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  Potential and efficiency of statistical learning closely intertwined with individuals’ executive functions: A mathematical modeling study

Park, J., Yoon, H.-D., Yoo, T., Shin, M., & Jeon, H.-A. (2020). Potential and efficiency of statistical learning closely intertwined with individuals’ executive functions: A mathematical modeling study. Scientific Reports, 10(1): 18843. doi:10.1038/s41598-020-75157-8.

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Park, Jungtak1, Author
Yoon, Hee-Dong1, 2, Author
Yoo, Taehyun1, Author
Shin, Minho1, Author
Jeon, Hyeon-Ae1, 2, 3, Author              
Affiliations:
1Department of Brain and Cognitive Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Republic of Korea, ou_persistent22              
2Convergence Research Advanced Center for Olfaction, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Republic of Korea, ou_persistent22              
3Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

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 Abstract: Statistical learning (SL) is essential in enabling humans to extract probabilistic regularities from the world. The ability to accomplish ultimate learning performance with training (i.e., the potential of learning) has been known to be dissociated with performance improvement per amount of learning time (i.e., the efficiency of learning). Here, we quantified the potential and efficiency of SL separately through mathematical modeling and scrutinized how they were affected by various executive functions. Our results showed that a high potential of SL was associated with poor inhibition and good visuo-spatial working memory, whereas high efficiency of SL was closely related to good inhibition and good set-shifting. We unveiled the distinct characteristics of SL in relation to potential and efficiency and their interaction with executive functions.

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Language(s): eng - English
 Dates: 2020-05-212020-10-122020-11-02
 Publication Status: Published online
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1038/s41598-020-75157-8
PMID: 33139784
PMC: PMC7606401
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Title: Scientific Reports
  Abbreviation : Sci. Rep.
Source Genre: Journal
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Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 10 (1) Sequence Number: 18843 Start / End Page: - Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322