RNEL Team Publishes “A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations”
October 6, 2023
Lee Fisher, PhD, Robert Gaunt, PhD, and Elvira Pirondini, PhD, UPMC/Pitt Department of Physical Medicine and Rehabilitation and Pitt Rehab Neural Engineering Labs (RNEL) – along with colleagues from the University of Michigan – published “A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations” in The Journal of Physiology.
Seventy years ago, Hodgkin and Huxley published the first mathematical model to describe action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously, with studies spanning from basic neuroscience to clinical applications for neuromodulation.
Computer models of neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation. Spinal cord stimulation is a therapy widely used to treat chronic pain, with rapidly expanding indications, such as restoring motor function.
In general, simulations have contributed dramatically to improve lead designs, stimulation configurations, waveform parameters, and programming procedures and provided insight into potential mechanisms of action of electrical stimulation. Although the implementation of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and, ultimately, for clinical efficacy.
With this aim, the research team performed a systematic literature review and a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization and the use of medical imaging to capture realistic anatomy.
The team’s review showed that increased model complexity and personalization improved both mechanistic and translational studies. More specifically, the use of medical imaging enabled the development of patient-specific models that can help to transform clinical practice in spinal cord stimulation.
Finally, the team combined results to provide clear guidelines for standardization and expansion of computational models for spinal cord stimulation.
Learn more.
All study contributors
Lucy Liang
Arianna Damiani
Matteo Del Brocco
Evan R. Rogers
Maria K. Jantz
Lee E. Fisher
Robert A. Gaunt
Marco Capogrosso
Scott F. Lempka
Elvira Pirondini
