Biology subjects

Harpaz, R.

Publications and source records attributed to Harpaz, R..

5 recordsLinked to original sources

bioRxiv2025

Collective Behavior in Medaka Fish Depends on Discrete Kinematic States of Swimming Behavior

Complex collective behaviors such as schooling are believed to emerge from simple, individual-level computations that translate incoming information from conspecifics into actions. Recently, it has been proposed that discrete behavioral modes, or internal states, may modulate these computations, affecting the resulting collective behaviors. Direct evidence for such hierarchical control remains limited due to challenges in inferring hidden perception-action computations and uncovering discrete behavioral modes from continuous behaviors. To address this, we analyzed swimming behaviors of Medaka fish (Oryzias latipes) throughout development. At the group level, Medaka exhibit synchronized swimming formations that develop early, emerging around two weeks of age and stabilizing within one month. Unlike many teleost species that use burst-and-coast swim patterns, Medaka exhibit continuous tail and body undulations. We show that this continuous behavior can be segmented into three distinct kinematic states: acceleration, deceleration, and prolonged constant speed swimming. Using state-dependent computational models, we tested how Medaka translate social information from neighbors into actions across these kinematic states. The models revealed distinct computations governing social information processing and decision making in each state. Moreover, social responsiveness varied significantly between states--it was strongest during constant-speed epochs, intermediate during accelerations, and lowest during decelerations. Compared to similarly-sized zebrafish that employ burst-and-coast kinematics, Medaka exhibited greater diversity in state-dependent social interaction computations, ultimately resulting in stronger coordinated swimming. These findings highlight discrete behavioral modes as key modulators of social interaction computations underlying collective behavior.

animal behavior and cognition↗

bioRxiv2024

Experience-dependent modulation of collective behavior in larval zebrafish

Complex group behavior can emerge from simple inter-individual interactions. Commonly, these interactions are considered static and hardwired and little is known about how experience and learning affect collective group behavior. Young larvae use well described visuomotor transformations to guide interindividual interactions and collective group structure. Here, we use naturalistic and virtual-reality (VR) experiments to impose persistent changes in population density and measure their effects on future visually evoked turning behavior and the resulting changes in group structure. We find that neighbor distances decrease after exposure to higher population densities, and increase after the experience of lower densities. These adaptations develop slowly and gradually, over tens of minutes and remain stable over many hours. Mechanistically, we find that larvae estimate their current group density by tracking the frequency of neighbor-evoked looming events on the retina and couple the strength of their future interactions to that estimate. A time-varying state-space model that modulates agents social interactions based on their previous visual-social experiences, accurately describes our behavioral observations and predicts novel aspects of behavior. These findings provide concrete evidence that inter-individual interactions are not static, but rather continuously evolve based on past experience and current environmental demands. The underlying neurobiological mechanisms of experience dependent modulation can now be explored in this small and transparent model organism.

animal behavior and cognition↗

bioRxiv2021

Precise visuomotor transformations underlying collective behavior in larval zebrafish

Complex schooling behaviors result from local interactions among individuals. Yet, how sensory signals from neighbors are analyzed in the visuomotor stream of animals is poorly understood. Here, we studied aggregation behavior in larval zebrafish and found that over development larvae transition from overdispersed groups to tight shoals. Using a virtual reality assay, we characterized the algorithms fish use to transform visual inputs from neighbors into movement decisions. We found that young larvae turn away from retinal "clutter" by integrating and averaging retina-wide visual inputs within each eye, and by using a winner-take-all strategy for binocular integration. As fish mature, their responses expand to include attraction to low retinal clutter, that is based on similar algorithms of visual integration. Using model simulations, we show that the observed algorithms accurately predict group structure over development. These findings allow us to make testable predictions regarding the neuronal circuits underlying collective behavior in zebrafish.

neuroscience↗

bioRxiv2021

Collective behavior emerges from genetically controlled simple behavioral motifs in zebrafish

Since Darwin, coordinated movement of animal groups has been believed to be essential to species survival, but it is not understood how changes in the genetic makeup of individuals might alter behavior of the collective. Here we find that even at the early larval stage, zebrafish regulate their proximity and alignment with each other. Two simple visual responses, one that measures relative visual field occupancy and the other global visual motion, suffice to account for the group behavior that emerges. We analyze how mutations in genes known to affect social behavior of humans perturb these simple reflexes in larval zebrafish and thereby affect their collective behaviors. We use model simulations to show that changes in reflexive responses of individual mutant animals predict well the distinctive collective patterns that emerge in a group. Hence group behaviors reflect in part genetically defined primitive sensorimotor "motifs", which are evident even in young larvae.

animal behavior and cognition↗

bioRxiv2019

Social interactions drive efficient foraging and income equality in groups of fish

The social interactions underlying group foraging and their benefits have been mostly studied using mechanistic models replicating qualitative features of group behavior, and focused on a single resource or a few clustered ones. Here, we tracked groups of freely foraging adult zebrafish with spatially dispersed food items and found that fish perform stereotypical maneuvers when consuming food, which attract neighboring fish. We then present a mathematical model, based on inferred functional interactions between fish, which accurately describes individual and group foraging of real fish. We show that these interactions allow fish to combine individual and social information to achieve near-optimal foraging efficiency and promote income equality within groups. We further show that the interactions that would maximize efficiency in these social foraging models depend on group size, but not on food distribution - suggesting that fish may adaptively pick the subgroup of neighbors they "listen to" to determine their own behavior. Impact statementAnalysis and modeling of group behavior of adult zebrafish shows that a specialized social interaction mechanism increases foraging efficiency and equality within groups, under a variety of environmental conditions.

animal behavior and cognition↗