Evidence map›Paper›PMID 37841669›Full record

ArticleJournal of cognition2023

Brain Signatures of Embodied Semantics and Language: A Consensus Paper.

Laura Bechtold, Samuel H Cosper, Anastasia Malyshevskaya, Maria Montefinese, Piermatteo Morucci, Valentina Niccolai, Claudia Repetto, Ana Zappa, Yury Shtyrov

Abstract read
In one paragraph

Article in Journal of cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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

9 authors.

Laura BechtoldInstitute for Experimental Psychology, Department for Biological Psychology, Heinrich-Heine University Düsseldorf, Germany.ORCID https://orcid.org/0000-0001-6677-965X
Samuel H CosperInstitute of Cognitive Science, University of Osnabrück, Germany.ORCID https://orcid.org/0000-0002-4099-4340
Anastasia MalyshevskayaCentre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Russian Federation.ORCID https://orcid.org/0000-0001-8082-711X
Maria MontefineseIRCCS San Camillo Hospital, Venice, Italy.ORCID https://orcid.org/0000-0002-7685-1034
Piermatteo MorucciBasque Center on Cognition Brain and Language, Donosti, Spain.ORCID https://orcid.org/0000-0002-4972-0864
Valentina NiccolaiInstitute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany.ORCID https://orcid.org/0000-0002-1159-943X
Claudia RepettoDepartment of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.ORCID https://orcid.org/0000-0001-8365-7697
Ana ZappaLaboratoire parole et langage, Aix-Marseille Université, Aix-en-Provence, France.ORCID https://orcid.org/0000-0003-4427-0988
Yury ShtyrovCentre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Russian Federation.ORCID https://orcid.org/0000-0001-7203-4902

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

According to embodied theories (including embodied, embedded, extended, enacted, situated, and grounded approaches to cognition), language representation is intrinsically linked to our interactions with the world around us, which is reflected in specific brain signatures during language processing and learning. Moving on from the original rivalry of embodied vs. amodal theories, this consensus paper addresses a series of carefully selected questions that aim at determining

Indexed as

EEGembodied cognitionlanguage learningprimingsemantic processingvirtual reality

Identifiers

PMID37841669
PMCPMC10573703

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.