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Cingulate dynamics track depression recovery with deep brain stimulation

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Listed:
  • Sankaraleengam Alagapan

    (Georgia Institute of Technology)

  • Ki Sueng Choi

    (Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai)

  • Stephen Heisig

    (Icahn School of Medicine at Mount Sinai)

  • Patricio Riva-Posse

    (Emory University School of Medicine)

  • Andrea Crowell

    (Emory University School of Medicine)

  • Vineet Tiruvadi

    (Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University
    Emory University School of Medicine)

  • Mosadoluwa Obatusin

    (Icahn School of Medicine at Mount Sinai)

  • Ashan Veerakumar

    (Schulich School of Medicine and Dentistry at Western University)

  • Allison C. Waters

    (Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai)

  • Robert E. Gross

    (Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University
    Emory University School of Medicine
    Emory University School of Medicine)

  • Sinead Quinn

    (Emory University School of Medicine)

  • Lydia Denison

    (Emory University School of Medicine)

  • Matthew O’Shaughnessy

    (Georgia Institute of Technology)

  • Marissa Connor

    (Georgia Institute of Technology)

  • Gregory Canal

    (Georgia Institute of Technology)

  • Jungho Cha

    (Icahn School of Medicine at Mount Sinai)

  • Rachel Hershenberg

    (Emory University School of Medicine)

  • Tanya Nauvel

    (Icahn School of Medicine at Mount Sinai)

  • Faical Isbaine

    (Emory University School of Medicine)

  • Muhammad Furqan Afzal

    (Icahn School of Medicine at Mount Sinai)

  • Martijn Figee

    (Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai)

  • Brian H. Kopell

    (Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai)

  • Robert Butera

    (Georgia Institute of Technology
    Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University)

  • Helen S. Mayberg

    (Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai
    Icahn School of Medicine at Mount Sinai)

  • Christopher J. Rozell

    (Georgia Institute of Technology)

Abstract

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD)1. However, achieving stable recovery is unpredictable2, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting3. We currently lack objective brain-based biomarkers to guide clinical decisions by distinguishing natural transient mood fluctuations from situations requiring intervention. To address this gap, we used a new device enabling electrophysiology recording to deliver SCC DBS to ten TRD participants (ClinicalTrials.gov identifier NCT01984710). At the study endpoint of 24 weeks, 90% of participants demonstrated robust clinical response, and 70% achieved remission. Using SCC local field potentials available from six participants, we deployed an explainable artificial intelligence approach to identify SCC local field potential changes indicating the patient’s current clinical state. This biomarker is distinct from transient stimulation effects, sensitive to therapeutic adjustments and accurate at capturing individual recovery states. Variable recovery trajectories are predicted by the degree of preoperative damage to the structural integrity and functional connectivity within the targeted white matter treatment network, and are matched by objective facial expression changes detected using data-driven video analysis. Our results demonstrate the utility of objective biomarkers in the management of personalized SCC DBS and provide new insight into the relationship between multifaceted (functional, anatomical and behavioural) features of TRD pathology, motivating further research into causes of variability in depression treatment.

Suggested Citation

  • Sankaraleengam Alagapan & Ki Sueng Choi & Stephen Heisig & Patricio Riva-Posse & Andrea Crowell & Vineet Tiruvadi & Mosadoluwa Obatusin & Ashan Veerakumar & Allison C. Waters & Robert E. Gross & Sinea, 2023. "Cingulate dynamics track depression recovery with deep brain stimulation," Nature, Nature, vol. 622(7981), pages 130-138, October.
  • Handle: RePEc:nat:nature:v:622:y:2023:i:7981:d:10.1038_s41586-023-06541-3
    DOI: 10.1038/s41586-023-06541-3
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