Literature DB >> 9671681

The role of inertial sensitivity in motor planning.

P N Sabes1, M I Jordan, D M Wolpert.   

Abstract

To achieve a given motor task a single trajectory must be chosen from the infinite set of possibilities consistent with the task. To investigate such motor planning in a natural environment, we examined the kinematics of reaching movements made around a visual obstacle in three-dimensional space. Within each session, the start and end points of the movement were uniformly varied around the obstacle. However, the distribution of the near points, where the paths came closest to the obstacle, showed a strong anisotropy, clustering at the poles of a preferred axis through the center of the obstacle. The preferred axes for movements made with the left and right arms were mirror symmetric about the midsagittal plane, suggesting that the anisotropy stems from intrinsic properties of the arm rather than extrinsic visual factors. One account of these results is a sensitivity model of motor planning, in which the movement path is skewed so that when the hand passes closest to the obstacle, the arm is in a configuration that is least sensitive to perturbations that might cause collision. To test this idea, we measured the mobility ellipse of the arm. The mobility minor axis represents the direction in which the hand is most inertially stable to a force perturbation. In agreement with the sensitivity model, the mobility minor axis was not significantly different from the preferred near point axis. The results suggest that the sensitivity of the arm to perturbations, as determined by its inertial stability, is taken into account in the planning process.

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Mesh:

Year:  1998        PMID: 9671681      PMCID: PMC6793054     

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  26 in total

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  32 in total

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8.  Extending Fitts' Law to three-dimensional obstacle-avoidance movements: support for the posture-based motion planning model.

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9.  It's Not (Only) the Mean that Matters: Variability, Noise and Exploration in Skill Learning.

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10.  Negative viscosity can enhance learning of inertial dynamics.

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Journal:  IEEE Int Conf Rehabil Robot       Date:  2009-06
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