Evidence map›Paper›PMID 37751811›Full record

ArticleNeuroImage2023

Inter-subject correlation during long narratives reveals widespread neural correlates of reading ability.

David C Jangraw, Emily S Finn, Peter A Bandettini, Nicole Landi, Haorui Sun, Fumiko Hoeft, Gang Chen, Kenneth R Pugh, Peter J Molfese

Open access · goldAbstract read
In one paragraph

Article in NeuroImage, 2023. 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
4.9field-weighted citation impact, top 4% of its field
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

14 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Optimistic people are all alike: Shared neural representations supporting episodic future thinking among optimistic individuals.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Deciphering the neural responses to a naturalistic persuasive message.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Review
  14. 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

9 authors at 5 institutions in 1 country.

David C JangrawSection on Functional Imaging Methods, NIMH, Bethesda, MD, United States; Emotion and Development Branch, NIMH, Bethesda, MD, United States; Department of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, United States. Electronic address: djangraw@uvm.edu.
Emily S FinnSection on Functional Imaging Methods, NIMH, Bethesda, MD, United States; Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, United States.
Peter A BandettiniSection on Functional Imaging Methods, NIMH, Bethesda, MD, United States; Center for Multimodal Neuroimaging, NIMH, Bethesda, MD, United States.
Nicole LandiHaskins Laboratories, New Haven, CT, United States.
Haorui SunDepartment of Electrical and Biomedical Engineering, University of Vermont, Burlington, VT, United States.
Fumiko HoeftHaskins Laboratories, New Haven, CT, United States; Department of Psychological Sciences, University of Connecticut, Hartford, CT, United States.
Gang ChenStatistical Computing Core, NIMH, Bethesda, MD, United States.
Kenneth R PughHaskins Laboratories, New Haven, CT, United States; Department of Pediatrics, Yale University School of Medicine, New Haven, CT, United States.
Peter J MolfeseCenter for Multimodal Neuroimaging, NIMH, Bethesda, MD, United States; Haskins Laboratories, New Haven, CT, United States.
Haskins Laboratories · USUniversity of Vermont · USCenter for Information Technology · USDartmouth College · USNational Institutes of Health · US

Funding

Functional MRI Method DevelopmentZIAMH002783 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI BANDETTINI, PETER · 2009 to 2025
$38.4M
Neurobiological predictors of spoken and written language learningR01HD065794 · NICHD · HASKINS LABORATORIES, INC. · PI PUGH, KENNETH R. · 2011 to 2015
$3.5M
Intramural NIH HHS ZIA MH002783NICHD NIH HHS R01 HD065794
6 · The paper itself

Abstract

Recent work using fMRI inter-subject correlation analysis has provided new information about the brain's response to video and audio narratives, particularly in frontal regions not typically activated by single words. This approach is very well suited to the study of reading, where narrative is central to natural experience. But since past reading paradigms have primarily presented single words or phrases, the influence of narrative on semantic processing in the brain - and how that influence might change with reading ability - remains largely unexplored. In this study, we presented coherent stories to adolescents and young adults with a wide range of reading abilities. The stories were presented in alternating visual and auditory blocks. We used a dimensional inter-subject correlation analysis to identify regions in which better and worse readers had varying levels of consistency with other readers. This analysis identified a widespread set of brain regions in which activity timecourses were more similar among better readers than among worse readers. These differences were not detected with standard block activation analyses. Worse readers had higher correlation with better readers than with other worse readers, suggesting that the worse readers had "idiosyncratic" responses rather than using a single compensatory mechanism. Close inspection confirmed that these differences were not explained by differences in IQ or motion. These results suggest an expansion of the current view of where and how reading ability is reflected in the brain, and in doing so, they establish inter-subject correlation as a sensitive tool for future studies of reading disorders.

Indexed as

Brain MappingDyslexiaAdolescentBrainCognitionHumansMagnetic Resonance ImagingSemanticsYoung AdultfMRIInter-subject correlationNarrativeNaturalisticReading

Identifiers

PMID37751811
PMCPMC10783814
OpenAlexW4386997149

What OpenQuestion holds

Textmetadata
LicenceTDM
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.