2023 Fiscal Year Final Research Report
Estimation and experimental verification of causal connectivity and network structure among brain regions and neurons
| Project/Area Number |
19K12212
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 62010:Life, health and medical informatics-related
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| Research Institution | The Institute of Statistical Mathematics |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
尾家 慶彦 兵庫医科大学, 医学部, 助教 (50396470)
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Keywords | ニューロインフォマティクス / 多変量時系列解析 / 因果解析 / 生体イメージングデータ |
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| Outline of Final Research Achievements |
The outcomes of this study have brought about significant advancements in both causal relationship analysis and neural activity analysis. These methods and insights are expected to play an important role in future scientific research. In particular, the new guidelines for the application of bootstrap methods and the proposal of new techniques for spatiotemporal analysis of neural activity will be a crucial foundation for future research. Moreover, these findings not only deepen the understanding of neural networks but also provide specific guidelines to improve the reliability of data analysis.
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| Free Research Field |
時系列解析
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| Academic Significance and Societal Importance of the Research Achievements |
本研究成果は、因果関係解析と神経活動解析の分野で重要な進展をもたらし、新たなガイドラインを提供した。これにより、神経ネットワークの構造と機能の理解が深まり、データ解析の精度と信頼性が向上する。また、神経疾患の診断や治療法の開発に貢献し、医療分野における革新を促進する点が期待される。さらに、本成果は神経科学以外にも広く適用可能であり、経済学や社会科学、気候科学など多様な分野での因果関係の解明と予測への貢献が期待される。
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