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A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments
Bertrand Collignon1, Axel Séguret1, José Halloy1
1Université Paris Diderot , Sorbonne Paris Cité, LIED, UMR 8236, 75013 Paris, France.
Royal Society Open Science
|February 25, 2016
Summary
This study introduces a new model for collective motion in fish, focusing on their visual perception and a novel stochastic movement process. The model successfully simulates fish behavior in diverse environments, advancing our understanding of animal group dynamics.
Area of Science:
- Animal Behavior
- Biophysics
- Computational Biology
Background:
- Collective motion is a widespread behavior in social organisms, with existing models often relying on simplified decisional algorithms.
- Recent insights into animal sensory systems and information processing necessitate revising classical assumptions in collective motion models.
Purpose of the Study:
- To develop a novel model of collective motion in fish based on their three-dimensional visual sensory system and perception field.
- To introduce a stochastic movement process using probability distribution functions, departing from traditional vector summation approaches.
- To validate the model using experimental data from zebrafish in varied environments.
Main Methods:
- Developed a 3D visual sensory model for fish trajectory adjustment based on perception.
- Implemented a stochastic process with probability distribution functions for directional movement.
- Collected experimental data on individual and group (10 fish) zebrafish swimming in homogeneous and heterogeneous environments.
- Used experimental data to parameterize and validate the perception-based model.
Main Results:
- The perception-based model effectively simulates collective motion in zebrafish, particularly their cohesive behavior in heterogeneous environments.
- The stochastic movement process provides a more nuanced representation of individual movement decisions within a group.
- The model's parameters were successfully calibrated using empirical data, demonstrating its predictive capability.
Conclusions:
- The developed multilayer model, incorporating visual perception and stochasticity, offers a more realistic simulation of fish collective motion.
- This approach advances the understanding of how sensory perception influences group dynamics in biological systems.
- The model has potential applications in biological, physical, and robotic sciences for studying collective behaviors.
