Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis

Tanaka, Yudai; Nakata, Takuto; Hibino, Hiroshi; Nishiyama, Masaaki; Ino, Daisuke

doi:https://doi.org/10.1371/journal.pone.0288930

Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis

Tanaka, Yudai; Nakata, Takuto; Hibino, Hiroshi et al.

PLoS ONE, 2023, 18(7), e0288930

アクセス数:661件（2025-12-03 09:17 集計）

固定URL: https://hdl.handle.net/11094/92476

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タイトル	Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis
著者	著者名 Tanaka, Yudai
	著者名 Nakata, Takuto
	NRID 1000070314317 1000070314317 researchmap permalink hiroshi_hibino hiroshi_hibino Scopus Author ID 7007020846 7007020846 著者名 Hibino, Hiroshi
	NRID 1000050423562 1000050423562 著者名 Nishiyama, Masaaki
	NRID 1000040721981 1000040721981 ORCID 0000-0002-8112-0746 0000-0002-8112-0746 researchmap permalink daisukeino daisukeino 著者名 Ino, Daisuke
内容	Tanaka Y., Nakata T., Hibino H., et al. Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis. PLoS ONE 18, e0288930 (2023); https://doi.org/10.1371/journal.pone.0288930.
抄録	Facial expressions are widely recognized as universal indicators of underlying internal states in most species of animals, thereby presenting as a non-invasive measure for assessing physical and mental conditions. Despite the advancement of artificial intelligence-assisted tools for automated analysis of voluminous facial expression data in human subjects, the corresponding tools for mice still remain limited so far. Considering that mice are the most prevalent model animals for studying human health and diseases, a comprehensive characterization of emotion-dependent patterns of facial expressions in mice could extend our knowledge on the basis of emotions and the related disorders. Here, we present a framework for the development of a deep learning-powered tool for classifying facial expressions in head-fixed mouse. We demonstrate that our machine vision was capable of accurately classifying three different emotional states from lateral facial images in head-fixed mouse. Moreover, we objectively determined how our classifier characterized the differences among the facial images through the use of an interpretation technique called Gradient-weighted Class Activation Mapping. Importantly, our machine vision presumably discerned the data by leveraging multiple facial features. Our approach is likely to facilitate the non-invasive decoding of a variety of emotions from facial images in head-fixed mice.
出版者	Public Library of Science
収録物名	PLoS ONE
巻(号)	18(7)
ページ	e0288930
刊行年月	2023-07-20
言語	英語
ハンドルURL	https://hdl.handle.net/11094/92476
eISSN	19326203
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1371/journal.pone.0288930
アクセス権	open access
権利情報	© 2023 Tanaka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCMI資源タイプ	text
DCTERMS.bibliographicCitation	PLoS ONE. 2023, 18(7), p. e0288930
DC.title	Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis
DC.creator	Tanaka, Yudai
	Nakata, Takuto
	Hibino, Hiroshi
	Nishiyama, Masaaki
	Ino, Daisuke
DC.publisher	Public Library of Science
DC.language' scheme='DCTERMS.RFC1766	英語
DC.type' scheme='DCTERMS.DCMIType	text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2023-07-20
DC.identifier	https://doi.org/10.1371/journal.pone.0288930
DC.description	Tanaka Y., Nakata T., Hibino H., et al. Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis. PLoS ONE 18, e0288930 (2023); https://doi.org/10.1371/journal.pone.0288930.
DCTERMS.abstract	Facial expressions are widely recognized as universal indicators of underlying internal states in most species of animals, thereby presenting as a non-invasive measure for assessing physical and mental conditions. Despite the advancement of artificial intelligence-assisted tools for automated analysis of voluminous facial expression data in human subjects, the corresponding tools for mice still remain limited so far. Considering that mice are the most prevalent model animals for studying human health and diseases, a comprehensive characterization of emotion-dependent patterns of facial expressions in mice could extend our knowledge on the basis of emotions and the related disorders. Here, we present a framework for the development of a deep learning-powered tool for classifying facial expressions in head-fixed mouse. We demonstrate that our machine vision was capable of accurately classifying three different emotional states from lateral facial images in head-fixed mouse. Moreover, we objectively determined how our classifier characterized the differences among the facial images through the use of an interpretation technique called Gradient-weighted Class Activation Mapping. Importantly, our machine vision presumably discerned the data by leveraging multiple facial features. Our approach is likely to facilitate the non-invasive decoding of a variety of emotions from facial images in head-fixed mice.
DC.rights	© 2023 Tanaka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
DC.format	92476
citation_title	Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis
citation_author	Tanaka, Yudai
	Nakata, Takuto
	Hibino, Hiroshi
	Nishiyama, Masaaki
	Ino, Daisuke
citation_publisher	Public Library of Science
citation_language	英語
citation_date	2023-07-20
citation_journal_title	PLoS ONE
citation_volume	18
citation_issue	7
citation_firstpage	e0288930
citation_doi	https://doi.org/10.1371/journal.pone.0288930
citation_public_url	https://hdl.handle.net/11094/92476

Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis

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