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This work concerns spatial localization of sources of EEG patterns the most specific for control of the motor imagery based BCI. In our previous work we have shown that performance of Bayesian BCI classifier can be drastically improved by extraction of the most relevant independent components of the EEG signal. This paper presents the results of spatial localization of electrical brain activity sources which activity is reflected by the extracted components. The localization was performed by solving the inverse problem in EEG source localization, using individual finite-element head models. The sources were located in central sulcus (Brodmann area 3a), in the superior regions of post- and precentral gyri, and supplementary motor cortex.