Reward During Arm Training Improves Impairment and Activity After Stroke: A Randomized Controlled Trial

Abstract

Background Learning and learning-related neuroplasticity in motor cortex are potential mechanisms mediating recovery of movement abilities after stroke. These mechanisms depend on dopaminergic projections from midbrain that may encode reward information. Likewise, therapist experience confirms the role of feedback/reward for training efficacy after stroke. Objective To test the hypothesis that rehabilitative training can be enhanced by adding performance feedback and monetary rewards. Methods This multicentric, assessor-blinded, randomized controlled trial used the ArmeoSenso virtual reality rehabilitation system to train 37 first-ever subacute stroke patients in arm-reaching to moving targets. The rewarded group (n = 19) trained with performance feedback (gameplay) and contingent monetary reward. The control group (n = 18) used the same system without monetary reward and with graphically minimized performance feedback. Primary outcome was the change in the two-dimensional reaching space until the end of the intervention period. Secondary clinical assessments were performed at baseline, after 3 weeks of training (15 1-hour sessions), and at 3 month follow-up. Duration and intensity of the interventions as well as concomitant therapy were comparable between groups. Results The two-dimensional reaching space showed an overall improvement but no difference between groups. The rewarded group, however, showed significantly greater improvements from baseline in secondary outcomes assessing arm activity (Box and Block Test at post-training: 6.03±2.95, P = .046 and 3 months: 9.66±3.11, P = .003; Wolf Motor Function Test [Score] at 3 months: .63±.22, P = .007) and arm impairment (Fugl-Meyer Upper Extremity at 3 months: 8.22±3.11, P = .011). Conclusions Although neutral in its primary outcome, the trial signals a potential facilitating effect of reward on training-mediated improvement of arm paresis. Trial registration ClinicalTrials.gov (ID: NCT02257125).

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

“…For instance, the addition of reinforcement feedback during motor training can improve motor learning, presumably by boosting the retention of newly acquired motor memories 6,7 . Interestingly, reinforcement feedback also appears to be relevant for the rehabilitation of patients suffering from motor impairments [8][9][10] . Yet, despite these promising results, there is currently a lack of understanding of the brain mechanisms that are critical to implement this behaviour.…”

Reward enhances motor adaptation learning in acute stroke patients

“…Moreover, reward has recently been discussed to improve the generalization of adaptation learning in the healthy brain (Yin et al, 2023). Accordingly, while reward failed to enhance arm-reaching performance of subacute stroke patients compared to neutral feedback, patients who received reward during arm-reaching training showed greater improvements in secondary outcome measures such as the Fugl-Meyer Upper Extremity score which may similarly be interpreted as a generalization effect of the arm-reaching training (Widmer et al, 2022). While we did not test for generalization, the superior performance during the washout period observed after reward may suggest that reward did not only improve retention of the novel control policy, but also led to an increased ability to flexibly adapt to changing environments.…”

Reward network dysfunction is associated with cognitive impairment after stroke

“…Since the reward system is a crucial modulator of reinforcement in various cognitive functions, it also plays a critical role in the learning processes ( Bowen et al, 2020 , Cohen et al, 2016 , Schultz et al, 1997 , Spaniol et al, 2014 ). Performance-related reward feedback improves motor skill learning processes and reinforces long-term learning outcome ( Boyd et al, 2009 , Lam et al, 2013 , Vassiliadis et al, 2021 , Wachter et al, 2009 , Widmer et al, 2022 , Widmer et al, 2016 ). In healthy individuals, the speed of learning depends on the reward magnitude.…”