NONLINEARITY IN NORMAL HUMAN EEG - CYCLES, TEMPORAL ASYMMETRY, NONSTATIONARITY AND RANDOMNESS, NOT CHAOS

Two-hour vigilance and sleep electroencephalogram (EEG) recordings fro m five healthy volunteers were analyzed using a method for identifying nonlinearity and chaos which combines the redundancy-linear redundanc y approach with the surrogate data technique. A nonlinear component in the EEG was detected, however, inconsistent with the hypothesis of lo w-dimensional chaos. A possibility that a temporally asymmetric proces s may underlie or influence the EEG dynamics was indicated. A process that merges nonstationary nonlinear deterministic oscillations with ra ndomness is proposed for an explanation of observed properties of the analyzed EEG signals. Taking these results into consideration, the use of dimensional and related chaos-based algorithms in quantitative EEG analysis is critically discussed.