.<\/p>\n

How does the fish control its movements?<\/strong>
\nWe developed a unified dynamical model that reconstructs the full spatio-temporal structure of zebrafish tail movements from a low-dimensional control space. By feeding low-dimensional controls, the model captures the continuous nature of movement space. This sparse control framework allows precise reconstruction of entire tail movement and offers a window into the neural structure of motor commands, linking movement generation to neural dynamics.<\/p>\n

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Or lab studies how neural circuits develop and give rise to behavior. We combine computational and experimental approaches to understand how the brain encodes and processes sensory information, and how these neural codes change during development. 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