Toward a fully coupled network model that yields specific spike timings and patterns

カテゴリ: 部門大会

論文No: SS2-7

グループ名: 【C】2021年電気学会電子・情報・システム部門大会

発行日: 2021/09/08

タイトル(英語): Toward a fully coupled network model that yields specific spike timings and patterns

著者名: 野山 大樹（東京大学）,吉開 悠人（東京大学）,井口 龍輝（東京大学）,鄭 天逸（東京大学）,小谷 潔（東京大学）,神保 泰彦（東京大学）

著者名(英語): Hiroki Noyama (The University of Tokyo),Yuto Yoshikai (The University of Tokyo),Ryuki Iguchi (The University of Tokyo),Tianyi Zheng (The University of Tokyo),Kiyoshi Kotani (The University of Tokyo),Yasuhiko Jimbo (The University of Tokyo)

キーワード: 振動連想記憶モデル|セルアセンブリ|oscillatory associative memory model|cell assembly

要約(日本語): Cell assembly fires synchronously throughout the brain, and the spike-timings and patterns of cell assembly are thought to be influenced by LFP generated by the interaction of individual neurons. However, the mechanism on how those two are coordinated has not been clarified. In this study, we embed spatial patterns into the fully coupled model and consider a model that oscillates with different spatial patterns when different inputs are given from outside the system. By considering these spatial patterns as the activity patterns of the cell assembly, we can quantitatively evaluate how different input affects the spike-timings and patterns of the cell assembly. we aim to construct a fully coupled neural network model that controls the specific spike-timings and patterns.

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