TOWARDS PAIN CONTROL BY MODELING THE INTERACTIONS IN A MAMMALIAN NERVE FIBER

Objectives. Electrical stimulation of nerve fibers is used to treat various diseases. Despite efforts to model the effects of stimulation, its underlying mechanisms remain unclear. This is because current mechanistic models just quantify the effects that the electrical field produces near the fiber and do not capture interactions between stimulus-initiated action potentials (APs) and underlying physiological activity initiated APs. Physiological activity induced APs, noxious or innocuous, travel along the fibers and may, for example, collide with a stimulus AP, and thus may never be relayed to the brain. In this study, we aim to quantify the effects of stimulation frequency on these interactions. Methods. We construct three computational models of a nerve fiber of varying degrees of complexity (probabilistic, reduced and mechanistic) each receiving two inputs: the underlying physiological activity at one end of the fiber, and the external stimulus applied to the middle of the fiber. We then define conduction reliability, C, as the percentage of physiological APs that make it to the other end of the nerve fiber. We apply the two inputs to the fiber at various frequencies and analyze conduction reliability. Results. We find that at input frequencies (< 50Hz), both reduced and mechanistic models generate similar relay maps, and interactions are mainly due to collisions and inter-signal loss of excitability (stimulus AP induces refractory period and thus fiber does not respond to a physiological input and vice-versa). Higher frequency (>