SOFOMORE: Combined EEG source and forward model reconstruction

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearch

    196 Downloads (Pure)

    Abstract

    We propose a new EEG source localization method that simultaneously performs source and forward model reconstruction (SOFOMORE) in a hierarchical Bayesian framework. Reconstruction of the forward model is motivated by the many uncertainties involved in the forward model, including the representation of the cortical surface, conductivity distribution, and electrode positions. We demonstrate in both simulated and real EEG data that reconstruction of the forward model improves localization of the underlying sources.
    Original languageEnglish
    Title of host publicationIEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009. ISBI '09.
    PublisherIEEE
    Publication date2009
    Pages450-453
    ISBN (Print)978-1-4244-3931-7
    DOIs
    Publication statusPublished - 2009
    Event6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Boston, United States
    Duration: 28 Jun 20091 Jul 2009
    Conference number: 6
    http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=14121

    Conference

    Conference6th IEEE International Symposium on Biomedical Imaging
    Number6
    CountryUnited States
    CityBoston
    Period28/06/200901/07/2009
    Internet address

    Bibliographical note

    Copyright: 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

    Cite this

    Stahlhut, C., Mørup, M., Winther, O., & Hansen, L. K. (2009). SOFOMORE: Combined EEG source and forward model reconstruction. In IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. (pp. 450-453). IEEE. https://doi.org/10.1109/ISBI.2009.5193081