Transient phase synchrony of independent cognitive components underlying scalp EEG

Dynamic synchronization between different brain regions has long been considered as the underlying neural mechanism of sensory, motor and cognitive functions. Practical methods of accurately quantifying this kind of dynamics by using scalp EEG are plagued by volume conduction effects and background noise. We propose a new method of measuring transient phase locking between independent components underlying cognitive brain activities. This unique combination of independent component analysis (ICA) and phase locking statistics (PLS) provides a promising technique for investigating the dynamics of neural synchronization between different cortical regions, without the contamination of background coherence. This method was tested on the EEG from a cross-modal working memory experiment and its efficacy in detecting transient phase synchrony was demonstrated.