Mechanisms underlying reinforcement learning of motor skills

Motor learning allows animals, including human beings, to acquire skills that are es-sential for efficient interactions with the environment. This ability to learn new motor skills is of great practical relevance for daily-life activities (such as when learning to drive), but also for motor rehabilitation after a lesion of the nervous system (such as a stroke). For a long time, motor learning has been mainly conceptualized as a process allowing to itera-tively correct movements based on sensory information (e.g., visual, somatosensory). Im-portantly though, in the last years, there has been an increased appreciation that motor learning also results from other mechanisms including reinforcement learning, a process through which appropriate actions are selected through outcome-based feedback (e.g., success or failure). As such, recent evidence shows that reinforcement feedback and mo-tivation can be beneficial for motor learning both in healthy individuals and neurological populations. Despite the potential importance of these findings to improve current rehabili-tation protocols, the mechanisms underlying reinforcement-related improvements in motor learning remain largely unexplored. This PhD aimed at providing deeper mechanistic un-derstanding of reinforcement learning of motor skills through behavioral analyses, neu-roimaging and non-invasive brain stimulation. In Study 1, I found that enhancing motiva-tion (by providing monetary reward for good performance) during a motor training can lead to persistent improvements in performance that are not obtained with reinforcement feed-back only, and are related to an increased regulation of motor variability based on previ-ous outcomes. In Study 2, I investigated the effect of reinforcement timing (i.e., the delay between the end of movement execution and reinforcement feedback) on motor learning and found that delaying reinforcement by only a few seconds could strongly influence mo-tor learning dynamics and consolidation. Finally, in Study 3, I investigated the causal role of the striatum in reinforcement motor learning. Here, I show, by combining an innovative non-invasive deep brain stimulation approach called transcranial electric temporal interfer-ence stimulation and neuroimaging, that a specific mechanism relying on striatal high gamma oscillations is causally involved in reinforcement learning of motor skills. Overall this work, characterizes key mechanisms underlying the effect of reinforcement on motor learning, paving the way towards the incorporation of optimized reinforcements in motor rehabilitation protocols.