ON THE DIMENSIONALITY OF SLEEP-EEG DATA - USING CHAOS MATHEMATICS ANDA SYSTEMATIC VARIATION OF THE PARAMETERS OF THE COREX PROGRAM TO DETERMINE THE CORRELATION EXPONENTS OF SLEEP EEG SEGMENTS

Sleep-EEG data of 16 healthy subjects, classified according to the Rec htschaffen and Kales criteria, were taken to determine the correlation exponent (CE) or dimensionality (D-2) Of the data using the Corex pro gram. We tested the applicability of this program to the analysis of s leep-EEG data changing systematically the embedding dimension (ED), th e time lag (tau), the number of involved pairs of vectors and the EEG segment by split half. We could confirm the results of other authors a ccording to which the complexity of the EEG signal decreases from stag e 'awake, eyes closed' to sleep stages 1, 2, 3 and 4. The differences between the various sleep stages were significant. Stage REM could be differentiated from every stage but stage 1. The most important findin g of our study was that the absolute value of the dimensionality depen ds on almost all the parameters tested: with increasing tau up to tau = 200 the CE increases, which means a 1.56-second shift. A higher numb er of pairs is needed when the signal is more complex. The ED is selec ted well between 6 and 11, that means reasonably higher or close to th e dimensionalities for that purpose as presented in the literature. Di fferent segments of one sleep stage in 1 subject led to different CE v alues, thus demonstrating that the EEG signal is not stationary over a segment of 2 min time. Although using chaos mathematics seems to be a useful tool in analyzing EEG data to explore their complexity, we cou ld demonstrate the urgent need of calibrations and conventions to be a ble to interpret the absolute values.