Multimodal integration of EEG, MEG and fMRI data for the solution of the neuroimage puzzle

Fabio Babiloni, Donetella Mattia, Claudio Babiloni, Laura Astolfi, Serenella Salinari, Alessandra Basilisco, Paolo Maria Rossini, Maria Grazia Marciani, Febo Cincotti

Research output: Contribution to journalArticle

Abstract

In this paper, advanced methods for the modeling of human cortical activity from combined high-resolution electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) data are presented. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from magnetic resonance images, multidipole source model and regularized linear inverse source estimates of cortical current density. Determination of the priors in the resolution of the linear inverse problem was performed with the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI. Examples of the application of these methods to the estimation of the time varying cortical current density activity in selected region of interest (ROI) are presented for movement-related high-resolution EEG data.

Original languageEnglish
Pages (from-to)1471-1476
Number of pages6
JournalMagnetic Resonance Imaging
Volume22
Issue number10 SPEC. ISS.
DOIs
Publication statusPublished - Dec 2004

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Keywords

  • Linear inverse source estimate
  • MEG and fMRI integration
  • Movement-related potentials
  • Multimodal EEG

ASJC Scopus subject areas

  • Biophysics
  • Clinical Biochemistry
  • Structural Biology
  • Radiology Nuclear Medicine and imaging
  • Condensed Matter Physics

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