NEST is a simulator for spiking neural network models from small-scale microcircuits to brain-scale networks of the order of 10^8 neurons and 10^12 synapses. The same code can be used on a large range of architectures from laptops and workstations to HPC clusters and supercomputer.

The development of NEST is driven by the demands of the neuroscientific community and carried out by the NEST Initiative, a collaboration between the members of different academic institutes.

NEST is free and open source software. To learn more about NEST and download the source code, visit the homepage of the NEST Initiative at

Main features:

  • Integrate-and-fire neuron models with current- and conductance-based synapses
  • Adaptive threshold integrate-and-fire neuron models (AdEx, MAT2)
  • Hodgkin-Huxley type neuron models with one compartment
  • Simple multi-compartmental neuron models
  • Static and plastic synapse models (STDP, short-term plasticity, neuromodulation)
  • Grid based spike interaction and interaction in continuous time
  • Exact Integration for linear neuron models and appropriate solvers for others
  • Topology Module and support for CSA for creating complex networks
  • Python based user interfaces (PyNEST, PyNN)
  • Interface to MUSIC for simulator-simulator interaction at run-time
  • Extensive testsuite to ensure reliability and reproducibility
  • Continuous integration to support agile development
  • OpenMP and MPI parallelism for efficient simulation