Literature DB >> 32101490

Generalizing movement patterns following shoulder fixation.

Rodrigo S Maeda1,2,3, Julia M Zdybal1,2,4, Paul L Gribble1,3,4, J Andrew Pruszynski1,2,3,4.   

Abstract

Generalizing newly learned movement patterns beyond the training context is challenging for most motor learning situations. Here we tested whether learning of a new physical property of the arm during self-initiated reaching generalizes to new arm configurations. Human participants performed a single-joint elbow reaching task and/or countered mechanical perturbations that created pure elbow motion with the shoulder joint free to rotate or locked by the manipulandum. With the shoulder free, we found activation of shoulder extensor muscles for pure elbow extension trials, appropriate for countering torques that arise at the shoulder due to forearm rotation. After locking the shoulder joint, we found a partial reduction in shoulder muscle activity, appropriate because locking the shoulder joint cancels the torques that arise at the shoulder due to forearm rotation. In our first three experiments, we tested whether and to what extent this partial reduction in shoulder muscle activity generalizes when reaching in different situations: 1) different initial shoulder orientation, 2) different initial elbow orientation, and 3) different reach distance/speed. We found generalization for the different shoulder orientation and reach distance/speed as measured by a reliable reduction in shoulder activity in these situations but no generalization for the different elbow orientation. In our fourth experiment, we found that generalization is also transferred to feedback control by applying mechanical perturbations and observing reflex responses in a distinct shoulder orientation. These results indicate that partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of arm dynamics.NEW & NOTEWORTHY Here we show that partially learning to reduce shoulder muscle activity following shoulder fixation generalizes to other movement conditions, but it does not generalize globally. These findings suggest that the partial learning of new intersegmental dynamics is not sufficient for modifying a general internal model of the arm's dynamics.

Entities:  

Keywords:  feedback control; internal model; intersegmental limb dynamics; motor learning; stretch reflex; voluntary movements

Mesh:

Year:  2020        PMID: 32101490      PMCID: PMC7099470          DOI: 10.1152/jn.00696.2019

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


  60 in total

1.  Compensation for interaction torques during single- and multijoint limb movement.

Authors:  P L Gribble; D J Ostry
Journal:  J Neurophysiol       Date:  1999-11       Impact factor: 2.714

2.  Generalization of dynamics learning across changes in movement amplitude.

Authors:  Andrew A G Mattar; David J Ostry
Journal:  J Neurophysiol       Date:  2010-05-12       Impact factor: 2.714

3.  Linear hypergeneralization of learned dynamics across movement speeds reveals anisotropic, gain-encoding primitives for motor adaptation.

Authors:  Wilsaan M Joiner; Obafunso Ajayi; Gary C Sing; Maurice A Smith
Journal:  J Neurophysiol       Date:  2010-09-29       Impact factor: 2.714

4.  Generalization as a behavioral window to the neural mechanisms of learning internal models.

Authors:  Reza Shadmehr
Journal:  Hum Mov Sci       Date:  2004-11       Impact factor: 2.161

5.  Single limb performance following contralateral bimanual limb training.

Authors:  Jamie Kaye Burgess; Rachel Bareither; James L Patton
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2007-09       Impact factor: 3.802

6.  Long-latency reflexes of the human arm reflect an internal model of limb dynamics.

Authors:  Isaac L Kurtzer; J Andrew Pruszynski; Stephen H Scott
Journal:  Curr Biol       Date:  2008-03-25       Impact factor: 10.834

7.  Modifiability of generalization in dynamics learning.

Authors:  Andrew A G Mattar; David J Ostry
Journal:  J Neurophysiol       Date:  2007-10-10       Impact factor: 2.714

8.  Learning not to generalize: modular adaptation of visuomotor gain.

Authors:  Toni S Pearson; John W Krakauer; Pietro Mazzoni
Journal:  J Neurophysiol       Date:  2010-03-31       Impact factor: 2.714

9.  Perturbation-evoked responses in primary motor cortex are modulated by behavioral context.

Authors:  Mohsen Omrani; J Andrew Pruszynski; Chantelle D Murnaghan; Stephen H Scott
Journal:  J Neurophysiol       Date:  2014-09-10       Impact factor: 2.714

10.  Amplitude of responses to perturbation in primate sensorimotor cortex as a function of task.

Authors:  J R Wolpaw
Journal:  J Neurophysiol       Date:  1980-12       Impact factor: 2.714

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