AUTHOR=Korik Attila , Sosnik Ronen , Siddique Nazmul , Coyle Damien 

TITLE=Decoding Imagined 3D Hand Movement Trajectories From EEG: Evidence to Support the Use of Mu, Beta, and Low Gamma Oscillations

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 12 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2018.00130

DOI=10.3389/fnins.2018.00130

ISSN=1662-453X

ABSTRACT=Objective: To date, motion trajectory prediction (MTP) of a limb from non-invasive electroencephalography (EEG) has relied, primarily, on band-pass filtered samples of EEG potentials i.e., the potential time-series model. Most MTP studies involve decoding 2D and 3D arm movements i.e., executed arm movements. Decoding of observed or imagined 3D movements has been demonstrated with limited success and only reported in a few studies. MTP studies normally use EEG potential filtered in the low delta (~1Hz) band for reconstructing the trajectory of an executed or an imagined/observed movement. In contrast to MTP, multiclass classification based sensorimotor rhythm brain-computer interfaces aim to classify movements using the power spectral density of mu (8-12Hz) and beta (12-28Hz) bands. Approach: Here, we investigated if replacing the standard potential times series input with a power spectral density based bandpower time-series improves trajectory decoding accuracy of imagined hand movements are obtained by performing kinesthetically imagined 3D arm movement tasks and whether imagined arm kinematics are encoded also in mu and beta bands. Twelve naïve subjects were asked to generate or imagine generating pointing movements with their right dominant arm to four targets distributed in 3D space in synchrony with an auditory cue (beep). Main results: Using the bandpower time-series based model, the highest decoding accuracy for motor execution was obtained in mu and beta bands. For imagined movements it was obtained in mu, beta, and low gamma (28-40Hz) bands. Moreover, for both (executed and imagined) movement types, the bandpower time-series model in mu, beta, and low gamma bands provided significantly higher reconstruction accuracy than the potential time-series model in the delta band. Significance: As oppose to many studies that investigated only executed hand movements and recommended using delta band information for decoding directional information of a single limb join, our findings suggest that motor kinematics for imagined movements are reflected mostly in power spectral density of mu, beta and low gamma bands, and that these bands may be most informative for decoding 3D trajectories of imagined limb movements.