ABSTRACT
Practice of movement in virtual-reality and other artificially altered environments has been proposed as a method for rehabilitation following neurological injury and for training new skills in healthy humans. For such training to be useful, there must be transfer of learning from the artificial environment to the performance of desired skills in the natural environment. Therefore an important assumption of such methods is that practice in the altered environment engages the same learning and plasticity mechanisms that are required for skill performance in the natural environment. We test the hypothesis that transfer of learning may fail because the learning and plasticity mechanism that adapts to the altered environment is different from the learning mechanism required for improvement of motor skill. In this paper, we propose that a model that separates skill learning and environmental adaptation is necessary to explain the learning and aftereffects that are observed in virtual reality experiments. In particular, we studied the condition where practice in the altered environment should lead to correct skill performance in the original environment. Our 2-mechanism model predicts that aftereffects will still be observed when returning to the original environment, indicating a lack of skill transfer from the artificial environment to the original environment. To illustrate the model prediction, we tested 10 healthy participants on the interaction between a simple overlearned motor skill (straight hand movements to targets in different directions) and an artificially altered visuomotor environment (rotation of visual feedback of the results of movement). As predicted by the models, participants show adaptation to the altered environment and after-effects on return to the baseline environment even when practice in the altered environment should have led to correct skill performance. The presence of aftereffect under all conditions that involved changes in environment demonstrates separation of environmental adaptation and skill learning. Our results support the existence of two distinct learning modules with different adaptation properties. Therefore we suggest that adaptation to an altered environment may not be useful for training new skills.
ABSTRACT
Successful reaching requires that we plan movements to compensate for variability in motor output. Previous studies have shown that healthy adults optimally incorporate estimates of motor variability when planning a pointing task. Children with dystonia have increased variability compared with healthy children. It is not known whether they are able to compensate appropriately for the increased variability and whether this compensation leads to changes in reaching behavior. We examined healthy children and those with increased motor variability due to secondary dystonia. Using a simple virtual display, children performed a motor task where the variability of their movements was manipulated. Results showed that both subject groups changed their movement strategies in response to changes in the level of perceived motor variability. Both groups changed their strategy in a way that improved performance relative to the perceived motor variability. Importantly, dystonic children faced with decreased motor variability adapted their movement strategy to perform better and more similarly to healthy children. These findings show that both healthy and dystonic children are able to respond to changes in motor variability and alter their movement strategies.
