Visuomotor discordance during visually-guided hand movement in virtual reality modulates sensorimotor cortical activity in healthy and hemiparetic subjects

Abstract

We investigated neural effects of visuomotor discordances during visually-guided finger movements. A functional magnetic resonance imaging (fMRI)-compatible data glove was used to actuate (in real-time) virtual hand models shown on a display in first person perspective. In Experiment 1, we manipulated virtual hand motion to simulate either hypometric or unintentional (actuation of a mismatched finger) feedback of sequential finger flexion in healthy subjects. Analysis of finger motion revealed no significant differences in movement behavior across conditions, suggesting that between-condition differences in brain activity could only be attributed to varying modes of visual feedback rather than motor output. Hypometric feedback and mismatched finger feedback (relative to veridical) were associated with distinct activation. Hypometric feedback was associated with activation in the contralateral motor cortex. Mismatched feedback was associated with activation in bilateral ventral premotor, left dorsal premotor, and left occipitotemporal cortex. The time it took the subject to evaluate visuomotor discordance was positively correlated with activation in bilateral supplementary motor area, bilateral insula, right postcentral gyrus, bilateral dorsal premotor areas, and bilateral posterior parietal lobe. In Experiment 2, we investigated the effects of hypo- and hypermetric visual feedback in three stroke subjects. We observed increased activation of ipsilesional motor cortex in both hypometric and hypermetric feedback conditions. Our data indicate that manipulation of visual feedback of one's own hand movement may be used to facilitate activity in select brain networks. We suggest that these effects can be exploited in neurorehabilition to enhance the processes of brain reorganization after injury and, specifically, might be useful in aiding recovery of hand function in patients during virtual reality-based training.

Figure 1

Behavioral measurements and experimental setup. (A) A subject wearing the 5DT data glove and flexing the index finger at the start of a sequential movement. B) The display showing the left and right VR hand models. The right virtual hand model was actuated (in real-time) by the subject’s right hand movement. (C) The four feedback manipulations imposed on the virtual finger are: “V”, veridical; “G65” and “G25”, virtual hand amplitude down-scaled to 65% or 25% of movement, respectively; and “MF”, mismatched (non-corresponding) finger. (D) A sample trace showing 3-seconds (separated by hash marks) of MCP joint angle movement (y-axis, degrees) for the index (i), middle (m), ring (r), and pinky (p) fingers in each of the four conditions; the conditions in panel D correspond to the conditions in panel C.

Figure 2

Regions showing significant activity during movement. Activation is plotted on a rendering of the fiducial brain (Caret [19]). Colormap represents t-statistics. This map has been used as an inclusive mask for subsequent analyses.

Figure 3

Contrasts between veridical (V) and hypometric (G25) feedback conditions. Regions where activity increased (red) and decreased (blue) with visual discordance gain are shown as SPM T-maps superimposed on an inflated fiducial anatomical rendering (Caret [19]). For plotting, threshold was slightly lowered (p<0.01) to better illustrate activated regions. Beta estimates for activation in each condition (V, G65, G25) are shown in the bar plots. Error bars indicate 90% confidence intervals.

Figure 4

Contrasts between veridical (V) and mismatched feedback (MF) conditions. SPM T-maps are superimposed on an inflated fiducial anatomical rendering using Caret software [19]. For plotting, threshold was slightly lowered (p<0.01) to better illustrate activated regions. Beta estimates for activation in each feedback condition (V, MF) are shown in the bar plots. Error bars indicate 90% confidence intervals.

Figure 5

(A) Scatter plot showing strong correlation between subject’s perception of feedback congruence and strength of visuomotor discordance. (B) Decision time (to estimate visuomotor discordance) per condition.

Figure 6

Results of stroke subjects, experiment 2. Regions showing significantly more activation in the veridical (V) than the G25 condition shown over a fiducial brain (Caret [19]). Beta estimates for activation in the ipsilesional motor cortex in each condition are shown in the bar plots to the right (G175, V, G25). Error bars indicate 90% confidence intervals.