Evidence map›Paper›PMID 40767276›Full record

ArticlePsychophysiology2025

Individual Differences in Statistical Learning and Semantic Adaptation: An N400 Study.

Márton Munding, Bálint Forgács, Krisztina Sára Lukics, Ágnes Lukács

Abstract read
In one paragraph

Article in Psychophysiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Márton MundingDoctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.ORCID 0009-0003-8239-4647
Bálint ForgácsDepartment of Cognitive Psychology, Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.
Krisztina Sára LukicsDepartment of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary.
Ágnes LukácsDepartment of Cognitive Science, Faculty of Natural Sciences, Budapest University of Technology and Economics, Budapest, Hungary.

Funding

Deutsche Forschungsgemeinschaft CI247/7-1Magyar Tudományos Akadémia Momentum 96233Magyar Tudományos Akadémia TKP2021-NVA-02
6 · The paper itself

Abstract

Recent empirical results have linked the N400 ERP with predictive language comprehension processes based on statistical learning (SL). However, links between SL abilities and N400 on the level of individual differences have so far been underexplored. The present study tested SL performance in 29 participants using speech segmentation and artificial grammar learning tasks, followed by EEG recordings of their N400 responses to sentences varying in cloze probability (high, intermediate, low). Mixed-effects models revealed that better online SL performance (SL-ON) was associated with larger N400 amplitudes across conditions. Additionally, working memory showed a significant main effect and interacted with SL-ON in modulating N400 amplitude, while cloze probability also had a robust, independent effect on it. These results demonstrate that individual differences in SL abilities contribute to N400 response variability, supporting the view that the semantic operations reflected by the N400 may involve some form of statistical learning as well. Our findings also raise the possibility that SL and CP tap into distinct levels of predictive mechanisms in language comprehension.

Indexed as

BrainComprehensionEvoked PotentialsIndividualityLearningSemanticsSpeech PerceptionAdolescentAdultElectroencephalographyFemaleHumansMaleMemory, Short-TermYoung Adult

Identifiers

PMID40767276
PMCPMC12326519

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.