title: Large-scale EEG/MEG source localization with spatial flexibility.
abstract: We propose a novel approach to solving the electro-/magnetoencephalographic (EEG/MEG) inverse problem which is based upon a decomposition of the current density into a small number of spatial basis fields. It is designed to recover multiple sources of possibly different extent and depth, while being invariant with respect to phase angles and rotations of the coordinate system. We demonstrate the method's ability to reconstruct simulated sources of random shape and show that the accuracy of the recovered sources can be increased, when interrelated field patterns are co-localized. Technically, this leads to large-scale mathematical problems, which are solved using recent advances in convex optimization. We apply our method for localizing brain areas involved in different types of motor imagery using real data from Brain-Computer Interface (BCI) sessions. Our approach based on single-trial localization of complex Fourier coefficients yields class-specific focal sources in the sensorimotor cortices.
authors.affiliation: Department of Computer Science, Berlin Institute of Technology, Berlin, Germany. stefan.haufe@tu-berlin.de
authors.forename: Stefan
authors.initials: S
authors.lastname: Haufe
authors.forename: Ryota
authors.initials: R
authors.lastname: Tomioka
authors.forename: Thorsten
authors.initials: T
authors.lastname: Dickhaus
authors.forename: Claudia
authors.initials: C
authors.lastname: Sannelli
authors.forename: Benjamin
authors.initials: B
authors.lastname: Blankertz
authors.forename: Guido
authors.initials: G
authors.lastname: Nolte
authors.forename: Klaus-Robert
authors.initials: KR
authors.lastname: Müller
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D004569:Electroencephalography; D006801:Humans; D015225:Magnetoencephalography; D012815:Signal Processing, Computer-Assisted