title: DYNAMO: dynamic multi-model source localization method for EEG and/or MEG.
abstract: This paper proposes a multiple model method that addresses the estimation of the EEG/MEG neural sources as a multihypothesis, multidimensional and dynamic estimation problem. The key aspect is the probabilistic integration of several neural models to simultaneously estimate and integrate the brain activity of different dynamic neural processes that are characterized by the number of sources, the dynamic of those sources and the initial conditions. The method was validated with EEG data gathered in a protocol to elicit error-related potentials, since there is evidence of the brain region that generate those signals. The results reveal that the proposed multiple model method is able to identify the brain structure associated with error processing, which is a preliminary indicator of the validity of the proposed method.
authors.affiliation: Aragon Institute of Engineering Research (I3A) and Department of informatics and Systems Engineering, University of Zaragoza, 50018, Spain. antelis@unizar.es
authors.forename: Javier M
authors.initials: JM
authors.lastname: Antelis
authors.forename: Javier
authors.initials: J
authors.lastname: Minguez
mesh_terms: D000465:Algorithms; D058256:Brain Waves / Q000502:physiology; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008297:Male; D008959:Models, Neurological