EEG frequency dynamics during movements imagery.

The study is an attempt to reveal the EEG frequency dynamic changes over sites covering areas reflecting the cognitive processes during movement imagery. Subjects were instructed to imagine a self-paced movement after listening to randomized sentences differing in lack of object or instrument of action. EEG was recorded over frontal, sensorimotor and temporo-parietal areas in both hemispheres. Frequency dynamics was estimated using power spectra (PS), band-pass filtering and bispectra. Two types of frequency dynamics were established: (A) a linear one, up to 24 Hz, with most pronounced oscillations in 12-14 Hz and in 16-22 Hz, synchronized first in frontal and precentral areas; (B) a nonlinear one between 24 and 63 Hz, with fractal structure and self-similarity, characterized by fractal dimension of 1.7-1.9. The narrow band of 23-26 Hz in the boundary between linear and nonlinear regimes expressed obvious synchronization and time re-distribution of oscillations among sites and sentence-types.

Nonlinear EEG dynamics during imagined self-paced movements.

The majority of studies devoted to reveal electrophysiological correlates of words and sentences comprehension, imageability and remembering are based on the event-related potentials and frequency synchronization in different narrow frequency bands. These linear methods reveal some patterns of EEG activity in time and frequency domain. Having in mind that the activation of many cortical structures is a result of mass of nonlinearly interconnected neurons, the linear methods seem to be insufficient to discover the complexity of the information transfer. We revealed recently nonlinear dynamic transients in EEG, long before real performance of goal-directed voluntary movements with different temporal and spatial distributions over frontal, sensorimotor and parietal cortical areas (Popivanov and Dushanova, 1999). The aim of this study was to establish whether similar behavior of the nonlinear characteristics exists when the subject imagines movements of a given type. The Kolmogorov entropy computed over time after the sentence end proved to be an useful characteristic that complement the linear methods.