Computational Modeling of Dorsal Root Ganglion Stimulation: Understanding Pain Suppression Mechanisms.

This study aims to advance our mechanistic understanding of electrical stimulation of dorsal root ganglia (DRG) for treating chronic pain. While DRG stimulation has shown moderate clinical success in managing certain types of chronic pain, the underlying neural mechanism remains inconclusive, hindering the further development of the technology to treat a broader range of chronic pain symptoms and benefit a larger patient population. In this study, we conducted computational simulations in the NEURON simulation environment to assess the neuromodulatory effect of DRG stimulation on action potential transmission in Aδ-fiber and C-fiber sensory afferents. Our simulation incorporates Markov-type state models to capture the subtle gating characteristics of voltage-gated sodium channel subtypes, especially NaV1.6, the anatomical distribution of which was revealed by our immunohistological staining on sparsely labeled afferents. Our simulation results indicate that DRG stimulation causes a significant increase in intra-axonal Na+ concentration and a reduction in K+ concentration, collectively disrupting the transaxonal ionic gradients. This disruption resulted in activitydependent conduction slowing, leading to the eventual conduction block in both Aδ- and C-fiber afferents. This research marks a crucial step forward in unraveling the intricate mechanisms underlying DRG stimulation, presenting a framework for the further development of innovative pain modulation strategies that target the DRG.