Analysis of phase shifts in clinical EEG evoked by ECT

We propose a new strategy for studying the phase shifts of electroencephalography (EEG) after electroconvulsive therapy (ECT) of patients with major depression. We divide each ECT EEG time series into four phases and calculate the power spectrum and coherence of left and right prefrontal EEGs for each phase. Previously, we have qualitatively demonstrated certain ECT EEG dynamical patterns by using a neo-cortical neural network model. Now we quantitatively analyze the dynamical phase shifts of the ECT EEG data. Our results are suggestive for a deeper understanding of the ECT EEG patterns and for building more realistic cortical models