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Initial exposure to random input decreases subsequent statistical learning: Behavioral and neural evidence.

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Τίτλος: Initial exposure to random input decreases subsequent statistical learning: Behavioral and neural evidence.
Συγγραφείς: Iorio C; Université Bourgogne Europe, CNRS, LEAD UMR5022, 21000 Dijon, France. Electronic address: claudiaiorio11@gmail.com., Edalati M; GRAMFC (Inserm U1105), Centre Universitaire de Recherche en Santé, Université de Picardie Jules Verne, Amiens, France., Moghimi S; GRAMFC (Inserm U1105), Centre Universitaire de Recherche en Santé, Université de Picardie Jules Verne, Amiens, France., Tillmann B; Université Bourgogne Europe, CNRS, LEAD UMR5022, 21000 Dijon, France.
Πηγή: Brain and cognition [Brain Cogn] 2026 Oct; Vol. 198, pp. 106460. Date of Electronic Publication: 2026 Aug 07.
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Academic Press Country of Publication: United States NLM ID: 8218014 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1090-2147 (Electronic) Linking ISSN: 02782626 NLM ISO Abbreviation: Brain Cogn Subsets: MEDLINE
Imprint Name(s): Original Publication: New York : Academic Press, [c1982-
Ιατρικοί όροι (MeSH): Learning*/physiology , Speech Perception*/physiology , Brain*/physiology , Probability Learning*, Humans ; Female ; Adult ; Male ; Young Adult ; Electroencephalography ; Language
Περίληψη: Statistical learning, the ability to detect regularities between events, can be understood as an emergent property of predictive and memory-based mechanisms that continuously shape how sensory input is encoded and segmented based on prior experience. However, the extent to which statistical learning is influenced by prior context remains relatively underexplored. This work investigated whether initial exposure to a random syllable stream alters the neural and behavioral mechanisms underlying subsequent artificial language learning. In Experiment 1 (random-first group, N = 41; structure-first group; N = 40), adult participants completed a two-alternative forced-choice task after exposure to a structured stream containing trisyllabic "words," either preceded by a random stream or not. Similarly, Experiment 2 (random-first group, N = 20; structure-first group; N = 20) captured listeners' neural responses to syllable and word frequencies during exposure to the artificial language, providing a real-time index of segmentation processes. Results showed better word segmentation for the structure-first group than for the random-first group in both experiments. These findings that early exposure to randomness can interfere with the neural encoding of regularities suggest that statistical learning is not purely stimulus-driven, but dynamically shaped by learning context.
(Copyright © 2026 The Authors. Published by Elsevier Inc. All rights reserved.)
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributed Indexing: Keywords: EEG; Frequency-tagging; Order; Statistical learning
Entry Date(s): Date Created: 20260807 Date Completed: 20260908 Latest Revision: 20260908
Update Code: 20260909
DOI: 10.1016/j.bandc.2026.106460
PMID: 42567074
Βάση Δεδομένων: MEDLINE
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  Data: Statistical learning, the ability to detect regularities between events, can be understood as an emergent property of predictive and memory-based mechanisms that continuously shape how sensory input is encoded and segmented based on prior experience. However, the extent to which statistical learning is influenced by prior context remains relatively underexplored. This work investigated whether initial exposure to a random syllable stream alters the neural and behavioral mechanisms underlying subsequent artificial language learning. In Experiment 1 (random-first group, N = 41; structure-first group; N = 40), adult participants completed a two-alternative forced-choice task after exposure to a structured stream containing trisyllabic "words," either preceded by a random stream or not. Similarly, Experiment 2 (random-first group, N = 20; structure-first group; N = 20) captured listeners' neural responses to syllable and word frequencies during exposure to the artificial language, providing a real-time index of segmentation processes. Results showed better word segmentation for the structure-first group than for the random-first group in both experiments. These findings that early exposure to randomness can interfere with the neural encoding of regularities suggest that statistical learning is not purely stimulus-driven, but dynamically shaped by learning context.<br /> (Copyright © 2026 The Authors. Published by Elsevier Inc. All rights reserved.)
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