MEG and EEG source localization in beamspace

摘要: Beamspace methods are applied to EEG/MEG source localization problems in this paper. processing involves passing the data through a linear transformation that reduces dimension prior applying desired statistical signal algorithm. This process generally requirements of subsequent We present one approach for designing beamspace transformations optimized preserve activity located within given region interest and show substantial reductions obtained with negligible loss. versions maximum likelihood dipole fitting, MUSIC, minimum variance beamforming algorithms presented. The performance improvement offered by limited is demonstrated bootstrapping somatosensory evaluate variability location estimates each quantitative benefits depend on algorithm, noise ratio, amount data. Dramatic improvements scenarios low ratio small number independent samples.