Segmental structure of EEG more likely reveals the dynamic multistability of the brain tissue than the continual plasticity one

Abstract

A critical review of the principal strategies of the EEG description as a piecewise stationary process is given and new methodology of EEG segmentation, based on nonparametric statistical analysis, is proposed. Our methodology provides the detection of moments of quasi-stationary segments' boundaries in almost any EEG characteristic for a given level of false alarm probability. Relatively high temporal resolution of the method makes it possible to formulate a new approach to investigation of the functional synchrony between different brain areas. We discuss also the achievements, problems, and prospects of EEG signal segmentation.