Collective response to perturbations in a data-driven fish school model

Abstract

Fish schools are able to display a rich variety of collective states and behavioural responses when they are confronted to threats. However a school's response to perturbations may be different depending on its collective state. Here we use a previously developed data-driven fish school model to investigate how a single or a small number of perturbing individuals affect the long-term behaviour of a school depending on its collective state. These perturbing fish are characterised by a set of attraction and alignment parameters different from those of the main population. We find that the responsiveness of the school to the perturbation is maximum near the transition region between milling and schooling states where the school exhibits multistability and regularly shifts between these two states. We also find that a significant school's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio.

22 pages, 9 figures and 3 videos in the supplementary material

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• Acoustic density estimation of dense fish shoals
• Collective response to local perturbations: how to evade threats without losing coherence
• Anomalous Behaviour of Mutual Information in Finite Flocks
• CBIL: Collective Behavior Imitation Learning for Fish from Real Videos
• Excess of Social Behavior Reduces the Capacity to Respond to Perturbations
• Computational Human Dynamics