Recurrent Connections Might Be Important for Hierarchical Categorization
Visual short-term memory is an important ability of primates and is thought to be stored in area TE. We previously reported that the initial transient responses of neurons in area TE represented information about a global category of faces, e.g., monkey faces vs. human faces vs. simple shapes, and t...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Systems Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnsys.2022.805990/full |
| _version_ | 1818872220019064832 |
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| author | Narihisa Matsumoto Yusuke Taguchi Yusuke Taguchi Masaumi Shimizu Shun Katakami Masato Okada Yasuko Sugase-Miyamoto |
| author_facet | Narihisa Matsumoto Yusuke Taguchi Yusuke Taguchi Masaumi Shimizu Shun Katakami Masato Okada Yasuko Sugase-Miyamoto |
| author_sort | Narihisa Matsumoto |
| collection | DOAJ |
| description | Visual short-term memory is an important ability of primates and is thought to be stored in area TE. We previously reported that the initial transient responses of neurons in area TE represented information about a global category of faces, e.g., monkey faces vs. human faces vs. simple shapes, and the latter part of the responses represented information about fine categories, e.g., facial expression. The neuronal mechanisms of hierarchical categorization in area TE remain unknown. For this study, we constructed a combined model that consisted of a deep neural network (DNN) and a recurrent neural network and investigated whether this model can replicate the time course of hierarchical categorization. The visual images were stored in the recurrent connections of the model. When the visual images with noise were input to the model, the model outputted the time course of the hierarchical categorization. This result indicates that recurrent connections in the model are important not only for visual short-term memory but for hierarchical categorization, suggesting that recurrent connections in area TE are important for hierarchical categorization. |
| first_indexed | 2024-12-19T12:35:21Z |
| format | Article |
| id | doaj.art-7b39de497ea6425987a5375eaab64601 |
| institution | Directory Open Access Journal |
| issn | 1662-5137 |
| language | English |
| last_indexed | 2024-12-19T12:35:21Z |
| publishDate | 2022-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Systems Neuroscience |
| spelling | doaj.art-7b39de497ea6425987a5375eaab646012022-12-21T20:21:11ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372022-02-011610.3389/fnsys.2022.805990805990Recurrent Connections Might Be Important for Hierarchical CategorizationNarihisa Matsumoto0Yusuke Taguchi1Yusuke Taguchi2Masaumi Shimizu3Shun Katakami4Masato Okada5Yasuko Sugase-Miyamoto6Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, JapanHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, JapanGraduate School of Science and Technology, University of Tsukuba, Tsukuba, JapanGraduate School of Frontier Sciences, The University of Tokyo, Kashiwa, JapanGraduate School of Frontier Sciences, The University of Tokyo, Kashiwa, JapanGraduate School of Frontier Sciences, The University of Tokyo, Kashiwa, JapanHuman Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, JapanVisual short-term memory is an important ability of primates and is thought to be stored in area TE. We previously reported that the initial transient responses of neurons in area TE represented information about a global category of faces, e.g., monkey faces vs. human faces vs. simple shapes, and the latter part of the responses represented information about fine categories, e.g., facial expression. The neuronal mechanisms of hierarchical categorization in area TE remain unknown. For this study, we constructed a combined model that consisted of a deep neural network (DNN) and a recurrent neural network and investigated whether this model can replicate the time course of hierarchical categorization. The visual images were stored in the recurrent connections of the model. When the visual images with noise were input to the model, the model outputted the time course of the hierarchical categorization. This result indicates that recurrent connections in the model are important not only for visual short-term memory but for hierarchical categorization, suggesting that recurrent connections in area TE are important for hierarchical categorization.https://www.frontiersin.org/articles/10.3389/fnsys.2022.805990/fullvisual categoryvisual cortexshort-term memorydeep learningmodeling |
| spellingShingle | Narihisa Matsumoto Yusuke Taguchi Yusuke Taguchi Masaumi Shimizu Shun Katakami Masato Okada Yasuko Sugase-Miyamoto Recurrent Connections Might Be Important for Hierarchical Categorization Frontiers in Systems Neuroscience visual category visual cortex short-term memory deep learning modeling |
| title | Recurrent Connections Might Be Important for Hierarchical Categorization |
| title_full | Recurrent Connections Might Be Important for Hierarchical Categorization |
| title_fullStr | Recurrent Connections Might Be Important for Hierarchical Categorization |
| title_full_unstemmed | Recurrent Connections Might Be Important for Hierarchical Categorization |
| title_short | Recurrent Connections Might Be Important for Hierarchical Categorization |
| title_sort | recurrent connections might be important for hierarchical categorization |
| topic | visual category visual cortex short-term memory deep learning modeling |
| url | https://www.frontiersin.org/articles/10.3389/fnsys.2022.805990/full |
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