Frontiers in Neuroscience (Dec 2021)

Practical Closed-Loop Strategies for Deep Brain Stimulation: Lessons From Chronic Pain

  • Jordan Prosky,
  • Jordan Prosky,
  • Jackson Cagle,
  • Kristin K. Sellers,
  • Kristin K. Sellers,
  • Ro’ee Gilron,
  • Cora de Hemptinne,
  • Cora de Hemptinne,
  • Ashlyn Schmitgen,
  • Ashlyn Schmitgen,
  • Philip A. Starr,
  • Philip A. Starr,
  • Philip A. Starr,
  • Edward F. Chang,
  • Edward F. Chang,
  • Edward F. Chang,
  • Prasad Shirvalkar,
  • Prasad Shirvalkar,
  • Prasad Shirvalkar,
  • Prasad Shirvalkar

DOI
https://doi.org/10.3389/fnins.2021.762097
Journal volume & issue
Vol. 15

Abstract

Read online

Deep brain stimulation (DBS) is a plausible therapy for various neuropsychiatric disorders, though continuous tonic stimulation without regard to underlying physiology (open-loop) has had variable success. Recently available DBS devices can sense neural signals which, in turn, can be used to control stimulation in a closed-loop mode. Closed-loop DBS strategies may mitigate many drawbacks of open-loop stimulation and provide more personalized therapy. These devices contain many adjustable parameters that control how the closed-loop system operates, which need to be optimized using a combination of empirically and clinically informed decision making. We offer a practical guide for the implementation of a closed-loop DBS system, using examples from patients with chronic pain. Focusing on two research devices from Medtronic, the Activa PC+S and Summit RC+S, we provide pragmatic details on implementing closed- loop programming from a clinician’s perspective. Specifically, by combining our understanding of chronic pain with data-driven heuristics, we describe how to tune key parameters to handle feature selection, state thresholding, and stimulation artifacts. Finally, we discuss logistical and practical considerations that clinicians must be aware of when programming closed-loop devices.

Keywords