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Inferring social influence in animal groups across multiple timescales
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939267/ https://www.ncbi.nlm.nih.gov/pubmed/36802787 http://dx.doi.org/10.1098/rstb.2022.0062 |
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author | Sridhar, Vivek H. Davidson, Jacob D. Twomey, Colin R. Sosna, Matthew M. G. Nagy, Máté Couzin, Iain D. |
author_facet | Sridhar, Vivek H. Davidson, Jacob D. Twomey, Colin R. Sosna, Matthew M. G. Nagy, Máté Couzin, Iain D. |
author_sort | Sridhar, Vivek H. |
collection | PubMed |
description | 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’. |
format | Online Article Text |
id | pubmed-9939267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-99392672023-02-20 Inferring social influence in animal groups across multiple timescales Sridhar, Vivek H. Davidson, Jacob D. Twomey, Colin R. Sosna, Matthew M. G. Nagy, Máté Couzin, Iain D. Philos Trans R Soc Lond B Biol Sci Articles 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’. The Royal Society 2023-04-10 2023-02-20 /pmc/articles/PMC9939267/ /pubmed/36802787 http://dx.doi.org/10.1098/rstb.2022.0062 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles Sridhar, Vivek H. Davidson, Jacob D. Twomey, Colin R. Sosna, Matthew M. G. Nagy, Máté Couzin, Iain D. Inferring social influence in animal groups across multiple timescales |
title | Inferring social influence in animal groups across multiple timescales |
title_full | Inferring social influence in animal groups across multiple timescales |
title_fullStr | Inferring social influence in animal groups across multiple timescales |
title_full_unstemmed | Inferring social influence in animal groups across multiple timescales |
title_short | Inferring social influence in animal groups across multiple timescales |
title_sort | inferring social influence in animal groups across multiple timescales |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939267/ https://www.ncbi.nlm.nih.gov/pubmed/36802787 http://dx.doi.org/10.1098/rstb.2022.0062 |
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