Spatial filter approach for evaluation of the surface Laplacian of the electroencephalogram and magnetoencephalogram

The surface Laplacian is a technique that has been utilized to improve the spatial resolution of the electroencephalogram (EEG) and the magnetoencepha logram (MEG). We investigate the amount of improvement to the spatial resol ution afforded by the surface Laplacian by examining the spatial filters th at describe the relationship between cortical current sources and the surfa ce Laplacian. The surface Laplacian spatial filters extend into higher spat ial frequencies than do raw signal spatial filters, particularly for EEG La placian spatial filters, indicating that substantial improvement in spatial resolution is possible. However, the response of the surface Laplacian ope ration to the nature and amount of noise in the raw EEG and MEG signals is of paramount importance. Spatially correlated noise, coupled with uncorrela ted noise, requires additional regularization of inverse spatial filters re sulting in a decrease in spatial resolution. Substantial improvements in sp atial resolution may-be obtained using the surface Laplacian techniques as long as correlated noise levels are small and raw signals have relatively h igh signal-to-noise ratios. (C) 2001 Biomedical Engineering Society.