Recurrent Connections Might Be Important for Hierarchical Categorization.

Matsumoto, Narihisa; Taguchi, Yusuke; Shimizu, Masaumi; Katakami, Shun; Okada, Masato; Sugase-Miyamoto, Yasuko

Matsumoto, Narihisa; Taguchi, Yusuke; Shimizu, Masaumi; Katakami, Shun; Okada, Masato; Sugase-Miyamoto, Yasuko.

Afiliación

Matsumoto N; Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
Taguchi Y; Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
Shimizu M; Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Japan.
Katakami S; Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Okada M; Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
Sugase-Miyamoto Y; Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.

Front Syst Neurosci ; 16: 805990, 2022.

Article en En | MEDLINE | ID: mdl-35283736

Palabras clave

deep learning; modeling; short-term memory; visual category; visual cortex

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Syst Neurosci Año: 2022 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Suiza

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