DYNAMICS OF THE EEG SENSORIMOTOR RHYTHM DURING MENTAL REPETITION OF THE OBSERVED MOVEMENT

Abstract

Mental simulation of one’s own movement, or imagery of movement, as well as observation of other people’s movements are used in neurorehabilitation as methods of stimulation of sensorimotor parts of the brain. The present work tests a new way of representation - mental simulation of movement, synchronous with the movement observed from the first person on a video screen. The objectives of the study were to compare the reactivity of sensorimotor EEG rhythms during voluntary movement representation and representation following a video stimulus, and to identify the relationship between the phases of movement in the video and the dynamics of EEG patterns. The study involved 30 healthy volunteers in whom a 69-channel encephalogram was recorded during their performance and presentation of right thumb movements in two modes: arbitrarily (without an external reference) and synchronously imitating movement on a video clip. During EEG analysis, individual spatial-frequency components with the highest EEG mu-rhythm reactivity (8–14 Hz) were identified in the subjects, followed by quantitative assessment of desynchronization under the studied conditions based on analysis of probability density distributions of mu-rhythm power. A generalized additive model describing the function of responses to single events in the observed movements and their summation during serial execution or presentation of the movements was applied to assess the relationship between the dynamics of mu-rhythm desynchronization and video events. It was shown that the mental kinesthetic simulation of the observed movement did not result in increased desynchronization of sensorimotor rhythms compared to the voluntary representation of the same movement. It was found for the first time that there are perturbations in the temporal course of desynchronization of the mu-rhythm that depend on the phase and speed of the observed movement both during its synchronous muscle repetition and during mental synchronous imitation. The results obtained can be used to optimize movement parameters in individual systems of ideomotor training with EEG control to achieve the greatest sensorimotor activation.