Independent component approach to the analysis of EEG and MEG recordings

Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extr action methods are, therefore, useful to facilitate the representation and interpretation of the data, Recently developed independent component analysis (ICA) has been shown to b e an efficient tool for artifact identification and extraction from electro encephalographic (EEG) and magnetoencephalographic (MEG) recordings. In add ition, ICA has been applied to the analysis of brain signals evoked by sens ory stimuli. This paper reviews our recent results in this field.