Evidence map›Paper›PMID 31396111›Full record

ArticleFrontiers in psychiatry2019

Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia.

Victor M Vergara, Eswar Damaraju, Jessica A Turner, Godfrey Pearlson, Aysenil Belger, Daniel H Mathalon, Steven G Potkin, Adrian Preda, Jatin G Vaidya, Theo G M van Erp and 2 more

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

12 authors.

Victor M VergaraTri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.
Eswar DamarajuTri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.
Jessica A TurnerPsychology Department Georgia State University, Atlanta, GA, United States.
Godfrey PearlsonDepartments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, United States.
Aysenil BelgerDepartment of Psychiatry, University of North Carolina, Chapel Hill, NC, United States.
Daniel H MathalonDepartment of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States.
Steven G PotkinDepartment of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States.
Adrian PredaDepartment of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States.
Jatin G VaidyaDepartment of Psychiatry, University of Iowa, IA, United States.
Theo G M van ErpTranslational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States.
Sarah McEwenPacific Neuroscience Institute, Santa Monica, CA, United States.
Vince D CalhounTri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.

Funding

Transcranial Direct Current Stimulation for Treatment of Auditory Verbal HalluciP20GM103472 · NIGMS · THE MIND RESEARCH NETWORK · PI BEDRICK, EDWARD J · 2012 to 2017
$14.3M
Informed Data-Driven Fusion of Behavior, Brain Function, and GenesR01EB005846 · NIBIB · THE MIND RESEARCH NETWORK · PI CALHOUN, VINCE D · 2005 to 2016
$5.5M
Unified multivariate data-driven solutions for static and dynamic brain connectivityR01EB020407 · NIBIB · THE MIND RESEARCH NETWORK · PI ADALI, TULAY, CALHOUN, VINCE D · 2015 to 2018
$2.7M
NIBIB NIH HHS R01 EB005846NIBIB NIH HHS R01 EB020407NIGMS NIH HHS P20 GM103472
6 · The paper itself

Abstract

Functional connectivity is one of the most widely used tools for investigating brain changes due to schizophrenia. Previous studies have identified abnormal functional connectivity in schizophrenia patients at the resting state brain network level. This study tests the existence of functional connectivity effects at whole brain and domain levels. Domain level refers to the integration of data from several brain networks grouped by their functional relationship. Data integration provides more consistent and accurate information compared to an individual brain network. This work considers two domain level measures: functional connectivity strength and randomness. The first measure is simply an average of connectivities within the domain. The second measure assesses the unpredictability and lack of pattern of functional connectivity within the domain. Domains with less random connectivity have higher chance of exhibiting a biologically meaningful connectivity pattern. Consistent with prior observations, individuals with schizophrenia showed aberrant domain connectivity strength between subcortical, cerebellar, and sensorial brain areas. Compared to healthy volunteers, functional connectivity between cognitive and default mode domains showed less randomness, while connectivity between default mode-sensorial areas showed more randomness in schizophrenia patients. These differences in connectivity patterns suggest deleterious rewiring trade-offs among important brain networks.

Indexed as

connectivity strength functionfunctional MRIfunctional network connectivityrandomnessschizophrenia

Identifiers

PMID31396111
PMCPMC6664085

What OpenQuestion holds

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Registered trials

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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.