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NEST simulator is part of a larger network of projects that focus on simulation, analysis, visualization, or modeling of biologically realistic neural networks.
Here you can find further information about some of these projects.
NESTML allows you to modify and create models for NEST in a simplified format.
It is a domain-specific language that supports the specification of neuron and synapse models in a precise and concise syntax, based on the syntax of Python. Model equations can either be given as a simple string of mathematical notation or as an algorithm written in the built-in procedural language. The equations are analyzed by the associated toolchain, written in Python, to compute an exact solution if possible or use an appropriate numeric solver otherwise.
NEST extension module¶
The NEST extension module allows you to extend the functionality of NEST without messing with the source code of NEST itself. It makes sharing custom extensions with other researchers easy.
NEST Desktop is a web-based GUI application for the NEST Simulator. The app enables the rapid construction, parametrization, and instrumentation of neuronal network models.
PyNN is a simulator-independent language for building neuronal network models.
In other words, you can write the code for a model once, using the PyNN API and the Python programming language, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST, and Brian) and on a number of neuromorphic hardware systems.
Elephant (Electrophysiology Analysis Toolkit) is an open-source, community-centered library for the analysis of electrophysiological data in the Python programming language.
Arbor is a high-performance library for computational neuroscience simulations with multi-compartment, morphologically-detailed cells, from single cell models to very large networks
SpiNNaker and BrainScaleS are neuromorphic computing systems, which enable energy-efficient, large-scale neuronal network simulations with simplified spiking neuron models. The BrainScaleS system is based on physical (analog) emulations of neuron models and offers highly accelerated operation (\(10^4\) x real time). The SpiNNaker system is based on a digital many-core architecture and provides real-time operation.