A topographic analysis of human scalp alpha EEG by the complex-valued ICA (MEとバイオサイバネティックス)

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Sleepiness at the wheel is one of the causes of fatal crashes and highway accidents by car drivers. Since the EEG alpha activity occurs in association with the subjective sleepiness, and the alpha activities are observed in a mixed signal, aureate decomposition method has been required. In this study, we propose a method to decompose the time-delayed mixture of alpha source signals by using the time-frequency domain analysis and complex-valued independent component analysis. The method is applied to the human scalp EEG data to decompose the alpha activities occur associated with the subjective sleepiness during a driving simulation task. It is shown that this method provide information about not only the spatial distribution of alpha power (power map) generated by each source but also the phase difference among the recording site (phase map). The alpha power map and the phase map would be useful for the investigation of the mechanism of cortical alpha rhythms such as dipole estimation in the brain
2009-11-05