Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion

TLDR

Coordination among social animals depends on rapid information transfer, yet the structure of communication networks underlying collective behavior remains largely unexplored. The study aims to investigate collective evasion maneuvers—rapid behavioral cascades—in schooling fish. The authors automatically tracked positions and postures of ~150 fish, computed visual fields, and mapped socially generated sensory input to motor responses during evasion. They found that fish use simple, robust cues to detect neighbors’ behavioral changes, forming complex weighted directed networks that enable fractional social contagion, with highly connected yet few neighbors being most influential and susceptible, and that these networks allow prediction of behavioral cascades before they occur, providing a quantitative understanding of contagion.

Abstract

Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.