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J Neurophysiol. 2019 Apr 1;121(4):1575-1583. doi: 10.1152/jn.00794.2018. Epub 2019 Mar 6.

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

Author information

1
Graduate Program in Neuroscience, Western University , London, Ontario , Canada.
2
Brain and Mind Institute, Western University , London, Ontario , Canada.
3
Department of Psychology, Western University , London, Ontario , Canada.
4
Faculty of Kinesiology, University of Calgary , Calgary, Alberta , Canada.
5
Hotchkiss Brain Institute, University of Calgary , Calgary, Alberta , Canada.
6
Department of Physiology and Pharmacology, Schulich School of Medicine & Dentistry, Western University , London, Ontario , Canada.
7
Haskins Laboratories , New Haven, Connecticut.

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.

KEYWORDS:

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

PMID:
30840553
PMCID:
PMC6485725
[Available on 2020-04-01]
DOI:
10.1152/jn.00794.2018
[Indexed for MEDLINE]

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