Literature DB >> 25098963

Reductions in muscle coactivation and metabolic cost during visuomotor adaptation.

Helen J Huang1, Alaa A Ahmed2.   

Abstract

We often have to adapt our movements as we interact with a variety of objects in various conditions on a daily basis. Evidence suggests that motor adaptation relies on a process that minimizes error and effort; however, much of this evidence involved adapting to novel dynamics with physical perturbations to counteract. To examine the generality of the process of minimizing error and effort during motor adaptation, we used a visuomotor adaptation task that did not involve dynamic perturbations. We investigated the time courses of muscle activity, coactivation, and metabolic cost as subjects reached to a target with a visuomotor rotation. We wanted to determine whether subjects would modulate muscle activity, coactivation, and metabolic cost during a visuomotor adaptation task. Interestingly, subjects increased muscle coactivation early during visuomotor adaptation when there were large cursor-trajectory errors but no physical perturbations to reject. As adaptation progressed, muscle activity and coactivation decreased. Metabolic cost followed a similar time course. When the perturbation was removed, typical after-effects were observed: trajectory error increased and then was reduced quickly. This was accompanied by increases in muscle activity, coactivation, and metabolic cost, along with subsequent rapid reductions. These results demonstrate that subjects modulate muscle activity, coactivation, and metabolic cost similarly across different forms of motor adaptation. Overall, our findings suggest that minimization of error and effort may be a general process underlying various forms of motor adaptation.
Copyright © 2014 the American Physiological Society.

Entities:  

Keywords:  effort minimization; internal model; metabolic cost; motor adaptation; motor learning; visuomotor

Mesh:

Year:  2014        PMID: 25098963     DOI: 10.1152/jn.00014.2014

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


  8 in total

1.  The optimal neural strategy for a stable motor task requires a compromise between level of muscle cocontraction and synaptic gain of afferent feedback.

Authors:  Jakob L Dideriksen; Francesco Negro; Dario Farina
Journal:  J Neurophysiol       Date:  2015-07-22       Impact factor: 2.714

2.  Feedforward and Feedback Control Share an Internal Model of the Arm's Dynamics.

Authors:  Rodrigo S Maeda; Tyler Cluff; Paul L Gribble; J Andrew Pruszynski
Journal:  J Neurosci       Date:  2018-10-24       Impact factor: 6.167

3.  Using asymmetry to your advantage: learning to acquire and accept external assistance during prolonged split-belt walking.

Authors:  Natalia Sánchez; Surabhi N Simha; J Maxwell Donelan; James M Finley
Journal:  J Neurophysiol       Date:  2020-12-09       Impact factor: 2.714

4.  Context-dependent memory decay is evidence of effort minimization in motor learning: a computational study.

Authors:  Ken Takiyama
Journal:  Front Comput Neurosci       Date:  2015-02-04       Impact factor: 2.380

5.  Evidence of Energetic Optimization during Adaptation Differs for Metabolic, Mechanical, and Perceptual Estimates of Energetic Cost.

Authors:  Natalia Sánchez; Sungwoo Park; James M Finley
Journal:  Sci Rep       Date:  2017-08-09       Impact factor: 4.379

6.  Rapid visuomotor feedback gains are tuned to the task dynamics.

Authors:  Sae Franklin; Daniel M Wolpert; David W Franklin
Journal:  J Neurophysiol       Date:  2017-08-23       Impact factor: 2.714

7.  Corrective Muscle Activity Reveals Subject-Specific Sensorimotor Recalibration.

Authors:  Pablo A Iturralde; Gelsy Torres-Oviedo
Journal:  eNeuro       Date:  2019-05-01

8.  Asymmetric valuation of gains and losses in effort-based decision making.

Authors:  Megan K O'Brien; Alaa A Ahmed
Journal:  PLoS One       Date:  2019-10-15       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.