Evidence map›Paper›PMID 38911462›Full record

ArticleNeurobiology of language (Cambridge, Mass.)2024

The Language Network Reliably "Tracks" Naturalistic Meaningful Nonverbal Stimuli.

Yotaro Sueoka, Alexander Paunov, Alyx Tanner, Idan A Blank, Anna Ivanova, Evelina Fedorenko

Abstract read
In one paragraph

Article in Neurobiology of language (Cambridge, Mass.), 2024. 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
–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

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
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  4. The cerebellar components of the human language network.bioRxiv : the preprint server for biology · 2025
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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

6 authors.

Yotaro SueokaDepartment of Brain and Cognitive Sciences, Massachusetts Instititute of Technology, Cambridge, MA, USA.ORCID https://orcid.org/0000-0001-6417-9052
Alexander PaunovDepartment of Brain and Cognitive Sciences, Massachusetts Instititute of Technology, Cambridge, MA, USA.ORCID https://orcid.org/0000-0003-4342-0534
Alyx TannerMcGovern Institute for Brain Research, Massachusetts Instititute of Technology, Cambridge, MA, USA.
Idan A BlankDepartment of Psychology and Linguistics, University of California Los Angeles, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0001-7057-8391
Anna IvanovaSchool of Psychology, Georgia Institute of Technology, Atlanta, GA, USA.ORCID https://orcid.org/0000-0002-1184-8299
Evelina FedorenkoDepartment of Brain and Cognitive Sciences, Massachusetts Instititute of Technology, Cambridge, MA, USA.ORCID https://orcid.org/0000-0003-3823-514X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The language network, comprised of brain regions in the left frontal and temporal cortex, responds robustly and reliably during language comprehension but shows little or no response during many nonlinguistic cognitive tasks (e.g., Fedorenko & Blank, 2020). However, one domain whose relationship with language remains debated is semantics-our conceptual knowledge of the world. Given that the language network responds strongly to meaningful linguistic stimuli, could some of this response be driven by the presence of rich conceptual representations encoded in linguistic inputs? In this study, we used a naturalistic cognition paradigm to test whether the cognitive and neural resources that are responsible for language processing are also recruited for processing semantically rich nonverbal stimuli. To do so, we measured BOLD responses to a set of ∼5-minute-long video and audio clips that consisted of meaningful event sequences but did not contain any linguistic content. We then used the intersubject correlation (ISC) approach (Hasson et al., 2004) to examine the extent to which the language network "tracks" these stimuli, that is, exhibits stimulus-related variation. Across all the regions of the language network, meaningful nonverbal stimuli elicited reliable ISCs. These ISCs were higher than the ISCs elicited by semantically impoverished nonverbal stimuli (e.g., a music clip), but substantially lower than the ISCs elicited by linguistic stimuli. Our results complement earlier findings from controlled experiments (e.g., Ivanova et al., 2021) in providing further evidence that the language network shows some sensitivity to semantic content in nonverbal stimuli.

Indexed as

fMRIintersubject correlationlanguage networknaturalistic stimulinonverbal semantics

Identifiers

PMID38911462
PMCPMC11192443

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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.