Incremental implicit learning of bundles of statistical patterns.
Forming an accurate representation of a task environment often takes place incrementally as the information relevant to learning the representation only unfolds over time. This incremental nature of learning poses an important problem: it is usually unclear whether a sequence of stimuli consists of...
| Publicado en: | Cognition Vol. 157; pp. 156 - 174 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Dec2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=119156047&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 119156047 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00100277 3H9 jtl: Cognition issn: 00100277 maglogo: N pubinfo: dt: Dec2016 vid: 157 pid: 1004 pub: Elsevier B.V. artinfo: ui: 119156047 119156047 NLM27639552 119156047 10.1016/j.cognition.2016.09.002 NLM27639552 119156047 ppf: 156 ppct: 18 formats: tig: atl: Incremental implicit learning of bundles of statistical patterns. aug: au: Qian, Ting Jaeger, T. Florian Aslin, Richard N. affil: Department of Biomedical and Health Informatics, The Children’s Hospital of Philadelphia, United States sug: subj: Memory Learning Visual Perception Cues Models, Psychological Probability Reaction Time Funding Source Human ab: Forming an accurate representation of a task environment often takes place incrementally as the information relevant to learning the representation only unfolds over time. This incremental nature of learning poses an important problem: it is usually unclear whether a sequence of stimuli consists of only a single pattern, or multiple patterns that are spliced together. In the former case, the learner can directly use each observed stimulus to continuously revise its representation of the task environment. In the latter case, however, the learner must first parse the sequence of stimuli into different bundles, so as to not conflate the multiple patterns. We created a video-game statistical learning paradigm and investigated (1) whether learners without prior knowledge of the existence of multiple "stimulus bundles" - subsequences of stimuli that define locally coherent statistical patterns - could detect their presence in the input and (2) whether learners are capable of constructing a rich representation that encodes the various statistical patterns associated with bundles. By comparing human learning behavior to the predictions of three computational models, we find evidence that learners can handle both tasks successfully. In addition, we discuss the underlying reasons for why the learning of stimulus bundles occurs even when such behavior may seem irrational. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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