Evidence map›Paper›PMID 28504361›Full record

ArticleHuman brain mapping2017

Alterations of resting-state fMRI measurements in individuals with cervical dystonia.

Zhihao Li, Cecília N Prudente, Randall Stilla, K Sathian, H A Jinnah, Xiaoping Hu

Open access · bronzeAbstract read
In one paragraph

Article in Human brain mapping, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 9% of its field
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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Brain network pathophysiology in dystonia.Dystonia (Lausanne, Switzerland) · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. The Whiplash Disease Reconsidered.Frontiers in neurology · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. A microstructural neural network biomarker for dystonia diagnosis identified by a DystoniaNet deep learning platform.Proceedings of the National Academy of Sciences of the United States of America · 2020
    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

6 authors at 4 institutions in 2 countries.

Zhihao LiSchool of Psychology and Sociology, Shenzhen University, Shenzhen, Guangdong, People's Republic of China.ORCID 0000-0002-6009-7903
Cecília N PrudenteDepartment of Rehabilitation Medicine, University of Minnesota, Minneapolis, Minnesota.
Randall StillaDepartment of Neurology, Emory University, Atlanta, Georgia.
K SathianDepartment of Neurology, Emory University, Atlanta, Georgia.
H A JinnahDepartment of Neurology, Emory University, Atlanta, Georgia.
Xiaoping HuDepartment of Bioengineering, University of California at Riverside, Riverside, California.
Emory University · USShenzhen University · CNUniversity of California, Riverside · USUniversity of Minnesota · US

Funding

CTSA INFRASTRUCTURE FOR PEDIATRIC RESEARCHUL1RR025008 · NCRR · EMORY UNIVERSITY · PI STEPHENS, DAVID S · 2007 to 2011
$29.0M
Dystonia CoalitionU54NS065701 · NINDS · EMORY UNIVERSITY · PI JINNAH, HYDER A · 2009 to 2014
$7.0M
Dystonia CoalitionU54TR001456 · NCATS · EMORY UNIVERSITY · PI JINNAH, HYDER A · 2015 to 2016
$2.5M
NCATS NIH HHS U54 TR001456NCRR NIH HHS UL1 RR025008NINDS NIH HHS U54 NS065701
6 · The paper itself

Abstract

Cervical dystonia (CD) is a neurological disorder with typical symptoms of involuntary and abnormal movements and postures of the head. CD-associated alterations of functional brain networks have not been well characterized. Previous studies of CD using resting-state functional MRI (rfMRI) are limited in two aspects: (i) the analyses were not directly focused on the functional brain network related to head movement and (ii) rfMRI measurements other than functional connectivity (FC) were not investigated. The present study examined alterations of FC in CD by capitalizing on newly identified brain regions supporting isometric head rotation (Prudente et al.: J Neurosci 35 (2015) 9163-9172). In addition to FC, which only reflects inter-regional signal synchronization, local, or intraregional alterations were also examined using rfMRI measurements of the fractional amplitude of low-frequency fluctuations and regional homogeneity (ReHo). Finally, with alterations of different rfMRI measures identified, a support vector machine (SVM) learning algorithm was implemented for group classification. The results revealed both inter- (FC) and intra-regional (ReHo) alterations extensively distributed in both cortical and subcortical structures; and common alterations of these measures were identified bilaterally in the postcentral gyrus as well as in the basal ganglia and thalamus. Of the rfMRI features examined, seven of them (four FC and three ReHo measures) survived the SVM procedure of recursive feature elimination and together provided the highest group classification accuracy of 90.6%. The present findings extend previous studies of rfMRI in CD and offer insight into the underlying pathophysiology of the disorder in relation to network dysfunction and somatosensory disturbances. Hum Brain Mapp 38:4098-4108, 2017. © 2017 Wiley Periodicals, Inc.

Indexed as

Magnetic Resonance ImagingBrain MappingFemaleHead MovementsHumansMaleMiddle AgedNeural PathwaysRestSupport Vector MachineTorticolliscervical dystoniafractional amplitude of low-frequency fluctuationfunctional connectivityregional homogeneityresting-state fMRIsupport vector machine

Identifiers

PMID28504361
PMCPMC5553075
OpenAlexW2616426212

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.