Pain is transmitted from the periphery to the central nervous system by afferent C-fibers. These C-fibers are characterized by slow conduction velocity (velocity of the propagating action potential), activity dependent slowing (decreasing velocity of the action potential) and large proportions of conduction failures during high firing activity. However, these properties look different in chronic pain patients, where these fibres are characterized by spontaneous activity and the ability to fire at high frequencies. This thesis aims to study the molecular mechanisms affecting the properties of these neurons, allowing them to fire at high frequencies and exhibit spontaneous activity. This is studied by means of mathematical modeling and computational simulation. The goal is to develop models and methods for relating cellular physiology to molecular changes that can’t be measured in humans. The model can thereby complement existing experimental techniques. The work includes both the development of simulation technology, mainly methods for estimation of biological parameters, and the use of simulation to study the mechanistic relationship between molecular components and macroscopic properties of the fiber. The work is conducted in close collaboration with experimental groups where the data is gathered from physiological measurements in humans and animals. Early result indicate that biological parameters, such as time constants for the inactivation of ion channels, and macroscopic behavior such as unproportionally large change in axonal conduction velocity, can be estimated from experimental data using a simple mathematical model consisting of coupled exponential functions. We also found that the C-fibers can be grouped into classes based on where conduction failure occurs along the axon.
