Change in a probabilistic representation of meaning can account for N400 effects on articles: a neural network model
- 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.…
Verfasserangaben: | Milena RabovskyORCiDGND |
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URN: | urn:nbn:de:kobv:517-opus4-526988 |
DOI: | https://doi.org/10.25932/publishup-52698 |
ISSN: | 1866-8364 |
Titel des übergeordneten Werks (Deutsch): | Postprints der Universität Potsdam : Humanwissenschaftliche Reihe |
Schriftenreihe (Bandnummer): | Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe (731) |
Publikationstyp: | Postprint |
Sprache: | Englisch |
Datum der Erstveröffentlichung: | 17.03.2019 |
Erscheinungsjahr: | 2020 |
Veröffentlichende Institution: | Universität Potsdam |
Datum der Freischaltung: | 17.11.2021 |
Freies Schlagwort / Tag: | ERPs; N400; cue validity; meaning; neural networks; prediction |
Aufsatznummer: | 107466 |
Seitenanzahl: | 9 |
Quelle: | Neuropsychologia, Volume 143, 2020, 107466, ISSN 0028-3932, https://doi.org/10.1016/j.neuropsychologia.2020.107466 |
Organisationseinheiten: | Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Psychologie |
DDC-Klassifikation: | 1 Philosophie und Psychologie / 15 Psychologie / 150 Psychologie |
Peer Review: | Referiert |
Publikationsweg: | Open Access / Green Open-Access |
Lizenz (Deutsch): | CC-BY-NC-ND - Namensnennung, nicht kommerziell, keine Bearbeitungen 4.0 International |
Externe Anmerkung: | Bibliographieeintrag der Originalveröffentlichung/Quelle |