Institute for Theoretical Computer Science, Graz University of Technology Graz, Austria.
Front Neuroinform. 2014 Aug 14;8:70. doi: 10.3389/fninf.2014.00070. eCollection 2014.
NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies.
NEVESIM 是一个用于事件驱动的 Spike 神经元网络模拟的软件包,其快速仿真核心采用 C++编写,脚本用户界面采用 Python 编程语言。它支持具有不同类型神经元和突触的异质网络的模拟,并且可以通过用户轻松扩展新的神经元和突触类型。为了实现异质网络和可扩展性,NEVESIM 旨在将网络级神经元之间通信事件( Spike )的仿真逻辑与单个神经元的内部动力学的实现分离。在本文中,我们将介绍 NEVESIM 的仿真框架、其概念和特点,以及在有效实现框架的概念和功能时所采用的面向对象设计方法和仿真策略的一些方面。我们还将概述 Python 用户界面、其基本命令和结构,并讨论将 NEVESIM 与 Python 集成的好处。模拟器的一个有价值的功能是能够从最近开发的神经采样理论框架中准确而有效地模拟随机 Spike 神经元网络。此功能是在基本 NEVESIM 框架之上实现的扩展功能。总的来说,NEVESIM 框架的目的是提供一个基础,以便进一步扩展,支持模拟各种包含不同神经元和突触类型的神经网络模型,这些模型也可以使用不同的仿真策略。