Abstract
We here present a new technique for visualizing the temporal dynamics of brain area activation and interaction at high-temporal resolution. We first applied independent component analysis to concatenated single-trial EEG data from a fast go–nogo categorization task of natural images and showed that individual independent components might index neural synchrony within and between intracranial brain sources. We used time-frequency decomposition to model their dynamic interactions. In particular, following stimulus presentations, we showed that several independent components were activated and synchronized in the theta frequency range (near 4 Hz ).
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