Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data

Kenta Tachikawa, Shun Izawa, Yumie Ono, Shinya Kuriki, Atsushi Ishiyama

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    Significant correlation exists in the blood-oxygen-level-dependent (BOLD) signals of resting-state fMRI across different regions in the brain. These regions form the default mode network (DMN), salience network (SN), sensory networks, and others. Among these, the DMN is widely investigated in relation to various mental diseases. Several analytic methods are available for obtaining the DMN activity from individuals' fMRI time-series signals, but a fully effective method has not yet been established. In the present study, we examined a functional connectivity analysis and three algorithms of blind source separation including independent component analysis, second-order blind identification, and non-negative matrix factorization using a set of resting-state fMRI data measured for twelve young participants. Results showed that the second-order blind identification yielded superior performance for the DMN detection, indicating significant activation in all DMN regions based on statistical parametric maps.

    本文言語English
    ホスト出版物のタイトルProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    出版社Institute of Electrical and Electronics Engineers Inc.
    ページ1805-1808
    ページ数4
    2015-November
    ISBN(印刷版)9781424492718
    DOI
    出版ステータスPublished - 2015 11 4
    イベント37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
    継続期間: 2015 8 252015 8 29

    Other

    Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
    国/地域Italy
    CityMilan
    Period15/8/2515/8/29

    ASJC Scopus subject areas

    • コンピュータ ビジョンおよびパターン認識
    • 信号処理
    • 生体医工学
    • 健康情報学

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