A novel mesh generator for the numerical simulation of multi-scale physics in neurons

Abstract

Computational Neuroscience deals with spatio-temporal scales which vary considerably.For example interactions at synaptic contact regions occur on the scale of nanometers and nanoseconds to milliseconds (micro-scale) whereas networks of neurons can measure up to millimeters and signals are processed on the scale of seconds (macro-scale). Whole-cell calcium dynamics models (meso-scale) mediate between the multiple spatio-temporal scales. Of crucial importance is the calcium propagation mediated by the highly complex endoplasmic reticulum network. Most models do not account for the intricate intracellular architecture of neurons and consequently cannot resolve the interplay between structure and calcium-mediated function. To incorporate the detailed cellular architecture in intracellular Calcium models, a novel mesh generation methodology has been developed to allow for the efficient generation of computational meshes of neurons with a three-dimensionally resolved endoplasmic reticulum. Mesh generation routines are compiled into a versatile and fully automated reconstruct-and-simulation toolbox for multi-scale physics to be utilized on high-performance or regular computing infrastructures. First-principle numerical simulations on the neuronal reconstructions reveal that intracellular Calcium dynamics are effected by morphological features of the neurons, for instance a change of endoplasmic reticulum diameter leads to a significant spatio-temporal variability of the calcium signal at the soma.