MiV-Simulator: A computational framework to simulate exact scale in-vitro neuronal networks

In vitro studies of neuronal networks have played a pivotal role in expanding our understanding of neural dynamics, leading to considerable developments in the field of neuroscience. However, in vitro experiments can be demanding in terms of resources and technical skills. To complement experiments, aid their design, and overall accelerate investigation, we present an open-source computational framework for the simulation and analysis of these systems. Our high performance computing solver, based on the NEURON and CoreNEURON simulators, entails detailed biophysical models of neurons and neuronal networks, and allows to resolve the dynamics of millions of neurons.

Importantly, our framework supports the simulation of local field potentials (LFP), optogenetic stimulation, and other common paradigms of experimental neuroscience. The framework's ability to simulate signals at different spatial scales allows not only to closely mimic in vitro experiments, but also the concurrent observation and analysis of all components of the neural dynamical system. We validate our approach by comparing firing rate distributions of simulated networks with those obtained from multi-electrode array recordings across a variety of neuron cultures and demonstrate that key features can be recapitulated in silico.