The regularities of the discrete nature of multi-variability of EEG spectral patterns

The short-term structure of electroencephalogram (EEG) spectral transformations during different brain functional states (closed/opened eyes and memory task) was studied. It was shown that approximately 50% of spectral pattern (SP) types occur not more than 2-3 times per 149 analysis epochs in a 1-min EEG. The remaining 50% of SP types were the same for the different EEG channels, in all subjects and various brain functional states. Additionally, a high incidence of the neighboring SP types in strongly overlapping (by 80%) 2-s analysis epochs of the EEG was shown. The SP identified in a given epoch has only a limited predictive value on the SPs identified in the subsequent epochs. The incidence effect was restricted by the limited SP set and by a 50% reduction in the functionally active SPs, which resulted in a temporary stabilization of SPs in sequential combinations. The parameters of temporary stabilization of SPs were significantly different from 'random' EEG which provides evidence of the non-occasional character of stabilization of the main dynamic parameters of neuronal activity. Thus, the findings suggest that the multi-variability of neuronal nets is discrete in time, and limited by the dynamics of the short quasi-stable brain states.