Time-varying synchronization of visual ERP during sentences identification

The study of the synchronization of EEG signals can help us to understand the underlying cognitive processes and detect the learning deficiencies. The cognitive and information processing take place in different brain regions at different time. To investigate how these distributed brain regions are linked together and the information is exchanged with time, this paper proposes a modern time-frequency coherent analysis that employs an alternative way for quantifying synchronization with both temporal and spectral resolution. Wavelet coherent spectrum is defined and computed from the EEG data set such that the cross wavelet magnitude spectra serves to indicate the degree of coherence and the cross wavelet phase can be used to provide the direction of information flow between channels on different brain regions. Several real ERP data are collected based on the cognitive tasks of sentences identification in both English and Chinese. It is observed from the time-varying synchronization that there are obviously differences during identifying both Chinese and English sentences.