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

Abstract The short-term structure of EEG spectral transformations during different brain functional states (closed/opened eyes and memory task) was studied. It was shown that about 50% of spectral pattern types occur not more than 2-3 times per 149 analysis epochs in a one-minute EEG. The remaining 50% of spectral pattern types were the same for the different EEG channels, in all subjects and various brain functional states. Additionally, a high incidence of the neighboring spectral pattern types in strongly overlapping (by 80%) 2-s analysis epochs of the EEG was shown. The spectral pattern identified in a given epoch has only a limited predictive value on the spectral patterns identified in the subsequent epochs. The incidence effect was restricted by the limited spectral pattern set and by a 50% reduction in the functionally active spectral patterns, which resulted in a temporary stabilization of spectral patterns in sequential combinations. The parameters of temporary stabilization of spectral patterns 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. Keywords: EEG, short-term spectral patterns, memory, adaptive classification, variability, discrete brain states.

International Journal of Psychophysiology. 2003, V. 47. No 1. P. 23-41.

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