Evidence map›Paper›PMID 36224186›Full record

ArticleScientific data2022

An analysis-ready and quality controlled resource for pediatric brain white-matter research.

Adam Richie-Halford, Matthew Cieslak, Lei Ai, Sendy Caffarra, Sydney Covitz, Alexandre R Franco, Iliana I Karipidis, John Kruper, Michael Milham, Bárbara Avelar-Pereira and 6 more

Erratum issuedAbstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. The Brain-Age Gap in Pediatric Dystonia: Neuroanatomical Deviations Inform Deep Brain Stimulation Outcomes.Movement disorders : official journal of the Movement Disorder Society · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Two axes of white matter development.Nature communications · 2026
    Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Free water elimination tractometry for aging brains.Imaging neuroscience (Cambridge, Mass.) · 2025
    Article
  15. Article
  16. Tractometry of Human Visual White Matter Pathways in Health and Disease.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024
    Review
  17. Article
  18. Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  19. White matter and literacy: A dynamic system in flux.Developmental cognitive neuroscience · 2024
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Adam Richie-Halford *Stanford University, Division of Developmental and Behavioral Pediatrics, Stanford, California, 94305, USA. adamrh@stanford.edu.ORCID http://orcid.org/0000-0001-9276-9084
Matthew Cieslak *Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA. matthew.cieslak@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0002-1931-4734
Lei AiChild Mind Institute, Center for the Developing Brain, New York City, New York, 10022, USA.
Sendy CaffarraStanford University, Division of Developmental and Behavioral Pediatrics, Stanford, California, 94305, USA.
Sydney CovitzLifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA.
Alexandre R FrancoChild Mind Institute, Center for the Developing Brain, New York City, New York, 10022, USA.
Iliana I KaripidisStanford University, Graduate School of Education, Stanford, California, 94305, USA.
John KruperUniversity of Washington, Department of Psychology, Seattle, Washington, 98195, USA.ORCID http://orcid.org/0000-0003-0081-391X
Michael MilhamChild Mind Institute, Center for the Developing Brain, New York City, New York, 10022, USA.ORCID http://orcid.org/0000-0003-3532-1210
Bárbara Avelar-PereiraStanford University, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford, California, 94305, USA.ORCID http://orcid.org/0000-0003-4719-8504
Ethan RoyStanford University, Graduate School of Education, Stanford, California, 94305, USA.
Valerie J SydnorLifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA.
Jason D YeatmanStanford University, Division of Developmental and Behavioral Pediatrics, Stanford, California, 94305, USA.
Fibr Community Science Consortium
Theodore D SatterthwaiteLifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA.
Ariel RokemUniversity of Washington, Department of Psychology, Seattle, Washington, 98195, USA.ORCID http://orcid.org/0000-0003-0679-1985

Funding

Reproducible imaging-based brain growth charts for psychiatryR01MH120482 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI MILHAM, MICHAEL PETER, SATTERTHWAITE, THEODORE · 2019 to 2023
$3.5M
CRCNS: Community-supported open-source software for computational neuroanatomyR01EB027585 · NIBIB · TRUSTEES OF INDIANA UNIVERSITY · PI Eleftherios Garyfallidis · 2018 to 2026
$2.6M
A data science toolbox for analysis of Human Connectome Project diffusion MRIRF1MH121868 · NIMH · UNIVERSITY OF WASHINGTON · PI ROKEM, ARIEL SHALOM · 2019 to 2019
$707k
NIBIB NIH HHS R01 EB027585NIMH NIH HHS R01 MH120482NIMH NIH HHS RF1 MH121868
6 · The paper itself

Abstract

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets.

Indexed as

Image Processing, Computer-AssistedWhite MatterBrainChildDiffusion Magnetic Resonance ImagingHumansNeuroimaging

Identifiers

PMID36224186
PMCPMC9556519

What OpenQuestion holds

Textmetadata
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.