Evidence map›Paper›PMID 28603919›Full record

ArticleHuman brain mapping2017

Dynamic brain connectivity is a better predictor of PTSD than static connectivity.

Changfeng Jin, Hao Jia, Pradyumna Lanka, D Rangaprakash, Lingjiang Li, Tianming Liu, Xiaoping Hu, Gopikrishna Deshpande

Abstract 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 74 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 1 pooled it
–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

74 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Functional brain imaging in posttraumatic stress disorder: a review.Journal of neural transmission (Vienna, Austria : 1996) · 2026
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  7. Review
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  15. Altered brain state dynamics between preterm and term-born infants.Imaging neuroscience (Cambridge, Mass.) · 2025
    Article
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  18. Article
  19. Review
  20. Review

14 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

8 authors.

Changfeng JinThe Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, China.
Hao JiaAU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama.
Pradyumna LankaAU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama.
D RangaprakashAU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama.ORCID 0000-0001-9553-1354
Lingjiang LiThe Mental Health Institute, The Second Xiangya Hospital, Central South University, Changsha, China.
Tianming LiuCortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, University of Georgia, Athens, Georgia.
Xiaoping HuCenter for Advanced Neuroimaging, Department of Bioengineering, University of California, Riverside, California.
Gopikrishna DeshpandeAU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, Alabama.ORCID 0000-0001-7471-5357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using resting-state functional magnetic resonance imaging, we test the hypothesis that subjects with post-traumatic stress disorder (PTSD) are characterized by reduced temporal variability of brain connectivity compared to matched healthy controls. Specifically, we test whether PTSD is characterized by elevated static connectivity, coupled with decreased temporal variability of those connections, with the latter providing greater sensitivity toward the pathology than the former. Static functional connectivity (FC; nondirectional zero-lag correlation) and static effective connectivity (EC; directional time-lagged relationships) were obtained over the entire brain using conventional models. Dynamic FC and dynamic EC were estimated by letting the conventional models to vary as a function of time. Statistical separation and discriminability of these metrics between the groups and their ability to accurately predict the diagnostic label of a novel subject were ascertained using separate support vector machine classifiers. Our findings support our hypothesis that PTSD subjects have stronger static connectivity, but reduced temporal variability of connectivity. Further, machine learning classification accuracy obtained with dynamic FC and dynamic EC was significantly higher than that obtained with static FC and static EC, respectively. Furthermore, results also indicate that the ease with which brain regions engage or disengage with other regions may be more sensitive to underlying pathology than the strength with which they are engaged. Future studies must examine whether this is true only in the case of PTSD or is a general organizing principle in the human brain. Hum Brain Mapp 38:4479-4496, 2017. © 2017 Wiley Periodicals, Inc.

Indexed as

Magnetic Resonance ImagingBrainBrain MappingDiagnosis, Computer-AssistedDisastersEarthquakesHumansNeural PathwaysRestStress Disorders, Post-TraumaticSupport Vector Machinedynamic brain connectivityeffective connectivityfunctional connectivitypost-traumatic stress disorderresting-state functional magnetic resonance imagingsupport vector machine

Identifiers

PMID28603919
PMCPMC6866943

What OpenQuestion holds

Textmetadata
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.