Nonparametric analysis of inter‐individual relations using an attention‐based neural network
Abstract Social network analysis, which has been widely adopted in animal studies over the past decade, enables the revelation of global characteristic patterns of animal social systems from pairwise inter‐individual relations. Animal social networks are typically drawn based on the geometric proxim...
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| Format: | Article |
| Language: | English |
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Wiley
2021-08-01
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| Series: | Methods in Ecology and Evolution |
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| Online Access: | https://doi.org/10.1111/2041-210X.13613 |
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| author | Takashi Morita Aru Toyoda Seitaro Aisu Akihisa Kaneko Naoko Suda‐Hashimoto Ikuma Adachi Ikki Matsuda Hiroki Koda |
| author_facet | Takashi Morita Aru Toyoda Seitaro Aisu Akihisa Kaneko Naoko Suda‐Hashimoto Ikuma Adachi Ikki Matsuda Hiroki Koda |
| author_sort | Takashi Morita |
| collection | DOAJ |
| description | Abstract Social network analysis, which has been widely adopted in animal studies over the past decade, enables the revelation of global characteristic patterns of animal social systems from pairwise inter‐individual relations. Animal social networks are typically drawn based on the geometric proximity and/or frequency of social behaviours (e.g. grooming), but the appropriate metric for inter‐individual relationship is not clear, especially when prior knowledge on the species/data is limited. In this study, researchers explored a nonparametric analysis of inter‐individual relations using a neural network with the attention mechanism, which plays a central role in natural language processing. The high interpretability of the attention mechanism and flexibility of the entire neural network allow for automatic detection of inter‐individual relations included in the raw data, without requiring prior knowledge/assumptions about what modes/types of relations are included in the data. For these case studies, three‐dimensional location data collected from simulated agents and real Japanese macaques were analysed. The proposed method successfully recovered the latent relations behind the simulated data and discovered female‐oriented relations in the real data, which are in accordance with the previous generalizations about the macaque social structure. The proposed method does not exploit any behavioural patterns that are particular to Japanese macaques, and researchers can use it for location data of other animals. The flexibility of the neural network would also allow for its application to a wide variety of data with interacting components, such as vocal communication. |
| format | Article |
| id | doaj-art-de04cf2d42b54d6b8e67fcdab5ff606b |
| institution | Kabale University |
| issn | 2041-210X |
| language | English |
| publishDate | 2021-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Methods in Ecology and Evolution |
| spelling | doaj-art-de04cf2d42b54d6b8e67fcdab5ff606b2025-02-07T06:21:05ZengWileyMethods in Ecology and Evolution2041-210X2021-08-011281425144010.1111/2041-210X.13613Nonparametric analysis of inter‐individual relations using an attention‐based neural networkTakashi Morita0Aru Toyoda1Seitaro Aisu2Akihisa Kaneko3Naoko Suda‐Hashimoto4Ikuma Adachi5Ikki Matsuda6Hiroki Koda7Institute of Scientific and Industrial Research Osaka University Ibaraki JapanChubu University Academy of Emerging Sciences Kasugai JapanPrimate Research Institute Kyoto University Inuyama JapanPrimate Research Institute Kyoto University Inuyama JapanPrimate Research Institute Kyoto University Inuyama JapanPrimate Research Institute Kyoto University Inuyama JapanChubu University Academy of Emerging Sciences Kasugai JapanPrimate Research Institute Kyoto University Inuyama JapanAbstract Social network analysis, which has been widely adopted in animal studies over the past decade, enables the revelation of global characteristic patterns of animal social systems from pairwise inter‐individual relations. Animal social networks are typically drawn based on the geometric proximity and/or frequency of social behaviours (e.g. grooming), but the appropriate metric for inter‐individual relationship is not clear, especially when prior knowledge on the species/data is limited. In this study, researchers explored a nonparametric analysis of inter‐individual relations using a neural network with the attention mechanism, which plays a central role in natural language processing. The high interpretability of the attention mechanism and flexibility of the entire neural network allow for automatic detection of inter‐individual relations included in the raw data, without requiring prior knowledge/assumptions about what modes/types of relations are included in the data. For these case studies, three‐dimensional location data collected from simulated agents and real Japanese macaques were analysed. The proposed method successfully recovered the latent relations behind the simulated data and discovered female‐oriented relations in the real data, which are in accordance with the previous generalizations about the macaque social structure. The proposed method does not exploit any behavioural patterns that are particular to Japanese macaques, and researchers can use it for location data of other animals. The flexibility of the neural network would also allow for its application to a wide variety of data with interacting components, such as vocal communication. https://doi.org/10.1111/2041-210X.13613animal societyattention mechanismdeep learninginteractionJapanese macaquesocial network analysis |
| spellingShingle | Takashi Morita Aru Toyoda Seitaro Aisu Akihisa Kaneko Naoko Suda‐Hashimoto Ikuma Adachi Ikki Matsuda Hiroki Koda Nonparametric analysis of inter‐individual relations using an attention‐based neural network Methods in Ecology and Evolution animal society attention mechanism deep learning interaction Japanese macaque social network analysis |
| title | Nonparametric analysis of inter‐individual relations using an attention‐based neural network |
| title_full | Nonparametric analysis of inter‐individual relations using an attention‐based neural network |
| title_fullStr | Nonparametric analysis of inter‐individual relations using an attention‐based neural network |
| title_full_unstemmed | Nonparametric analysis of inter‐individual relations using an attention‐based neural network |
| title_short | Nonparametric analysis of inter‐individual relations using an attention‐based neural network |
| title_sort | nonparametric analysis of inter individual relations using an attention based neural network |
| topic | animal society attention mechanism deep learning interaction Japanese macaque social network analysis |
| url | https://doi.org/10.1111/2041-210X.13613 |
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