The Significance of Concentration-dependent Components in Computational Models of C-Fibers.

Abstract

Computational models of neurons are valuable tools that allow researchers to form and evaluate hypotheses and minimize high-cost animal work. We soon plan to use computational modeling to explore the response of different sensory fiber types to long duration external stimulation to try to selectively block nociceptive C-fibers. In this work, we modified an existing C-fiber-specific axon model to additionally include concentration-dependent conductance changes, the contribution of longitudinal current flow to changes in local concentrations, and longitudinal currents generated by concentration gradients along the axon. Then, we examined the impact of these additional elements on the modeled action potential properties, activity-dependent latency increases, and concentration changes due to external stimulation. We found that these additional model elements did not significantly affect the action potential properties or activity-dependent behavior, but they did have a significant impact on the modeled response to external long duration stimulation.Clinical Relevance- This presents a computational model that can be used to help investigate and develop electrical stimulation therapies for pathological pain.