Juliana Dushanova, Bulgarian Academy of Sciences, Sofia, Bulgaria
David Popivanov, Bulgarian Academy of Sciences, Sofia, Bulgaria

Abstract: The study was aimed at comparison of several nonlinear characteristics (NC) computed in time for one and the same EEG record accompanying voluntary goal-directed movements. This allowed us to reveal different aspects of the nonlinear behavior of the process underlying the self-paced movement organization. Parallel alterations of these characteristics during the task performance supported the hypothesis that cognitive task performance is reflected by the changes in the nonlinear dynamics of the EEG activity. Four NCs of scalar EEG time series were estimated: Point-wise Correlation Dimension (PD2), Kolmogorov Entropy (K2), and Largest Lyapunov Exponent (LLE) as a function of time, and Nonlinear Prediction (NP) for successive EEG segments. The time evolution of these characteristics exhibited several transients between chaos-like states to almost periodic states during the task performance: the gradual increase to higher values indicating chaos are probably related to the onset of the successive phases of brain organization of the movement. The results suggest that even in short periods an EEG signal changes its dynamic structure and these periods could be determined precisely enough using different methods of nonlinear dynamics.

Keywords: human EEG, nonlinear dynamics, self-paced complex movements, movement self-organization