Evidence map›Paper›PMID 37229512›Full record

ArticleNeurobiology of language (Cambridge, Mass.)2023

Independency of Coding for Affective Similarities and for Word Co-occurrences in Temporal Perisylvian Neocortex.

Antonietta Gabriella Liuzzi, Karen Meersmans, Gerrit Storms, Simon De Deyne, Patrick Dupont, Rik Vandenberghe

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 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

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

6 authors.

Antonietta Gabriella LiuzziLaboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.ORCID https://orcid.org/0000-0001-8960-5601
Karen MeersmansLaboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.ORCID https://orcid.org/0000-0001-6018-0072
Gerrit StormsLaboratory of Experimental Psychology, KU Leuven, Leuven, Belgium.ORCID https://orcid.org/0000-0002-4100-8725
Simon De DeyneComputational Cognitive Science Lab, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0002-7899-6210
Patrick DupontLaboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.ORCID https://orcid.org/0000-0003-1980-2540
Rik VandenbergheLaboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.ORCID https://orcid.org/0000-0001-6237-2502

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Word valence is one of the principal dimensions in the organization of word meaning. Co-occurrence-based similarities calculated by predictive natural language processing models are relatively poor at representing affective content, but very powerful in their own way. Here, we determined how these two canonical but distinct ways of representing word meaning relate to each other in the human brain both functionally and neuroanatomically. We re-analysed an fMRI study of word valence. A co-occurrence-based model was used and the correlation with the similarity of brain activity patterns was compared to that of affective similarities. The correlation between affective and co-occurrence-based similarities was low (

Indexed as

fMRIrepresentational similarity analysissemanticsword embedding models

Identifiers

PMID37229512
PMCPMC10205158

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.