Literature DB >> 1857964

Computations underlying the execution of movement: a biological perspective.

E Bizzi1, F A Mussa-Ivaldi, S Giszter.   

Abstract

To execute voluntary movements, the central nervous system must transform the neural representation of the direction, amplitude, and velocity of the limb, represented by the activity of cortical and subcortical neurons, into signals that activate the muscles that move the limb. This task is equivalent to solving an "ill-posed" computational problem because the number of degrees of freedom of the musculoskeletal apparatus is much larger than that specified in the plan of action. Some of the mechanisms and circuitry underlying the transformation of motor plans into motor commands are described. A central feature of this transformation is a coarse map of limb postures in the premotor areas of the spinal cord. Vectorial combination of motor outputs among different areas of the spinal map may produce a large repertoire of motor behaviors.

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Year:  1991        PMID: 1857964     DOI: 10.1126/science.1857964

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  124 in total

1.  Human arm movements described by a low-dimensional superposition of principal components.

Authors:  T D Sanger
Journal:  J Neurosci       Date:  2000-02-01       Impact factor: 6.167

2.  Rapid correction of aimed movements by summation of force-field primitives.

Authors:  W J Kargo; S F Giszter
Journal:  J Neurosci       Date:  2000-01-01       Impact factor: 6.167

3.  Motor learning through the combination of primitives.

Authors:  F A Mussa-Ivaldi; E Bizzi
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2000-12-29       Impact factor: 6.237

4.  Modelling the control of interceptive actions.

Authors:  P J Beek; J C Dessing; C E Peper; D Bullock
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2003-09-29       Impact factor: 6.237

5.  The construction of movement with behavior-specific and behavior-independent modules.

Authors:  Jian Jing; Elizabeth C Cropper; Itay Hurwitz; Klaudiusz R Weiss
Journal:  J Neurosci       Date:  2004-07-14       Impact factor: 6.167

6.  From basis functions to basis fields: vector field approximation from sparse data.

Authors:  F A Mussa-Ivaldi
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

7.  Vector field approximation: a computational paradigm for motor control and learning.

Authors:  F A Mussa-Ivaldi; S F Giszter
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

8.  The inflow of sensory information for the control of standing is graded and bidirectional.

Authors:  Behdad Tahayori; Nicholas L Port; David M Koceja
Journal:  Exp Brain Res       Date:  2012-04       Impact factor: 1.972

9.  Passive motion paradigm: an alternative to optimal control.

Authors:  Vishwanathan Mohan; Pietro Morasso
Journal:  Front Neurorobot       Date:  2011-12-27       Impact factor: 2.650

10.  Task-level feedback can explain temporal recruitment of spatially fixed muscle synergies throughout postural perturbations.

Authors:  Seyed A Safavynia; Lena H Ting
Journal:  J Neurophysiol       Date:  2011-09-28       Impact factor: 2.714

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