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NEST is a simulation software for spiking neural network models, including large-scale neuronal networks. NEST was initially developed by Markus Diesmann and Marc-Oliver Gewaltig and is now developed and maintained by the NEST Initiative.
Brian is aimed at researchers developing models based on networks of spiking neurons. The general design is aimed at maximising flexibility, simplicity and users' development time. [ 2 ] Users specify neuron models by giving their differential equations in standard mathematical form as strings , create groups of neurons and connect them via ...
EDLUT (Event-Driven LookUp Table) is a computer application for simulating networks of spiking neurons. It was developed in the University of Granada and source code was released under GNU GPL version 3. EDLUT uses event-driven simulation scheme and lookup tables to efficiently simulate medium or large spiking neural networks. [1]
While the notion of an artificial spiking neural network became very popular only during the first quarter of the twenty-first century, [8] [9] [10] there are a number of studies between 1980 and 1995 that supported the concept and in which the first models of this type of artificial neural networks appeared to simulate non-algorithmic ...
NEST - open-source software for spiking neural network models. NetLogo - an open-source multi-agent simulation software. ns-3 - an open-source network simulator. OpenFOAM - open-source software used for computational fluid dynamics (or CFD). OpenModelica - an open source modeling environment based on Modelica the open standard for modeling ...
Biological neuron models, also known as spiking neuron models, [1] are mathematical descriptions of the conduction of electrical signals in neurons. Neurons (or nerve cells) are electrically excitable cells within the nervous system, able to fire electric signals, called action potentials, across a neural network.
3D Vizualization of the Galves–Löcherbach model simulating the spiking of 4000 neurons (4 layers with one population of inhibitory neurons and one population of excitatory neurons each) in 180 time intervals. The Galves–Löcherbach model (or GL model) is a mathematical model for a network of neurons with intrinsic stochasticity. [1] [2]
Emergent, neural simulation software. GENESIS, a general neural simulation system. NEST is a simulator for spiking neural network models that focuses on the dynamics, size and structure of neural systems rather than on the exact morphology of individual neurons.