title: Localization of extended brain sources from EEG/MEG: the ExSo-MUSIC approach.
abstract: We propose a new MUSIC-like method, called 2q-ExSo-MUSIC (q ≥ 1). This method is an extension of the 2q-MUSIC (q ≥ 1) approach for solving the EEG/MEG inverse problem, when spatially-extended neocortical sources ("ExSo") are considered. It introduces a novel ExSo-MUSIC principle. The novelty is two-fold: i) the parameterization of the spatial source distribution that leads to an appropriate metric in the context of distributed brain sources and ii) the introduction of an original, efficient and low-cost way of optimizing this metric. In 2q-ExSo-MUSIC, the possible use of higher order statistics (q ≥ 2) offers a better robustness with respect to Gaussian noise of unknown spatial coherence and modeling errors. As a result we reduced the penalizing effects of both the background cerebral activity that can be seen as a Gaussian and spatially correlated noise, and the modeling errors induced by the non-exact resolution of the forward problem. Computer results on simulated EEG signals obtained with physiologically-relevant models of both the sources and the volume conductor show a highly increased performance of our 2q-ExSo-MUSIC method as compared to the classical 2q-MUSIC algorithms.
authors.affiliation: Inserm, UMR 642, Campus de Beaulieu, Rennes, F-35042, France. gwenael.birot@univ-rennesl.fr
authors.forename: Gwénaël
authors.initials: G
authors.lastname: Birot
authors.forename: Laurent
authors.initials: L
authors.lastname: Albera
authors.forename: Fabrice
authors.initials: F
authors.lastname: Wendling
authors.forename: Isabelle
authors.initials: I
authors.lastname: Merlet
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008959:Models, Neurological; D012815:Signal Processing, Computer-Assisted