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Procedural learning: A developmental study of motor sequence learning and probabilistic classification learning in school-aged children.

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Title: Procedural learning: A developmental study of motor sequence learning and probabilistic classification learning in school-aged children.
Authors: Mayor-Dubois, Claire (AUTHOR), Zesiger, Pascal (AUTHOR), Van der Linden, Martial (AUTHOR), Roulet-Perez, Eliane (AUTHOR)
Source: Child Neuropsychology. Aug2016, Vol. 22 Issue 6, p718-734. 17p. 1 Chart, 3 Graphs.
Subjects: Movement sequences, Learning ability, Mathematical models, Task performance, Statistical correlation
Abstract: In this study, we investigated motor and cognitive procedural learning in typically developing children aged 8–12 years with a serial reaction time (SRT) task and a probabilistic classification learning (PCL) task. The aims were to replicate and extend the results of previous SRT studies, to investigate PCL in school-aged children, to explore the contribution of declarative knowledge to SRT and PCL performance, to explore the strategies used by children in the PCL task via a mathematical model, and to see whether performances obtained in motor and cognitive tasks correlated. The results showed similar learning effects in the three age groups in the SRT and in the first half of the PCL tasks. Participants did not develop explicit knowledge in the SRT task whereas declarative knowledge of the cue–outcome associations correlated with the performances in the second half of the PCL task, suggesting a participation of explicit knowledge after some time of exposure in PCL. An increasing proportion of the optimal strategy use with increasing age was observed in the PCL task. Finally, no correlation appeared between cognitive and motor performance. In conclusion, we extended the hypothesis of age invariance from motor to cognitive procedural learning, which had not been done previously. The ability to adopt more efficient learning strategies with age may rely on the maturation of the fronto-striatal loops. The lack of correlation between performance in the SRT task and the first part of the PCL task suggests dissociable developmental trajectories within the procedural memory system. [ABSTRACT FROM PUBLISHER]
Copyright of Child Neuropsychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Label: Title
  Group: Ti
  Data: Procedural learning: A developmental study of motor sequence learning and probabilistic classification learning in school-aged children.
– Name: Author
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  Data: <searchLink fieldCode="AR" term="%22Mayor-Dubois%2C+Claire%22">Mayor-Dubois, Claire</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zesiger%2C+Pascal%22">Zesiger, Pascal</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Van+der+Linden%2C+Martial%22">Van der Linden, Martial</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Roulet-Perez%2C+Eliane%22">Roulet-Perez, Eliane</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Child+Neuropsychology%22">Child Neuropsychology</searchLink>. Aug2016, Vol. 22 Issue 6, p718-734. 17p. 1 Chart, 3 Graphs.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Movement+sequences%22">Movement sequences</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+ability%22">Learning ability</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Task+performance%22">Task performance</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+correlation%22">Statistical correlation</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In this study, we investigated motor and cognitive procedural learning in typically developing children aged 8–12 years with a serial reaction time (SRT) task and a probabilistic classification learning (PCL) task. The aims were to replicate and extend the results of previous SRT studies, to investigate PCL in school-aged children, to explore the contribution of declarative knowledge to SRT and PCL performance, to explore the strategies used by children in the PCL task via a mathematical model, and to see whether performances obtained in motor and cognitive tasks correlated. The results showed similar learning effects in the three age groups in the SRT and in the first half of the PCL tasks. Participants did not develop explicit knowledge in the SRT task whereas declarative knowledge of the cue–outcome associations correlated with the performances in the second half of the PCL task, suggesting a participation of explicit knowledge after some time of exposure in PCL. An increasing proportion of the optimal strategy use with increasing age was observed in the PCL task. Finally, no correlation appeared between cognitive and motor performance. In conclusion, we extended the hypothesis of age invariance from motor to cognitive procedural learning, which had not been done previously. The ability to adopt more efficient learning strategies with age may rely on the maturation of the fronto-striatal loops. The lack of correlation between performance in the SRT task and the first part of the PCL task suggests dissociable developmental trajectories within the procedural memory system. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Child Neuropsychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=118174089
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        Value: 10.1080/09297049.2015.1058347
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        Text: English
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      – SubjectFull: Mathematical models
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      – SubjectFull: Task performance
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              Text: Aug2016
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