Evidence map›Paper›PMID 36207331›Full record

ArticleScientific reports2022

Reduced subgenual cingulate-dorsolateral prefrontal connectivity as an electrophysiological marker for depression.

Lars Benschop, Gert Vanhollebeke, Jian Li, Richard M Leahy, Marie-Anne Vanderhasselt, Chris Baeken

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 5% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

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  7. Genome-wide methylome-based molecular pathologies associated with depression and suicide.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2025
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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

6 authors at 4 institutions in 3 countries.

Lars BenschopDepartment of Psychiatry, Ghent University Hospital (UZ Gent), Corneel Heymanslaan 10, 9000, Ghent, Belgium. lars.benschop@ugent.be.
Gert VanhollebekeDepartment of Psychiatry, Ghent University Hospital (UZ Gent), Corneel Heymanslaan 10, 9000, Ghent, Belgium.
Jian LiAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Richard M LeahyMing Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA.
Marie-Anne VanderhasseltDepartment of Psychiatry, Ghent University Hospital (UZ Gent), Corneel Heymanslaan 10, 9000, Ghent, Belgium.
Chris BaekenDepartment of Psychiatry, Ghent University Hospital (UZ Gent), Corneel Heymanslaan 10, 9000, Ghent, Belgium.
Ghent University Hospital · BEEindhoven University of Technology · NLHarvard University · USUniversity of Southern California · US

Funding

BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG ImagingR01EB026299 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI LEAHY, RICHARD M · 2018 to 2025
$5.4M
NIBIB NIH HHS R01 EB026299NIH HHS R01 EB026299
6 · The paper itself

Abstract

Major Depressive Disorder (MDD) is a widespread mental illness that causes considerable suffering, and neuroimaging studies are trying to reduce this burden by developing biomarkers that can facilitate detection. Prior fMRI- and neurostimulation studies suggest that aberrant subgenual Anterior Cingulate (sgACC)-dorsolateral Prefrontal Cortex (DLPFC) functional connectivity is consistently present within MDD. Combining the need for reliable depression markers with the electroencephalogram's (EEG) high clinical utility, we investigated whether aberrant EEG sgACC-DLPFC functional connectivity could serve as a marker for depression. Source-space Amplitude Envelope Correlations (AEC) of 20 MDD patients and 20 matched controls were contrasted using non-parametric permutation tests. In addition, extracted AEC values were used to (a) correlate with characteristics of depression and (b) train a Support Vector Machine (SVM) to determine sgACC-DLPFC connectivity's discriminative power. FDR-thresholded statistical maps showed reduced sgACC-DLPFC AEC connectivity in MDD patients relative to controls. This diminished AEC connectivity is located in the beta-1 (13-17 Hz) band and is associated with patients' lifetime number of depressive episodes. Using extracted sgACC-DLPFC AEC values, the SVM achieved a classification accuracy of 84.6% (80% sensitivity and 89.5% specificity) indicating that EEG sgACC-DLPFC connectivity has promise as a biomarker for MDD.

Indexed as

Major Depressive DisorderBiomarkersDepressionGyrus CinguliHumansMagnetic Resonance ImagingPrefrontal CortexBiomarkers

Identifiers

PMID36207331
PMCPMC9546885
OpenAlexW4303453461

What OpenQuestion holds

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LicenceCC BY
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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.