Transitional probabilities outweigh frequency of occurrence in statistical learning of simultaneously presented visual shapes.
Statistical learning is a mechanism for detecting associations among co-occurring elements in many domains and species. A key controversy is whether it leads to memory for discrete chunks composed of these associated elements, or merely to pairwise associations among elements. Critical evidence for...
| Publicado en: | Memory & Cognition Vol. 53; no. 5; pp. 1497 - 1510 |
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| Formato: | Artículo |
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Springer Nature
Jul2025
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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=ssf&AN=186988127&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 186988127 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0090502X MEG jtl: Memory & Cognition issn: 0090502X maglogo: N pubinfo: dt: Jul2025 vid: 53 iid: 5 pid: 237 pub: Springer Nature artinfo: ui: 186988127 10.3758/s13421-024-01665-x ppf: 1497 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P size: 627KB tig: atl: Transitional probabilities outweigh frequency of occurrence in statistical learning of simultaneously presented visual shapes. aug: au: Endress, Ansgar D. affil: https://ror.org/04cw6st05 Department of Psychology, City St George's, University of London, Northampton Square, EC1V 0HB, London, UK su: United Kingdom Recognition (Psychology) Task performance Learning Students Memory Language acquisition Cognition Statistical models Data analysis Probability theory Pilot projects Neuroplasticity Psychology of movement Statistics Learning strategies Visual perception sug: subj: Recognition (Psychology) Task performance Learning Students Memory Language acquisition Cognition United Kingdom Statistical models Data analysis Probability theory Pilot projects Neuroplasticity Psychology of movement Statistics Learning strategies Visual perception keyword: Declarative memory Hebbian learning Psychology and Cognitive Sciences Psychology Statistical learning Declarative memory Hebbian learning Psychology and Cognitive Sciences Psychology Statistical learning ab: Statistical learning is a mechanism for detecting associations among co-occurring elements in many domains and species. A key controversy is whether it leads to memory for discrete chunks composed of these associated elements, or merely to pairwise associations among elements. Critical evidence for the mere-association view comes from the "phantom-word" phenomenon, where learners recognize statistically coherent but unattested items better than actually presented items with weaker internal associations, suggesting that they prioritize pairwise associations over memories for discrete units. However, this phenomenon has only been demonstrated for sequentially presented stimuli, but not for simultaneously presented visual shapes, where learners might prioritize discrete units over pairwise associations. Here, I ask whether the phantom-word phenomenon can be observed with simultaneously presented visual shapes. Learners were familiarized with scenes combining two triplets of visual shapes (hereafter "words"). They were then tested on their recognition of these words vs. part-words (attested items with weaker internal associations), of phantom-words (unattested items with strong internal associations) vs. part-words, and of words vs. phantom-words. Learners preferred both words and phantom-words over part-words and showed no preference for words over phantom-words. This suggests that, as for sequentially input, statistical learning in simultaneously presented shapes leads primarily to pairwise associations rather than to memories for discrete chunks. However, as, in some analyses, the preference for words over part-words was slightly higher than for phantom-words over part-words, the results do not rule out that, for simultaneous presented items, learners might have some limited sensitivity to frequency of occurrence. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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