Evidence map›Paper›PMID 38814982›Full record

ArticlePLoS biology2024

Negation mitigates rather than inverts the neural representations of adjectives.

Arianna Zuanazzi, Pablo Ripollés, Wy Ming Lin, Laura Gwilliams, Jean-Rémi King, David Poeppel

Abstract read
In one paragraph

Article in PLoS biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Arianna ZuanazziDepartment of Psychology, New York University, New York, New York, United States of America.ORCID 0000-0002-8330-4450
Pablo RipollésDepartment of Psychology, New York University, New York, New York, United States of America.
Wy Ming LinHector Research Institute for Education Sciences and Psychology, University of Tübingen, Tübingen, Germany.
Laura GwilliamsDepartment of Psychology, Stanford University, Stanford, California, United States of America.
Jean-Rémi KingDepartment of Psychology, New York University, New York, New York, United States of America.
David PoeppelDepartment of Psychology, New York University, New York, New York, United States of America.

Funding

NIH HHS 2043717
6 · The paper itself

Abstract

Combinatoric linguistic operations underpin human language processes, but how meaning is composed and refined in the mind of the reader is not well understood. We address this puzzle by exploiting the ubiquitous function of negation. We track the online effects of negation ("not") and intensifiers ("really") on the representation of scalar adjectives (e.g., "good") in parametrically designed behavioral and neurophysiological (MEG) experiments. The behavioral data show that participants first interpret negated adjectives as affirmative and later modify their interpretation towards, but never exactly as, the opposite meaning. Decoding analyses of neural activity further reveal significant above chance decoding accuracy for negated adjectives within 600 ms from adjective onset, suggesting that negation does not invert the representation of adjectives (i.e., "not bad" represented as "good"); furthermore, decoding accuracy for negated adjectives is found to be significantly lower than that for affirmative adjectives. Overall, these results suggest that negation mitigates rather than inverts the neural representations of adjectives. This putative suppression mechanism of negation is supported by increased synchronization of beta-band neural activity in sensorimotor areas. The analysis of negation provides a steppingstone to understand how the human brain represents changes of meaning over time.

Indexed as

LanguageAdultBrainFemaleHumansLinguisticsMagnetoencephalographyMaleSemanticsYoung Adult

Identifiers

PMID38814982
PMCPMC11139306

What OpenQuestion holds

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Registered trials

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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.