title: Spatiotemporal dynamics of online motor correction processing revealed by high-density electroencephalography.
abstract: The ability to control online motor corrections is key to dealing with unexpected changes arising in the environment with which we interact. How the CNS controls online motor corrections is poorly understood, but evidence has accumulated in favor of a submovement-based model in which apparently continuous movement is segmented into distinct submovements. Although most studies have focused on submovements' kinematic features, direct links with the underlying neural dynamics have not been extensively explored. This study sought to identify an electroencephalographic signature of submovements. We elicited kinematic submovements using a double-step displacement paradigm. Participants moved their wrist toward a target whose direction could shift mid-movement with a 50% probability. Movement kinematics and cortical activity were concurrently recorded with a low-friction robotic device and high-density electroencephalography. Analysis of spatiotemporal dynamics of brain activation and its correlation with movement kinematics showed that the production of each kinematic submovement was accompanied by (1) stereotyped topographic scalp maps and (2) frontoparietal ERPs time-locked to submovements. Positive ERP peaks from frontocentral areas contralateral to the moving wrist preceded kinematic submovement peaks by 220-250 msec and were followed by positive ERP peaks from contralateral parietal areas (140-250 msec latency, 0-80 msec before submovement peaks). Moreover, individual subject variability in the latency of frontoparietal ERP components following the target shift significantly predicted variability in the latency of the corrective submovement. Our results are in concordance with evidence for the intermittent nature of continuous movement and elucidate the timing and role of frontoparietal activations in the generation and control of corrective submovements.
authors.affiliation: Massachusetts Institute of Technology.
authors.forename: Laura
authors.initials: L
authors.lastname: Dipietro
authors.forename: Howard
authors.initials: H
authors.lastname: Poizner
authors.forename: Hermano I
authors.initials: HI
authors.lastname: Krebs
mesh_terms: D000293:Adolescent; D000328:Adult; D001288:Attention / Q000502:physiology; D001696:Biomechanical Phenomena; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D004569:Electroencephalography; D019054:Evoked Potentials, Motor / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D009068:Movement / Q000502:physiology*; D017711:Nonlinear Dynamics; D009862:Online Systems; D025341:Principal Component Analysis; D011597:Psychomotor Performance / Q000502:physiology*; D013223:Statistics as Topic; D013997:Time Factors; D014953:Wrist / Q000294:innervation; D055815:Young Adult