• Maria L Stavrinou, Liviu Moraru, Laura Cimponeriu, Stefania Della Penna, and Anastasios Bezerianos.
• Department of Medical Physics, School of Medicine, University of Patras, University Campus, Rio, 26500, Patras, Greece.
• Brain Topogr. 2007 Jan 1; 19 (3): 137-45.

AbstractAccumulating evidence suggests the existence of a shared neural substrate between imagined and executed movements. However, a better understanding of the mechanisms involved in the motor execution and motor imagery requires knowledge of the way the co-activated brain regions interact to each other during the particular (real or imagined) motor task. Within this general framework, the aim of the present study is to investigate the cortical activation and connectivity sub-serving real and imaginary rhythmic finger tapping, from the analysis of multi-channel electroencephalogram (EEG) scalp recordings. A sequence of 250 auditory pacing stimuli has been used for both the real and imagined right finger tapping task, with a constant inter-stimulus interval of 1.5 s length. During the motor execution, healthy subjects were asked to tap in synchrony with the regular sequence of stimulus events, whereas in the imagery condition subjects imagined themselves tapping in time with the auditory cue. To improve the spatial resolution of the scalp fields and suppress unwanted interferences, the EEG data have been spatially filtered. Further, event related synchronization and desynchronization phenomena and phase synchronization analysis have been employed for the study of functionally active brain areas and their connectivity during real and imagery finger tapping. Our results show a fronto-parietal co-activation during both real and imagined movements and similar connectivity patterns among contralateral brain areas. The results support the hypothesis that functional connectivity over the contralateral hemisphere during finger tapping is preserved in imagery. The approach and results can be regarded as indicative evidences of a new strategy for recognizing imagined movements in EEG-based brain computer interface research.

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