Brain-computer Interface Based on Motor Imagery: the Most Relevant Sources of Electrical Brain Activity

Examined are sources of brain activity, contributing to EEG patterns which correspond to motor imagery during training to control brain-computer interface (BCI). To identify individual source contribution into EEG recorded during the training, Independent Component Analysis (ICA) was employed. Those independent components, for which the BCI system classification accuracy was at maximum, were treated as relevant to performing the motor imagery tasks. To reveal neurophysiological nature of these components we solved the inverse EEG problem in order to localize the sources of brain activity causing these components to appear in EEG. Individual geometry of brain and its covers provided by anatomical MR images, was taken into account when localizing the sources. Their positions were compared with foci of BOLD activity obtained in fMRI study.