Asymptotic Spatiotemporal Averaging of the Power of EEG Signals for Schizophrenia Diagnostics

Although many sophisticated EEG analysis methods have been developed, they are rarely used in clinical practice. Individual differences in brain bioelectrical activity are quite substantial, therefore simple methods that can provide stable results reflecting the basic characteristics of individual neurodynamics are very important. Here, we explore the potential for brain disorder classification based on patterns extracted from the asymptotic spatial power distributions, and compare it with 4–20 microstates, providing information about the dynamics of clustered global power patterns. Applied to the 16-channel EEG data such methods gave discrimination between adolescent schizophrenia patients and a healthy control group at the level of 86–100%.