Literature DB >> 30840553

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

Susan K Coltman1,2,3, Joshua G A Cashaback4,5, Paul L Gribble2,3,6,7.   

Abstract

Recent work suggests that the rate of learning in sensorimotor adaptation is likely not fixed, but rather can change based on previous experience. One example is savings, a commonly observed phenomenon whereby the relearning of a motor skill is faster than the initial learning. Sensorimotor adaptation is thought to be driven by sensory prediction errors, which are the result of a mismatch between predicted and actual sensory consequences. It has been proposed that during motor adaptation the generation of sensory prediction errors engages two processes (fast and slow) that differ in learning and retention rates. We tested the idea that a history of errors would influence both the fast and slow processes during savings. Participants were asked to perform the same force field adaptation task twice in succession. We found that adaptation to the force field a second time led to increases in estimated learning rates for both fast and slow processes. While it has been proposed that savings is explained by an increase in learning rate for the fast process, here we observed that the slow process also contributes to savings. Our work suggests that fast and slow adaptation processes are both responsive to a history of error and both contribute to savings. NEW & NOTEWORTHY We studied the underlying mechanisms of savings during motor adaptation. Using a two-state model to represent fast and slow processes that contribute to motor adaptation, we found that a history of error modulates performance in both processes. While previous research has attributed savings to only changes in the fast process, we demonstrated that an increase in both processes is needed to account for the measured behavioral data.

Entities:  

Keywords:  human; motor learning; prediction error; savings; two-state model

Mesh:

Year:  2019        PMID: 30840553      PMCID: PMC6485725          DOI: 10.1152/jn.00794.2018

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


  30 in total

1.  Learning to move amid uncertainty.

Authors:  R A Scheidt; J B Dingwell; F A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2001-08       Impact factor: 2.714

2.  Quantifying generalization from trial-by-trial behavior of adaptive systems that learn with basis functions: theory and experiments in human motor control.

Authors:  Opher Donchin; Joseph T Francis; Reza Shadmehr
Journal:  J Neurosci       Date:  2003-10-08       Impact factor: 6.167

3.  Memory of learning facilitates saccadic adaptation in the monkey.

Authors:  Yoshiko Kojima; Yoshiki Iwamoto; Kaoru Yoshida
Journal:  J Neurosci       Date:  2004-08-25       Impact factor: 6.167

4.  Modeling sensorimotor learning with linear dynamical systems.

Authors:  Sen Cheng; Philip N Sabes
Journal:  Neural Comput       Date:  2006-04       Impact factor: 2.026

5.  Long-term retention explained by a model of short-term learning in the adaptive control of reaching.

Authors:  Wilsaan M Joiner; Maurice A Smith
Journal:  J Neurophysiol       Date:  2008-09-10       Impact factor: 2.714

6.  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

7.  Savings for visuomotor adaptation require prior history of error, not prior repetition of successful actions.

Authors:  Li-Ann Leow; Aymar de Rugy; Welber Marinovic; Stephan Riek; Timothy J Carroll
Journal:  J Neurophysiol       Date:  2016-07-13       Impact factor: 2.714

8.  The Neural Feedback Response to Error As a Teaching Signal for the Motor Learning System.

Authors:  Scott T Albert; Reza Shadmehr
Journal:  J Neurosci       Date:  2016-04-27       Impact factor: 6.167

9.  Adaptation to visuomotor transformations: consolidation, interference, and forgetting.

Authors:  John W Krakauer; Claude Ghez; M Felice Ghilardi
Journal:  J Neurosci       Date:  2005-01-12       Impact factor: 6.167

10.  Savings upon Re-Aiming in Visuomotor Adaptation.

Authors:  J Ryan Morehead; Salman E Qasim; Matthew J Crossley; Richard Ivry
Journal:  J Neurosci       Date:  2015-10-21       Impact factor: 6.167

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  13 in total

1.  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

2.  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

3.  Random Practice Enhances Retention and Spatial Transfer in Force Field Adaptation.

Authors:  Michael Herzog; Anne Focke; Philipp Maurus; Benjamin Thürer; Thorsten Stein
Journal:  Front Hum Neurosci       Date:  2022-05-04       Impact factor: 3.473

4.  Competition between parallel sensorimotor learning systems.

Authors:  Scott T Albert; Jihoon Jang; Shanaathanan Modchalingam; Bernard Marius 't Hart; Denise Henriques; Gonzalo Lerner; Valeria Della-Maggiore; Adrian M Haith; John W Krakauer; Reza Shadmehr
Journal:  Elife       Date:  2022-02-28       Impact factor: 8.713

5.  The cost of correcting for error during sensorimotor adaptation.

Authors:  Ehsan Sedaghat-Nejad; Reza Shadmehr
Journal:  Proc Natl Acad Sci U S A       Date:  2021-10-05       Impact factor: 12.779

6.  An implicit memory of errors limits human sensorimotor adaptation.

Authors:  Scott T Albert; Jihoon Jang; Hannah R Sheahan; Lonneke Teunissen; Koenraad Vandevoorde; David J Herzfeld; Reza Shadmehr
Journal:  Nat Hum Behav       Date:  2021-02-04

7.  Timescales of motor memory formation in dual-adaptation.

Authors:  Marion Forano; David W Franklin
Journal:  PLoS Comput Biol       Date:  2020-10-19       Impact factor: 4.475

8.  Reexposure to a sensorimotor perturbation produces opposite effects on explicit and implicit learning processes.

Authors:  Guy Avraham; J Ryan Morehead; Hyosub E Kim; Richard B Ivry
Journal:  PLoS Biol       Date:  2021-03-05       Impact factor: 8.029

9.  Younger and Late Middle-Aged Adults Exhibit Different Patterns of Cognitive-Motor Interference During Locomotor Adaptation, With No Disruption of Savings.

Authors:  Cristina Rossi; Ryan T Roemmich; Nicolas Schweighofer; Amy J Bastian; Kristan A Leech
Journal:  Front Aging Neurosci       Date:  2021-11-26       Impact factor: 5.750

10.  A Very Fast Time Scale of Human Motor Adaptation: Within Movement Adjustments of Internal Representations during Reaching.

Authors:  Frédéric Crevecoeur; Jean-Louis Thonnard; Philippe Lefèvre
Journal:  eNeuro       Date:  2020-02-05
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