NeuVision: A novel simulation environment to model spontaneous and stimulus-evoked activity of large-scale neuronal networks

NeuVision is a novel simulation environment tailored to simulate the dynamics of large-scale neuronal networks. It has been developed using .NET programming languages and allows the user to implement networks of neurons made up of thousands of synaptically connected elements. This simulator (available at the website http://www.neuvisionsimulator.org) offers the user several visualization tools. At the same time, a rich repertoire of data analysis algorithms to process both spontaneous and stimulus-evoked activity has been introduced to create a complete package for the generation and analysis of synthetic data. In this paper, we provide a detailed description of the simulation environment, its features, and an estimation of the performance. In addition, we present some results related to the simulation of highly connected large-scale neuronal networks focusing on the stimulus-evoked activity and the propagation of network activity. We found that the simulated results qualitatively fit experimental recordings obtained by recently developed high density multi-electrode transducers for in vitro applications. In this context, NeuVision can be utilized along with multi-site recordings to understand neural networks dynamics.