An analysis of EEG based on information flow with SD method

We propose and examine methods for analyzing an EEG (electroencephalogram) during music listening in particular based on information flow combined with the source derivation (SD) method. The relationship between EEG and music cognition is also discussed. Music can be regarded as input to the brain system which influences human mentality. Since music cognition has many emotional aspects, it is expected that the EEG recorded during music listening may reflect the electrical activity of brain regions related to those emotional aspects. The brain system consists of dozens of functional subsystems and we agree with the hypothesis that their cooperative process enables high level recognition such as music listening. From the point of view of informational neurobiology, we extracted the spatial and temporal frequency patterns from the EEG. First, the SD method was applied to the raw data of EEGs as pre-processing. The SD method is a powerful technique to avoid noises which are evoked and overlapped from other regions of the brain. We improved this method for realizing higher accuracy. Then, we calculated the information flow between EEG channels by directional coherence analysis. In this paper, we especially focused on the directional coherence analysis and spatial patterns of the brain´s activated area in response to the music structure. Several observations have shown that there were differences in activated areas between relaxing and music listening conditions