Identifying influential neighbors in animal flocking

Li Jiang, Luca Giuggioli, Andrea Perna, Ramón Escobedo, Valentin Lecheval, Clément Sire, Zhangang Han, Guy Theraulaz*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

64 Citations (Scopus)
334 Downloads (Pure)

Abstract

Schools of fish and flocks of birds can move together in synchrony and decide on new directions of movement in a seamless way. This is possible because group members constantly share directional information with their neighbors. Although detecting the directionality of other group members is known to be important to maintain cohesion, it is not clear how many neighbors each individual can simultaneously track and pay attention to, and what the spatial distribution of these influential neighbors is. Here, we address these questions on shoals of Hemigrammus rhodostomus, a species of fish exhibiting strong schooling behavior. We adopt a data-driven analysis technique based on the study of short-term directional correlations to identify which neighbors have the strongest influence over the participation of an individual in a collective U-turn event. We find that fish mainly react to one or two neighbors at a time. Moreover, we find no correlation between the distance rank of a neighbor and its likelihood to be influential. We interpret our results in terms of fish allocating sequential and selective attention to their neighbors.

Original languageEnglish
Article numbere1005822
Number of pages32
JournalPLoS Computational Biology
Volume13
Issue number12
DOIs
Publication statusPublished - 21 Nov 2017

Bibliographical note

Correction to article: The link to this article’s data is incorrect. The correct link is: https://doi.org/10.6084/m9.figshare.5631988.v1

Research Groups and Themes

  • Engineering Mathematics Research Group

Keywords

  • Collective animal behavior
  • Collective motion
  • Fish interaction
  • Delay dynamics
  • Interaction networks

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