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An electroencephalographic signature predicts antidepressant response in major depression. 2020
Wei Wu, and
Yu Zhang, and
Jing Jiang, and
Molly V Lucas, and
Gregory A Fonzo, and
Camarin E Rolle, and
Crystal Cooper, and
Cherise Chin-Fatt, and
Noralie Krepel, and
Carena A Cornelssen, and
Rachael Wright, and
Russell T Toll, and
Hersh M Trivedi, and
Karen Monuszko, and
Trevor L Caudle, and
Kamron Sarhadi, and
Manish K Jha, and
Joseph M Trombello, and
Thilo Deckersbach, and
Phil Adams, and
Patrick J McGrath, and
Myrna M Weissman, and
Maurizio Fava, and
Diego A Pizzagalli, and
Martijn Arns, and
Madhukar H Trivedi, and
Amit Etkin
School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China.
Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part because the clinical diagnosis of major depression encompasses biologically heterogeneous conditions. Here, we sought to identify a neurobiological signature of response to antidepressant treatment as compared to placebo. We designed a latent-space machine-learning algorithm tailored for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-coupled, placebo-controlled antidepressant study (n = 309). Symptom improvement was robustly predicted in a manner both specific for the antidepressant sertraline (versus placebo) and generalizable across different study sites and EEG equipment. This sertraline-predictive EEG signature generalized to two depression samples, wherein it reflected general antidepressant medication responsivity and related differentially to a repetitive transcranial magnetic stimulation treatment outcome. Furthermore, we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as measured by concurrent transcranial magnetic stimulation and EEG. Our findings advance the neurobiological understanding of antidepressant treatment through an EEG-tailored computational model and provide a clinical avenue for personalized treatment of depression.
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