Evidence map›Paper›PMID 38568476›Full record

ReviewNeuroinformatics2024

Gradients of Brain Organization: Smooth Sailing from Methods Development to User Community.

Jessica Royer, Casey Paquola, Sofie L Valk, Matthias Kirschner, Seok-Jun Hong, Bo-Yong Park, Richard A I Bethlehem, Robert Leech, B T Thomas Yeo, Elizabeth Jefferies and 3 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Neuroinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 5% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
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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

13 authors at 13 institutions in 8 countries.

Jessica RoyerMontreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada. jessica.royer@mail.mcgill.ca.
Casey PaquolaInstitute for Neuroscience and Medicine (INM-7), Forschungszentrum Jülich, Jülich, Germany.
Sofie L ValkMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Matthias KirschnerDivision of Adult Psychiatry, Department of Psychiatry, University Hospitals of Geneva, Thonex, Switzerland.
Seok-Jun HongCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea.
Bo-Yong ParkCenter for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea.
Richard A I BethlehemDepartment of Psychology, University of Cambridge, Cambridge, UK.
Robert LeechCentre for Neuroimaging Science, King's College London, London, UK.
B T Thomas YeoCentre for Sleep & Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Elizabeth JefferiesDepartment of Psychology, University of York, York, UK.
Jonathan SmallwoodDepartment of Psychology, Queens University, Kingston, ON, Canada.
Daniel MarguliesIntegrative Neuroscience and Cognition Center (UMR 8002), Centre National de la Recherche Scientifique (CNRS), Université de Paris, Paris, France.
Boris C BernhardtMontreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
Forschungszentrum Jülich · DEInstitute for Basic Science · KRMax Planck Institute for Human Cognitive and Brain Sciences · DEMcGill University · CAMontreal Neurological Institute and Hospital · CANational University Cancer Institute, Singapore · SGQueen's University · CASungkyunkwan University · KRUniversité Paris Cité · FRUniversity Hospital of Geneva · CHUniversity of Cambridge · GBUniversity of York · GBWellcome Centre for Human Neuroimaging · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multimodal neuroimaging grants a powerful in vivo window into the structure and function of the human brain. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends - or gradients - in brain structure and function, offering a framework to unify principles of brain organization across multiple scales. Strong community enthusiasm for these techniques has been instrumental in their widespread adoption and implementation to answer key questions in neuroscience. Following a brief review of current literature on this framework, this perspective paper will highlight how pragmatic steps aiming to make gradient methods more accessible to the community propelled these techniques to the forefront of neuroscientific inquiry. More specifically, we will emphasize how interest for gradient methods was catalyzed by data sharing, open-source software development, as well as the organization of dedicated workshops led by a diverse team of early career researchers. To this end, we argue that the growing excitement for brain gradients is the result of coordinated and consistent efforts to build an inclusive community and can serve as a case in point for future innovations and conceptual advances in neuroinformatics. We close this perspective paper by discussing challenges for the continuous refinement of neuroscientific theory, methodological innovation, and real-world translation to maintain our collective progress towards integrated models of brain organization.

Indexed as

BrainBrain MappingHumansInformation DisseminationNeuroimagingNeurosciencesSoftwareGradientsMultimodalNeuroinformaticsOpen science

Identifiers

PMID38568476
OpenAlexW4393857338

What OpenQuestion holds

Textmetadata
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.