21 research outputs found

    Distinct Haptic Cues Do Not Reduce Interference when Learning to Reach in Multiple Force Fields

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    Background: Previous studies of learning to adapt reaching movements in the presence of novel forces show that learning multiple force fields is prone to interference. Recently it has been suggested that force field learning may reflect learning to manipulate a novel object. Within this theoretical framework, interference in force field learning may be the result of static tactile or haptic cues associated with grasp, which fail to indicate changing dynamic conditions. The idea that different haptic cues (e.g. those associated with different grasped objects) signal motor requirements and promote the learning and retention of multiple motor skills has previously been unexplored in the context of force field learning. Methodology/Principle Findings: The present study tested the possibility that interference can be reduced when two different force fields are associated with differently shaped objects grasped in the hand. Human subjects were instructed to guide a cursor to targets while grasping a robotic manipulandum, which applied two opposing velocity-dependent curl fields to the hand. For one group of subjects the manipulandum was fitted with two different handles, one for each force field. No attenuation in interference was observed in these subjects relative to controls who used the same handle for both force fields. Conclusions/Significance: These results suggest that in the context of the present learning paradigm, haptic cues on their own are not sufficient to reduce interference and promote learning multiple force fields

    Current pharmacotherapy for tic disorders

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    Visual Cues Signaling Object Grasp Reduce Interference in Motor Learning

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    Recent motor learning studies show that human subjects and nonhuman primates form neural representations of novel mechanical environments and associated forces. Whereas proficient adaptation is seen for a single force field, when faced with multiple novel force environments, movement performance and in particular the ability to switch between different force environments declines. It is difficult to reconcile these findings with the notion that primates can proficiently switch between multiple motor skills. Conceivably, particular kinds of sensory, cognitive, or perceptual contextual cues are required. This study examined the effect of visual feedback on motor learning, in particular, cues that simulated interaction with a virtual object. A robot arm was used to deliver novel patterns of forces (force fields) to the limb during reaching movements. We tested the possibility that subjects transition more easily between novel forces and their sudden absence when they are accompanied by visual cues that relate to object grasp. We used a virtual display system to present subjects with different kinds of visual feedback during reaching, including illusory feedback, indicating grasp of a virtual object during reaching in the force field, and object release in the absence of forces. Throughout the experiment, subjects in fact maintained grasp of the robot. We found that, indeed, the most effective visual cues were those associating the force field with grasp of the virtual object and the absence of the force field with release of the object. Our findings show more broadly that specific visual cues can protect motor skills from interference. </jats:p

    Movement perpendicular distance for subjects who grasped the same handle in three consecutive blocks of the CWFF.

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    <p>Each data point represents the mean perpendicular distance over 6 movements, averaged over subjects.</p

    Believers versus non-believers.

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    <p>a: Mean perpendicular distance for movements in the CWFF, CCWFF and CWFF are shown for subjects who reported believing that they were grasping two different objects in the CWFF and CCWFF sessions (“believers”, indicated by traces marked with triangles), and those who reported believing that they were grasping the same object in all sessions (“non-believers”, indicated by traces marked with open circles). For each group data are further decomposed into subjects who grasped the same cylindrical handle for all three sessions (dark traces), and those who grasped the cylindrical handle for CWFF sessions and a spherical handle for the CCWFF session (light traces). Each data point represents the mean perpendicular distance over 6 movements, averaged over subjects. b: Catch-trial performance for believers and non-believers. Each data point represents mean perpendicular distance averaged over subjects for single movements.</p
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