Evidence map›Paper›PMID 37167841›Full record

ArticleNeuroImage. Clinical2023

Structural-functional connectivity bandwidth predicts processing speed in mild traumatic brain Injury: A multiplex network analysis.

Nicholas Parsons, Andrei Irimia, Anar Amgalan, Julien Ugon, Kerri Morgan, Sergiy Shelyag, Alex Hocking, Govinda Poudel, Karen Caeyenberghs

Abstract read
In one paragraph

Article in NeuroImage. Clinical, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. The Role of MRI in Debunking the Fallacy of "Mild" Traumatic Brain Injury.Journal of magnetic resonance imaging : JMRI · 2026
    Review
  3. Review
  4. Review
  5. Review
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

9 authors.

Nicholas ParsonsCognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia; BrainCast Neurotechnologies, Australia; School of Psychological Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia. Electronic address: Nicholas.parsons@monash.edu.
Andrei IrimiaEthel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
Anar AmgalanEthel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
Julien UgonSchool of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia.
Kerri MorganSchool of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia.
Sergiy ShelyagSchool of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia.
Alex HockingSchool of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia.
Govinda PoudelBrainCast Neurotechnologies, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia.
Karen CaeyenberghsCognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An emerging body of work has revealed alterations in structural (SC) and functional (FC) brain connectivity following mild TBI (mTBI), with mixed findings. However, these studies seldom integrate complimentary neuroimaging modalities within a unified framework. Multilayer network analysis is an emerging technique to uncover how white matter organization enables functional communication. Using our novel graph metric (SC-FC Bandwidth), we quantified the information capacity of synchronous brain regions in 53 mild TBI patients (46 females; age mean = 40.2 years (y), σ = 16.7 (y), range: 18-79 (y). Diffusion MRI and resting state fMRI were administered at the acute and chronic post-injury intervals. Moreover, participants completed a cognitive task to measure processing speed (30 Seconds and Counting Task; 30-SACT). Processing speed was significantly increased at the chronic, relative to the acute post-injury intervals (p = <0.001). Nonlinear principal components of direct (t = -1.84, p = 0.06) and indirect SC-FC Bandwidth (t = 3.86, p = <0.001) predicted processing speed with a moderate effect size (R

Indexed as

Brain ConcussionBrain Injuries, TraumaticConnectomeAdultBrainFemaleHumansMagnetic Resonance ImagingNerve NetProcessing SpeedDiffusion MRIFunctional connectivityFunctional MRIMild traumatic brain injuryMultiplex Network AnalysisStructural connectivity

Identifiers

PMID37167841
PMCPMC10196722

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.