Modeling Synchronized Neuronal Activities by Quantum Constrained Probabilistic Computational Neuro-Genetic Method: Insight into the Coupling among Brain's Sub-systems from a Systems View
カテゴリ: 論文誌(論文単位)グループ名: 【C】電子・情報・システム部門発行日: 2014/11/01タイトル(英語): Modeling Synchronized Neuronal Activities by Quantum Constrained Probabilistic Computational Neuro-Genetic Method: Insight into the Coupling among Brain's Sub-systems from a Systems View著者名: Jian-Qin Liu (National Institute of Information and Communications Technology, Center for Information and Neural Networks), Katsunori Shimohara (Department of Information Systems Design, Faculty of Science and Engineering, Doshisha University)著者名(英語): Jian-Qin Liu (National Institute of Information and Communications Technology, Center for Information and Neural Networks), Katsunori Shimohara (Department of Information Systems Design, Faculty of Science and Engineering, Doshisha University)キーワード: probabilistic computational neuro-genetic modeling，systems science，synchronization，signal processing要約(英語): In order to better understand neurodegenerative diseases, characterization of neuronal activities at different regions correlated with the resting state brain activity, which indicates the normality of the spontaneous cognition, to sustain the memory of the brain is needed. The signaling dynamics of these neuronal activities are determined by the so-called default mode network consisting of nodes overlapped with the major functional regions of the brain for task-driven cognition and links among the nodes with correlation coefficients. In the case that the brain's signaling system is an integrated network system, which integrates several sub-systems - molecular, cellular, and cognitive networks, and the signaling network of the brain exists as a complex network that systematically determines the function of the brain, how can the coupling relationship among these interacted sub-systems be modelled and quantitatively analyzed. To answer this question, we propose a new modeling method based on the framework of a systems approach extended from probabilistic computational neuro-genetic modeling (pCNGM), which maps individual neuronal signals at molecular level to the brain's signals at regional level. We use the extended pCNGM model where a new theoretical-physics-inspired data structure is used to quantitatively analyze the region-level correlation of the brain which indicates a kind of synchronization and is used as an indicator of quantitative analysis of neuro-dynamics. The results show that the coupling constrained by structural dynamics with quantum effects embedded in the brain's network plays a pivotal role in the synchronization among regional nodes within the brain's spontaneous signaling network.本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.11 （2014） 特集Ⅰ：電気関係学会関西連合大会 特集Ⅱ：国際会議ヒューマナイズド システム2013本誌掲載ページ: 1628-1633 p原稿種別: 論文／英語電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/134/11/134_1628/_article/-char/ja/
