A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments

Authored by Bertrand Collignon, Axel Seguret, Jose Halloy

Date Published: 2016

DOI: 10.1098/rsos.150473

Sponsors: European Union

Platforms: MATLAB

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayermodel and its possible outcomes in biological, physical and robotic sciences.

Tags

Dynamics networks movement patterns morphogenesis Animal groups Transition Fish schools Motion Cell-migration