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Change in a probabilistic representation of meaning can account for N400 effects on articles

  • Increased N400 amplitudes on indefinite articles (a/an) incompatible with expected nouns have been initially taken as strong evidence for probabilistic pre-activation of phonological word forms, and recently been intensely debated because they have been difficult to replicate. Here, these effects are simulated using a neural network model of sentence comprehension that we previously used to simulate a broad range of empirical N400 effects. The model produces the effects when the cue validity of the articles concerning upcoming noun meaning in the learning environment is high, but fails to produce the effects when the cue validity of the articles is low due to adjectives presented between articles and nouns during training. These simulations provide insight into one of the factors potentially contributing to the small size of the effects in empirical studies and generate predictions for cross-linguistic differences in article induced N400 effects based on articles’ cue validity. The model accounts for article induced N400 effectsIncreased N400 amplitudes on indefinite articles (a/an) incompatible with expected nouns have been initially taken as strong evidence for probabilistic pre-activation of phonological word forms, and recently been intensely debated because they have been difficult to replicate. Here, these effects are simulated using a neural network model of sentence comprehension that we previously used to simulate a broad range of empirical N400 effects. The model produces the effects when the cue validity of the articles concerning upcoming noun meaning in the learning environment is high, but fails to produce the effects when the cue validity of the articles is low due to adjectives presented between articles and nouns during training. These simulations provide insight into one of the factors potentially contributing to the small size of the effects in empirical studies and generate predictions for cross-linguistic differences in article induced N400 effects based on articles’ cue validity. The model accounts for article induced N400 effects without assuming pre-activation of word forms, and instead simulates these effects as the stimulus-induced change in a probabilistic representation of meaning corresponding to an implicit semantic prediction error.show moreshow less

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Metadaten
Author details:Milena RabovskyORCiDGND
DOI:https://doi.org/10.1016/j.neuropsychologia.2020.107466
ISSN:0028-3932
ISSN:1873-3514
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/32315697
Title of parent work (English):Neuropsychologia : an international journal in behavioural and cognitive neuroscience
Subtitle (English):a neural network model
Publisher:Elsevier
Place of publishing:Oxford
Publication type:Article
Language:English
Date of first publication:2020/04/18
Publication year:2020
Release date:2023/01/23
Tag:ERPs; N400; cue validity; meaning; neural networks; prediction
Volume:143
Article number:107466
Number of pages:7
Funding institution:Emmy Noether grant from the German Research FoundationGerman Research; Foundation (DFG) [RA 2715/2-1]
Organizational units:Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Psychologie
DDC classification:1 Philosophie und Psychologie / 15 Psychologie / 150 Psychologie
Peer review:Referiert
Publishing method:Open Access / Hybrid Open-Access
License (German):License LogoCC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International
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