ArticleScientific reports2019
Resting state functional connectivity predictors of treatment response to electroconvulsive therapy in depression.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 5 of them syntheses that pooled it.
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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.
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Who cites it
36 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Subcallosal cingulate functional connectivity in depression: a systematic review of brain stimulation-induced changes and pretreatment connectivity predictors.Translational psychiatry · 2026Pooled it
- Ultrabrief pulse electroconvulsive therapy for depression: a systematic review and meta-analysis.Molecular psychiatry · 2026Pooled it
- Predicting the treatment outcomes of major depressive disorder interventions with baseline resting-state functional connectivity: a meta-analysis.BMC psychiatry · 2025Pooled it
- Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis.Molecular psychiatry · 2025Pooled it
- Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis.Translational psychiatry · 2021Pooled it
- Neural and behavioral markers of inhibitory control predict symptom improvement during internet-delivered cognitive behavioral therapy for depression.Translational psychiatry · 2024Trial
- Rostral anterior cingulate network effective connectivity in depressed adolescents and associations with treatment response in a randomized controlled trial.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Trial
- Prefrontal resting-state connectivity and antidepressant response: no associations in the ELECT-TDCS trial.European archives of psychiatry and clinical neuroscience · 2021Trial
- Computational modeling of prefrontal-amygdala circuits links functional connectivity alterations to circuit-level mechanisms in major depression.Journal of computational neuroscience · 2026Article
- Effects of electroconvulsive therapy on cerebellar-cerebral functional connectivity in patients with treatment-resistant depression and their correlations with gene expression profiles.Psychiatry and clinical neurosciences · 2026Article
- Network localization of brain structural and functional alterations induced by electroconvulsive therapy for depression.Translational psychiatry · 2026Article
- Virtual Neuronavigation for Parcel-guided TMS.medRxiv : the preprint server for health sciences · 2025Article
- Exploring the capabilities of repetitive transcranial magnetic stimulation in major depressive disorder: Dynamic causal modeling of the neural network.Translational psychiatry · 2025Article
- Towards closed-loop precision psychiatry: Integrating MRI biomarkers for individualized care of major depressive disorder.Psychoradiology · 2025Review
- Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Study protocol TransTAM: Transdiagnostic research into emotional disorders and cognitive-behavioral therapy of the adaptive mind.BMC psychiatry · 2024Article
- Functional connectivity changes between amygdala and prefrontal cortex after ECT are associated with improvement in distinct depressive symptoms.European archives of psychiatry and clinical neuroscience · 2023Article
- Functional connectomics in depression: insights into therapies.Trends in cognitive sciences · 2023Review
- Sex differences of brain cortical structure in major depressive disorder.Psychoradiology · 2023Article
- Predictive signature of static and dynamic functional connectivity for ECT clinical outcomes.Frontiers in pharmacology · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
There is increasing focus on use of resting-state functional connectivity (RSFC) analyses to subtype depression and to predict treatment response. To date, identification of RSFC patterns associated with response to electroconvulsive therapy (ECT) remain limited, and focused on interactions between dorsal prefrontal and regions of the limbic or default-mode networks. Deficits in visual processing are reported in depression, however, RSFC with or within the visual network have not been explored in recent models of depression. Here, we support prior studies showing in a sample of 18 patients with depression that connectivity between dorsal prefrontal and regions of the limbic and default-mode networks serves as a significant predictor. In addition, however, we demonstrate that including visual connectivity measures greatly increases predictive power of the RSFC algorithm (>80% accuracy of remission). These exploratory results encourage further investigation into visual dysfunction in depression, and use of RSFC algorithms incorporating the visual network in prediction of response to both ECT and transcranial magnetic stimulation (TMS), offering a new framework for the development of RSFC-guided TMS interventions in depression.
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