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.

Figure 1

Experimental set-up (left) and wrist robot details (right).

Figure 2

Examples of speed profiles (red) and decomposition into submovements (green) for the control (top) and shift (bottom) condition for Participant 1 (single trial). The main submovements are defined as the submovements with the highest peaks (highlighted in gray).

Figure 3

Examples of ICs from Participant 1. Scalp topographies, power spectra, and ERP images are shown. In the ERP images, the vertical black line indicates when the visual target was presented to the participant. IC10 displays a scalp topography having a focal point of activation located near the neck, a power spectrum with increasing power at high frequencies, and an ERP image in which there is constant activation for the full duration of a number of trials and little activation at all in the remaining trials. These patterns are indicative of muscle activity. In contrast, IC4 displays a scalp topography having activations located in the brain (and with a dipole-like structure), a power spectrum smoothly decreasing, and an ERP image showing variation in scalp potentials over the course of a trial. These patterns are indicative of brain activity.

Figure 4

Topographic ERP scalp map series for Participant 1 for control (top) and shift (bottom) condition (100-msec interval). Target was presented at 0 msec. For the control condition, submovement onset/offset occurred at SOn/SOff; for the shift condition, target shift occurred at Ts; submovement onset/offset occurred at SOn1/SOff1 and SOn2/SOff2 for the preshift and postshift movement phase, respectively (see arrows). Note the similarity between maps for the two conditions at latencies 0–500 msec. Also note that in the shift condition maps at 600–1000 msec are similar to maps at 200–500 msec.

Figure 5

ERP image of channel C1 for the control (top) and shift (bottom) condition for Participant 1. Amplitude of EEG recordings during individual trials is shown. The vertical black line indicates when the visual target was presented to the participant. The red arrows indicates target shift. The gray and blue arrows indicate submovement onsets (average across the participant’s trials). The ERP signal is shown as the blue trace at the bottom of each panel.

Figure 6

ERP image of channel P1 for the control (top) and shift (bottom) condition for Participant 1. Amplitude of EEG recordings during individual trials is shown. The vertical black line indicates when the visual target was presented to the participant. The red arrows indicates target shift. The gray and blue arrows indicate submovement onsets (average across the participant’s trials). The ERP signal is shown as the blue trace at the bottom of each panel.

Figure 7

ERP image and signal of channel C2 for the control (top) and shift (bottom) condition for Participant 1. The vertical black line indicates when the visual target was presented to the participant. The red arrow indicates target shift. The gray and blue arrows indicate submovement onsets (average across the participant’s trials). Compare with Figure 5: ERPs have shapes similar to corresponding ERPs recorded from channel C1 but lower amplitudes.