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
| Identifer | oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/10318182 |
| Date | January 2011 |
| Creators | Gonzalez Castro, Luis Nicolas |
| Contributors | Smith, Maurice A. |
| Publisher | Harvard University |
| Source Sets | Harvard University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Rights | closed access |
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