Assessing Impairments in Visuomotor Adaptation After Stroke

Abstract

Background: Motor impairment in the arms is common after stroke and many individuals participate in therapy to improve function. It is assumed that individuals with stroke can adapt and improve their movements using feedback that arises from movement or is provided by a therapist. Here we investigated visuomotor adaptation in individuals with sub-acute and chronic stroke.

Objective: We examined the impact of the stroke-affected arm (dominant or non-dominant), time post-stroke, and relationships with clinical measures of motor impairment and functional independence.

Methods: Participants performed reaching movements with their arm supported in a robotic exoskeleton. We rotated the relationship between the motion of the participant's hand and a feedback cursor displayed in their workspace. Outcome measures included the amount that participants adapted their arm movements and the number of trials they required to adapt.

Results: Participants with stroke (n = 36) adapted less and required more trials to adapt than controls (n = 29). Stroke affecting the dominant arm impaired the amount of adaptation more than stroke affecting the non-dominant arm. Overall, 53% of participants with stroke were impaired in one or more measures of visuomotor adaptation. Initial adaptation was weakly correlated with time post-stroke, and the amount of adaptation correlated moderately with clinical measures of motor impairment and functional independence.

Conclusion: Our findings reveal impairments in visuomotor adaptation that are associated with motor impairment and function after stroke. Longitudinal studies are needed to understand the relationship between adaptation and recovery attained in a therapy setting.

Keywords: motor learning; recovery; rehabilitation; robotics; stroke; upper limb.

Figure 1.

Experimental apparatus, protocol, and analysis. ( A ) Kinarm exoskeleton robot. ( B ) General layout of the task. Participants were instructed to guide a small white cursor between two targets located in front of their body. Participants began each trial by moving the feedback cursor into a central start position (2 cm diameter). After a brief hold period (750 ± 500 ms, uniformly distributed), a goal target appeared 10 cm directly in front of the start position. The start target then disappeared. Participants reached to the goal position and then briefly held their feedback cursor in the goal (1000 ms). The start target then reappeared on the visual display. ( C ) Experimental protocol. Participants began with 25 baseline trials (cursor aligned to the tip of the index finger), followed by 125 adaptation trials with a 30° counter-clockwise visuomotor rotation, then finally 25 washout trials (cursor aligned to index fingertip). ( D ) The initial reach direction on each trial was calculated as the angular deviation of the hand relative to a straight line connecting the targets at 150 ms after the onset of movement. ( E ) Lesion overlap of all participants with stroke (neurological display convention; n = 36). MNI coordinates (z-axis) are labeled below each axial slice. Color bar shows the number of participants with damage in each voxel (brighter intensity indicates more participants with lesions in that region).

Figure 2.

Hand paths, adaptation patterns, and bootstrap hypothesis tests. ( A ) Exemplar hand paths and standard deviation (shaded regions) for a control (Final Adaptation = 91%), a participant with mild motor impairment and poor adaptation (Final Adaptation = 50%), and a participant with moderate motor impairment and good adaptation (Final Adaptation = 80%). The arrow represents full adaptation (30° clockwise). ( B ) Adaptation curves for controls and participants with stroke. Adaptation data were smoothed with a moving average filter (window length = 5; overlap = 4) and are presented as the mean (line) and SE (shaded regions). Initial reach direction (measured in degrees) is plotted throughout trials in the baseline (B), adaptation (A), and washout (W) phases. Gray regions indicate when Initial Adaptation and Final Adaptation were measured. Bootstrapped probability distributions (PD: red and blue), cumulative distribution functions (CD), and hypothesis tests (C vs S; gray distributions) are shown for ( C ) Initial Adaptation, ( D ) Final Adaptation, and ( E ) Trials to Adapt. The observed difference between controls and participants with stroke (Control (C) – Stroke (S), black dot and dashed line) was evaluated against the null (gray PD and black CD). P-values are shown for ( C ) Initial Adaptation,( D ) Final Adaptation, and ( E ) Trials to Adapt. Bar plots represent the proportion of participants who performed poorly on each measure.

Figure 3.

Visuomotor adaptation curves and bootstrap hypothesis tests examining the influence of the stroke-affected arm. ( A ) Visuomotor adaptation curves for controls (C: red), dominant arm affected participants with stroke (DA: cyan), and non-dominant affected participants with stroke (NDA: black). Adaptation curves were smoothed using a moving average (window length = 5; overlap = 4) and show the group mean (line) and SE (shaded regions). Initial reach direction (measured in degrees) is plotted throughout trials in the baseline (B), adaptation (A), and washout (W) phases. Gray regions indicate when Initial Adaptation and Final Adaptation were measured. ( B ) Bootstrapped probability distributions (PD (%)), cumulative distribution functions (CD (%)), hypothesis tests (gray distributions, black dots, and dashed lines), and the proportion of participants who performed poorly are shown for Final Adaptation.

Figure 4.

Scatter plots of ( A ) Time Post-Stroke vs Initial Adaptation, ( B ) FMA-UE, and ( C ) FIM scores vs Final Adaptation. Individual participant data is coded based on the side of the stroke-affected arm. Vertical dashed lines indicate the maximum achievable score for FMA-UE and FIM assessments.