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Collective detection based on visual information in animal groups
We investigate key principles underlying individual, and collective, visual detection of stimuli, and how this relates to the internal structure of groups. While the individual and collective detection principles are generally applicable, we employ a model experimental system of schooling golden shi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261228/ https://www.ncbi.nlm.nih.gov/pubmed/34229461 http://dx.doi.org/10.1098/rsif.2021.0142 |
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author | Davidson, Jacob D. Sosna, Matthew M. G. Twomey, Colin R. Sridhar, Vivek H. Leblanc, Simon P. Couzin, Iain D. |
author_facet | Davidson, Jacob D. Sosna, Matthew M. G. Twomey, Colin R. Sridhar, Vivek H. Leblanc, Simon P. Couzin, Iain D. |
author_sort | Davidson, Jacob D. |
collection | PubMed |
description | We investigate key principles underlying individual, and collective, visual detection of stimuli, and how this relates to the internal structure of groups. While the individual and collective detection principles are generally applicable, we employ a model experimental system of schooling golden shiner fish (Notemigonus crysoleucas) to relate theory directly to empirical data, using computational reconstruction of the visual fields of all individuals. This reveals how the external visual information available to each group member depends on the number of individuals in the group, the position within the group, and the location of the external visually detectable stimulus. We find that in small groups, individuals have detection capability in nearly all directions, while in large groups, occlusion by neighbours causes detection capability to vary with position within the group. To understand the principles that drive detection in groups, we formulate a simple, and generally applicable, model that captures how visual detection properties emerge due to geometric scaling of the space occupied by the group and occlusion caused by neighbours. We employ these insights to discuss principles that extend beyond our specific system, such as how collective detection depends on individual body shape, and the size and structure of the group. |
format | Online Article Text |
id | pubmed-8261228 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-82612282021-07-20 Collective detection based on visual information in animal groups Davidson, Jacob D. Sosna, Matthew M. G. Twomey, Colin R. Sridhar, Vivek H. Leblanc, Simon P. Couzin, Iain D. J R Soc Interface Life Sciences–Physics interface We investigate key principles underlying individual, and collective, visual detection of stimuli, and how this relates to the internal structure of groups. While the individual and collective detection principles are generally applicable, we employ a model experimental system of schooling golden shiner fish (Notemigonus crysoleucas) to relate theory directly to empirical data, using computational reconstruction of the visual fields of all individuals. This reveals how the external visual information available to each group member depends on the number of individuals in the group, the position within the group, and the location of the external visually detectable stimulus. We find that in small groups, individuals have detection capability in nearly all directions, while in large groups, occlusion by neighbours causes detection capability to vary with position within the group. To understand the principles that drive detection in groups, we formulate a simple, and generally applicable, model that captures how visual detection properties emerge due to geometric scaling of the space occupied by the group and occlusion caused by neighbours. We employ these insights to discuss principles that extend beyond our specific system, such as how collective detection depends on individual body shape, and the size and structure of the group. The Royal Society 2021-07-07 /pmc/articles/PMC8261228/ /pubmed/34229461 http://dx.doi.org/10.1098/rsif.2021.0142 Text en © 2021 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 | Life Sciences–Physics interface Davidson, Jacob D. Sosna, Matthew M. G. Twomey, Colin R. Sridhar, Vivek H. Leblanc, Simon P. Couzin, Iain D. Collective detection based on visual information in animal groups |
title | Collective detection based on visual information in animal groups |
title_full | Collective detection based on visual information in animal groups |
title_fullStr | Collective detection based on visual information in animal groups |
title_full_unstemmed | Collective detection based on visual information in animal groups |
title_short | Collective detection based on visual information in animal groups |
title_sort | collective detection based on visual information in animal groups |
topic | Life Sciences–Physics interface |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261228/ https://www.ncbi.nlm.nih.gov/pubmed/34229461 http://dx.doi.org/10.1098/rsif.2021.0142 |
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