NNMT: Mean-Field Based Analysis Tools for Neuronal Network Models

Frontiers in Neuroinformatics

Moritz Helias¹  Hannah Bos²  Johanna Senk²  Alexander van Meegen³  Simon Essink⁴  Moritz Layer⁴ 

[1] Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany;Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany;Institute of Zoology, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany;RWTH Aachen University, Aachen, Germany;

关键词: mean-field theory;    (spiking) neuronal network;    integrate-and-fire neuron;    open-source software;    parameter space exploration;    (hybrid) modeling;   

DOI  :  10.3389/fninf.2022.835657

来源: DOAJ

【 摘 要 】

Mean-field theory of neuronal networks has led to numerous advances in our analytical and intuitive understanding of their dynamics during the past decades. In order to make mean-field based analysis tools more accessible, we implemented an extensible, easy-to-use open-source Python toolbox that collects a variety of mean-field methods for the leaky integrate-and-fire neuron model. The Neuronal Network Mean-field Toolbox (NNMT) in its current state allows for estimating properties of large neuronal networks, such as firing rates, power spectra, and dynamical stability in mean-field and linear response approximation, without running simulations. In this article, we describe how the toolbox is implemented, show how it is used to reproduce results of previous studies, and discuss different use-cases, such as parameter space explorations, or mapping different network models. Although the initial version of the toolbox focuses on methods for leaky integrate-and-fire neurons, its structure is designed to be open and extensible. It aims to provide a platform for collecting analytical methods for neuronal network model analysis, such that the neuroscientific community can take maximal advantage of them.

【 授权许可】

Unknown