Literature DB >> 32639925

Time course of changes in the long-latency feedback response parallels the fast process of short-term motor adaptation.

Susan K Coltman1,2,3, Paul L Gribble2,3,4,5.   

Abstract

Adapting to novel dynamics involves modifying both feedforward and feedback control. We investigated whether the motor system alters feedback responses during adaptation to a novel force field in a manner similar to adjustments in feedforward control. We simultaneously tracked the time course of both feedforward and feedback systems via independent probes during a force field adaptation task. Participants (n = 35) grasped the handle of a robotic manipulandum and performed reaches to a visual target while the hand and arm were occluded. We introduced an abrupt counterclockwise velocity-dependent force field during a block of reaching trials. We measured movement kinematics and shoulder and elbow muscle activity with surface EMG electrodes. We tracked the feedback stretch response throughout the task. Using force channel trials, we measured overall learning, which was later decomposed into a fast and slow process. We found that the long-latency feedback response (LLFR) was upregulated in the early stages of learning and was correlated with the fast component of feedforward adaptation. The change in feedback response was specific to the long-latency epoch (50-100 ms after muscle stretch) and was observed only in the triceps muscle, which was the muscle required to counter the force field during adaptation. The similarity in time course for the LLFR and the estimated time course of the fast process suggests both are supported by common neural circuits. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.NEW & NOTEWORTHY We investigated whether changes in the feedback stretch response were related to the proposed fast and slow processes of motor adaptation. We found that the long-latency component of the feedback stretch response was upregulated in the early stages of learning and the time course was correlated with the fast process. While some propose that the fast process reflects an explicit strategy, we argue instead that it may be a proxy for the feedback controller.

Entities:  

Keywords:  feedback controller; human; long-latency feedback response; short-term motor adaptation, two-state model

Mesh:

Year:  2020        PMID: 32639925      PMCID: PMC7500369          DOI: 10.1152/jn.00286.2020

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


  41 in total

1.  Forward modeling allows feedback control for fast reaching movements.

Authors: 
Journal:  Trends Cogn Sci       Date:  2000-11-01       Impact factor: 20.229

2.  Forward Models for Physiological Motor Control.

Authors:  D M. Wolpert; R C. Miall
Journal:  Neural Netw       Date:  1996-11

Review 3.  Optimal feedback control and the long-latency stretch response.

Authors:  J Andrew Pruszynski; Stephen H Scott
Journal:  Exp Brain Res       Date:  2012-02-28       Impact factor: 1.972

Review 4.  A computational neuroanatomy for motor control.

Authors:  Reza Shadmehr; John W Krakauer
Journal:  Exp Brain Res       Date:  2008-02-05       Impact factor: 1.972

5.  Rapid feedback responses correlate with reach adaptation and properties of novel upper limb loads.

Authors:  Tyler Cluff; Stephen H Scott
Journal:  J Neurosci       Date:  2013-10-02       Impact factor: 6.167

6.  Internal models in the cerebellum.

Authors:  D M Wolpert; R C Miall; M Kawato
Journal:  Trends Cogn Sci       Date:  1998-09-01       Impact factor: 20.229

7.  Corticospinal correlates of fast and slow adaptive processes in motor learning.

Authors:  Adjmal M E Sarwary; Miles Wischnewski; Dennis J L G Schutter; Luc P J Selen; W Pieter Medendorp
Journal:  J Neurophysiol       Date:  2018-08-22       Impact factor: 2.714

Review 8.  A perspective on multisensory integration and rapid perturbation responses.

Authors:  Tyler Cluff; Frédéric Crevecoeur; Stephen H Scott
Journal:  Vision Res       Date:  2014-07-09       Impact factor: 1.886

9.  Electromyographic correlates of learning an internal model of reaching movements.

Authors:  K A Thoroughman; R Shadmehr
Journal:  J Neurosci       Date:  1999-10-01       Impact factor: 6.167

10.  Interacting adaptive processes with different timescales underlie short-term motor learning.

Authors:  Maurice A Smith; Ali Ghazizadeh; Reza Shadmehr
Journal:  PLoS Biol       Date:  2006-05-23       Impact factor: 8.029

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  3 in total

Review 1.  Adaptive Feedback Control in Human Reaching Adaptation to Force Fields.

Authors:  James Mathew; Frédéric Crevecoeur
Journal:  Front Hum Neurosci       Date:  2021-12-27       Impact factor: 3.169

2.  Individual Differences in Sensorimotor Adaptation Are Conserved Over Time and Across Force-Field Tasks.

Authors:  Robert T Moore; Tyler Cluff
Journal:  Front Hum Neurosci       Date:  2021-11-30       Impact factor: 3.169

3.  Movement Kinematics and Interjoint Coordination Are Influenced by Target Location and Arm in 6-Year-Old Children.

Authors:  Leia B Bagesteiro; Rogerio B Balthazar; Charmayne M L Hughes
Journal:  Front Hum Neurosci       Date:  2020-09-16       Impact factor: 3.169

  3 in total

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