Understanding the neural processes underlying motor learning in humans is important to facilitate the acquisition of new motor skills and to aid the relearning of skills lost after neurologic injury. Although it is known that the learning of a new movement is guided by the error feedback received after each repeated attempt to produce the movement, how the central nervous system (CNS) processes individual errors and how it modulates its learning rate in response to the history of errors experienced are issues that remain to be elucidated. To address these issues we studied the generalization of learning and learning decay – the transfer of what has been learned, or unlearned, in a particular movement condition to new movement conditions. Generalization offers a window into the process of error credit assignment during motor learning, since it allows us to measure which actions benefit the most in terms of learning after experiencing an error. We found that the distributions that describe generalization after learning are unimodal and biased towards the motion directions experienced during training, a finding that suggests that the credit for the learning experienced after a particular trial is assigned to the actual motion (motion-referenced learning) and not to the planned motion (plan-referenced learning) as it had previously been assumed in the motor learning literature. In addition, after training the same action along multiple directions, we found that the pattern of learning decay has two distinct components: one that is time-dependent and affects all trained directions, and one that is trial-dependent and affects mostly the direction where decay was induced, generalizing narrowly with a unimodal pattern similar to the one observed for learning generalization. We finally studied the effect that the consistency of the error perturbations in the training environment has on the learning rate adopted by the CNS. We found that learning rate increases when the perturbations experienced in training are consistent, and decreases when these perturbations are inconsistent. Besides increasing our understanding of the mechanisms underlying motor learning, the findings described in the present dissertation will enable the principled design of skill training and rehabilitation protocols that accelerate learning. / Engineering and Applied Sciences

Dans la littérature, de nombreuses recherches dans le domaine du contrôle moteur, des sciences du sport ou encore de la rééducation se sont intéressées à l’apprentissage moteur consécutif à un entrainement mental. Cependant, plusieurs mécanismes, qu’ils soient comportementaux ou neurophysiologiques, demeurent encore aujourd’hui peu étudiés. Dans notre première étude, nous avons montré qu’il était impossible de prédire la future amélioration de la performance suite à un entrainement mental aigu, sur une tâche de vitesse-précision, par la simple évaluation subjective des capacités d’imagerie chez une population jeune. Il apparait cependant essentiel de produire des images claires et précises tout au long de l’entrainement pour obtenir de meilleures performances in fine. De plus, par l’analyse fine de la performance, nos résultats ont montré, dans notre seconde étude, les véritables effets des répétitions imaginées sur la mémorisation des habiletés motrices. L’entrainement mental est également apparu efficace pour compenser le déficit de mémoire motrice rapidement observable dans la population âgée. Enfin, une troisième étude a révélé que les répétitions d’un mouvement imaginé pouvaient modifier, de façon transitoire, le codage des réseaux neuronaux impliqués dans le processus de mémoire motrice. / For many years, research in motor control, sport science and rehabilitation focused on the performance improvement following mental practice. However, some mechanisms, behavioral and neurophysiological, remain insufficiently understood. In our first study, we demonstrated the impossibility to predict the future performance improvement following imagined repetitions of a speed accuracy trade-off task, with a subjective evaluation of imagery ability of young healthy individuals. However, it is essential to produce clear and vivid mental simulations throughout the training to obtain a better performance improvement. Besides, by a further analysis of performance, the results of our second study have shown the real impact of mental training on the memorization of motor skills. Motor imagery training also appeared to be effective to compensate the motor memory deficit observed in the elderly. Finally, a third study revealed that the repetitions of imagined movements could modify, temporarily, the coding of neural networks involved in the motor memory process.

No description available.