ArticleJournal of affective disorders2024
Individual deviations from normative electroencephalographic connectivity predict antidepressant response.
Article in Journal of affective disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 15 citations in OpenAlex.
- Whole-brain mapping of TMS-induced discomfort with large-scale concurrent TMS-fMRI.bioRxiv : the preprint server for biology · 2026Article
- Generalizable structure-function covariation predictive of antidepressant response revealed by target-oriented multimodal fusion.Nature. Mental health · 2026Article
- Multiband EEG signatures decoded using machine learning for predicting rTMS treatment response in MDD.Journal of affective disorders · 2025Article
- Exploring electroencephalographic chronic pain biomarkers: a mega-analysis.EBioMedicine · 2025Article
- Early Brain Functional Connectivity Changes Induced by Antidepressants and Placebo.bioRxiv : the preprint server for biology · 2025Article
- Harnessing electroencephalography connectomes for cognitive and clinical neuroscience.Nature biomedical engineering · 2025Review
- Common neuroanatomical differential factors underlying heterogeneous gray matter volume variations in five common psychiatric disorders.Communications biology · 2025Article
- Individualized resting-state functional connectivity abnormalities unveil two major depressive disorder subtypes with contrasting abnormal patterns of abnormality.Translational psychiatry · 2025Article
- Optimizing Antidepressant Efficacy: Generalizable Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.medRxiv : the preprint server for health sciences · 2024Article
- COVID-19 lockdown effects on adolescent brain structure suggest accelerated maturation that is more pronounced in females than in males.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Abnormalities in Electroencephalographic Microstates in Patients with Late-Life Depression.Neuropsychiatric disease and treatment · 2024Article
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Authors and funding
9 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundAntidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo, partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment. Here we develop a novel normative modeling framework to quantify individual deviations in psychopathological dimensions that offers a promising avenue for the personalized treatment for psychiatric disorders.
methodsWe built a normative model with resting-state electroencephalography (EEG) connectivity data from healthy controls of three independent cohorts. We characterized the individual deviation of MDD patients from the healthy norms, based on which we trained sparse predictive models for treatment responses of MDD patients (102 sertraline-medicated and 119 placebo-medicated). Hamilton depression rating scale (HAMD-17) was assessed at both baseline and after the eight-week antidepressant treatment.
resultsWe successfully predicted treatment outcomes for patients receiving sertraline (r = 0.43, p < 0.001) and placebo (r = 0.33, p < 0.001). We also showed that the normative modeling framework successfully distinguished subclinical and diagnostic variabilities among subjects. From the predictive models, we identified key connectivity signatures in resting-state EEG for antidepressant treatment, suggesting differences in neural circuit involvement between sertraline and placebo responses.
conclusionsOur findings and highly generalizable framework advance the neurobiological understanding in the potential pathways of antidepressant responses, enabling more targeted and effective personalized MDD treatment.
trial registrationEstablishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT#01407094.
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