Collective Motion in Danionella Emerges from Discrete Copying Interactions

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Authors: Anonymous, Geoffrey T. Meyerhof, Julia L. Napoli, David Zada, Matthew Lovett-Barron, Johnatan Aljadeff
Cited by: 1
References: 33

Abstract

Understanding how animals move as collectives requires knowledge of movement and interaction rules implemented by individuals within such groups. We report that micro glassfish Danionella cerebrum exhibit highly dynamic schooling that is explained by a stochastic model with pairwise copying of swimming direction. We identify discrete time points that correspond directly to these copying interactions, and confirm the model's predictions by examining the behavior of fish as they school with virtual conspecifics. The model's success in quantitatively recapitulating group behaviors opens a door to future investigations into models of collective motion where emergent group behaviors are highly dynamic and depend strongly on group size. Furthermore, the interactions in the model serve as candidate computations implemented in the brains of individuals, facilitating future studies into the neuronal mechanisms underlying complex group behaviors.

Fields of Study & Subjects

Micro and Nano Robotics Modular Robots and Swarm Intelligence Origins and Evolution of Life

Publication details

Journal / source
Physical Review Letters
Publisher
American Physical Society (APS)
Volume
137
Issue
9
Pages
098403–098403
Publication date
15 July 2026
Language
EN