ArticleFrontiers in neuroscience2024
Tractometry of the Human Connectome Project: resources and insights.
Article in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
The trial behind it
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Who cites it
11 citing papers in PubMed.
- Molecular, cellular and network mapping of brain structural deviations in patients with Post-COVID19 syndrome.Brain, behavior, & immunity - health · 2026Article
- Neonatal brain-age models in full- and preterm infants.Developmental cognitive neuroscience · 2026Article
- Graph-Based White Matter Tractometry: Methods, Applications, and the Path to Validation.Neuroinformatics · 2026Review
- Two axes of white matter development.Nature communications · 2026Article
- Neonatal brain-age models in full- and preterm infants.bioRxiv : the preprint server for biology · 2026Article
- What needs to be standardized for reliable, reproducible, and robust tractography?GigaScience · 2026Review
- A software ecosystem for brain tractometry processing, analysis, and insight.PLoS computational biology · 2025Article
- From MRIcro to MRIcron: The evolution of neuroimaging visualization tools.Neuropsychologia · 2025Article
- If Freud had known….Frontiers in psychology · 2025Article
- Fiber microstructure quantile (FMQ) regression: A novel statistical approach for analyzing white matter bundles from periphery to core.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Massively parallelized brain tractography using compute clusters, supercomputers, and graphics processing units.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Introduction: The Human Connectome Project (HCP) has become a keystone dataset in human neuroscience, with a plethora of important applications in advancing brain imaging methods and an understanding of the human brain. We focused on tractometry of HCP diffusion-weighted MRI (dMRI) data. Methods: We used an open-source software library (pyAFQ; https://yeatmanlab.github.io/pyAFQ) to perform probabilistic tractography and delineate the major white matter pathways in the HCP subjects that have a complete dMRI acquisition ( Results: We released the processing outputs and tract profiles as a publicly available data resource through the AWS Open Data program's Open Neurodata repository. We found heritability as high as 0.9 for DKI-based metrics in some brain pathways. We also found that tractometry extracts as much useful information about individual differences as the local connectome method. We released a new web-based visualization tool for tractometry-"Tractoscope" (https://nrdg.github.io/tractoscope). We found that the TRX files require considerably less disk space-a crucial attribute for large datasets like HCP. In addition, TRX incorporates a specification for grouping streamlines, further simplifying tractometry analysis.
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Registered trials
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 Socratic graph.