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Updated: Jan 15, 2026

MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder
Published on: August 11, 2015
Early treatment-related changes in dorsolateral prefrontal cortex activity and functional connectivity as potential
1Department of Neurology and Psychiatry, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract:
Cognitive deficits are prevalent in major depressive disorder (MDD). Given that the dorsolateral prefrontal cortex (DLPFC) is a crucial region within the executive control network, its activity and functional connectivity (FC) may serve as potential indicators of antidepressant response. This prospective cohort study recruited 115 MDD patients and 43 healthy controls. Psychological assessments, electroencephalogram and event-related potential recordings were performed at baseline and 1 week after venlafaxine treatment, with a 12-week follow-up. Independent sample t-tests and Mann-Whitney U tests analyzed group differences, while linear mixed-effects models and logistic regression evaluated associations between DLPFC activity/FC changes and clinical outcomes. The MDD group showed significantly reduced right DLPFC current density during the N2 time window evoked by oddball stimuli (p = 0.028). Higher right DLPFC current density during the N2 time window was correlated with lower HAMD-21 scores one week after treatment (p = 0.041, n = 46). Furthermore, an early increase predicted remission at week 12 (p = 0.005). Decreased beta-band FC between the left DLPFC and both side of posterior cingulate cortex (PCC) (left: p = 0.003; right: p = 0.004) were correlated with lower HAMD-21 scores (n = 71). Moreover, an early reduction in these connectivity measures (left: odds ratio (OR) = 0.534, 95% confidence interval (CI): 0.297-0.972, p = 0.036; right: OR = 0.533, 95% CI: 0.299-0.950, p = 0.033) predicted remission at week 12. Early changes in DLPFC activity and FC may serve as biomarkers for monitoring treatment efficacy and predicting clinical outcomes, informing personalized treatment approaches.
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