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dc.contributor.authorBogaerts, Louisa
dc.contributor.authorFrost, Ram
dc.contributor.authorChristiansen, Morten H.
dc.date2022-08-11
dc.date.accessioned2020-09-18T06:45:15Z
dc.date.available2020-09-18T06:45:15Z
dc.date.issued2020
dc.identifier.citationLouisa Bogaerts, Ram Frost, Morten H. Christiansen, Integrating statistical learning into cognitive science, Journal of Memory and Language, Volume 115, 2020, 104167, ISSN 0749-596X, https://doi.org/10.1016/j.jml.2020.104167es_ES
dc.identifier.issn0749-596X
dc.identifier.urihttp://hdl.handle.net/10810/46141
dc.descriptionAvailable online 11 August 2020.es_ES
dc.description.abstractOver the last two decades statistical learning (SL) has evolved into a key explanatory mechanism underlying the incidental learning of regularities across different domains of cognition, such as language, visual and auditory perception, and memory. Yet SL has mainly been investigated as an independent research area, separated from the primary study of the relevant cognitive domains. The aim of this special issue is to foster a bilateral integration of SL research with cognitive science: not only should domain-relevant evidence about the complexity of real-world input become more tightly integrated into SL research, but non-SL studies should also carefully consider the nature and range of statistical regularities that may affect learning and processing in a given domain. Four papers on reading in this volume demonstrate that such integration can lead to a better understanding of reading, while also revealing the complexity and abundance of different statistical patterns present in printed text. Moving beyond disciplinary boundaries has the promise to broaden the focus of SL research beyond simple artificial patterns, to examine the rich and subtle intricacies of real-world cognition. A final paper on the neurobiological underpinnings of SL and the consolidation of learned statistical regularities further illustrates what might be gained from a better integration of SL and memory research. We conclude by discussing possible directions for taking an integrative approach to SL forward.es_ES
dc.description.sponsorshipThis paper was supported by the European Research Council (ERC) Advanced grant (project 692502-L2STAT) under the Horizon 2020 research and innovation program awarded to RF. MHC was supported in part by the Danish Council for Independent Research (FKK-grant DFF- 7013-00074).es_ES
dc.language.isoenges_ES
dc.publisherJournal of Memory and Languagees_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/ERC-692502-L2STATes_ES
dc.rightsinfo:eu-repo/semantics/embargoedAccesses_ES
dc.subjectStatistical learninges_ES
dc.subjectCognitiones_ES
dc.subjectReadinges_ES
dc.subjectMemoryes_ES
dc.subjectNeurosciencees_ES
dc.titleIntegrating statistical learning into cognitive sciencees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2020 Elsevier Inc. All rights reserved.es_ES
dc.relation.publisherversionwww.elsevier.com/locate/jmles_ES


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