ArticleHuman brain mapping2021
Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.
Article in Human brain mapping, 2021. 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, 19 citations in OpenAlex.
- The postictal systems window hypothesis of electroconvulsive therapy in major depression.Frontiers in psychiatry · 2026Article
- Age-Dependent Efficacy of Electroconvulsive Therapy in Depression: A Longitudinal Study of Symptom Trajectories and Treatment Predictions.Brain and behavior · 2025Article
- Prediction of individual treatment allocation between electroconvulsive therapy or ketamine using the Personalized Advantage Index.NPJ digital medicine · 2025Article
- Electroconvulsive Therapy (ECT) in Major Depression: Oldies but Goodies.Advances in experimental medicine and biology · 2024Review
- Individual Prediction of Optimal Treatment Allocation Between Electroconvulsive Therapy or Ketamine using the Personalized Advantage Index.Research square · 2023Article
- 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
- Article
- Investigation of Neurofunctional Changes Over the Course of Electroconvulsive Therapy.The international journal of neuropsychopharmacology · 2023Article
- Anterior default mode network and posterior insular connectivity is predictive of depressive symptom reduction following serial ketamine infusion.Psychological medicine · 2022Article
- Convergence, preliminary findings and future directions across the four human connectome projects investigating mood and anxiety disorders.NeuroImage · 2021Article
- Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.Human brain mapping · 2021Article
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 4 countries.
Funding
Abstract
Depression symptom heterogeneity limits the identifiability of treatment-response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing three latent symptom dimensions within the 17-item Hamilton Depression Rating Scale (HDRS) and use data-driven methods to relate multivariate patterns of patient clinical, demographic, and brain structural changes over electroconvulsive therapy (ECT) to dimensional changes in depressive symptoms. We included 110 ECT patients from Global ECT-MRI Research Collaboration (GEMRIC) sites who underwent structural MRI and HDRS assessments before and after treatment. Cross validated random forest regression models predicted change along symptom dimensions. HDRS symptoms clustered into dimensions of somatic disturbances (SoD), core mood and anhedonia (CMA), and insomnia. The coefficient of determination between predicted and actual changes were 22%, 39%, and 39% (all p < .01) for SoD, CMA, and insomnia, respectively. CMA and insomnia change were predicted more accurately than HDRS-6 and HDRS-17 changes (p < .05). Pretreatment symptoms, body-mass index, and age were important predictors. Important imaging predictors included the right transverse temporal gyrus and left frontal pole for the SoD dimension; right transverse temporal gyrus and right rostral middle frontal gyrus for the CMA dimension; and right superior parietal lobule and left accumbens for the insomnia dimension. Our findings support that recovery along depressive symptom dimensions is predicted more accurately than HDRS total scores and are related to unique and overlapping patterns of clinical and demographic data and volumetric changes in brain regions related to depression and near ECT electrodes.
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