Dissertation > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory

Research on the Mechanisms of Motor Learning and Adaptation in Rhesus Monkeys

Author JiangZuo
Tutor LiZuo
School Huazhong University of Science and Technology
Course Control Engineering
Keywords Motor Learning Motor Adaptation Bayesian Decision Theory Cognition
Type Master's thesis
Year 2013
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Motor is the only way to interact with the external environment as well as the basicfunction for human body. At present, human motor control system that experience a longevolution process is the most impeccable and intelligent control system. When faced withthe uncertainty and high noise exist in the motor system,it displays favorable robust andadaptive and it can gradually adapt to the external environment by motor learning, thepurpose of this thesis is to research on the mechanisms of motor learning and adaptation inmotor control system.In this thesis, we first introduce the background,purpose and meaning of motorcontrol and review the study situation in and out of China of this field. Based on this, weproposed a hypothesis that the motor control system can adapt to repeat perturbations andcan’t adapt to random perturbations and moreover, the adaption to repeat perturbations isbased on the modulation of cognition. Based on the hypothesis, we performed areach-to-grasp experiment with perturbations. By analyzing the activity of motor corticalneurons and movement trajectories recorded in the experiment, we find the motor systemdisplays non adaption to random perturbations and an obvious learning and adaptionprocess and develop a predictive control strategy at last, i.e., the experiment results provethe correctness of the hypothesis.We proposed a hypothetical motor control model composed of motor plan and motorexecution to explain the results. The motor plan in this model is based on Bayesiandecision theory framework and the result of it is that the system will invoke the inherentpatterns stored in motor memory with different weights, which are determined by theresults of Bayesian decision. A linear regress equation was used to represent the wholeinvoking process. At last, the movement trajectories were used to calculate the parametersof this regress equation, the calculations are consistent with the preconceived results of hypothetical model, which can prove that the hypothetical model is reasonable.

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