Academic Journal

Visuospatial working memory load reduces semantic prediction in the visual world.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Visuospatial working memory load reduces semantic prediction in the visual world.
Συγγραφείς: Allison, Christopher, Huettig, Falk, Fernandez, Leigh, Lachmann, Thomas
Πηγή: Language, Cognition & Neuroscience; Nov2025, Vol. 40 Issue 9, p1252-1261, 10p
Θεματικοί όροι: Communicative competence, Cognitive testing, Phonological awareness, Questionnaires, Descriptive statistics, English as a foreign language, Experimental design, Visual perception, Short-term memory, Semantics, Eye movements
Περίληψη: Prediction in language is often about objects in the language users' visual surroundings. Previous research suggests that linguistic working memory limitations in such task environments constrain language-mediated anticipatory eye movements. In this study, we investigated the effects of visuospatial cognitive load on language-mediated predictive eye gaze behaviour in a diverse group of L2 English speakers using the visual-world paradigm. Participants completed three levels of an increasingly difficult visuospatial working memory task before hearing either semantically constraining or unconstraining sentences, choosing an object best fitting the sentence, and completing the working memory task. Evidence of L2 anticipatory eye gaze was observed in all conditions. Importantly, a significant effect of difficulty, especially in the higher-load condition, suggests that increasing visuospatial working memory reduces anticipatory eye gaze. We close by discussing the importance of (visual) working memory in visual world studies and highlight the inherently integrative nature of predictive processing during language-vision interactions. [ABSTRACT FROM AUTHOR]
Copyright of Language, Cognition & Neuroscience is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
Περιγραφή
ISSN:23273798
DOI:10.1080/23273798.2025.2522272