Evidence map›Paper›PMID 37716311›Full record

ArticleCognition2023

Multiple predictions during language comprehension: Friends, foes, or indifferent companions?

Trevor Brothers, Emily Morgan, Anthony Yacovone, Gina Kuperberg

Open access · greenAbstract read
In one paragraph

Article in Cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.2field-weighted citation impact, top 5% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Dynamics of learning new words from context.Journal of experimental psychology. General · 2025
    Article
  12. Article
  13. Article
  14. Review
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 at 3 institutions in 1 country.

Trevor BrothersDepartment of Psychology, North Carolina A&T, United States of America; Department of Psychology, Tufts University, United States of America.
Emily MorganDepartment of Linguistics, University of California, Davis, United States of America.
Anthony YacovoneDepartment of Psychology, Tufts University, United States of America; Department of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, United States of America.
Gina KuperbergDepartment of Psychology, Tufts University, United States of America; Department of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, United States of America. Electronic address: GKuperberg@mgh.harvard.edu.
Tufts University · USAthinoula A. Martinos Center for Biomedical Imaging · USUniversity of California, Davis · US

Funding

The neural basis of language comprehension: Insights from spatiotemporal imagingR01HD082527 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI GINA R KUPERBERG · 2015 to 2026
$5.8M
NICHD NIH HHS R01 HD082527
6 · The paper itself

Abstract

To comprehend language, we continually use prior context to pre-activate expected upcoming information, resulting in facilitated processing of incoming words that confirm these predictions. But what are the consequences of disconfirming prior predictions? To address this question, most previous studies have examined unpredictable words appearing in contexts that constrain strongly for a single continuation. However, during natural language processing, it is far more common to encounter contexts that constrain for multiple potential continuations, each with some probability. Here, we ask whether and how pre-activating both higher and lower probability alternatives influences the processing of the lower probability incoming word. One possibility is that, similar to language production, there is continuous pressure to select the higher-probability pre-activated alternative through competitive inhibition. During comprehension, this would result in relative costs in processing the lower probability target. A second possibility is that if the two pre-activated alternatives share semantic features, they mutually enhance each other's pre-activation. This would result in greater facilitation in processing the lower probability target. To distinguish between these accounts, we recorded ERPs as participants read three-sentence scenarios that constrained either for a single word or for two potential continuations - a higher probability expected candidate and a lower probability second-best candidate. We found no evidence that competitive pre-activation between the expected and second-best candidates resulted in costs in processing the second-best target, either during lexico-semantic processing (indexed by the N400) or at later stages of processing (indexed by a later frontal positivity). Instead, we found only benefits of pre-activating multiple alternatives, with evidence of enhanced graded facilitation on lower-probability targets that were semantically related to a higher-probability pre-activated alternative. These findings are consistent with a previous eye-tracking study by Luke and Christianson (2016, Cogn Psychol) using corpus-based materials. They have significant theoretical implications for models of predictive language processing, indicating that routine graded prediction in language comprehension does not operate through the same competitive mechanisms that are engaged in language production. Instead, our results align more closely with hierarchical probabilistic accounts of language comprehension, such as predictive coding.

Indexed as

ElectroencephalographyEvoked PotentialsComprehensionFemaleFriendsHumansLanguageMaleSemanticsCompetitionExplaining awayLate frontal positivityN400PredictionPredictive coding

Identifiers

PMID37716311
PMCPMC10783882
OpenAlexW4386790810

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.