Publication

Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation

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Last modified
  • 05/14/2025
Type of Material
Authors
    Mohammad S. E. Sendi, Emory UniversityAllison C. Waters, Icahn School of Medicine at Mount SinaiVineet Tiruvadi, Emory UniversityPatricio Riva Posse, Emory UniversityAndrea Crowell, Emory UniversityFaical Isbaine, Emory UniversityJohn T. Gale, Emory UniversityKi Sueng Choi, Emory UniversityRobert Gross, Emory UniversityHelen S Mayberg, Emory UniversityBabak Mahmoudi, Emory University
Language
  • English
Date
  • 2021-11-03
Publisher
  • SPRINGERNATURE
Publication Version
Copyright Statement
  • © The Author(s) 2021
License
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 11
Issue
  • 1
Start Page
  • 551
End Page
  • 551
Grant/Funding Information
  • Funding support was provided by the National Institutes of Health, Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative (UH3NS103550), Hope for Depression Research Foundation, and 1R01MH102238, 1R01MH106173. BM was additionally supported by UG3NS100559 and 1R01EB028350. Implanted devices used in this research were donated by Medtronic, Inc. (Minneapolis, MN).
Supplemental Material (URL)
Abstract
  • Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is a promising intervention for treatment-resistant depression (TRD). Despite the failure of a clinical trial, multiple case series have described encouraging results, especially with the introduction of improved surgical protocols. Recent evidence further suggests that tractography targeting and intraoperative exposure to stimulation enhances early antidepressant effects that further evolve with ongoing chronic DBS. Accelerating treatment gains is critical to the care of this at-risk population, and identification of intraoperative electrophysiological biomarkers of early antidepressant effects will help guide future treatment protocols. Eight patients underwent intraoperative electrophysiological recording when bilateral DBS leads were implanted in the SCC using a connectomic approach at the site previously shown to optimize 6-month treatment outcomes. A machine learning classification method was used to discriminate between intracranial local field potentials (LFPs) recorded at baseline (stimulation-naïve) and after the first exposure to SCC DBS during surgical procedures. Spectral inputs (theta, 4–8 Hz; alpha, 9–12 Hz; beta, 13–30 Hz) to the model were then evaluated for importance to classifier success and tested as predictors of the antidepressant response. A decline in depression scores by 45.6% was observed after 1 week and this early antidepressant response correlated with a decrease in SCC LFP beta power, which most contributed to classifier success. Intraoperative exposure to therapeutic stimulation may result in an acute decrease in symptoms of depression following SCC DBS surgery. The correlation of symptom improvement with an intraoperative reduction in SCC beta power suggests this electrophysiological finding as a biomarker for treatment optimization.
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Keywords
Research Categories
  • Biology, Neuroscience
  • Psychology, Clinical

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