Magnetoencephalography: Basic theory and estimation techniques of working brain activity

Yumie Ono, Atsushi Ishiyama

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    It is widely accepted that magnetoencephalography (MEG) is a promising tool for investigating human brain activity in good temporal and spatial resolution. However, the use of MEG is currently quite limited, mostly due to excessive diversity in localization techniques to estimate regional brain activity using MEG data. Because source localization in MEG is an ill-posed problem, an adequate localization technique varies depending on the task design and the timing of interest in MEG signals, which sometimes confuses investigators when choosing an analysis technique or comparing the results with those obtained with other modalities, such as functional magnetic resonance imaging. This chapter reviews the introductory theories and applications of currently available MEG source localization techniques as well as principles of MEG signals and its measurement for beginners and possible future MEG users. The physiological and mathematical backgrounds of cerebral MEG source are briefly introduced followed by the technical requirements for MEG data acquisition. Modern localization techniques for inverse problem solving with MEG, from a simple dipole model to an underdetermined type of norm estimation or spatial filter technique, are thoroughly described.

    Original languageEnglish
    Title of host publicationNovel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain
    PublisherSpringer Japan
    Pages77-93
    Number of pages17
    ISBN (Print)9784431732426, 9784431732419
    DOIs
    Publication statusPublished - 2008

    Fingerprint

    Magnetoencephalography
    Brain
    Human Activities
    Research Personnel
    Magnetic Resonance Imaging

    Keywords

    • Dipole model
    • Inverse problem
    • Magnetoencephalography
    • Source localization
    • Spatial filter

    ASJC Scopus subject areas

    • Medicine(all)
    • Neuroscience(all)

    Cite this

    Ono, Y., & Ishiyama, A. (2008). Magnetoencephalography: Basic theory and estimation techniques of working brain activity. In Novel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain (pp. 77-93). Springer Japan. https://doi.org/10.1007/978-4-431-73242-6_5

    Magnetoencephalography : Basic theory and estimation techniques of working brain activity. / Ono, Yumie; Ishiyama, Atsushi.

    Novel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain. Springer Japan, 2008. p. 77-93.

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Ono, Y & Ishiyama, A 2008, Magnetoencephalography: Basic theory and estimation techniques of working brain activity. in Novel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain. Springer Japan, pp. 77-93. https://doi.org/10.1007/978-4-431-73242-6_5
    Ono Y, Ishiyama A. Magnetoencephalography: Basic theory and estimation techniques of working brain activity. In Novel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain. Springer Japan. 2008. p. 77-93 https://doi.org/10.1007/978-4-431-73242-6_5
    Ono, Yumie ; Ishiyama, Atsushi. / Magnetoencephalography : Basic theory and estimation techniques of working brain activity. Novel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain. Springer Japan, 2008. pp. 77-93
    @inbook{00a714bb989f4f789dedb8908282cf5f,
    title = "Magnetoencephalography: Basic theory and estimation techniques of working brain activity",
    abstract = "It is widely accepted that magnetoencephalography (MEG) is a promising tool for investigating human brain activity in good temporal and spatial resolution. However, the use of MEG is currently quite limited, mostly due to excessive diversity in localization techniques to estimate regional brain activity using MEG data. Because source localization in MEG is an ill-posed problem, an adequate localization technique varies depending on the task design and the timing of interest in MEG signals, which sometimes confuses investigators when choosing an analysis technique or comparing the results with those obtained with other modalities, such as functional magnetic resonance imaging. This chapter reviews the introductory theories and applications of currently available MEG source localization techniques as well as principles of MEG signals and its measurement for beginners and possible future MEG users. The physiological and mathematical backgrounds of cerebral MEG source are briefly introduced followed by the technical requirements for MEG data acquisition. Modern localization techniques for inverse problem solving with MEG, from a simple dipole model to an underdetermined type of norm estimation or spatial filter technique, are thoroughly described.",
    keywords = "Dipole model, Inverse problem, Magnetoencephalography, Source localization, Spatial filter",
    author = "Yumie Ono and Atsushi Ishiyama",
    year = "2008",
    doi = "10.1007/978-4-431-73242-6_5",
    language = "English",
    isbn = "9784431732426",
    pages = "77--93",
    booktitle = "Novel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain",
    publisher = "Springer Japan",

    }

    TY - CHAP

    T1 - Magnetoencephalography

    T2 - Basic theory and estimation techniques of working brain activity

    AU - Ono, Yumie

    AU - Ishiyama, Atsushi

    PY - 2008

    Y1 - 2008

    N2 - It is widely accepted that magnetoencephalography (MEG) is a promising tool for investigating human brain activity in good temporal and spatial resolution. However, the use of MEG is currently quite limited, mostly due to excessive diversity in localization techniques to estimate regional brain activity using MEG data. Because source localization in MEG is an ill-posed problem, an adequate localization technique varies depending on the task design and the timing of interest in MEG signals, which sometimes confuses investigators when choosing an analysis technique or comparing the results with those obtained with other modalities, such as functional magnetic resonance imaging. This chapter reviews the introductory theories and applications of currently available MEG source localization techniques as well as principles of MEG signals and its measurement for beginners and possible future MEG users. The physiological and mathematical backgrounds of cerebral MEG source are briefly introduced followed by the technical requirements for MEG data acquisition. Modern localization techniques for inverse problem solving with MEG, from a simple dipole model to an underdetermined type of norm estimation or spatial filter technique, are thoroughly described.

    AB - It is widely accepted that magnetoencephalography (MEG) is a promising tool for investigating human brain activity in good temporal and spatial resolution. However, the use of MEG is currently quite limited, mostly due to excessive diversity in localization techniques to estimate regional brain activity using MEG data. Because source localization in MEG is an ill-posed problem, an adequate localization technique varies depending on the task design and the timing of interest in MEG signals, which sometimes confuses investigators when choosing an analysis technique or comparing the results with those obtained with other modalities, such as functional magnetic resonance imaging. This chapter reviews the introductory theories and applications of currently available MEG source localization techniques as well as principles of MEG signals and its measurement for beginners and possible future MEG users. The physiological and mathematical backgrounds of cerebral MEG source are briefly introduced followed by the technical requirements for MEG data acquisition. Modern localization techniques for inverse problem solving with MEG, from a simple dipole model to an underdetermined type of norm estimation or spatial filter technique, are thoroughly described.

    KW - Dipole model

    KW - Inverse problem

    KW - Magnetoencephalography

    KW - Source localization

    KW - Spatial filter

    UR - http://www.scopus.com/inward/record.url?scp=84920191379&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84920191379&partnerID=8YFLogxK

    U2 - 10.1007/978-4-431-73242-6_5

    DO - 10.1007/978-4-431-73242-6_5

    M3 - Chapter

    AN - SCOPUS:84920191379

    SN - 9784431732426

    SN - 9784431732419

    SP - 77

    EP - 93

    BT - Novel Trends in Brain Science: Brain Imaging, Learning and Memory, Stress and Fear, and Pain

    PB - Springer Japan

    ER -