2013 Fiscal Year Final Research Report
Mathematical Modeling of Neural Information Processing Based on Presynapitc Control and its Applications to Engineering
Project/Area Number |
20246026
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Research Category |
Grant-in-Aid for Scientific Research (A)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Engineering fundamentals
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Research Institution | The University of Tokyo |
Principal Investigator |
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Co-Investigator(Kenkyū-buntansha) |
MORITA Kenji 東京大学, 教育学研究科(研究院), 講師 (60446531)
WATANABE Hiroki 東京大学, 法学(政治学)研究科(研究院), 助教 (20570609)
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Co-Investigator(Renkei-kenkyūsha) |
FUJII Hiroshi 京都産業大学, 名誉教授 (90065839)
KOHNO Takashi 東京大学, 生産技術研究所, 准教授 (90447350)
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Research Collaborator |
ROBINSON Hugh ケンブリッジ大学, School of the Biological Sciences, 講師
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Project Period (FY) |
2008-04-08 – 2013-03-31
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Keywords | 数理工学 / モデル化 / 脳・神経 / 生体生命情報学 / ソフトコンピューティング |
Research Abstract |
This study aims to derive mathematical models of presynaptic control found in the brain, analyse neural information processing mechanisms based on presynaptic control, and view its possible applications to engineering. First, we have proposed a neural network model with breakdown of Dale's principle caused by presynaptic excitatory inhibitory-synapses. In addition, regarding short-term synaptic plasticity, we have estimated parameters such as time constants from physiological data, and proposed a hypothesis on how short-term plasticity modulates corticospinal information flow. Further, we have explored the relation between the presynaptic control and higher brain functions such as attension, memory and excessive synchronization. Finally, on the basis of these results, we have considered possible engineering applications of the related higher brain functions such as memory and attention.
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Research Products
(13 results)