Localizing Current Dipoles from EEG Data Using a Birth-Death Process

Keita Nakamura, Sho Sonoda, Hideitsu Hino, Masahiro Kawasaki, Shotaro Akaho, Noboru Murata

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

    Abstract

    A common approach to the electroencephalogram (EEG) source localization problem is to estimate the states of current dipoles. However, the dipole estimation problem is difficult because not only is it an inverse problem but also the number of dipoles can change over time. In this paper, we model the relationship between current dipoles and EEG observations using a state-space model where the creation and annihilation of dipoles is represented as a birth-death process. We estimate the dipoles' positions and moments with a Rao-Blackwellized particle filter and estimate whether a new dipole has been created or an existing one annihilated via the Bayesian information criterion. Experiments on both synthetic and real data show that the proposed model and estimation method can effectively estimate the number and positions of the dipoles.

    Original languageEnglish
    Title of host publicationProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
    EditorsHarald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2645-2651
    Number of pages7
    ISBN (Electronic)9781538654880
    DOIs
    Publication statusPublished - 2019 Jan 21
    Event2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain
    Duration: 2018 Dec 32018 Dec 6

    Publication series

    NameProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

    Conference

    Conference2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
    CountrySpain
    CityMadrid
    Period18/12/318/12/6

    Fingerprint

    Electroencephalography
    Parturition
    Space Simulation
    Inverse problems
    Experiments

    Keywords

    • model selection
    • sequential Bayesian estimation
    • source localization
    • state-space model

    ASJC Scopus subject areas

    • Biomedical Engineering
    • Health Informatics

    Cite this

    Nakamura, K., Sonoda, S., Hino, H., Kawasaki, M., Akaho, S., & Murata, N. (2019). Localizing Current Dipoles from EEG Data Using a Birth-Death Process. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, ... L. Zhang (Eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 (pp. 2645-2651). [8621504] (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2018.8621504

    Localizing Current Dipoles from EEG Data Using a Birth-Death Process. / Nakamura, Keita; Sonoda, Sho; Hino, Hideitsu; Kawasaki, Masahiro; Akaho, Shotaro; Murata, Noboru.

    Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. ed. / Harald Schmidt; David Griol; Haiying Wang; Jan Baumbach; Huiru Zheng; Zoraida Callejas; Xiaohua Hu; Julie Dickerson; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2645-2651 8621504 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).

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

    Nakamura, K, Sonoda, S, Hino, H, Kawasaki, M, Akaho, S & Murata, N 2019, Localizing Current Dipoles from EEG Data Using a Birth-Death Process. in H Schmidt, D Griol, H Wang, J Baumbach, H Zheng, Z Callejas, X Hu, J Dickerson & L Zhang (eds), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018., 8621504, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Institute of Electrical and Electronics Engineers Inc., pp. 2645-2651, 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018, Madrid, Spain, 18/12/3. https://doi.org/10.1109/BIBM.2018.8621504
    Nakamura K, Sonoda S, Hino H, Kawasaki M, Akaho S, Murata N. Localizing Current Dipoles from EEG Data Using a Birth-Death Process. In Schmidt H, Griol D, Wang H, Baumbach J, Zheng H, Callejas Z, Hu X, Dickerson J, Zhang L, editors, Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2645-2651. 8621504. (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). https://doi.org/10.1109/BIBM.2018.8621504
    Nakamura, Keita ; Sonoda, Sho ; Hino, Hideitsu ; Kawasaki, Masahiro ; Akaho, Shotaro ; Murata, Noboru. / Localizing Current Dipoles from EEG Data Using a Birth-Death Process. Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018. editor / Harald Schmidt ; David Griol ; Haiying Wang ; Jan Baumbach ; Huiru Zheng ; Zoraida Callejas ; Xiaohua Hu ; Julie Dickerson ; Le Zhang. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 2645-2651 (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018).
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    abstract = "A common approach to the electroencephalogram (EEG) source localization problem is to estimate the states of current dipoles. However, the dipole estimation problem is difficult because not only is it an inverse problem but also the number of dipoles can change over time. In this paper, we model the relationship between current dipoles and EEG observations using a state-space model where the creation and annihilation of dipoles is represented as a birth-death process. We estimate the dipoles' positions and moments with a Rao-Blackwellized particle filter and estimate whether a new dipole has been created or an existing one annihilated via the Bayesian information criterion. Experiments on both synthetic and real data show that the proposed model and estimation method can effectively estimate the number and positions of the dipoles.",
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    AU - Murata, Noboru

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