Network Analysis of MRI for the Diagnosis of Epilepsy

2018 Fiscal Year Final Research Report

• Project/Area Number: 15K19773
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Radiation science
• Research Institution: The University of Tokyo
• Principal Investigator: Amemiya Shiori 東京大学, 医学部附属病院, 助教 (90631135)
• Project Period (FY): 2015-04-01 – 2019-03-31
• Keywords: fMRI / network

Outline of Final Research Achievements

The study aims to develop fMRI analyses to identify disease-specific abnormal neural activity. First, we compared the spatiotemporal pattern of BOLD signal and that of the hemodynamics and showed that there might be multiple global neural activities besides local synchronous activity (i.e. so-called resting-state network: RSN) (Amemiya et al. Neuroimage 2016). In order to understand the basis of the interaction between networks, we further try to develop an analysis that enables the separate identification of both components. We have also developed a method for detecting spatiotemporal asymmetry of the spontaneous nerve activity and reported it together with the usefulness of the integrated multi-echo denoising strategy (Amemiya et al. MRM 2019).

Free Research Field

脳計測科学

Academic Significance and Societal Importance of the Research Achievements

fMRIを用いて疾患特異的な異常神経活動を同定するためには、非神経活動成分の正確な同定が必要となり、特に動態解析における重要性が高い。今回の研究では、神経活動の時空間解析に血行動態解析を合わせること、またtemporal ICAの応用により全脳性神経活動の伝播経路を推計する事を可能とした。安静時fMRIが主に対象とするresting-state networks(RSN)活動は自発性神経活動全体から見ればごく一部の現象であり、ネットワーク間相互作用等を理解する上でも、広汎性活動性の評価は重要性が高い。但し解析難易度の高さから、これまで試みられた事が少ない領域であり、今後の応用拡大が期待される。