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

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 potentials filtered in the low delta (~1 Hz) 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 (8–12 Hz) and beta (12–28 Hz) bands.Approach: We investigated if replacing the standard potentials time-series input with a power spectral density based bandpower time-series improves trajectory decoding accuracy of kinesthetically imagined 3D hand movement tasks (i.e., imagined 3D trajectory of the hand joint) and whether imagined 3D hand movements 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 observed in mu and beta bands whilst for imagined movements the low gamma (28–40 Hz) band was also observed to improve decoding accuracy for some subjects. Moreover, for both (executed and imagined) movements, the bandpower time-series model with mu, beta, and low gamma bands produced significantly higher reconstruction accuracy than the commonly used potential time-series model and delta oscillations.Significance: Contrary to many studies that investigated only executed hand movements and recommend using delta oscillations for decoding directional information of a single limb joint, 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.

Induced Gamma-Band Activity during Actual and Imaginary Movements: EEG Analysis

“…Works [24,26] likewise describe an increase, relative to basal activity, in the gamma band in both the imaginary movement and the actual movement. In addition, they do not find any difference in GBA between the actual movement and the imaginary movement.…”

The Application of EEG Mu Rhythm Measures to Neurophysiological Research in Stuttering

“…This interpretation was supported by the lack of differences in either the strength or timing of peri-labial EMG in overt production conditions. As the strength and timing of movement parameters are encoded in sensorimotor oscillations (Korik et al, 2018;Li et al, 2018), primary motor and somatosensory (i.e., external loop) influences on mu activity cannot account for observed group differences, and we propose that they represent differential internal modeling activity within the internal loop. As these differences were present in spontaneously fluent speech, we suggest that they represent an underlying sensorimotor instability that predisposes the speech of PWS to breakdown.…”

Spectral and topological analyses of the cortical representation of the head position: Does hypnotizability matter?

“…Alpha power is mainly involved in cognitive processes (Başar, Schürmann, Başar-Eroglu, & Karakas, 1997;Klimesch, 1999) but modulation of alpha rhythms has been observed also during the elaboration of event-specific sensory and motor information (Babiloni et al, 2016) and is influenced by the specific task and by the individual motor experience (Duru & Assem, 2018). Gamma power synchronization has been found in a wide range of cognitive (Bosman et al, 2014) and sensory operations (van Ede et al, 2014) and has been associated with imagined rather than executed motor actions (Korik, Sosnik, Siddique, & Coyle, 2018). Theta/delta modulation, however, has not been observed during movement.…”