Effort, success, and side of lesion determine arm choice in individuals with chronic stroke

Abstract

In neurotypical individuals, arm choice in reaching movements depends on expected biomechanical effort, expected success, and a handedness bias. Following a stroke, does arm choice change to account for the decreased motor performance, or does it follow a preinjury habitual preference pattern? Participants with mild-to-moderate chronic stroke who were right-handed before stroke performed reaching movements in both spontaneous and forced-choice blocks, under no-time, medium-time, and fast-time constraint conditions designed to modulate reaching success. Mixed-effects logistic regression models of arm choice revealed that expected effort predicted choices. However, expected success only strongly predicted choice in left-hemiparetic individuals. In addition, reaction times decreased in left-hemiparetic individuals between the no-time and the fast-time constraint conditions but showed no changes in right-hemiparetic individuals. Finally, arm choice in the no-time constraint condition correlated with a clinical measure of spontaneous arm use for right-, but not for left-hemiparetic individuals. Our results are consistent with the view that right-hemiparetic individuals show a habitual pattern of arm choice for reaching movements relatively independent of failures. In contrast, left-hemiparetic individuals appear to choose their paretic left arm more optimally: that is, if a movement with the paretic arm is predicted to be not successful in the upcoming movement, the nonparetic right arm is chosen instead.NEW & NOTEWORTHY Although we are seldom aware of it, we constantly make decisions to use one arm or the other in daily activities. Here, we studied whether these decisions change following stroke. Our results show that effort, success, and side of lesion determine arm choice in a reaching task: whereas left-paretic individuals modified their arm choice in response to failures in reaching the target, right-paretic individuals showed a pattern of choice independent of failures.

Keywords: arm choice; chronic stroke; habits; reaching; value-based models of choice.

Graphical abstract

Figure 1.

Bilateral arm reaching test setup, target locations, and protocol. A: setup. The circles on the bottom and the middle of the touch screen show the home position and a target, respectively. At each trial, participants were instructed to reach to the target using either right or left index finger (depending on conditions) as quickly and accurately as possible. Magnetic sensors were attached to the index finger tips of both hands to record the choice of hand and kinematics. B: 35 targets displayed in the workspace (plus the home target, shown surrounded by a square). Gray shading shows the time constraint for each target in the fast condition. C: experimental protocol common for the stroke group. On day 1, the forced choice blocks (PA and NA) were always presented before the spontaneous choice blocks (SC) for familiarization purpose. On days 2 and 3, reminder sessions (R) were presented before the spontaneous choice blocks, followed by the forced choice blocks (PA) for the medium and fast conditions (see materials and methods). The spontaneous choice blocks used for the analysis of the paretic arm choice are shaded in gray. D: examples of velocity profile of a single reaching movements for one subject poststroke illustrating the computation of movement time. E: example of estimated joint angle. An inverse kinematics model was used to estimate shoulder and elbow joint angles from hand trajectories. F: example of shoulder and elbow joint torques estimated by an inverse dynamics model of the arm in 2 dimensions. Fast, fast-time constraint condition; Medium, medium-time constraint condition; NA, nonparetic arm only block; No-time, no-time constraint condition; PA, paretic arm only block; R, reminder block; SC, spontaneous choice block.

Figure 2.

Arm choice in the spontaneous choice block across no-time, medium, and fast conditions for 1 representative participant from each group. Circle markers represent right arm choice and square markers represent left arm choice. Black-shaded markers represent the paretic arm choice for the RH and the LH participants. Overall, the RH and LH participants chose their paretic arm less often than the nonparetic arm, whereas the (right-handed) participant in the control group chose the right arm more than the left arm. Across conditions, the participants in the RH and the control groups maintained similar arm choice patterns, whereas the LH participant largely decreased paretic arm choice in the fast condition. Control, neurotypical age-match participant; LH, participant with left hemiparesis; RH, participant with right hemiparesis.

Figure 3.

Effort and success of the paretic arm and choice reaction times in RH, LH, and control groups. A and B: effort and success rates measured in the forced choice blocks of the paretic arm for RH and LH groups (and the right arm for control group) in the no-time (white), medium- (light gray), and fast- (dark gray) time constraint conditions. Dots indicate each individual. C: reaction times measured in the spontaneous choice blocks across the time-constraint conditions for all groups. a.u., arbitrary unit; LH, left hemiparesis; Lt., Left arm; n.s., not significant; RH, right hemiparesis; Rt., right arm; *P < 0.05, **P < 0.01, ***P < 0.001. Error bars show standard deviations.

Figure 4.

Right arm choice from actual data, best-fit models, and reduced models. A: right arm choice measured by the spontaneous choice block in the no-time (white), the medium- (light gray) and the fast- (dark gray) time constraint conditions for RH, LH, and control groups. Note that the percentage of (left) paretic arm choice for the LH group is given by 100% minus right arm choice. B: average choice predicted by the best-fit models with effort and success: the models well predict the average right arm choice in all time conditions (compare with the data in A). C: fixed-effect coefficients significantly different from zero are indicated by *P < 0.05, **P < 0.01, ***P < 0.001. The success term is only significant for the LH group. The constant terms that are statistically positive for the control and LH groups indicate the bias of using the right arm. D: average choice predicted by the reduced models with the effort terms but without the success terms (model 1 in Table 1): the model for the LH group does not account for the modulation of arm choice with the time condition (compare with B). LH, left hemiparesis; n.s., not significant; RH, right hemiparesis.

Figure 5.

Correlation analysis between AAUT and paretic arm choice for RH and LH groups in no-time, medium-, and fast-time constraint conditions. Top row shows the correlations between the paretic arm use measured by AAUT and the paretic arm choice measured by the reaching system in the no-time (A), the medium- (B), and the fast- (C) time constraint conditions in the RH group. Bottom row shows the correlations in the LH group. The RH group shows moderate-to-good correlations between clinical test and the paretic arm choice in all time conditions, whereas the LH group shows only good correlation under the fast- (F) time constraint conditions, but not under the no-time (D) or the medium- (E) time constraint conditions. **P < 0.01, ***P < 0.001. AAUT, Amount of Arm Use Test; LH, left hemiparesis; QOM, quality of movement scale; RH, right hemiparesis.