title: A multitrial analysis for revealing significant corticocortical networks in magnetoencephalography and electroencephalography.
abstract: We present an MEG/EEG framework to reveal statistically significant brain areas engaged in the same cognitive process across trials without resort to averaging procedures. The variability of neuronal responses is assumed to take place only in the reconstructed time series of cortical sources and not in their positions. This hypothesis allows the use of the surrogate data method to detect recurrently active brain areas across trials adjusted with any cortically constrained focal MEEG inverse solution. Results obtained from synthetic data show that considering several trials enhances the accuracy of the source localisation. We apply this approach on MEG data recorded during a simple visual stimulation. The considered stimulus is frequency tagged in order to reveal the neural network correlated to its perception using phase synchronisation analysis. The results show consistent patterns of distributed synchronous networks centred on occipital areas.
authors.affiliation: Cognitive Neuroscience and Brain Imaging Laboratory, CNRS UPR 640, Hôpital de La Salpêtrière, 47 bld de l'Hôpital, 75651 Paris Cedex 13, France. odavid@fil.ion.ucl.ac.uk
authors.forename: Olivier
authors.initials: O
authors.lastname: David
authors.forename: Diego
authors.initials: D
authors.lastname: Cosmelli
authors.forename: Dominique
authors.initials: D
authors.lastname: Hasboun
authors.forename: Line
authors.initials: L
authors.lastname: Garnero
mesh_terms: D000328:Adult; D000465:Algorithms; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000502:physiology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004569:Electroencephalography; D005260:Female; D006801:Humans; D015225:Magnetoencephalography; D008297:Male; D008959:Models, Neurological; D009010:Monte Carlo Method; D009415:Nerve Net / Q000502:physiology*