A novel method for reliable and fast extraction of neuronal EEG/MEG oscillations on the basis of spatio-spectral decomposition

Neuronal oscillations have been shown to underlie various cognitive, perceptual and motor functions in the brain. However, studying these oscillations is notoriously difficult with EEG/MEG recordings due to a massive overlap of activity from multiple sources and also due to the strong background noise. In EEG/MEG research frequently used algorithms are based on independent component analysis (ICA) not requiring inverse modeling calculations. These ICA approaches might meet intrinsic limitations for regular EEG/MEG oscillatory components which not only represent a mixture of narrow-band signals with very similar…