Electrocorticographic Dynamics Predict Visually Guided Motor Imagery of Grasp Shaping [article]

Jing Wu, Kaitlyn Casimo, David J. Caldwell, Rajesh P.N. Rao, Jeffrey G. Ojemann
2017 arXiv   pre-print
Identification of intended movement type and movement phase of hand grasp shaping are critical features for the control of volitional neuroprosthetics. We demonstrate that neural dynamics during visually-guided imagined grasp shaping can encode intended movement. We apply Procrustes analysis and LASSO regression to achieve 72% accuracy (chance = 25%) in distinguishing between visually-guided imagined grasp trajectories. Further, we can predict the stage of grasp shaping in the form of elapsed
more » ... me from start of trial (R2=0.4). Our approach contributes to more accurate single-trial decoding of higher-level movement goals and the phase of grasping movements in individuals not trained with brain-computer interfaces. We also find that the overall time-varying trajectory structure of imagined movements tend to be consistent within individuals, and that transient trajectory deviations within trials return to the task-dependent trajectory mean. These overall findings may contribute to the further understanding of the cortical dynamics of human motor imagery.
arXiv:1702.06251v1 fatcat:w4jg5jubtndtbbueodb5cs6jde