Analysis of spontaneous magnetoencephalography data by similarity measures

We discuss application of dissimilarity measures technique to the classification of time series obtained in experimental measurements, and use it to analyze multi-channel magnetoencephalography data (MEG). Dissimilarity measures for the 1/f component of MEG data allow to distinguish signals coming from left and right hemispheres. The α-wave component does not allow this distinction, supporting the earlier research, indicating that α-wave sources travel along the whole of the posterior region of the brain.