Evidence map›Paper›PMID 39235695›Full record

ArticleBrain imaging and behavior2024

Functional correlation tensors in brain white matter and the effects of normal aging.

Lyuan Xu, Yurui Gao, Muwei Li, Richard Lawless, Yu Zhao, Kurt G Schilling, Baxter P Rogers, Adam W Anderson, Zhaohua Ding, Bennett A Landman and 1 more

Abstract read
In one paragraph

Article in Brain imaging and behavior, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Distributed fMRI Patterns Coupled to Low-Frequency Cardiorespiratory Dynamics Provide Markers of Aging.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  3. Article
  4. Article
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

11 authors.

Lyuan XuVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Yurui GaoVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Muwei LiVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Richard LawlessVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Yu ZhaoVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Kurt G SchillingVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Baxter P RogersVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Adam W AndersonVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Zhaohua DingVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
Bennett A LandmanVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA.
John C GoreVanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, 1161 21st Ave. S, Medical Center North, Nashville, TN, AA-1105, 37232-2310, USA. john.gore@vanderbilt.edu.

Funding

Overall: Eunice Kennedy Shriver Intellectual and Developmental Disabilities Research Center at VanderbiltP50HD103537 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Jeffrey L Neul · 2020 to 2026
$10.3M
Resting State Connectivity in White MatterR01NS093669 · NINDS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GORE, JOHN C · 2016 to 2020
$2.7M
Biophysical basis of functional MRI of white matterR01NS113832 · NINDS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GORE, JOHN C · 2020 to 2024
$2.4M
Functional Connectome of Brain White MatterR01NS129855 · NINDS · VANDERBILT UNIVERSITY · PI ZHAOHUA DING · 2023 to 2026
$1.9M
Secondary analysis of functional MRI and resting state connectivity in white matterRF1MH123201 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GORE, JOHN C, LANDMAN, BENNETT A. · 2021 to 2021
$1.3M
NICHD NIH HHS P50 HD103537NIMH NIH HHS RF1 MH123201NINDS NIH HHS R01 NS093669NINDS NIH HHS R01 NS113832NINDS NIH HHS R01 NS129855Vanderbilt University Vanderbilt Discovery Grant FF600670
6 · The paper itself

Abstract

Resting state correlations between blood oxygenation level dependent (BOLD) MRI signals from voxels in white matter (WM) are demonstrably anisotropic, so that functional correlation tensors (FCT) may be used to quantify the underlying microstructure of BOLD effects in WM tracts. However, the overall spatial distribution of FCTs and their metrics in specific populations has not yet been established, and the factors that affect their precise arrangements remain unclear. Changes in WM occur with normal aging, and these may be expected to affect FCTs. We hypothesized that FCTs exhibit a characteristic spatial pattern and may show systematic changes with aging or other factors. Here we report our analyses of the FCT characteristics of fMRI images of a large cohort of 461 cognitively normal subjects (190 females, 271 males) sourced from the Open Access Series of Imaging Studies (OASIS), with age distributions of 42 y/o - 95 y/o. Group averages and statistics of FCT indices, including axial functional correlations, radial functional correlations, mean functional correlations and fractional anisotropy, were quantified in WM bundles defined by the JHU ICBM-DTI-81 WM atlas. In addition, their variations with normal aging were examined. The results revealed a dimorphic distribution of changes in FCT metrics with age, with decreases of the functional correlations in some regions and increases in others. Supplementary analysis revealed that females exhibited significant age effects on a greater number of WM areas, but the interaction between age and sex was not significant. The findings demonstrate the reproducibility of the spatial distribution of FCT metrics and reveal subtle regional changes with age.

Indexed as

AgingBrainMagnetic Resonance ImagingWhite MatterAdultAgedAged, 80 and overAnisotropyCohort StudiesDiffusion Tensor ImagingFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedOxygenOxygenAgingBOLDfMRIFunctional correlation tensorResting stateWhite matter

Identifiers

PMID39235695
PMCPMC11582213

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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.