Exploring disruption as a force for good in motor learning. Jamieson, E., Mushtaq, F., Fath, A., J., Bingham, G., P., Culmer, P., Wilkie, R., M., & Mon-Williams, M., A. ![Exploring disruption as a force for good in motor learning [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper abstract bibtex Motor performance might be enhanced through haptic guidance but we propose, counter-intuitively, that disruption benefits motor learning. We used an admittance-controlled robotic device to study motor learning in workspaces with complex novel force fields in the presence of haptic assistance and disturbance. Experiment 1 showed that haptic guidance hindered learning. Experiment 2 explored generalization across the workspace with three groups who experienced: (1) partial haptic assistance (error reduction); (2) no guidance; or (3) a constant disruptive force (error augmentation). Haptic assistance showed the worst learning whilst those exposed to disruptive forces evidenced the most training errors, but steepest training curves and best generalized learning. Experiment 3 revealed that a random combination of assistive and disruptive force enhanced learning, but learning was impaired if workspace exploration was constrained. Taken together these results demonstrate that humans can: (i) detect and rapidly adapt to a simple externally imposed force field; and (ii) benefit from the presence of task-irrelevant disturbance due to increased workspace exploration.
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title = {Exploring disruption as a force for good in motor learning},
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abstract = {Motor performance might be enhanced through haptic guidance but we propose, counter-intuitively, that disruption benefits motor learning. We used an admittance-controlled robotic device to study motor learning in workspaces with complex novel force fields in the presence of haptic assistance and disturbance. Experiment 1 showed that haptic guidance hindered learning. Experiment 2 explored generalization across the workspace with three groups who experienced: (1) partial haptic assistance (error reduction); (2) no guidance; or (3) a constant disruptive force (error augmentation). Haptic assistance showed the worst learning whilst those exposed to disruptive forces evidenced the most training errors, but steepest training curves and best generalized learning. Experiment 3 revealed that a random combination of assistive and disruptive force enhanced learning, but learning was impaired if workspace exploration was constrained. Taken together these results demonstrate that humans can: (i) detect and rapidly adapt to a simple externally imposed force field; and (ii) benefit from the presence of task-irrelevant disturbance due to increased workspace exploration.},
bibtype = {article},
author = {Jamieson, Earle and Mushtaq, Faisal and Fath, Aaron J and Bingham, Geoffrey P and Culmer, Peter and Wilkie, Richard M and Mon-Williams, Mark A}
}
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