From classical to Bayesian estimators in the interpretation of MEG and EEG

Jukka Sarvas*, Risto J. Ilmoniemi

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Abstract

    The interpretation of MEG and EEG measurements often leads to solving a noisy, ill-conditioned matrix equation for the unknown source; the solution becomes an estimator of the true source. In practice, we need to know how to choose that estimator and what its properties are. In this paper, we present how a search for better estimators leads from the classical least-squares estimators through their regularized versions to Bayesian estimators. Though these estimators are rather well-known, the presented 'evolutionary' path is less known and not easily found in the literature.

    Original languageEnglish
    Title of host publication17th International Conference on Biomagnetism Advances in Biomagnetism - Biomag2010
    Pages113-116
    Number of pages4
    Volume28
    DOIs
    Publication statusPublished - 2010
    MoE publication typeA4 Article in a conference publication
    EventInternational Conference on Biomagnetism - Dubrovnik, Croatia
    Duration: 28 Mar 20101 Apr 2010
    Conference number: 17

    Conference

    ConferenceInternational Conference on Biomagnetism
    Abbreviated titleBiomag
    Country/TerritoryCroatia
    CityDubrovnik
    Period28/03/201001/04/2010

    Keywords

    • Bayesian estimators
    • Interpretation of MEG and EEG
    • Least-squares estimators
    • Regularization

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