ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2023
Inferring social influence in animal groups across multiple timescales.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Best-of-n decision making by human groups.PloS one · 2026Article
- Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte Carlo.Entropy (Basel, Switzerland) · 2024Article
- Selective decision-making and collective behavior of fish by the motion of visual attention.PNAS nexus · 2024Article
- Perception of motion salience shapes the emergence of collective motions.Nature communications · 2024Article
- The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots.Journal of the Royal Society, Interface · 2023Article
- A multi-scale review of the dynamics of collective behaviour: from rapid responses to ontogeny and evolution.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many animal behaviours exhibit complex temporal dynamics, suggesting there are multiple timescales at which they should be studied. However, researchers often focus on behaviours that occur over relatively restricted temporal scales, typically ones that are more accessible to human observation. The situation becomes even more complex when considering multiple animals interacting, where behavioural coupling can introduce new timescales of importance. Here, we present a technique to study the time-varying nature of social influence in mobile animal groups across multiple temporal scales. As case studies, we analyse golden shiner fish and homing pigeons, which move in different media. By analysing pairwise interactions among individuals, we show that predictive power of the factors affecting social influence depends on the timescale of analysis. Over short timescales the relative position of a neighbour best predicts its influence and the distribution of influence across group members is relatively linear, with a small slope. At longer timescales, however, both relative position and kinematics are found to predict influence, and nonlinearity in the influence distribution increases, with a small number of individuals being disproportionately influential. Our results demonstrate that different interpretations of social influence arise from analysing behaviour at different timescales, highlighting the importance of considering its multiscale nature. This article is part of a discussion meeting issue 'Collective behaviour through time'.
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