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Интеллектуальная Система Тематического Исследования НАукометрических данных |
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Motor imagery (MI) is a mental rehearsal of person’s own body parts movement and thiscan be helpful as atraining technique for neurorehabilitation. MI is known to promote patterns of the event-related desynchronization (ERD) of mu-rhythm found in EEG over the sensorimotor areas of the human cortex. Brain-computer interfaces (BCI) introduce ways to decode those specific EEG patterns into the control signal for external devices providing direct communication channel between the brain and the outer world. Initially it seems that BCI approach promises additional benefit for the motor imagery practice by adding a feedback and therefore helping the subject to monitor the imagery quality. On the other hand, BCI-training favors subjects with a stronger mu-rhythm response which is not considered to be an indicator of the motor imagery effort quality. Due to the weak or absent EEG response during MI, a substantial portion of the population is characterized as «BCI-illiterate» or «inefficient» indicating poor performance in a brain-computer interface circuit, and therefore those people are being eliminated from such activity. The aim of our research is to clarify the connection between user’s BCI performance and the neurophysiological effects of motor imagery.