Wang JX, Zhang HS, Liu M, Zhao J, Wang YF, Shen LJ, Zhang M. Observations on dynamic brain network properties of emotional information processing in patients with depression and sex differences. World J Psychiatry 2026; 16(10): 120085 [DOI: 10.5498/wjp.120085]
Corresponding Author of This Article
Jin-Xiang Wang, PhD, Department of Clinical Psychology, The Second Affiliated Hospital of Henan Medical University, No. 207 Qianjin Road, Muye District, Xinxiang 453002, Henan Province, China. wangjinxiang2001@163.com
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Psychiatry
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research-article
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Wang JX, Zhang HS, Liu M, Zhao J, Wang YF, Shen LJ, Zhang M. Observations on dynamic brain network properties of emotional information processing in patients with depression and sex differences. World J Psychiatry 2026; 16(10): 120085 [DOI: 10.5498/wjp.120085]
Jin-Xiang Wang, Hong-Sheng Zhang, Meng Liu, Li-Juan Shen, Department of Clinical Psychology, The Second Affiliated Hospital of Henan Medical University, Xinxiang 453002, Henan Province, China
Jin Zhao, Department of Psychosomatic Medicine, The Second Affiliated Hospital of Henan Medical University, Xinxiang 453002, Henan Province, China
Yu-Feng Wang, Meng Zhang, School of Psychology, Henan Medical University, Xinxiang 453003, Henan Province, China
Author contributions: Wang JX contributed to writing - review and editing, data curation, statistical analysis, and writing - original draft; Zhang HS, Liu M, and Zhao J contributed to investigation and data curation, statistical analysis; Shen LJ, Wang YF, and Zhang M provided clinical advice. All authors contributed to the study and approved the final manuscript.
AI contribution statement: AI tools were not used to the manuscript.
Supported by Henan Provincial Health Commission Medical Science and Technology Joint Research Project, No. LHGJ20230530; Open Project of Psychiatry and Neuroscience Discipline of the Second Affiliated Hospital of Xinxiang Medical University, No. XYEFYJSSJ-2023-06; and Doctoral Research Startup Fund of the Second Affiliated Hospital of Xinxiang Medical University, No. 1777.
Institutional review board statement: The study was reviewed and approved by the Institutional Review Board of the Second Affiliated Hospital of Xinxiang Medical University (No. 2023-52-1).
Informed consent statement: All study participants or their legal guardians provided written informed consent before study enrollment.
Conflict-of-interest statement: The authors declare no conflict of interest.
STROBE statement: The authors reviewed the STROBE Statement checklist and prepared and revised the manuscript accordingly.
Data sharing statement: An anonymous dataset supporting the findings of this study is available from the corresponding author upon reasonable request.
Corresponding author: Jin-Xiang Wang, PhD, Department of Clinical Psychology, The Second Affiliated Hospital of Henan Medical University, No. 207 Qianjin Road, Muye District, Xinxiang 453002, Henan Province, China. wangjinxiang2001@163.com
Received: April 10, 2026 Revised: May 15, 2026 Accepted: June 3, 2026 Published online: October 19, 2026 Processing time: 183 Days and 0.7 Hours
Abstract
BACKGROUND
Depression is a leading cause of disability worldwide and is associated with abnormal emotional information processing. Traditional static brain network analyses are not suited for capturing the dynamic features of emotional processing. By characterizing temporal fluctuations in inter-regional connectivity, dynamic brain network analyses can provide new perspectives for elucidating the neural mechanisms of depression.
AIM
To use dynamic brain network analysis to explore emotional processing and sex differences in depression.
METHODS
From October 2023 to March 2025, 90 patients with major depressive disorder (45 men/45 women) and 30 healthy controls (15 men/15 women) were enrolled. Resting-state functional magnetic resonance imaging data were collected and preprocessed, and dynamic functional connectivity matrices were constructed using the sliding window technique. Global topology, modularity, and key network connectivity [default mode network (DMN), salience network (SN)], and executive control network) were analyzed and compared between the depression and control groups.
RESULTS
The depression group showed lower global efficiency, local efficiency, small-worldness, number of modules, and within-module connectivity strength; higher mean dynamic functional connectivity variability; shorter state dwell time; reduced within-DMN and SN-limbic connectivity; and reduced executive control network hub involvement than the control group. Sex differences were observed; women had a lower global efficiency, more pronounced within-module deficits, stronger fluctuations, and more DMN inhibition; men showed enhanced intermodule segregation, more frequent state transitions, and prominent SN-limbic connectivity deficits.
CONCLUSION
Patients with depression showed impaired dynamic brain network efficiency, modularity, and emotional regulation. These impairments also showed sex differences; women showed enhanced DMN inhibition, and men showed SN-limbic segregation.
Core Tip: This observational study included 90 patients with depression (45 men/45 women) and 30 healthy controls. Using resting-state functional magnetic resonance imaging and dynamic brain network analysis, we identified impaired network efficiency, modularity, and emotional regulation in depression, with sex-related patterns. Women showed enhanced default mode network inhibition, while men exhibited salience network-limbic segregation. These findings offer key neuroimaging evidence for sex-specific depression diagnostic criteria and treatments.
