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Id http://data.loterre.fr/ark:/67375/P66-H2017HMG-3
http://data.loterre.fr/ark:/67375/P66-H2017HMG-3
Preferred Name

statistical learning
Definitions
Nonconscious learning of recurring sequences or statistical regularities in the environment without reward or reinforcement.
Synonyms
implicit probabilistic learning
sequence learning
Type http://www.w3.org/2004/02/skos/core#Concept

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definition

Nonconscious learning of recurring sequences or statistical regularities in the environment without reward or reinforcement.
altLabel
implicit probabilistic learning
sequence learning
prefLabel
statistical learning
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bibliographicCitation
Isbilen, E. S., & Christiansen, M. H. (2022). Statistical learning of language : A meta-analysis into 25 years of research. Cognitive Science, 46(9), e13198. https://doi.org/10.1111/cogs.13198
Conway, C. M. (2020). How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning. Neuroscience & Biobehavioral Reviews, 112, 279–299. https://doi.org/10.1016/j.neubiorev.2020.01.032
Saffran, J. R., & Kirkham, N. Z. (2018). Infant statistical learning. Annual Review of Psychology, 69(1), 181–203. https://doi.org/10.1146/annurev-psych-122216-011805
Park, J., Janacsek, K., Nemeth, D., & Jeon, H.-A. (2022). Reduced functional connectivity supports statistical learning of temporally distributed regularities. NeuroImage, 260, 119459. https://doi.org/10.1016/j.neuroimage.2022.119459
Fiser, J., Berkes, P., Orbán, G., & Lengyel, M. (2010). Statistically optimal perception and learning: From behavior to neural representations. Trends in Cognitive Sciences, 14(3), 119–130. https://doi.org/10.1016/j.tics.2010.01.003
Sherman, B. E., & Turk-Browne, N. B. (2020). Statistical prediction of the future impairs episodic encoding of the present. Proceedings of the National Academy of Sciences, 117(37), 22760–22770. https://doi.org/10.1073/pnas.2013291117
Christiansen, M. H. (2019). Implicit statistical learning: A tale of two literatures. Topics in Cognitive Science, 11(3), 468–481. https://doi.org/10.1111/tops.12332
Frost, R., Armstrong, B. C., & Christiansen, M. H. (2019). Statistical learning research : A critical review and possible new directions. Psychological Bulletin, 145(12), 1128–1153. https://doi.org/10.1037/bul0000210
Szegedi-Hallgató, E., Janacsek, K., & Nemeth, D. (2019). Different levels of statistical learning—Hidden potentials of sequence learning tasks. PLOS ONE, 14(9), e0221966. https://doi.org/10.1371/journal.pone.0221966
Aslin, R. N., & Newport, E. L. (2012). Statistical learning: From acquiring specific items to forming general rules. Current Directions in Psychological Science, 21(3), 170–176. https://doi.org/10.1177/0963721412436806
Aslin, R. N. (2017). Statistical learning: A powerful mechanism that operates by mere exposure. WIREs Cognitive Science, 8(1–2), e1373. https://doi.org/10.1002/wcs.1373
Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science (New York, N.Y.), 274(5294), 1926–1928. https://doi.org/10.1126/science.274.5294.1926
Török, B., Nagy, D. G., Kiss, M., Janacsek, K., Németh, D., & Orbán, G. (2022). Tracking the contribution of inductive bias to individualised internal models. PLOS Computational Biology, 18(6), e1010182. https://doi.org/10.1371/journal.pcbi.1010182
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reviewedBy
Dezső Németh
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created
December 4, 2017
modified
May 15, 2025
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