Distribution of Variables Extracted from Spectral EEG-Analysis

For 1000 variables extracted from auto- and cross-spectra of two 12-channel montages, the empirical density function is investigated. Only a small group of them may be considered to have a univariate normal distribution. Another important group including the absolute and the relative power in the four classical frequency bands has distribution functions that may be more or less accurately approximated by gamma-type functions.A third group including some of the peak frequencies shows distribution functions with two peaks not assignable to any natural classification of the EEG.The power of discrimination between the four samples is investigated for each variable by means of Bayes-classification and by a quasi-Kolmogorov-statistic. Its quality is demonstrated using linear discriminant analysis.Correlations were computed to complete basic statistical information.