A new dynamical approach to auditory evoked magnetic field by blind identification

A new approach to understand neural dynamics underlying the generation of auditory evoked magnetic field is proposed. MEG time series data are temporally decorrelated by using a blind signal separation method. Two components are selected from their periodical property and a remixing matrix is applied to the two selected components to retrieve MEG signals of auditory evoked magnetic field. After principal component data for each sensor pairs are calculated, a minimum phase innovation model is identified from the viewpoint of statistical inverse problem. By using a blind identification method based on feedback system theory transfer functions can be evaluated to get a dynamical understanding of brain auditory functions. It is reported that all changes of their impulse responses between right and left hemisphere decay within about 40 ms, and that directional differences in transfer functions can be found.