The impact of internodal segmentation in biophysical nerve fiber models
Implementation of double cable models to simulate the behavior of myelinated peripheral nerve fibers requires defining a segmentation of the internode between successive nodes of Ranvier. The number of internodal segments is a model parameter that is not well agreed on, with values in the literature ranging from 1 to more than 500. Moreover, a lot of studies also lack a sensitivity study or a rationale behind the implementation used. In a model of a myelinated nerve fiber developed in our group, the segmentation scheme (i.e., the number of segments and their individual morphology) strongly influenced model outcomes such as action potential shape and velocity, stimulation threshold and absolute refractory period. In the present study these influences were investigated systematically in homogeneous neurons with different diameters. Uniformly segmented internodes were found to require several hundreds of segments (and associated computational power) to reach model outcomes differing by less than 1% from the asymptotic value. In fact, in the majority of segmentation schemes the main determinant is not the number of segments, but the length ? of the internodal segments directly adjacent to the nodes of Ranvier. If ? is larger than approximately 10 ?m, model outcomes for the tested fibers are almost independent of the total number of segments. Furthermore, ? can be optimized to enable models using just three segments per internode, to reach physiologically relevant model outcomes with limited computational resources. However, to study anatomical or physiological details of the internode itself, an appropriately detailed segmentation scheme is crucial.
internodal segmentation double cable peripheral nerve fiber computational model myelinated axon