Despite awareness of the theoretical advantages afforded by the surface Laplacian, first and foremost its independence of the EEG recording reference and ability to enhance the spatial information of the EEG signal (i.e., ‘high-resolution EEG’; Gevins et al., 1995; Nunez and Pilgreen, 1991; Nunez and Westdorp, 1994; Nunez et al., 1994), persistent reservations throughout the field have prevented a widespread and systematic use of these methods. Paradoxically, less straightforward data transformations, including multivariate data decomposition techniques and inverse solutions, which typically involve biophysical assumptions about tissue conductivity and geometry or number, orientation and independence of neuronal generators, have by far enjoyed a higher level of popularity among EEG researchers. This section directly addresses the validity and implications of these objections from a pragmatic perspective, focusing on the SP versus SL comparison.
