特性不安の違いによる視聴覚刺激後の脳波のグラフ理論解析

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2021/10/01

タイトル(英語): Graph Theoretical Analysis of EEG after Audiovisual Stimulation in Different Anxiety States

著者名: 山本　祐輔（兵庫県立大学大学院応用情報科学研究科），村松　歩（兵庫県立大学大学院応用情報科学研究科），水野(松本)　由子（兵庫県立大学大学院応用情報科学研究科／兵庫県立大学大学院情報科学研究科／大阪大学サイバーメディアセンター）

著者名(英語): Yusuke Yamamoto (Graduate School of Applied Informatics, University of Hyogo), Ayumi Muramatsu (Graduate School of Applied Informatics, University of Hyogo), Yuko Mizuno-Matsumoto (Graduate School of Applied Informatics, University of Hyogo/Graduate Schoo

キーワード: 脳波，脳内ネットワーク，グラフ理論 EEG，brain network，graph theory

要約(英語): In this study, a brain network was created using graph theoretical analysis based on electroencephalography (EEG) data. The purpose of the study was to investigate the functional connectivity of the brain in different states of anxiety. Seventeen adults with anxiety (A-G), and 13 adults without anxiety (AF-G) were examined. They were given three different stimulations: resting, pleasant, and unpleasant. EEG was measured immediately after the stimulation. The EEG was analyzed by Fast Fourier Transform (FFT), coherence analysis, and graph theory. The results of FFT and coherence analysis showed that the anxiety group (A-G) had higher power spectra and coherence values than those for the anxiety-free group (AF-G) in all sessions. The results of graph theory analysis showed that the clustering coefficient and small-worldness in A-G were lower than those in AF-G, although the characteristic path length in A-G was higher than that in AF-G. This study shows that the brain of A-G has smaller clusters and longer paths to compare with those of AF-G. These events suggest that the brain of A-G would have an inefficient network structure to transmit emotional information.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.141 No.10 （2021）

本誌掲載ページ: 1059-1068 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/141/10/141_1059/_article/-char/ja/