Date of Award

May 2015

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Health Sciences

First Advisor

Jinsung Wang

Committee Members

Kristian M. O'Connor, Kevin G. Keenan, Susan E. Cashin, Amol D. Mali

Keywords

Action Observation, Instance-Reliant Learning, Model-Based and Model-Free Learning, Motor Learning, Passive Training, Rehabilitation

Abstract

Passive training has been shown to be an effective rehabilitation approach for stroke survivors, especially for those who suffer from severe control loss or complete paralysis. However, the effectiveness of the treatments that utilize passive assist training is still low. The goal of this dissertation was to develop a training condition that can maximize the effects of passive training on motor learning by combining its effect with other motor learning strategies. To achieve this goal, two specific aims were pursued: one aim was to determine the effects of passive training on learning a visuomotor adaptation task; and the other aim was to determine the effects of passive training in combination with other strategies on learning a visuomotor adaptation task. Experimental results indicated that passive training has a positive effect on visuomotor learning. Furthermore, it was confirmed that a training condition consisting of action observation and passive training leads to significant performance gains beyond what either intervention alone can do. This suggests that passive training could elicit motor representational changes, inducing instance-reliant learning process (use-dependent plasticity) that encodes motor instances associated with specific effectors and task conditions. The findings from this study show great potential for developing specific rehabilitation protocols that utilize passive training and action observation together for severely impaired stroke patients in the future.

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