2020 Fiscal Year Final Research Report

Understanding of brain-state of creative insight: switching of large-scale brain network

Research Project

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Project/Area Number	20K20400
Project/Area Number (Other)	18H05395 (2018-2019)
Research Category	Grant-in-Aid for Challenging Research (Pioneering)
Allocation Type	Multi-year Fund (2020) Single-year Grants (2018-2019)
Review Section	Medium-sized Section 61:Human informatics and related fields
Research Institution	Advanced Telecommunications Research Institute International
Principal Investigator	Ogawa Takeshi 株式会社国際電気通信基礎技術研究所, 脳情報通信総合研究所, 主任研究員 (10614323)
Project Period (FY)	2018-06-29 – 2021-03-31
Keywords	創造性 / ひらめき / 機械学習 / 脳活動計測 / 信号処理
Outline of Final Research Achievements	This study aims to elucidate brain networks associated with creative insight by using machine learning techniques with multi-modal brain measurement. We conducted fMRI experiment during spatial insight problem solving, then we applied Hidden Markov Model to extract dynamic brain states. As a result, we succeeded to extract ten brain states from fourteen networks. In addition, we found a probability of one specific state was correlated with accuracy rate. Next, we conducted verbal insight problem experiment, then we found a state which was commonly found in the spatial insight problem solving even though different modality of problems.
Free Research Field	神経科学
Academic Significance and Societal Importance of the Research Achievements	本研究の成果として、個人の創造性を決定づける動的な脳内ネットワークの定量化を行うことで、テーラーメイドなトレーニング法の提案や人材育成の適正化に役立つと考えられる。このような科学的エビデンスに基づいた創造性の認知機能の解明は、教育分野を通した社会実装としての成果展開が考えられる。教育分野では、創造性を高めるトレーニング法を導入したカリキュラム・教材の作成や、スマホのアプリなどゲームを通したアクティブ・ラーニング、遊びの要素を取り入れながら楽しみつつ学習するプレイフル・ラーニングでの応用が予想される。