Evidence map›Paper›PMID 30793076›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2019

Global connectivity of the fronto-parietal cognitive control network is related to depression symptoms in the general population.

Douglas H Schultz, Takuya Ito, Levi I Solomyak, Richard H Chen, Ravi D Mill, Alan Anticevic, Michael W Cole

Abstract read
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 4 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

49 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Heterogeneous brain alterations in treatment-resistant depression converge on common control networks.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026
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  5. Baseline electrophysiology versus oxidative metabolism as traits of inter-network differences in neurometabolic association.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
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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.

Douglas H SchultzCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.ORCID 0000-0003-0809-9036
Takuya ItoCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.
Levi I SolomyakCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.
Richard H ChenCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.
Ravi D MillCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.
Alan AnticevicDepartment of Psychiatry, Yale University, New Haven, CT, USA.
Michael W ColeCenter for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, USA.

Funding

Characterizing Schizophrenia Progression via Multi-modal Neuroimaging and ComputationR01MH108590 · NIMH · YALE UNIVERSITY · PI ANTICEVIC, ALAN · 2016 to 2020
$2.0M
Mapping the Longitudinal Neurobiology of Early-course SchizophreniaR01MH112189 · NIMH · YALE UNIVERSITY · PI ANTICEVIC, ALAN · 2017 to 2021
$939k
Neuropsychiatric Classification via Connectivity and Machine LearningR03MH105765 · NIMH · YALE UNIVERSITY · PI ANTICEVIC, ALAN · 2014 to 2015
$180k
NIMH NIH HHS R01 MH108590NIMH NIH HHS R01 MH112189NIMH NIH HHS R03 MH105765
6 · The paper itself

Abstract

We all vary in our mental health, even among people not meeting diagnostic criteria for mental illness. Understanding this individual variability may reveal factors driving the risk for mental illness, as well as factors driving subclinical problems that still adversely affect quality of life. To better understand the large-scale brain network mechanisms underlying this variability, we examined the relationship between mental health symptoms and resting-state functional connectivity patterns in cognitive control systems. One such system is the fronto-parietal cognitive control network (FPN). Changes in FPN connectivity may impact mental health by disrupting the ability to regulate symptoms in a goal-directed manner. Here we test the hypothesis that FPN dysconnectivity relates to mental health symptoms even among individuals who do not meet formal diagnostic criteria but may exhibit meaningful symptom variation. We found that depression symptoms severity negatively correlated with between-network global connectivity (BGC) of the FPN. This suggests that decreased connectivity between the FPN and the rest of the brain is related to increased depression symptoms in the general population. These findings complement previous clinical studies to support the hypothesis that global FPN connectivity contributes to the regulation of mental health symptoms across both health and disease.

Indexed as

DepressionfMRIFronto-parietal networkFunctional connectivity

Identifiers

PMID30793076
PMCPMC6326740

What OpenQuestion holds

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LicenceCC BY
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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.