Neural Excitability and Entrainment as Predictive Biomarkers for Personalized Closed-Loop Neurostimulation in Depression

POSTER

Abstract

Major depressive disorder (MDD) remains a leading cause of disability worldwide, with substantial variability in treatment response. We developed a closed-loop, EEG-synchronized rTMS framework that aligns stimulation with each individual’s intrinsic alpha oscillations to enhance network-level synchrony and treatment predictability. In a randomized, double-blind, active comparator-controlled clinical trial, personalized phase-synchronized rTMS produced more predictable clinical outcomes in treatment-resistant depression compared to unsynchronized stimulation. We identified two EEG-derived neurophysiological biomarkers—progressive decreases in cortical excitability and increases in entrainment—that predicted clinical improvement following synchronized treatment. In an accelerated protocol combining EEG-synchronized rTMS with cognitive behavioral therapy in patients with recent suicide attempts, all participants achieved clinical response and remission sustained at one month. Biomarker trajectories replicated the entrainment-excitability pattern, with the optimal stimulation phase aligning across emotion regulation and cognitive flexibility networks, reinforcing synchrony as a robust and predictive mechanism for therapeutic modulation.

*This work was supported by a Vannevar Bush Faculty Fellowship from the US Department of Defense (N00014-20-1-2027), a Hughes Holden Foundation Fellowship, and the Defense Advanced Research Projects Agency (HR00112320032).

Publication: Sun, X., Doose, J., Faller, J., McIntosh, J. R., Saber, G. T., Huffman, S., ... & Sajda, P. (2023). Biomarkers predict the efficacy of closed-loop rTMS treatment for refractory depression. Research Square, rs-3.

Presenters

  • Xiaoxiao Sun

    • Columbia University/Penn State University
    • The Pennsylvania State University

Authors

  • Xiaoxiao Sun

    • Columbia University/Penn State University
    • The Pennsylvania State University
  • Jayce Doose

    • Medical University of South Carolina
  • Josef Faller

    • Columbia University
  • Ruxue Gong

    • Medical University of South Carolina
  • James McIntosh

    • Columbia University Irving Medical Center
  • Chichi Chang

    • Columbia University
  • Hengda He

    • Columbia University Irving Medical Center
  • Sarah Huffman

    • Medical University of South Carolina
  • Corbin Ping

    • Medical University of South Carolina
  • Sara Hashrmpour

    • Medical University of South Carolina
  • Abby Williams

    • Medical University of South Carolina
  • Gavin Doyle

    • Medical University of South Carolina
  • Linbi Hong

    • Columbia University
  • Christopher Sege

    • Medical University of South Carolina
  • Golbarg T Saber

    • Medical University of South Carolina
  • Spiro Pantazatos

    • Columbia University Irving Medical Center
    • Medical University of South Carolina
  • Danielle Taylor

    • Wayne State University
  • Noam Schneck

    • Columbia University Irving Medical Center
  • Han Yuan

    • The Ohio State University
    • University of Oklahoma
  • Robin I Goldman

    • University of Wisconsin-Madison
  • Truman R Brown

    • Medical University of South Carolina
  • Mark S George

    • Medical University of South Carolina
  • Lisa M McTeague

    • Medical University of South Carolina
  • Paul Sajda

    • Columbia University