What is happening in Dorsal Root Ganglia? A computational analysis of cross-excitation phenomenon

Abstract

The phenomenon of cross-excitation - interaction between neurons of a dorsal root ganglion (DRG) in intact organism, presents a great challenge since its discovery. It can not be addressed to classical neuron-neuron interactions, as the mentioned neurons are believed to be physiologically isolated by glial sheaths from one another. In this work we test existing hypotheses which explain the phenomenon from both biophysical and statistical perspectives. Our conclusion is that neither each proposed mechanism alone, nor interactions of them can adequately describe cross-excitation in normal conditions. We wish to draw greater attention towards the phenomenon, as it seems to be an important part of normal sensory information processing. Author summaryCross-excitation is a phenomenon discovered in Dorsal Root Ganglia (DRG), whereby activation of one neuron leads to increased excitability of its neighbors. As the mechanism is still poorly understood, we present a computational modelling study, in which we tested primary hypotheses which were proposed to the phenomenon. The objectives were to test two main ideas - diffusion-mediated and gap-junction mediated cross-excitation in biologically plausible setups. Firstly, we evaluated a diffusion-based hypothesis, which states that diffusion of K+ ions is the main mechanism by which cross-excitation is mediated. Our results suggest miniscule effect of ion diffusion, even if tightly-packed space of DRG is considered. Secondly, we analyzed the gap-junction hypothesis, which relates the phenomenon to physical connection between neurons glial envelopes. According to the results, this solution would require for each neuron to have an enormous amount of immediate neighbors, in order to sustain high-enough prevalence of connection. Geometrical conclusion is that, no matter how tightly packed the DRG, it is impossible to create enough contacts. As a result, our findings suggest that none of the leading hypotheses explain the phenomenon.