Extraction and Mapping of Alpha Activity in EEG Signals Using Augmented ICA

The alpha activity of brain has a frequency range of 8-12 Hz. In order to extract the alpha activity from EEG data we propose a new procedure based on independent component analysis (ICA), which can incorporate the a prior frequency information into the ICA to extract independent components in the desired frequency range. We named this procedure as augmented ICA (Au-ICA). The performance of the proposed procedure for alpha extraction has been compared to that of the conventional band-pass filtering via the scalp alpha power maps and cortical source maps of the alpha activity. Our results demonstrate that the alpha power maps and cortical source maps obtained with our method reveal more localized alpha generating regions of brain as compared with the conventional methods. Furthermore they match more closely to the activated regions of brain, mapped using functional magnetic resonance imaging (fMRI) thus validating our results. We believe that the Au-ICA is a more effective method of extracting brain activity reflected in the specific frequency range of EEG signals. The results presented here emphasize that the proposed method may be used for accurate source localization or imaging maps from EEG signals.