ArticleCerebral cortex (New York, N.Y. : 1991)2019
Changes in Functional Connectivity Predict Outcome of Repetitive Transcranial Magnetic Stimulation Treatment of Major Depressive Disorder.
Article in Cerebral cortex (New York, N.Y. : 1991), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine learning in the prediction of treatment response for emotional disorders: A systematic review and meta-analysis.Clinical psychology review · 2025Pooled it
- Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis.Translational psychiatry · 2022Pooled it
- Electroconvulsive Therapy (ECT) and Repetitive Transcranial Magnetic Stimulation (rTMS), Benefits and Adverse Effects in Patients with Depression: A Scoping Review.Journal of clinical medicine · 2026Review
- Differential neural responses to rhythmic and patterned TMS protocols: Insights from EEG spectral analysis.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Article
- Changes in Neural Activities and Neuroplasticity Related to Nonpharmacological Interventions for Major Depressive Disorder: A Systematic Literature Review.Biological psychiatry global open science · 2025Review
- EEG Biomarkers for a Precision-Medicine Approach to Noninvasive Brain Stimulation for Major Depressive Disorder.Research square · 2025Article
- Predicting Depression Therapy Outcomes Using EEG-Derived Amplitude Polar Maps.Brain sciences · 2025Article
- Cortical glutamate, Glx, and total N-acetylaspartate: potential biomarkers of repetitive transcranial magnetic stimulation treatment response and outcomes in major depression.Translational psychiatry · 2024Article
- Rumination symptoms in treatment-resistant major depressive disorder, and outcomes of repetitive Transcranial Magnetic Stimulation (rTMS) treatment.Translational psychiatry · 2023Article
- A convolutional recurrent neural network with attention for response prediction to repetitive transcranial magnetic stimulation in major depressive disorder.Scientific reports · 2023Article
- An effective brain connectivity technique to predict repetitive transcranial magnetic stimulation outcome for major depressive disorder patients using EEG signals.Physical and engineering sciences in medicine · 2023Article
- Functional Activity in the Effect of Transcranial Magnetic Stimulation Therapy for Patients with Depression: A Meta-Analysis.Journal of personalized medicine · 2023Review
- The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research.Biomedicines · 2022Review
- A systematic data-driven approach to analyze sensor-level EEG connectivity: Identifying robust phase-synchronized network components using surface Laplacian with spectral-spatial PCA.Psychophysiology · 2022Article
- Intersubject correlation analysis reveals the plasticity of cerebral functional connectivity in the long-term use of social media.Human brain mapping · 2022Article
- Effectiveness of Repetitive Transcranial Magnetic Stimulation in the Treatment of Bipolar Disorder in Comparison to the Treatment of Unipolar Depression in a Naturalistic Setting.Brain sciences · 2022Article
- Effects of HF-rTMS over the left and right DLPFC on proactive and reactive cognitive control.Social cognitive and affective neuroscience · 2022Article
- Cold Cognition as Predictor of Treatment Response to rTMS; A Retrospective Study on Patients With Unipolar and Bipolar Depression.Frontiers in human neuroscience · 2022Article
- Predicting the Effects of Repetitive Transcranial Magnetic Stimulation on Cognitive Functions in Patients With Alzheimer's Disease by Automated EEG Analysis.Frontiers in cellular neuroscience · 2022Article
- Precise Modulation Strategies for Transcranial Magnetic Stimulation: Advances and Future Directions.Neuroscience bulletin · 2021Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Repetitive transcranial magnetic stimulation (rTMS) treatment of major depressive disorder (MDD) is associated with changes in brain functional connectivity (FC). These changes may be related to the mechanism of action of rTMS and explain the variability in clinical outcome. We examined changes in electroencephalographic FC during the first rTMS treatment in 109 subjects treated with 10 Hz stimulation to left dorsolateral prefrontal cortex. All subjects subsequently received 30 treatments and clinical response was defined as ≥40% improvement in the inventory of depressive symptomatology-30 SR score at treatment 30. Connectivity change was assessed with coherence, envelope correlation, and a novel measure, alpha spectral correlation (αSC). Machine learning was used to develop predictive models of outcome for each connectivity measure, which were compared with prediction based upon early clinical improvement. Significant connectivity changes were associated with clinical outcome (P < 0.001). Machine learning models based on αSC yielded the most accurate prediction (area under the curve, AUC = 0.83), and performance improved when combined with early clinical improvement measures (AUC = 0.91). The initial rTMS treatment session produced robust changes in FC, which were significant predictors of clinical outcome of a full course of treatment for MDD.
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Registered trials
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.