title: A novel adaptive beamformer for MEG source reconstruction effective when large background brain activities exist.
abstract: This paper proposes a novel prewhitening eigenspace beamformer suitable for magnetoencephalogram (MEG) source reconstruction when large background brain activities exist. The prerequisite for the method is that control-state measurements, which contain only the contributions from the background interference, be available, and that the covariance matrix of the background interference can be obtained from such control-state measurements. The proposed method then uses this interference covariance matrix to remove the influence of the interference in the reconstruction obtained from the target measurements. A numerical example, as well as applications to two types of MEG data, demonstrates the effectiveness of the proposed method.
authors.affiliation: Department of Systems Design and Engineering, Tokyo Metropolitan University, Japan. ksekiha@cc.tmit.ac.jp
authors.forename: Kensuke
authors.initials: K
authors.lastname: Sekihara
authors.forename: Kenneth E
authors.initials: KE
authors.lastname: Hild
authors.forename: Srikantan S
authors.initials: SS
authors.lastname: Nagarajan
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001683:Biological Clocks / Q000502:physiology; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008959:Models, Neurological