Statistical Learning Subserves a Higher Purpose: Novelty Detection in an Information Foraging System.
Statistical learning (SL) is typically assumed to be a core mechanism by which organisms learn covarying structures and recurrent patterns in the environment, with the main purpose of facilitating processing of expected events. Within this theoretical framework, the environment is viewed as relative...
| Published in: | Psychological Review Vol. 133; no. 1; pp. 237 - 253 |
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| Main Authors: | , , , , , |
| Format: | Article |
| Published: |
American Psychological Association
Jan2026
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=190910348&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 190910348 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0033295X PYV jtl: Psychological Review issn: 0033295X maglogo: N pubinfo: dt: Jan2026 vid: 133 iid: 1 pid: 34 pub: American Psychological Association artinfo: ui: 190910348 10.1037/rev0000547 ppf: 237 ppct: 16 formats: tig: atl: Statistical Learning Subserves a Higher Purpose: Novelty Detection in an Information Foraging System. aug: au: Frost, Ram Bogaerts, Louisa Samuel, Arthur G. Magnuson, James S. Holt, Lori L. Christiansen, Morten H. affil: Department of Psychology, The Hebrew University of Jerusalem BCBL: Basque Center for Cognition Brain and Language, San Sebastian, Spain Department of Experimental Psychology, Ghent University Department of Psychology, Stony Brook University Ikerbasque: Basque Foundation for Science, Ikerbasque, Spain Department of Psychology, University of Connecticut Department of Psychology, The University of Texas at Austin School of Communication and Culture, Aarhus University Department of Psychology, Cornell University su: Statistical learning Cognitive neuroscience Pattern perception Cognitive psychology Outlier detection Cognitive structures sug: subj: Statistical learning Cognitive neuroscience Pattern perception Cognitive psychology Outlier detection Cognitive structures keyword: information foraging language novelty detection recurrent regularities statistical learning information foraging language novelty detection recurrent regularities statistical learning ab: Statistical learning (SL) is typically assumed to be a core mechanism by which organisms learn covarying structures and recurrent patterns in the environment, with the main purpose of facilitating processing of expected events. Within this theoretical framework, the environment is viewed as relatively stable, and SL "captures" the regularities therein through implicit unsupervised learning by mere exposure. Focusing primarily on language—the domain in which SL theory has been most influential—we review evidence that the environment is far from fixed: It is dynamic, in continual flux, and learners are far from passive absorbers of regularities; they interact with their environments, thereby selecting and even altering the patterns they learn from. We therefore argue for an alternative cognitive architecture, where SL serves as a subcomponent of an information foraging (IF) system. IF aims to detect and assimilate novel recurrent patterns in the input that deviate from randomness, for which SL supplies a baseline. The broad implications of this viewpoint and their relevance to recent debates in cognitive neuroscience are discussed. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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