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Context-dependent partitioning of motor learning in bimanual movements.

ABSTRACT: Human subjects easily adapt to single dynamic or visuomotor perturbations. In contrast, when two opposing dynamic or visuomotor perturbations are presented sequentially, interference is often observed. We examined the effect of bimanual movement context on interference between opposing perturbations using pairs of contexts, in which the relative direction of movement between the two arms was different across the pair. When each perturbation direction was associated with a different bimanual context, such as movement of the arms in the same direction versus movement in the opposite direction, interference was dramatically reduced. This occurred over a short period of training and was seen for both dynamic and visuomotor perturbations, suggesting a partitioning of motor learning for the different bimanual contexts. Further support for this was found in a series of transfer experiments. Having learned a single dynamic or visuomotor perturbation in one bimanual context, subjects showed incomplete transfer of this learning when the context changed, even though the perturbation remained the same. In addition, we examined a bimanual context in which one arm was moved passively and show that the reduction in interference requires active movement. The sensory consequences of movement are thus insufficient to allow opposing perturbations to be co-represented. Our results suggest different bimanual movement contexts engage at least partially separate representations of dynamics and kinematics in the motor system.

SUBMITTER: Howard IS

PROVIDER: S-EPMC2957447 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Context-dependent partitioning of motor learning in bimanual movements.

Howard Ian S IS Ingram James N JN Wolpert Daniel M DM

Journal of neurophysiology 20100804 4

Human subjects easily adapt to single dynamic or visuomotor perturbations. In contrast, when two opposing dynamic or visuomotor perturbations are presented sequentially, interference is often observed. We examined the effect of bimanual movement context on interference between opposing perturbations using pairs of contexts, in which the relative direction of movement between the two arms was different across the pair. When each perturbation direction was associated with a different bimanual cont ...[more]

PMID: 20685927

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Project description:Using robotic devices might improve recovery post-stroke, but the optimal way to apply robotic assistance has yet to be determined. The current study aimed to investigate whether training under the robotic active-assisted mode improves bimanual motor skill learning (biMSkL) more than training under the active mode in stroke patients. Twenty-six healthy individuals (HI) and 23 chronic hemiparetic stroke patients with a detectable lesion on MRI or CT scan, who demonstrated motor deficits in the upper limb, were randomly allocated to two parallel groups. The protocol included a two-day training on a new bimanual cooperative task, LIFT-THE-TRAY, under either the active or active-assisted modes (where assistance decreased in a pre-determined stepwise fashion) with the bimanual version of the REAplan® robotic device. The hypothesis was that the active-assisted mode would result in greater biMSkL than the active mode. The biMSkL was quantified by a speed-accuracy trade-off (SAT) before (T1) and immediately after (T2) training on days 1 and 2 (T3 and T4). The change in SAT after 2 days of training (T4/T1) indicated that both HI and stroke patients learned and retained the bimanual cooperative task. After 2 days of training, the active-assisted mode did not improve biMSkL more than the active mode (T4/T1) in HI nor stroke patients. Whereas HI generalized the learned bimanual skill to different execution speeds in both the active and active-assisted subgroups, the stroke patients generalized the learned skill only in the active subgroup. Taken together, the active-assisted mode, applied in a pre-determined stepwise decreasing fashion, did not improve biMSkL more than the active mode in HI and stroke subjects. Stroke subjects might benefit more from robotic assistance when applied "as-needed." This study was approved by the local ethical committee (Comité d'éthique médicale, CHU UCL Namur, Mont-Godinne, Yvoir, Belgium; Internal number: 54/2010, EudraCT number: NUB B039201317382) on July 14, 2016 and was registered with ClinicalTrials.gov (Identifier: NCT03974750) on June 5, 2019.

Project description: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.

Dataset Information

Context-dependent partitioning of motor learning in bimanual movements.

Publications

Context-dependent partitioning of motor learning in bimanual movements.

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