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Understanding the Effects of Constraint and Predictability in ERP

Intuitively, strongly constraining contexts should lead to stronger probabilistic representations of sentences in memory. Encountering unexpected words could therefore be expected to trigger costlier shifts in these representations than expected words. However, psycholinguistic measures commonly use...

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Autores principales: Stone, Kate, Nicenboim, Bruno, Vasishth, Shravan, Rösler, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205153/
https://www.ncbi.nlm.nih.gov/pubmed/37229506
http://dx.doi.org/10.1162/nol_a_00094
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author Stone, Kate
Nicenboim, Bruno
Vasishth, Shravan
Rösler, Frank
author_facet Stone, Kate
Nicenboim, Bruno
Vasishth, Shravan
Rösler, Frank
author_sort Stone, Kate
collection PubMed
description Intuitively, strongly constraining contexts should lead to stronger probabilistic representations of sentences in memory. Encountering unexpected words could therefore be expected to trigger costlier shifts in these representations than expected words. However, psycholinguistic measures commonly used to study probabilistic processing, such as the N400 event-related potential (ERP) component, are sensitive to word predictability but not to contextual constraint. Some research suggests that constraint-related processing cost may be measurable via an ERP positivity following the N400, known as the anterior post-N400 positivity (PNP). The PNP is argued to reflect update of a sentence representation and to be distinct from the posterior P600, which reflects conflict detection and reanalysis. However, constraint-related PNP findings are inconsistent. We sought to conceptually replicate Federmeier et al. (2007) and Kuperberg et al. (2020), who observed that the PNP, but not the N400 or the P600, was affected by constraint at unexpected but plausible words. Using a pre-registered design and statistical approach maximising power, we demonstrated a dissociated effect of predictability and constraint: strong evidence for predictability but not constraint in the N400 window, and strong evidence for constraint but not predictability in the later window. However, the constraint effect was consistent with a P600 and not a PNP, suggesting increased conflict between a strong representation and unexpected input rather than greater update of the representation. We conclude that either a simple strong/weak constraint design is not always sufficient to elicit the PNP, or that previous PNP constraint findings could be an artifact of smaller sample size.
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spelling pubmed-102051532023-05-24 Understanding the Effects of Constraint and Predictability in ERP Stone, Kate Nicenboim, Bruno Vasishth, Shravan Rösler, Frank Neurobiol Lang (Camb) Research Article Intuitively, strongly constraining contexts should lead to stronger probabilistic representations of sentences in memory. Encountering unexpected words could therefore be expected to trigger costlier shifts in these representations than expected words. However, psycholinguistic measures commonly used to study probabilistic processing, such as the N400 event-related potential (ERP) component, are sensitive to word predictability but not to contextual constraint. Some research suggests that constraint-related processing cost may be measurable via an ERP positivity following the N400, known as the anterior post-N400 positivity (PNP). The PNP is argued to reflect update of a sentence representation and to be distinct from the posterior P600, which reflects conflict detection and reanalysis. However, constraint-related PNP findings are inconsistent. We sought to conceptually replicate Federmeier et al. (2007) and Kuperberg et al. (2020), who observed that the PNP, but not the N400 or the P600, was affected by constraint at unexpected but plausible words. Using a pre-registered design and statistical approach maximising power, we demonstrated a dissociated effect of predictability and constraint: strong evidence for predictability but not constraint in the N400 window, and strong evidence for constraint but not predictability in the later window. However, the constraint effect was consistent with a P600 and not a PNP, suggesting increased conflict between a strong representation and unexpected input rather than greater update of the representation. We conclude that either a simple strong/weak constraint design is not always sufficient to elicit the PNP, or that previous PNP constraint findings could be an artifact of smaller sample size. MIT Press 2023-04-11 /pmc/articles/PMC10205153/ /pubmed/37229506 http://dx.doi.org/10.1162/nol_a_00094 Text en © 2023 Massachusetts Institute of Technology https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Research Article
Stone, Kate
Nicenboim, Bruno
Vasishth, Shravan
Rösler, Frank
Understanding the Effects of Constraint and Predictability in ERP
title Understanding the Effects of Constraint and Predictability in ERP
title_full Understanding the Effects of Constraint and Predictability in ERP
title_fullStr Understanding the Effects of Constraint and Predictability in ERP
title_full_unstemmed Understanding the Effects of Constraint and Predictability in ERP
title_short Understanding the Effects of Constraint and Predictability in ERP
title_sort understanding the effects of constraint and predictability in erp
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10205153/
https://www.ncbi.nlm.nih.gov/pubmed/37229506
http://dx.doi.org/10.1162/nol_a_00094
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