3D Hand Movements Reconstructed from Noninvasive EEG Signals

Researchers at the University of Maryland (College Park, USA) decoded hand movement velocity from neural data acquired with a 55-channel electroencephalograph (EEG) placed on the scalp during a 3D center-out reaching task. The participants were asked to reach from a center button and touch eight other buttons in random order 10 times, while the researchers recorded their brain signals and hand motions. To preserve ecological validity, five subjects self-initiated reaches and self-selected targets; eye movements were controlled so they would not confound the interpretation of the results.

The researchers found that with only 34 sensors, the correlation between measured and reconstructed hand velocity profiles compared reasonably well to that reported by studies that decoded hand kinematics from neural activity acquired intra-cranially. The researchers subsequently examined the contributions of individual EEG sensors to decoding and found substantial involvement of scalp areas over the sensorimotor cortex contralateral to the reaching hand. Using standardized low-resolution brain electromagnetic tomography (sLORETA), they then identified distributed current density sources that were related to hand velocity in the contralateral precentral gyrus, postcentral gyrus, and inferior parietal lobule.

The researchers found that one sensor in particular, located over the primary sensorimotor cortex-- a region associated with voluntary movement--provided the most accurate information. Useful signals were also recorded from the inferior parietal lobule, which is known to help guide limb movement. The researchers also found that movement variability was negatively correlated with decoding accuracy. The study was published in the March 3, 2010, issue of the Journal of Neuroscience.

"Our results showed that electrical brain activity acquired from the scalp surface carries enough information to reconstruct continuous, unconstrained hand movements,” concluded lead author José Contreras-Vidal, Ph.D., and colleagues of the department of bioengineering. "The ability to continuously decode 3D hand velocity from EEG during natural, center-out reaching holds promise for the furtherance of noninvasive neuromotor prostheses for movement-impaired individuals.”

"It may eventually be possible for people with severe neuromuscular disorders, such as amyotrophic lateral sclerosis (ALS), stroke, or spinal cord injury, to regain control of complex tasks without needing to have electrodes implanted in their brains," commented Jonathan Wolpaw, M.D., of the Wadsworth Center (Albany, NY, USA). "The paper enhances the potential value of EEG for laboratory studies and clinical monitoring of brain function.”

Related Links:
University of Maryland
Wadsworth Center