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  Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data

Bönstrup, M., Iturrate, I., Hebart, M. N., Censor, N., & Cohen, L. G. (2020). Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data. npj Science of Learning, 5: 7. doi:10.1038/s41539-020-0066-9.

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 Creators:
Bönstrup, Marlene1, Author
Iturrate, Iñaki1, Author
Hebart, Martin N.2, Author                 
Censor, Nitzan3, Author
Cohen, Leonardo G.1, Author
Affiliations:
1Human Cortical Physiology and Stroke Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA, ou_persistent22              
2Laboratory of Brain and Cognition, Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA, ou_persistent22              
3Sagol School of Neuroscience, Tel-Aviv University, Israel, ou_persistent22              

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Free keywords: Consolidation; Human behaviour
 Abstract: Performance improvements during early human motor skill learning are suggested to be driven by short periods of rest during practice, at the scale of seconds. To reveal the unknown mechanisms behind these "micro-offline" gains, we leveraged the sampling power offered by online crowdsourcing (cumulative N over all experiments = 951). First, we replicated the original in-lab findings, demonstrating generalizability to subjects learning the task in their daily living environment (N = 389). Second, we show that offline improvements during rest are equivalent when significantly shortening practice period duration, thus confirming that they are not a result of recovery from performance fatigue (N = 118). Third, retroactive interference immediately after each practice period reduced the learning rate relative to interference after passage of time (N = 373), indicating stabilization of the motor memory at a microscale of several seconds. Finally, we show that random termination of practice periods did not impact offline gains, ruling out a contribution of predictive motor slowing (N = 71). Altogether, these results demonstrate that micro-offline gains indicate rapid, within-seconds consolidation accounting for early skill learning.

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Language(s): eng - English
 Dates: 2019-10-012020-04-172020-06-04
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1038/s41539-020-0066-9
Other: eCollection 2020
PMID: 32550003
PMC: PMC7272649
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Project name : -
Grant ID : LPDS 2016-01
Funding program : -
Funding organization : German National Academy of Sciences Leopoldina
Project name : Intramural Research Program
Grant ID : -
Funding program : -
Funding organization : National Institute of Neurological Disorders and Stroke (NINDS)

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Title: npj Science of Learning
Source Genre: Journal
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Publ. Info: London, United Kingdom : Nature Publishing Group
Pages: - Volume / Issue: 5 Sequence Number: 7 Start / End Page: - Identifier: ISSN: 2056-7936
CoNE: https://pure.mpg.de/cone/journals/resource/2056-7936