Abstract
In the last decade, functional connectivity (FC) has been increasingly adopted based on its ability to capture statistical dependencies between multivariate brain signals. However, the role of FC in the context of brain-computer interface applications is still poorly understood. To address this gap in knowledge, we considered a group of 20 healthy subjects during an EEG-based hand motor imagery (MI) task. We studied two well-established FC estimators, i.e. spectral- and imaginary-coherence, and we investigated how they were modulated by the MI task. We characterized the resulting FC networks by extracting the strength of connectivity of each EEG sensor and we compared the discriminant power with respect to standard power spectrum features. At the group level, results showed that while spectral-coherence based network features were increasing in the sensorimotor areas, those based on imaginary-coherence were significantly decreasing. We demonstrated that this opposite, but complementary, behavior was respectively determined by the increase in amplitude and phase synchronization between the brain signals. At the individual level, we eventually assessed the potential of these network connectivity features in a simple off-line classification scenario. Taken together, our results provide fresh insights into the oscillatory mechanisms subserving brain network changes during MI and offer new perspectives to improve BCI performance.
Highlights
The results obtained with node strength were not associated with those obtained by using P values (Pearson’s correlation < 0.1). These findings indicated that the motor imagery of the hand grasping elicits detectable brain network changes that might be useful to characterize and discriminate MI-based brain-computer interfaces (BCIs) tasks
The main purpose of our work consists in characterizing brain network connectivity changes during motor imageryrelated BCI tasks
The fundamental contribution of our work consists in the fact that we unveiled two complementary connectivity mechanisms, measured respectively by spectral and imaginary coherence, that occurred simultaneously during the MI task
Summary
Corsi are with Institut du Cerveau, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Universite, Paris, France. D. S.Bassett is with Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104,USA. D. S.Bassett is with Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA. D. S.Bassett is with Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA. D. S.Bassett is with Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, 19104, USA. D. S.Bassett is with Department of Psychiatry, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
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