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This short technical report describes the approach submitted to the ClinicalBCI Challenge-WCCI2020. This submission aims to classify motor imagery taskfrom EEG signals and relies on Riemannian Geometry, with a twist. Instead ofusing the classical covariance matrices, we also rely on measures of functionalconnectivity. Our approach ranked 1st on the task 1 of the competition.

RIGOLETTO -- RIemannian GeOmetry LEarning: applicaTion To cOnnectivity. A contribution to the Clinical BCI Challenge -- WCCI2020