A Multivariate Approach to Correlation Analysis Based on Random Matrix Theory

In this talk we present a multivariate method for the analysis of interrelations between data channels of a $M$-dimensional recording. We describe in detail how and in which sense genuine multivariate features of the data set are extracted and illustrate the performance of the method with the help of numerical examples. As tools known from Random Matrix Theory are used, a brief overview of the origin of this field is given and some technical aspects of the calculation of RMT-measures are discussed. Finally we present several examples where this method has been applied successfully to he analysis of electroencephalographic recordings of epileptic patients.