Evidence map›Paper›PMID 40109660›Full record

ArticleFrontiers in neuroscience2025

Unveiling the dynamic effects of major depressive disorder and its rTMS interventions through energy landscape analysis.

Chun-Wang Su, Yurui Tang, Nai-Long Tang, Nian Liu, Jing-Wen Li, Shun Qi, Hua-Ning Wang, Zi-Gang Huang

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Observational
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

8 authors.

Chun-Wang SuSchool of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Yurui TangSchool of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Nai-Long TangDepartment of Psychiatry, First Affiliated Hospital of Air Force Medical University, Xi'an, Shaanxi, China.
Nian LiuDepartment of Psychiatry, First Affiliated Hospital of Air Force Medical University, Xi'an, Shaanxi, China.
Jing-Wen LiDepartment of Psychiatry, First Affiliated Hospital of Air Force Medical University, Xi'an, Shaanxi, China.
Shun QiResearch Center for Brain-inspired Intelligence, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Hua-Ning WangDepartment of Psychiatry, First Affiliated Hospital of Air Force Medical University, Xi'an, Shaanxi, China.
Zi-Gang HuangSchool of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Brain dynamics offer a more direct insight into brain function than network structure, providing a profound understanding of dysregulation and control mechanisms within intricate brain systems. This study investigates the dynamics of functional brain networks in major depressive disorder (MDD) patients to decipher the mechanisms underlying brain dysfunction during depression and assess the impact of repetitive transcranial magnetic stimulation (rTMS) intervention. Methods: We employed energy landscape analysis of functional magnetic resonance imaging (fMRI) data to examine the dynamics of functional brain networks in MDD patients. The analysis focused on key dynamical indicators of the default mode network (DMN), the salience network (SN), and the central execution network (CEN). The effects of rTMS intervention on these networks were also evaluated. Results: Our findings revealed notable dynamical alterations in the pDMN, the vDMN, and the aSN, suggesting their potential as diagnostic and therapeutic markers. Particularly striking was the altered activity observed in the dDMN in the MDD group, indicative of patterns associated with depressive rumination. Notably, rTMS intervention partially reverses the identified dynamical alterations. Discussion: Our results shed light on the intrinsic dysfunction mechanisms of MDD from a dynamic standpoint and highlight the effects of rTMS intervention. The identified alterations in brain network dynamics provide promising analytical markers for the diagnosis and treatment of MDD. Future studies should further explore the clinical applications of these markers and the comprehensive dynamical effects of rTMS intervention.

Indexed as

energy landscapefMRImajor depressive disorder (MDD)repetitive transcranial magnetic stimulation (rTMS)resting state dynamics

Identifiers

PMID40109660
PMCPMC11920141

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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.