EEG microstate analysis in human motor corrections

Abstract

How human movement is controlled is still poorly understood, but numerous studies have suggested that the Central Nervous System (CNS) generates and controls continuous movement via discrete, elementary building blocks of movement or submovements. Most supporting evidence has come from kinematic studies, with investigation of neural correlates lacking. In this study we used microstate analysis to model building blocks of neuroelectrical activity recorded from high-density electroencephalography (64-channel EEG) from healthy subjects during a reaching task that required online movement corrections. Our goal was to provide a proof-of-principle demonstration of the promise of this method of coupling neural activity with movement recording and analysis. We found that each kinematic submovement was accompanied by a stereotyped set of microstates generated by the activity of a frontoparietal network. These results provide further evidence for the hypothesis that the CNS generates and controls continuous movement via discrete submovements. Applications include design of algorithms for robot-assisted neuro-rehabilitation and quantitative outcome metrics for motor disorders of neurological origin including stroke and Parkinson's disease.