Evidence map›Paper›PMID 37229506›Full record

ArticleNeurobiology of language (Cambridge, Mass.)2023

Understanding the Effects of Constraint and Predictability in ERP.

Kate Stone, Bruno Nicenboim, Shravan Vasishth, Frank Rösler

Abstract read
In one paragraph

Article in Neurobiology of language (Cambridge, Mass.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

8 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.

Kate StoneDepartment of Psychology, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0002-2180-9736
Bruno NicenboimDepartment of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, Netherlands.ORCID https://orcid.org/0000-0002-5176-3943
Shravan VasishthDepartment of Linguistics, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0003-2027-1994
Frank RöslerDepartment of Biological Psychology and Neuropsychology, University of Hamburg, Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

anterior PNPconstraintentropyN400posterior P600predictabilityprobabilistic processing

Identifiers

PMID37229506
PMCPMC10205153

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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.