P 11 Motor adaptation learning and the effects of reinforcement in the acute phase post-stroke. (May 2022)

• Record Type: Journal Article
• Authors: Paul, T.; Wiemer, V.M.; Grafton, S.T.; Fink, G.R.; Volz, L.J.
• Is Part Of: Clinical neurophysiology. Volume 137(2022)
• Page Start: e20
• Page End: e21
• Publication Date: 2022-05
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2022.01.042
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Introduction: Motor recovery after stroke relies on reorganization processes that mainly occur within the critical period, a time-limited window of heightened neuronal plasticity in the first few weeks after stroke 1 . These processes are assumed to partly depend on training-dependent motor learning, which may assist in establishing new motor control policies. While chronic stroke patients have been shown to exhibit motor adaptation in response to perturbations in a reinforcement-dependent fashion 2, it remains unclear if this is also true early after stroke. Therefore, we probed whether acute stroke patients can perform motor adaptation and if motor adaptation can be enhanced by monetary reinforcement. Patients & Methods: Hospitalized patients within the first two weeks after ischemic stroke suffering from hemiparesis and an age-matched healthy control group performed a joystick-based visuomotor adaptation task. Using a crossover design, subjects received neutral or performance-based reinforcement feedback in the form of monetary reward and punishment during adaptation learning. Results: Acute stroke patients exhibited motor adaptation with their paretic hand ( p <.01) and retained the novel learned motor control policies. Patients showed increased learning rates after offline consolidation in the retention period ( p <.05), whereas control subjects featured earlier improvements in learning rates during the learning period ( p <.05). While monetary reward and punishment feedback amplified motor adaptation compared to the neutral condition ( p <.05), reward seemed to be a more suitable framework to support visuomotor learning. Conclusion: We demonstrate for the first time that acute stroke patients can perform motor adaptation by rapidly adjusting motor control policies. From a mechanistic perspective, motor adaptation is often conceptualized as a dual-rate model 3, including two parallel learning components acting on different timescales. Patients seem to rely on a slower learning component more heavily, while learning of controls aligns stronger with the fast component. The former is associated with slower unlearning, which may benefit effective motor rehabilitation as newly adapted motor control policies can be retained over a prolonged period and thus integrated into daily life. While both reward and punishment enhanced motor adaptation compared to neutral feedback, reward seemed to elicit the most beneficial effects on motor learning early after stroke. In summary, our findings suggest that motor adaptation may enhance relearning of motor control policies and might thus amplify recovery in a reinforcement-dependent fashion. These findings may impact future treatment protocols aiming at improving motor function in the critical period after stroke. References 1 Krakauer, 2015. Oxford Textbook of Neurorehabilitation, 55–64. 2 Quattrocchi et al., 2017. J Neurol Neurosurg Psychiatry, 88(9), 730–736. 3 Smith et al., 2006. PLoS Biol, 4(6), e179.