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@INPROCEEDINGS{Spreizer:1034642,
      author       = {Spreizer, Sebastian and Linssen, Charl and Babu, Pooja and
                      Diesmann, Markus and Morrison, Abigail and Weyers, Benjamin},
      title        = {{R}apid prototyping in spiking neural network modeling with
                      {NESTML} and {NEST} {D}esktop},
      reportid     = {FZJ-2024-07401},
      year         = {2024},
      abstract     = {NEST is a well-established open source simulator providing
                      researchers in computational neuroscience with the ability
                      to perform high-performance simulations of spiking neuronal
                      networks. However, as the simulation kernel is written in
                      C++ for performance reasons, this makes it challenging for
                      researchers without a programming background to customize
                      and extend the built-in neuron and synapse models.In order
                      to satisfy both the need for high-performance simulation
                      codes and a good user experience in terms of easy-to-use
                      modeling of neurons and synapses, NESTML was created as a
                      domain-specific language with an unambiguous syntax.
                      Alongside the language itself, a toolchain was developed
                      that parses the model, analyzes the underlying equations,
                      and performs code generation. The code generated by NESTML
                      can be used in simulations of brain activity on several
                      platforms, in particular the NEST Simulator. However,
                      specification of the network architecture requires using the
                      NEST Python API, which still requires users to be skilled at
                      programming. This poses a problem for beginners, as
                      experience shows that they usually have little to no coding
                      experience.This issue was addressed by the development of
                      NEST Desktop, a graphical user interface that serves as an
                      intuitive, programming-free interface to NEST. The interface
                      is easily installed and accessed via an internet browser on
                      the computers of individual users, or in cloud-based
                      deployments, which have already been proven in the field in
                      student courses at universities across Europe.Here, we
                      demonstrate for the first time the integration of all three
                      components: NEST Desktop, NESTML and NEST. As a result,
                      researchers and students can customize existing models or
                      develop new ones using NESTML, and have them instantly
                      available to create networks using the graphical interface
                      of NEST Desktop, before simulating them efficiently using
                      NEST as a back-end. The combined strength of these
                      components creates a low-barrier environment for rapid
                      prototyping and exploration of neuron, synapse and network
                      models.},
      month         = {Sep},
      date          = {2024-09-29},
      organization  = {Bernstein Conference 2024, Frankfurt
                       am Main (Germany), 29 Sep 2024 - 2 Oct
                       2024},
      subtyp        = {After Call},
      cin          = {IAS-6 / JSC},
      cid          = {I:(DE-Juel1)IAS-6-20130828 / I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / 5234 - Emerging NC
                      Architectures (POF4-523) / 5235 - Digitization of
                      Neuroscience and User-Community Building (POF4-523) / 5232 -
                      Computational Principles (POF4-523) / HBP SGA2 - Human Brain
                      Project Specific Grant Agreement 2 (785907) / HBP SGA3 -
                      Human Brain Project Specific Grant Agreement 3 (945539) /
                      ACA - Advanced Computing Architectures (SO-092) / SLNS -
                      SimLab Neuroscience (Helmholtz-SLNS) / PhD no Grant -
                      Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-HGF)POF4-5234 /
                      G:(DE-HGF)POF4-5235 / G:(DE-HGF)POF4-5232 /
                      G:(EU-Grant)785907 / G:(EU-Grant)945539 / G:(DE-HGF)SO-092 /
                      G:(DE-Juel1)Helmholtz-SLNS /
                      G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/1034642},
}