Review in GigaScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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.
Wei TangDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.ORCID 0000-0003-3550-4076
Garrett BanksDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0001-6292-977X
Matthew CieslakLifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0002-1931-4734
Kurt SchillingDepartment of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0003-3686-7645
Alberto De LucaImage Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands.ORCID 0000-0002-2553-7299
Jacques-Donald TournierDepartment of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, St. Thomas' Hospital, London, UK.ORCID 0000-0001-5591-7383
John KruperDepartment of Psychology, University of Washington, Seattle, WA, USA.ORCID 0000-0003-0081-391X
Francois RheaultSherbrooke Connectivity Imaging Lab (SCIL), Department of Computer Science, Université de Sherbrooke, Sherbrooke, Québec, Canada.ORCID 0000-0002-0097-8004
Stamatios N SotiropoulosSir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK.ORCID 0000-0003-4735-5776
Franco PestilliDepartment of Psychology, The University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-2469-0494
Joseph Yuan-Mou YangDepartment of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), Royal Children's Hospital, Melbourne, Victoria, Australia.ORCID 0000-0003-4081-7157
Maxime DescoteauxSherbrooke Connectivity Imaging Lab (SCIL), Department of Computer Science, Université de Sherbrooke, Sherbrooke, Québec, Canada.ORCID 0000-0002-8191-2129
Sarah HeilbronnerDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0003-0893-5364
Ariel RokemDepartment of Psychology, University of Washington, Seattle, WA, USA.ORCID 0000-0003-0679-1985
Funding
Translational pharmacoepidemiology: neuroprotection and neurotoxicity of antihypertensives and strong anticholinergicsU19AG066567 · NIA · KAISER FOUNDATION RESEARCH INSTITUTE · PI Christine L MacDonald · 2021 to 2026
$80.4M
Aging eyes and aging brains in studying alzheimer's disease: Modern ophthalmic data collection in the adult changes in thought (ACT) studyR01AG060942 · NIA · WASHINGTON UNIVERSITY · PI Cecilia Sungmin Lee · 2019 to 2026
$39.4M
BRAIN CONNECTS: Center for Mesoscale ConnectomicsUM1NS132207 · NINDS · UNIVERSITY OF MINNESOTA · PI TANER AKKIN, Damien A Fair · 2023 to 2026
$12.5M
Longitudinal Mapping of Network Development Underlying Executive Dysfunction in AdolescenceR01MH113550 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Danielle Smith Bassett, Theodore Satterthwaite · 2018 to 2026
$6.9M
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
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
BRAIN CONNECTS: The Axonal Projectome EXchange (APEX)U24NS140384 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI Franco Pestilli, Anastasia Yendiki · 2025 to 2026
$2.3M
NIPreps: integrating neuroimaging preprocessing workflows across modalities, populations, and speciesRF1MH121867 · NIMH · STANFORD UNIVERSITY · PI POLDRACK, RUSSELL A, ROKEM, ARIEL SHALOM · 2021 to 2022
$1.6M
Summer Institute in Neuroimaging and Data ScienceR25MH112480 · NIMH · UNIVERSITY OF WASHINGTON · PI Noah C Benson · 2017 to 2026
$1.6M
A data science toolbox for analysis of Human Connectome Project diffusion MRIRF1MH121868 · NIMH · UNIVERSITY OF WASHINGTON · PI ROKEM, ARIEL SHALOM · 2019 to 2019
$707k
Microstructure and connectivity modeling from the cortex to the spinal cord in Multiple SclerosisK01EB032898 · NIBIB · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SCHILLING, KURT G · 2022 to 2025
$630k
European Research Council 101000969European Research Council 101163214European Research Council 226486/Z/22/ZNatural Sciences and Engineering Research Council of CanadaNIA NIH HHS R01 AG060942NIA NIH HHS U19 AG066567NIBIB NIH HHS 2R01EB027585-04A1NIBIB NIH HHS K01 EB032898NIBIB NIH HHS R01 EB027585NIH HHS 2R01MH112847NIH HHS 2R01MH113550NIH HHS 2R01MH120482NIH HHS K01EB032898NIH HHS MH121867NIH HHS MH121868NIH HHS R01AG060942NIH HHS R01EB027585NIH HHS R25MH112480NIH HHS U19AG066567NIH HHS UM1NS132207NIMH NIH HHS R01 MH112847NIMH NIH HHS R01 MH113550NIMH NIH HHS R01 MH120482NIMH NIH HHS R25 MH112480NIMH NIH HHS RF1 MH121867NIMH NIH HHS RF1 MH121868NINDS NIH HHS U24 NS140384NINDS NIH HHS U24NS140384NINDS NIH HHS UM1 NS132207NINDS NIH HHS UM1NS132207NSF 1934292NSF 2334483NSF DGE-2140004Wellcome Trust 226486/Z/22/Z
6 · The paper itself
Abstract
Tractography is a key component of efforts to map brain connectivity. As a rapidly evolving field of neuroscience, current tractography methods are diverse, often varying across research laboratories and different software pipelines. Therefore, it suffers from a lack of standardization, leading to inconsistencies in results, which can limit reproducibility and affect the robustness needed for research and clinical applications of these methods. Variability in data acquisition procedures, inconsistencies in spatial referencing schemes and implementations, and anatomical heterogeneity-at the individual level, across the lifespan, and across species-hinder comparative analyses. Additionally, the lack of consensus on best practices complicates the development of robust automated quality control pipelines and limits the clinical translation of tractography-based procedures. Establishing standardized protocols for acquisition, preprocessing, and tractography reconstruction is critical toward enabling reliable tract-specific analyses, facilitating cross-study harmonization, and supporting replicable large-scale population studies. The present article provides an overview of the current challenges in tractography standardization and identifies the key aspects that require standardization for reliable, reproducible, and robust tractography.
Indexed as
BrainDiffusion Tensor ImagingImage Processing, Computer-AssistedAnimalsHumansReproducibility of ResultsSoftwarebrain connectivitycomputational neuroimagingneuroanatomystandardizationtractographywhite matter
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.
What needs to be standardized for reliable, reproducible, and robust tractography? · full record | OpenQuestion