Literature DB >> 1486132

Basic functions of variability of simple pre-planned movements.

S R Gutman1, G L Gottlieb.   

Abstract

A model of a pre-planned single joint movements performed without feedback is considered. Modifications of this movement result from transformation of a trajectory pattern f(t) in space and time. The control system adjusts the movement to concrete external conditions specifying values of the transform parameters before the movement performance. The pre-planned movement is considered to be simple one, if the transform can be approximated by an affine transform of the movement space and time. In this case, the trajectory of the movement is x(t) = Af (t/tau + s) + p, were A and l/tau are space and time scales, s and p are translations. The variability of movements is described by time profiles of variances and covariances of the trajectory x(t), velocity v(t), and acceleration a(t). It is assumed that the variability is defined only by parameters variations. From this assumption follows the main finding of this work: the variability time profiles can be expanded on a special system of basic functions corresponding to established movement parameters. Particularly, basic functions of variance time profiles, reflecting spatial and temporal scaling, are x2(t) and t2v2(t) for trajectory, v2(t) and (v(t)+t.a(t))2 for velocity, and a2(t) and (2a(t)+t.j(t))2, where j(t) = d3x(t)/dt3, for acceleration. The variability of a model of a reaching movement was studied analytically. The model predicts certain peculiarities of the form of time profiles (e.g., the variance time profile of velocity is bi-modal, the one of acceleration is tri-modal, etc.). Experimental measurements confirmed predictions. Their consistence allows them to be considered invariant properties of reaching movement. A conclusion can be made, that reaching movement belongs to the type of simple pre-planned movements. For a more complex movement, time profiles of variability are also measured and explained by the model of movements of this type. Thus, a movement can be attributed to the type of simple pre-planned ones by testing its variability.

Mesh:

Year:  1992        PMID: 1486132     DOI: 10.1007/bf00203138

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  21 in total

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Journal:  Psychol Rev       Date:  1988-01       Impact factor: 8.934

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Journal:  J Neurosci       Date:  1985-09       Impact factor: 6.167

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Journal:  Psychol Rev       Date:  1982-09       Impact factor: 8.934

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Journal:  Brain       Date:  1982-06       Impact factor: 13.501

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  8 in total

1.  Movement sway: changes in postural sway during voluntary shifts of the center of pressure.

Authors:  Mark L Latash; Sandra S Ferreira; Silvana A Wieczorek; Marcos Duarte
Journal:  Exp Brain Res       Date:  2003-04-12       Impact factor: 1.972

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Authors:  J-F Yang; J P Scholz
Journal:  Exp Brain Res       Date:  2005-01-19       Impact factor: 1.972

3.  Motor variability within a multi-effector system: experimental and analytical studies of multi-finger production of quick force pulses.

Authors:  Simon R Goodman; Jae Kun Shim; Vladimir M Zatsiorsky; Mark L Latash
Journal:  Exp Brain Res       Date:  2005-02-03       Impact factor: 1.972

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Authors:  Wei Zhang; Vladimir M Zatsiorsky; Mark L Latash
Journal:  Exp Brain Res       Date:  2006-05-24       Impact factor: 1.972

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Authors:  Julien Gori; Olivier Rioul
Journal:  Biol Cybern       Date:  2020-12-08       Impact factor: 2.086

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Authors:  S R Gutman; M L Latash; G L Almeida; G L Gottlieb
Journal:  Biol Cybern       Date:  1993       Impact factor: 2.086

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Authors:  Mark L Latash; Frederic Danion; John F Scholz; Vladimir M Zatsiorsky; Gregor Schöner
Journal:  Hum Mov Sci       Date:  2003-04       Impact factor: 2.161

8.  Analysis of kinematic invariances of multijoint reaching movement.

Authors:  S R Goodman; G L Gottlieb
Journal:  Biol Cybern       Date:  1995-09       Impact factor: 2.086

  8 in total

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