Development of methods for the analysis of neuroimaging data to identify processes in the human brain during motor activity for the development of brain-computer interfaces

The project is aimed at developing methods based on a combination of machine learning approaches and estimation of oscillation sources and time-frequency analysis, for the effective determination of the kind and type of imaginary movement made by the operator based on the registered EEG/MEG signals