Nonlinearity in Normal Human EEG: Cycles, temporal asymmetry, nonstationarity and randomness, not chaos

Abstract

Two-hour vigilance and sleep EEG recordings from five healthy volunteers were analyzed using a method for identifying nonlinearity and chaos, which combines the redundancy -- linear redundancy approach with the surrogate data technique. A nonlinear component in the EEG was detected, however, inconsistent with the hypothesis of low-dimensional chaos. A possibility, that a temporally asymmetric process may underlie or influence the EEG dynamics, was indicated. A process, that merges nonstationary nonlinear deterministic oscillations with randomness, 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. 1 Introduction During the last decade there has been a sustained interest in describing neural processes and brainsignals, especially the electroencephalogram (EEG), within the context of nonlinear dynamics an..