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

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1805-1808
    Number of pages4
    Volume2015-November
    ISBN (Print)9781424492718
    DOIs
    Publication statusPublished - 2015 Nov 4
    Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
    Duration: 2015 Aug 252015 Aug 29

    Other

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

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    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Signal Processing
    • Biomedical Engineering
    • Health Informatics

    Cite this

    Tachikawa, K., Izawa, S., Ono, Y., Kuriki, S., & Ishiyama, A. (2015). Evaluation of performance to detect default mode network among some algorithms applied to resting-state fMRI data. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Vol. 2015-November, pp. 1805-1808). [7318730] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7318730