Bridging the gap between motor imagery and motor execution with a brain-robot interface.

Area of Science:

• Neuroscience
• Motor Control
• Brain-Computer Interfaces

Background:

• Electrophysiological studies suggest overlapping brain oscillations for motor imagery and execution.
• Neuroimaging and lesion studies indicate distinct cortical networks for motor imagery versus execution.
• The precise relationship between these networks remains unclear.

Purpose of the Study:

• To disentangle the distinct cortical networks involved in motor imagery and motor execution.
• To investigate the role of brain-robot interfaces in modulating these networks.
• To explore potential applications in patient screening and rehabilitation.

Main Methods:

• Twenty right-handed subjects performed behavioral tasks for kinesthetic imagery, visual imagery, visuomotor integration, and tonic contraction.
• Motor imagery was also performed with haptic/proprioceptive feedback from a brain-robot interface.
• Principal component analysis and electroencephalography (EEG) in the alpha-range using the phase slope index were employed.

Main Results:

• Two distinct cortical networks were identified: a motor imagery network (left parietal/motor to right prefrontal cortex) and a motor execution network (left to right motor areas).
• Brain-robot interface feedback may facilitate communication between motor imagery and execution networks.
• Distinct abilities and cortical networks underlie motor control.

Conclusions:

• Motor imagery and execution involve separate, identifiable cortical networks.
• Brain-robot interfaces show potential for bridging these networks, offering a novel approach to accessing the motor execution system.
• Findings may inform patient screening and novel therapeutic strategies, particularly for post-stroke hemiparesis rehabilitation.