Literature DB >> 26134640

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

Samuel D McDougle1, Krista M Bond2, Jordan A Taylor3.   

Abstract

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning.
Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.

Entities:  

Keywords:  adaptation; cerebellum; explicit learning; motor control; motor learning; reaching

Mesh:

Year:  2015        PMID: 26134640      PMCID: PMC4571499          DOI: 10.1523/JNEUROSCI.5061-14.2015

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  34 in total

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3.  Reward feedback accelerates motor learning.

Authors:  Ali A Nikooyan; Alaa A Ahmed
Journal:  J Neurophysiol       Date:  2014-10-29       Impact factor: 2.714

4.  The influence of movement preparation time on the expression of visuomotor learning and savings.

Authors:  Adrian M Haith; David M Huberdeau; John W Krakauer
Journal:  J Neurosci       Date:  2015-04-01       Impact factor: 6.167

5.  Cerebellar contributions to reach adaptation and learning sensory consequences of action.

Authors:  Jun Izawa; Sarah E Criscimagna-Hemminger; Reza Shadmehr
Journal:  J Neurosci       Date:  2012-03-21       Impact factor: 6.167

6.  How each movement changes the next: an experimental and theoretical study of fast adaptive priors in reaching.

Authors:  Timothy Verstynen; Philip N Sabes
Journal:  J Neurosci       Date:  2011-07-06       Impact factor: 6.167

7.  Use-dependent and error-based learning of motor behaviors.

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Journal:  J Neurosci       Date:  2010-04-14       Impact factor: 6.167

Review 8.  Human category learning.

Authors:  F Gregory Ashby; W Todd Maddox
Journal:  Annu Rev Psychol       Date:  2005       Impact factor: 24.137

9.  The dissociable effects of punishment and reward on motor learning.

Authors:  Joseph M Galea; Elizabeth Mallia; John Rothwell; Jörn Diedrichsen
Journal:  Nat Neurosci       Date:  2015-02-23       Impact factor: 24.884

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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  111 in total

1.  The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

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3.  Rapid Automatic Motor Encoding of Competing Reach Options.

Authors:  Jason P Gallivan; Brandie M Stewart; Lee A Baugh; Daniel M Wolpert; J Randall Flanagan
Journal:  Cell Rep       Date:  2017-02-14       Impact factor: 9.423

4.  The 24-h savings of adaptation to novel movement dynamics initially reflects the recall of previous performance.

Authors:  Katrina P Nguyen; Weiwei Zhou; Erin McKenna; Katrina Colucci-Chang; Laurence C Jayet Bray; Eghbal A Hosseini; Laith Alhussein; Meena Rezazad; Wilsaan M Joiner
Journal:  J Neurophysiol       Date:  2019-07-10       Impact factor: 2.714

5.  Both fast and slow learning processes contribute to savings following sensorimotor adaptation.

Authors:  Susan K Coltman; Joshua G A Cashaback; Paul L Gribble
Journal:  J Neurophysiol       Date:  2019-03-06       Impact factor: 2.714

6.  Generalization via superposition: combined effects of mixed reference frame representations for explicit and implicit learning in a visuomotor adaptation task.

Authors:  Eugene Poh; Jordan A Taylor
Journal:  J Neurophysiol       Date:  2019-04-03       Impact factor: 2.714

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

Authors:  Susan K Coltman; Paul L Gribble
Journal:  J Neurophysiol       Date:  2020-07-08       Impact factor: 2.714

8.  Somatosensory Cortex Plays an Essential Role in Forelimb Motor Adaptation in Mice.

Authors:  Mackenzie Weygandt Mathis; Alexander Mathis; Naoshige Uchida
Journal:  Neuron       Date:  2017-03-22       Impact factor: 17.173

9.  Stretching the skin immediately enhances perceived stiffness and gradually enhances the predictive control of grip force.

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Journal:  Elife       Date:  2020-04-15       Impact factor: 8.140

10.  Seeing the Errors You Feel Enhances Locomotor Performance but Not Learning.

Authors:  Ryan T Roemmich; Andrew W Long; Amy J Bastian
Journal:  Curr Biol       Date:  2016-09-22       Impact factor: 10.834

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