Evidence map›Paper›PMID 32323112›Full record

ArticleBrain imaging and behavior2021

Abnormal large-scale resting-state functional networks in drug-free major depressive disorder.

Liang Luo, Huawang Wu, Jinping Xu, Fangfang Chen, Fengchun Wu, Chao Wang, Jiaojian Wang

Abstract read
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In one paragraph

Article in Brain imaging and behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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  6. The overlap across psychotic disorders: A functional network connectivity analysis.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2024
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  7. Article
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  15. Resting-State Functional Connectivity Impairment in Patients with Major Depressive Episode.International journal of environmental research and public health · 2022
    Article
  16. Article
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  18. Functional MRI in major depressive disorder: A review of findings, limitations, and future prospects.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2022
    Review
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  20. 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

7 authors.

Liang Luo *School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 625014, China.
Huawang Wu *The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, 510370, China.
Jinping XuInstitute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Fangfang ChenCollege of mathematics and statistics, Shenzhen University of China, Shenzhen, 518060, China.
Fengchun WuThe Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou, 510370, China.
Chao WangSchool of Psychology, Shenzhen University, Shenzhen, 518060, China. chao.wang@szu.edu.cn.
Jiaojian WangKey Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major depressive disorder (MDD) is associated with aberrant function and interaction encompassing large parts of cortical, subcortical and limbic regions that always organized into integrative networks implicated in specific tasks. And cumulative evidence suggests that MDD can be understood as a disorder of dysregulated network. Our study used resting-state fMRI and independent component analysis (ICA) to investigate intrinsic functional connectivity (FC) within and between resting-state networks (RSNs) in 27 drug-free MDD patients and 54 healthy control subjects (HCs). Granger causality analysis (GCA) was further used to identify the direct functional interaction between RSNs. We identified sixteen independent components (ICs) as meaningful RSNs. Compared with HCs, the MDD had significantly decreased intra-FC within lateral visual network (VN), parietal network (PN) and posterior default mode network (pDMN), decreased inter-FC between fronto-parietal network (FPN) and subcortical network, between pDMN and anterior DMN, and increased inter-FC between salience network and FPN, and enhanced effective connectivity from VN to PN and to cerebellum network. The functional synchronization of pDMN was negatively correlated with Hamilton Depression Rating Scores. The relatively small number of MDD, the use of medication and the application challenges of GCA on fMRI data may limit the interpretability. These findings indicated that MDD is indeed a disorder of dysregulated network, especially in the functional networks implicated in self-referential activities and emotional visual processing.

Indexed as

Major Depressive DisorderBrainBrain MappingHumansMagnetic Resonance ImagingNeural PathwaysRestDMNFronto-parietalGCAICASalience

Identifiers

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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.