Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks

Abstract

Neuronal activity is the result of both the electrophysiology and chemophysiology. A neuron can be well-represented for the purposes of electrophysiological simulation as a tree composed of connected cylinders. This representation is also apt for 1D simulations of their chemophysiology, provided the spatial scale is larger than the diameter of the cylinders and there is radial symmetry. Higher dimensional simulation is necessary to accurately capture the dynamics when these criteria are not met, such as with wave curvature, spines, or diffusion near the soma. We have developed a solution to enable efficient finite volume method simulation of reaction-diffusion kinetics in intracellular 3D regions in neuron and network models and provide an implementation within the NEURON simulator. An accelerated version of the CTNG 3D reconstruction algorithm transforms morphologies suitable for ion-channel based simulations into consistent 3D voxelized regions. Kinetics are then solved using a parallel algorithm based on Douglas-Gunn that handles the irregular 3D geometry of a neuron; these kinetics are coupled to NEURON's 1D mechanisms for ion channels, synapses, pumps, and so forth. The 3D domain may cover the entire cell or selected regions of interest. Simulations with dendritic spines and of the soma reveal details of dynamics that would be missed in a pure 1D simulation. We describe and validate the methods and discuss their performance.

Modernizing the NEURON Simulator for Sustainability, Portability, and Performance

“…NEURON does not use prefetching with intracellular simulation, as in practice we observed no comparable speedup. Finally, to accelerate both the initialization and simulation of models with reaction-diffusion dynamics to be studied in full 3D, we now construct voxel based representations of each of its constituent convex components (frusta and their joins) on a common mesh and merge them together (McDougal et al, 2022 ), instead of constructing a voxel-based representation of an entire neuron morphology at once.…”

“…An Extracellular region type (Newton et al, 2018) provides support for studying cellular interactions through changes in the extracellular space (e.g., in ischemic stroke or between neurons and astrocytes), simulated using a macroscopic volume averaging approach. Three-dimensional intracellular simulation (McDougal et al, 2022) allows study of microdomains and the sensitivity to precise positioning of synapses. Importantly, each of these extensions was designed to fit within the broader RxD context; reaction and diffusion rules are specified and interpreted in the same way for 1D and 3D simulation and for intra-and extracellular simulation.…”

Tutorial: using NEURON for neuromechanical simulations

“…In this paper, we describe a method for using the NEURON platform to incorporate biomechanics with the advantage of utilizing a single, cohesive application that does not require advanced software installation. NEURON is a widely used neural simulation platform that has enjoyed continuous development and active support for over three decades (Hines and Carnevale, 1997;Carnevale and Hines, 2006;Hines et al, 2009;Lytton et al, 2016;Awile et al, 2022;McDougal et al, 2022). NEURON is readily extensible and has a large and active user community.…”

Reaction-diffusion models in weighted and directed connectomes

“…On the macro and meso level, the application is suitable for neuronal networks, connectomes and local circuits. Recently, a paper on 3D reaction-diffusion models of neurons and networks was published [ 12 ]. At the micro level, reaction-diffusion systems are applied to the modeling of cellular and subcellular processes.…”