Evidence map›Paper›PMID 42212229›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

A 3.5-minute-long reading-based fMRI localizer for the language network.

Greta Tuckute, Elizabeth Jiachen Lee, Aalok Sathe, Evelina Fedorenko

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

4 authors.

Greta TuckuteDepartment of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States.ORCID https://orcid.org/0000-0002-5572-5469
Elizabeth Jiachen LeeDepartment of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States.
Aalok SatheDepartment of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States.ORCID https://orcid.org/0000-0002-5248-7557
Evelina FedorenkoDepartment of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States.ORCID https://orcid.org/0000-0003-3823-514X

Funding

Computational Neuroscience of Language Processing in the Human BrainU01NS121471 · NINDS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI FEDORENKO, EVELINA, RICHARDSON, ROBERT MARK · 2021 to 2025
$3.2M
The neural architecture of pragmatic processingR01DC016607 · NIDCD · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI FEDORENKO, EVELINA · 2018 to 2022
$2.4M
NIDCD NIH HHS R01 DC016607NINDS NIH HHS U01 NS121471
6 · The paper itself

Abstract

The field of human cognitive neuroscience is increasingly acknowledging inter-individual differences in the precise locations of functional areas and the corresponding need for individual-level analyses in functional magnetic resonance imaging (fMRI) studies. One approach to identifying functional areas and networks within individual brains is based on robust and extensively validated 'localizer' paradigms-contrasts of conditions that aim to isolate some mental process of interest. Here, we present a new version of a localizer for the fronto-temporal language-selective network. This localizer is similar to a commonly used localizer based on the reading of sentences and nonword sequences but uses speeded presentation (200 ms per word/nonword). Based on a direct comparison between the standard version (450 ms per word/nonword) and the speeded version of the language localizer in 24 participants, we show that a single run of the speeded localizer (3.5 minutes) is highly effective at identifying the language-selective areas: indeed, it is more effective than the standard localizer given that it leads to an increased response to the critical (sentence) condition and a decreased response to the control (nonwords) condition. This localizer may therefore become the version of choice for identifying the language network in neurotypical adults or special populations (as long as they are proficient readers), especially when time is of essence.

Indexed as

efficient functional localizationlanguage comprehensionlanguage networkMultiple Demand networkrapid serial visual presentationspeeded reading

Identifiers

PMID42212229
PMCPMC13214572

What OpenQuestion holds

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LicenceCC BY
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.