Multichannel data analyses-investigation of connectivity in the brain
In everyday practice of neurobiology research multivariate datasets are analyzed. This concerns EEG, ECoG, MEG data but also can be extended to fMRI and other recordings as well. Multichannel data require specifi c approach in order to fully explore information they contain. The issues and problems arising during analysis of such datasets will be discussed. With special emphasis relations between signals which describe infl uences between investigated structures will be discussed. The concept of Granger causality will be introduced and examples of estimators of causal infl uence of signals, especially the Directed Transfer Function, and time-varying DTF (which describes dynamical properties of transmissions between channels of the process) will be presented. The performance of the selected estimators will be shown on simulated examples as well as on real EEG data.