Phase/Amplitude Synchronization of Brain Signals During Motor Imagery BCI Tasks

In the last decade, functional connectivity (FC) has been increasingly adopted based on its ability to capture statistical dependencies between multivariate brain signals. However, role of FC in context brain-computer interface applications is still poorly understood. To address this gap knowledge, we considered a group 20 healthy subjects during an EEG-based hand motor imagery (MI) task. We studied two well-established estimators, i.e. spectral- and imaginary-coherence, investigated how they were modulated by MI characterized resulting networks extracting strength each EEG sensor compared discriminant power with respect standard spectrum features. At level, results showed that while spectral-coherence network features increasing sensorimotor areas, those imaginary-coherence significantly decreasing. demonstrated opposite, but complementary, behavior was respectively determined increase amplitude phase synchronization individual eventually assessed potential these simple off-line classification scenario. Taken together, our provide fresh insights into oscillatory mechanisms subserving changes offer new perspectives improve BCI performance.