title: MEG source localization using invariance of noise space.
abstract: We propose INvariance of Noise (INN) space as a novel method for source localization of magnetoencephalography (MEG) data. The method is based on the fact that modulations of source strengths across time change the energy in signal subspace but leave the noise subspace invariant. We compare INN with classical MUSIC, RAP-MUSIC, and beamformer approaches using simulated data while varying signal-to-noise ratios as well as distance and temporal correlation between two sources. We also demonstrate the utility of INN with actual auditory evoked MEG responses in eight subjects. In all cases, INN performed well, especially when the sources were closely spaced, highly correlated, or one source was considerably stronger than the other.
authors.affiliation: Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Junpeng
authors.initials: J
authors.lastname: Zhang
authors.forename: Tommi
authors.initials: T
authors.lastname: Raij
authors.forename: Matti
authors.initials: M
authors.lastname: Hämäläinen
authors.forename: Dezhong
authors.initials: D
authors.lastname: Yao
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology; D001931:Brain Mapping; D003198:Computer Simulation; D005072:Evoked Potentials, Auditory / Q000502:physiology; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008959:Models, Neurological; D015203:Reproducibility of Results; D059629:Signal-To-Noise Ratio