Analysis of time-varying synchronization of multi-channel EEG signals using wavelet coherence

This paper proposes a novel method based on the time-frequency coherent representation for quantifying synchronization of multi-channel signals with high resolution. The presented wavelet-coherent technique provides the information regarding both the degree of coherence and the relation of phase difference. The wavelet coherence enables to provide the synchronization and the direction of information flow between two-channel signals. In addition, real EEG recordings are collected based on the cognitive targets during sentences identification and the wavelet coherence is employed for the analysis of the multi-channel EEG signals. It is observed from both the magnitude spectra and phase of the wavelet coherence that there are obvious differences between two kinds of cognitive activities. Finally, some results are illustrated with both simulation and real EEG time series to show the effectiveness of the method.