2023 Fiscal Year Final Research Report

Systems modelling of hyper-adaptation mechanism for reconstruction of neural structure

Planned Research

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Project Area	Hyper-adaptability for overcoming body-brain dysfunction: Integrated empirical and system theoretical approaches
Project/Area Number	19H05727
Research Category	Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
Allocation Type	Single-year Grants
Review Section	Complex systems
Research Institution	Tokyo University of Agriculture and Technology
Principal Investigator	Kondo Toshiyuki 東京農工大学, 工学(系)研究科(研究院), 教授 (60323820)
Co-Investigator(Kenkyū-buntansha)	千葉龍介旭川医科大学, 医学部, 准教授 (80396936) 宮下恵東京農工大学, 工学(系)研究科(研究院), 助教 (60963311) 矢野史朗東京農工大学, 工学(系)研究科(研究院), 助教 (90636789)
Project Period (FY)	2019-06-28 – 2024-03-31
Keywords	テンソル分解 / 動的グラフ構造解析 / 筋骨格モデル / 運動学習
Outline of Final Research Achievements	The purpose of this study was to constructively clarify the reconstruction of brain structures from the standpoint of systems engineering, and addressed (1) statistical modeling and ensuring interpretability of long-term multimodal data, (2) gray-box modeling and aging simulation, and (3) motor learning through robotic intervention. In (1), we developed an analytical method that combines the extraction of low-dimensional structures by Tensor decomposition and ynamic graph structure estimation (TVGL), and verified its validity using brain activity data provided from the neuroscience group. In (2), we constructed a gray-box model of musculoskeletal and brain network models, and verified its validity by simulation experiement. In (3), we conducted motor learning experiments using a system in which a human and a robot were combined using VR amd robotic technology, and clarified the conditions under which learning is facilitated.
Free Research Field	身体教育学
Academic Significance and Societal Importance of the Research Achievements	本研究では、脳内神経構造に内在する低次元構造の時間的変化（例えば、運動学習の前後や障害の前後）を可視化する手法、脳内運動制御構造を数理モデルとして構成し、シミュレーションする技術、人の運動学習・機能回復過程に介入するロボット技術を開発した。これらの波及効果として、Systems Neurorehabilitationという新たな学際研究領域の創成につながると期待される。