Multivariate Correlation Coefficient Decomposition and Its Application to Visual Evoked Potentials

Interactions between cortical areas are crucial for cognitive functioning. We develop a method, called multivariate correlation coefficient decomposition, to access such interactions. By decomposing multi-channel mutual correlation coefficient (CC) matrix into individual CC, which is taken as mapping parameter, this method can map temporarily correlated sources activities. Both computer simulation and real visual evoked potentials (VEP) test show that, compared to traditional power mapping, the presented method is sensitive to the combination of the correlated brain sources with different energy levels. Thus, it is of theoretical significance and of practical value