Evidence map›Paper›PMID 41963852›Full record

ArticleBMC psychiatry2026

The association between spatiotemporal coupling of default mode network and behaviors is specifically modulated by peripheral inflammation in major depressive disorder.

Junxia Chen, Xiaoying Sun, Suping Yue, Zibin Feng, Ruikun Yang, Yue Yu, Hui He, Suli Zhao, Yifan Li, Shuxiao Chen and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Junxia ChenThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Xiaoying SunThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Suping YueThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Zibin FengThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Ruikun YangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Yue YuThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Hui HeThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Suli ZhaoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Yifan LiThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Shuxiao ChenThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Roberto Rodriguez-LabradaCuban Neuroscience Center, La Habana, Cuba.
Mingjun DuanThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Dezhong YaoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Sisi JiangThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China.
Cheng LuoThe Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China. chengluo@uestc.edu.cn.

Funding

National Key R&D Programme of China 2024YFE0215100
6 · The paper itself

Abstract

backgroundDefault mode network (DMN) disruption and systemic inflammation are hallmarks of major depressive disorder (MDD), but their relationship with behavioral impairments is unclear. This study aimed to characterize DMN spatiotemporal dynamics in MDD and link them to inflammation and behavioral deficits.

methodResting-state functional magnetic resonance imaging data were obtained from 87 MDD and 104 healthy controls (HC). Periodic spatiotemporal patterns (PSTPs) were defined by the switching of anti-correlation between the DMN and task-positive network. Functional couplings between DMN and cerebral networks within these patterns were then calculated. Subsequently, associations between DMN subsystem couplings and behaviors were assessed, and lasso regression was used to evaluate their predictive effects on behavior. Moderation analyses and cytokine-based subgroup comparisons were further conducted to examine the effect of inflammation on brain-behavior relationships.

resultsIn MDD, couplings within the DMN increased, whereas couplings between DMN and attention and salience networks decreased. Additionally, the association was observed between DMN B coupling and Trail Making Test Part B (TMT-B) performance in MDD. These alterations also predicted the digital span test (DST). Moderation analyses showed that interleukin (IL)-17 A strengthened DMN-behavior associations, whereas IL-8 attenuated them. Consistently, higher IL-17 A levels were associated with more pronounced DMN coupling abnormalities, while lower IL-8 levels were linked to DST and TMT-B deficits.

conclusionsThis study demonstrates internal enhancement and external decoupling of the DMN in MDD, along with the differential modulation of inflammation on brain-behavior relationships. These findings provide new insights into the pathophysiology of MDD.

trial registrationNot applicable.

Indexed as

BrainDefault Mode NetworkInflammationMajor Depressive DisorderAdultCase-Control StudiesFemaleHumansMagnetic Resonance ImagingMaleYoung AdultDefault mode networkFunctional couplingInflammationMajor depressive disorderPeriodic spatiotemporal patterns

Identifiers

PMID41963852
PMCPMC13185343

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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.