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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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Boenstrup_Iturrate_2020.pdf (Verlagsversion), 2MB
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 Urheber:
Bönstrup, Marlene1, Autor
Iturrate, Iñaki1, Autor
Hebart, Martin N.2, Autor                 
Censor, Nitzan3, Autor
Cohen, Leonardo G.1, Autor
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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Schlagwörter: Consolidation; Human behaviour
 Zusammenfassung: 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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Sprache(n): eng - English
 Datum: 2019-10-012020-04-172020-06-04
 Publikationsstatus: Online veröffentlicht
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 Identifikatoren: DOI: 10.1038/s41539-020-0066-9
Anderer: eCollection 2020
PMID: 32550003
PMC: PMC7272649
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Projektname : -
Grant ID : LPDS 2016-01
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Förderorganisation : German National Academy of Sciences Leopoldina
Projektname : Intramural Research Program
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Förderorganisation : National Institute of Neurological Disorders and Stroke (NINDS)

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Titel: npj Science of Learning
Genre der Quelle: Zeitschrift
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Affiliations:
Ort, Verlag, Ausgabe: London, United Kingdom : Nature Publishing Group
Seiten: - Band / Heft: 5 Artikelnummer: 7 Start- / Endseite: - Identifikator: ISSN: 2056-7936
CoNE: https://pure.mpg.de/cone/journals/resource/2056-7936