Richards, J.E.(2004). Recovering dipole sources from scalp-recorded event-related-potentials using component analysis: Principal component analysis and independent component analysis. International Journal of Psychophysiology, 54, 201-220 (PDF)
Principal components analysis (PCA) and independent component analysis (ICA) were examined in their ability to recover cortical sources from simulated data. Datasets of EEG segments were generated that contained cortical sources that were temporally overlapping or non-overlapping, and cortical sources with varying degree of spatial orthogonality. For temporal overlapping cortical sources, both PCA and ICA resulted in components that required multiple-source equivalent current dipole models. The spatially overlapping cortical sources affected the PCA method more than ICA, resulting in single PCA components in which all nonorthogonal cortical sources were represented. For both PCA and ICA, dipole models with fixed-location dipoles successfully accounted for most of the variance in the component weights, even when the spatial or temporal overlap of the generating sources required multiple-dipole models.