Literature DB >> 12522180

Coordinated turn-and-reach movements. II. Planning in an external frame of reference.

Pascale Pigeon1, Simone B Bortolami, Paul DiZio, James R Lackner.   

Abstract

The preceding study demonstrated that normal subjects compensate for the additional interaction torques generated when a reaching movement is made during voluntary trunk rotation. The present paper assesses the influence of trunk rotation on finger trajectories and on interjoint coordination and determines whether simultaneous turn-and-reach movements are most simply described relative to a trunk-based or an external reference frame. Subjects reached to targets requiring different extents of arm joint and trunk rotation at a natural pace and quickly in normal lighting and in total darkness. We first examined whether the larger interaction torques generated during rapid turn-and-reach movements perturb finger trajectories and interjoint coordination and whether visual feedback plays a role in compensating for these torques. These issues were addressed using generalized Procrustes analysis (GPA), which attempts to overlap a group of configurations (e.g., joint trajectories) through translations and rotations in multi-dimensional space. We first used GPA to identify the mean intrinsic patterns of finger and joint trajectories (i.e., their average shape irrespective of location and orientation variability in the external and joint workspaces) from turn-and-reach movements performed in each experimental condition and then calculated their curvatures. We then quantified the discrepancy between each finger or joint trajectory and the intrinsic pattern both after GPA was applied individually to trajectories from a pair of experimental conditions and after GPA was applied to the same trajectories pooled together. For several subjects, joint trajectories but not finger trajectories were more curved in fast than slow movements. The curvature of both joint and finger trajectories of turn-and-reach movements was relatively unaffected by the vision conditions. Pooling across speed conditions significantly increased the discrepancy between joint but not finger trajectories for most subjects, indicating that subjects used different patterns of interjoint coordination in slow and fast movements while nevertheless preserving the shape of their finger trajectory. Higher movement speeds did not disrupt the arm joint rotations despite the larger interaction torques generated. Rather, subjects used the redundant degrees of freedom of the arm/trunk system to achieve similar finger trajectories with differing joint configurations. We examined finger movement patterns and velocity profiles to determine the frame of reference in which turn-and-reach movements could be most simply described. Finger trajectories of turn-and-reach movements had much larger curvatures and their velocity profiles were less smooth and less bell-like in trunk-based coordinates than in external coordinates. Taken together, these results support the conclusion that turn-and-reach movements are controlled in an external frame of reference.

Entities:  

Keywords:  NASA Discipline Neuroscience; Non-NASA Center

Mesh:

Year:  2003        PMID: 12522180     DOI: 10.1152/jn.00160.2001

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  10 in total

1.  Movement planning with probabilistic target information.

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2.  Dynamics model for analyzing reaching movements during active and passive torso rotation.

Authors:  Simone B Bortolami; Pascale Pigeon; Paul Dizio; James R Lackner
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6.  Rapid adaptation of torso pointing movements to perturbations of the base of support.

Authors:  Todd E Hudson; James R Lackner; Paul DiZio
Journal:  Exp Brain Res       Date:  2005-06-08       Impact factor: 1.972

7.  Kinetic analysis of arm reaching movements during voluntary and passive rotation of the torso.

Authors:  Simone B Bortolami; Pascale Pigeon; Paul Dizio; James R Lackner
Journal:  Exp Brain Res       Date:  2008-03-11       Impact factor: 1.972

8.  Compensation for changing motor uncertainty.

Authors:  Todd E Hudson; Hadley Tassinari; Michael S Landy
Journal:  PLoS Comput Biol       Date:  2010-11-04       Impact factor: 4.475

9.  Effects of underestimating the kinematics of trunk rotation on simultaneous reaching movements: predictions of a biomechanical model.

Authors:  Martin Simoneau; Étienne Guillaud; Jean Blouin
Journal:  J Neuroeng Rehabil       Date:  2013-06-12       Impact factor: 4.262

10.  Adaptive use of interaction torque during arm reaching movement from the optimal control viewpoint.

Authors:  Van Hoan Vu; Brice Isableu; Bastien Berret
Journal:  Sci Rep       Date:  2016-12-12       Impact factor: 4.379

  10 in total

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