NEST Initiative

The Neural Simulation Technology Initiative

The NEST Initiative has advanced computational neuroscience since 2001 by pushing the limits of large-scale simulations of biologically realistic neuronal networks. Since 2012, the NEST Initiative is incorporated as a non-profit member-based organization promoting scientfic collaboration in computational neuroscience.

The Board and Members govern the NEST Initiative in accordance to its Statutes.

What we do

As a community of developers:

  • We coordinate and guide the development of the NEST Simulator.
  • We regularly publish on simulation technology, data structures and algorithms for large-scale neuronal network simulation:

    Latest Publications

    • [DOI] Plesser H, Diesmann M, Gewaltig M, Morrison A (2015) Nest: the neural simulation tool. In Encyclopedia of computational neuroscience, ed. Jaeger D Jung R 1849-1852Springer New York. .
      Title = {NEST: the Neural Simulation Tool},
      Author = {Plesser, HansEkkehard and Diesmann, Markus and Gewaltig,
      Marc-Oliver and Morrison, Abigail},
      Booktitle = {Encyclopedia of Computational Neuroscience},
      Publisher = {Springer New York},
      Year = {2015},
      Editor = {Jaeger, Dieter and Jung, Ranu},
      Pages = {1849-1852},
      Doi = {10.1007/978-1-4614-6675-8_258},
      ISBN = {978-1-4614-6674-1},
      Language = {English},
      Nest_category = {nest_technology},
      Owner = {steffen},
      Timestamp = {2015.03.24},
      Url = {}

    • [DOI] Hahne J, Helias M, Kunkel S, Igarashi J, Bolten M, Frommer A, Diesmann M (2015) A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations. Frontiers in neuroinformatics 9:22.
      Title = {A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations},
      Author = {Hahne, Jan and Helias, Moritz and Kunkel, Susanne and Igarashi, Jun and Bolten, Matthias and Frommer, Andreas and Diesmann, Markus},
      Journal = {Frontiers in Neuroinformatics},
      Year = {2015},
      Number = {22},
      Volume = {9},
      Abstract = {Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology.},
      Doi = {10.3389/fninf.2015.00022},
      ISSN = {1662-5196},
      Nest_category = {nest_technology},
      Owner = {steffen},
      Timestamp = {2015.09.09},
      Url = {}

    • [DOI] Kunkel S, Schmidt M, Eppler J M, Plesser H E, Masumoto G, Igarashi J, Ishii S, Fukai T, Morrison A, Diesmann M, Helias M (2014) Spiking network simulation code for petascale computers. Frontiers in neuroinformatics 8:78.
      Title = {Spiking network simulation code for petascale computers},
      Author = {Kunkel, Susanne and Schmidt, Maximilian and Eppler, Jochen Martin and Plesser, Hans Ekkehard and Masumoto, Gen and Igarashi, Jun and Ishii, Shin and Fukai, Tomoki and Morrison, Abigail and Diesmann, Markus and Helias, Moritz},
      Journal = {Frontiers in Neuroinformatics},
      Year = {2014},
      Number = {78},
      Volume = {8},
      Doi = {10.3389/fninf.2014.00078},
      Nest_category = {nest_technology},
      Owner = {graber},
      Timestamp = {2015.02.17},
      Url = {}

    You will find a detailed bibliography of publications on simulation technology and NEST-based computational neuroscience studies on our Publications page.

  • We teach NEST as summer schools, workshops and tutorials and provide user and developer support:
    More Activities…


How to join us

There are many ways to be a part of the NEST Community.

  • If you want to work with NEST you should definitely sign up for our NEST User and Announcement mailing lists and share your experiences with other NESTies.
  • If you want to work on NEST as a developer, stay abreast of the newest developments and contribute your own code to NEST, the NEST GitHub Repository is the place to go. Here, you will find current source code, our bug tracker, and developer discussions; plus, you can contribute your own code via pull requests.
  • As an active developer contributing code to NEST, you are welcome to join the NEST Initiative as an active member and shape the future developement of NEST. You will find more information on our Membership page.
  • If you just want to support the goals of the NEST Initiative without contributing code, you are welcome to join us as a community member, as described on our Membership page.

Welcome aboard!