Ricerc@Sapienza

Discriminating mental states from brain signals is crucial for many applications in cognitive and clinical neuroscience. Most of the studies relied on the feature extraction from the activity of single brain areas, thus neglecting the potential contribution of their functional coupling, or connectivity. Here, we consider spectral coherence and imaginary coherence to infer brain connectivity networks from electroencephalographic (EEG) signals recorded during motor imagery and resting states in a group of healthy subjects.