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Data-driven modeling of collective behavior in schooling fish

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MMVW02 - Collective Behaviour

Swarms of insects, schools of fish and flocks of birds display an impressive variety of collective movements that emerge from local interactions among group members. To understand the mechanisms that govern these phenomena, we need to decipher the interactions between individuals, to identify the information exchanged during these interactions and, finally, to characterize and quantify the effects of these interactions on the behavior of individuals. We have recently introduced a general method to extract from individuals’ trajectories the social interaction functions between two individuals that are required to achieve coordinated motion. Using large sets of tracking data, we used this method to reconstruct and model the interactions between individuals in rummy-nose tetra (H. rhodostomus). This species performs a burst-and-coast type of swimming characterized by sequences of sudden increase in speed followed by a mostly passive gliding period. The effect of social interactions on a fish heading can then be precisely measured. In particular, one can quantify the strength of attraction, repulsion, and alignment behavior resulting from these interactions as a function of the distance between fish and their relative positions and orientations. Our results show that both attraction and alignment behaviors control the reaction of fish to a neighbor. We used these results to build a model of spontaneous burst-and-coast swimming and social interactions of fish, with all parameters being estimated or directly measured from experiments. Then we have extended our approach to analyze collective behavior in larger groups of fish and showed that individuals typically interact with their two most influential neighbors. Overall, our results suggest that fish have to acquire only a minimal amount of information about their environment to coordinate their movements when swimming in groups.

This talk is part of the Isaac Newton Institute Seminar Series series.

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