Evidence map›Paper›PMID 31276262›Full record

ArticleHuman brain mapping2019

Exploring the functional connectome in white matter.

Jiao Li, Bharat B Biswal, Pan Wang, Xujun Duan, Qian Cui, Huafu Chen, Wei Liao

Abstract readValidation Study
In one paragraph

Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing 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

61 citing papers in PubMed.

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  17. White Matter Function and Network Abnormalities in Patients with Diabetic Retinopathy.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024
    Article
  18. Article
  19. Article
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1 more citing papers are in PubMed but not listed here.

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

7 authors.

Jiao LiThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
Bharat B BiswalThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
Pan WangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
Xujun DuanThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
Qian CuiSchool of Public Administration, University of Electronic Science and Technology of China, Chengdu, China.
Huafu ChenThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
Wei LiaoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.

Funding

"111" Project B12027China Postdoctoral Science Foundation 2013M532229National Natural Science Foundation of China 61533006National Natural Science Foundation of China 61673089National Natural Science Foundation of China 61871077National Natural Science Foundation of China 81771919National Natural Science Foundation of China U1808204Sichuan Science and Technology Program 2018TJPT0016
6 · The paper itself

Abstract

A major challenge in neuroscience is understanding how brain function emerges from the connectome. Most current methods have focused on quantifying functional connectomes in gray-matter (GM) signals obtained from functional magnetic resonance imaging (fMRI), while signals from white-matter (WM) have generally been excluded as noise. In this study, we derived a functional connectome from WM resting-state blood-oxygen-level-dependent (BOLD)-fMRI signals from a large cohort (n = 488). The WM functional connectome exhibited weak small-world topology and nonrandom modularity. We also found a long-term (i.e., over 10 months) topological reliability, with topological reproducibility within different brain parcellation strategies, spatial distance effect, global and cerebrospinal fluid signals regression or not. Furthermore, the small-worldness was positively correlated with individuals' intelligence values (r = .17, p

Indexed as

AdolescentAdultArea Under CurveConnectomeFemaleFollow-Up StudiesGray MatterHumansIntelligenceMagnetic Resonance ImagingMaleNerve NetNeural PathwaysOxygenReference ValuesReproducibility of ResultsOxygenfunctional connectomenetwork topologyresting-statetopological reliabilitywhite matter

Identifiers

PMID31276262
PMCPMC6865787

What OpenQuestion holds

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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.