Initial motor skill performance predicts future performance, but not learning

Abstract People show vast variability in skill performance and learning. What determines a person's individual performance and learning ability? In this study we explored the possibility to predict participants’ future performance and learning, based on their behavior during initial skill acqui...

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Main Authors: Dekel Abeles, Jasmine Herszage, Moni Shahar, Nitzan Censor
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-38231-5
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author Dekel Abeles
Jasmine Herszage
Moni Shahar
Nitzan Censor
author_facet Dekel Abeles
Jasmine Herszage
Moni Shahar
Nitzan Censor
author_sort Dekel Abeles
collection DOAJ
description Abstract People show vast variability in skill performance and learning. What determines a person's individual performance and learning ability? In this study we explored the possibility to predict participants’ future performance and learning, based on their behavior during initial skill acquisition. We recruited a large online multi-session sample of participants performing a sequential tapping skill learning task. We used machine learning to predict future performance and learning from raw data acquired during initial skill acquisition, and from engineered features calculated from the raw data. Strong correlations were observed between initial and final performance, and individual learning was not predicted. While canonical experimental tasks developed and selected to detect average effects may constrain insights regarding individual variability, development of novel tasks may shed light on the underlying mechanism of individual skill learning, relevant for real-life scenarios.
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spelling doaj.art-214da10abc04448e90cffea12d3345c22023-07-16T11:17:42ZengNature PortfolioScientific Reports2045-23222023-07-011311810.1038/s41598-023-38231-5Initial motor skill performance predicts future performance, but not learningDekel Abeles0Jasmine Herszage1Moni Shahar2Nitzan Censor3School of Psychological Sciences, Tel Aviv UniversitySagol School of Neuroscience, Tel Aviv UniversityAI and Data Science Center of Tel Aviv University (TAD)School of Psychological Sciences, Tel Aviv UniversityAbstract People show vast variability in skill performance and learning. What determines a person's individual performance and learning ability? In this study we explored the possibility to predict participants’ future performance and learning, based on their behavior during initial skill acquisition. We recruited a large online multi-session sample of participants performing a sequential tapping skill learning task. We used machine learning to predict future performance and learning from raw data acquired during initial skill acquisition, and from engineered features calculated from the raw data. Strong correlations were observed between initial and final performance, and individual learning was not predicted. While canonical experimental tasks developed and selected to detect average effects may constrain insights regarding individual variability, development of novel tasks may shed light on the underlying mechanism of individual skill learning, relevant for real-life scenarios.https://doi.org/10.1038/s41598-023-38231-5
spellingShingle Dekel Abeles
Jasmine Herszage
Moni Shahar
Nitzan Censor
Initial motor skill performance predicts future performance, but not learning
Scientific Reports
title Initial motor skill performance predicts future performance, but not learning
title_full Initial motor skill performance predicts future performance, but not learning
title_fullStr Initial motor skill performance predicts future performance, but not learning
title_full_unstemmed Initial motor skill performance predicts future performance, but not learning
title_short Initial motor skill performance predicts future performance, but not learning
title_sort initial motor skill performance predicts future performance but not learning
url https://doi.org/10.1038/s41598-023-38231-5
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AT nitzancensor initialmotorskillperformancepredictsfutureperformancebutnotlearning