Evidence map›Paper›PMID 38770197›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2023

An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank.

Bingxin Zhao, Tengfei Li, Yujue Li, Zirui Fan, Di Xiong, Xifeng Wang, Mufeng Gao, Stephen M Smith, Hongtu Zhu

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Gradient synchronization for multivariate functional data, with application to brain connectivity.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2024
    Article
  6. Review
  7. Article
  8. Article
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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.

Bingxin ZhaoDepartment of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA.
Tengfei LiDepartment of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Yujue LiDepartment of Statistics, Purdue University, West Lafayette, IN 47907, USA.
Zirui FanDepartment of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA.
Di XiongDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Xifeng WangDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Mufeng GaoDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Stephen M SmithWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Hongtu ZhuBiomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

Funding

Mapping the Causal Genetic-Imaging-Clinical Pathway for Alzheimer's DiseaseRF1AG082938 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Bingxin Zhao, Hongtu Zhu · 2023 to 2026
$3.6M
Analysis of Big Data Squared in Biomedical StudiesR01MH116527 · NIMH · YALE UNIVERSITY · PI ZHANG, HEPING · 2018 to 2022
$2.3M
NIA NIH HHS RF1 AG082938NIMH NIH HHS R01 MH116527
6 · The paper itself

Abstract

Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).

Indexed as

Brain functionFunctional connectivityHuman traitsMental HealthResting fMRITask fMRIUK Biobank

Identifiers

PMID38770197
PMCPMC11105703

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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.