Time Interval Learning of Dissociated Cortical Networks

カテゴリ: 部門大会

論文No: PS6-1

グループ名: 【C】平成30年電気学会電子・情報・システム部門大会プログラム

発行日: 2018/09/05

タイトル(英語): Time Interval Learning of Dissociated Cortical Networks

著者名: Chang Chih Hsiang(東京大学),榛葉 健太(東京大学),小谷 潔(東京大学),神保 泰彦(東京大学)

著者名(英語): Chih Hsiang Chang|Kenta Shimba|Kiyoshi Kotani|Yasuhiko Jimbo

要約(日本語): Development of rehabilitation devices for lost neuron connections is clue for curing dementia, where knowing what abilities neuron networks possess would be the task. In vitro models presents as great samples for studying properties of network dynamics. Temporal interval learning and spatiotemporal memory over seconds have shown to be intrinsic properties in cortical cultures and dissociated cortical neurons in recent results, supporting the hypothesis that computations are intrinsic to local neuron networks. In our work, we tried to reproduce the temporal interval learning property shown in cortical slices within dissociated neural networks, and may show structural independent property of such learning, which imply long term learning also possess within cortical cultures.

PDFファイルサイズ: 521 Kバイト