4.5 Article

NEST Desktop, an Educational Application for Neuroscience

期刊

ENEURO
卷 8, 期 6, 页码 -

出版社

SOC NEUROSCIENCE
DOI: 10.1523/ENEURO.0274-21.2021

关键词

code generation; graphical user interface; NEST simulator; neuronal dynamics; teaching; web-based application

资金

  1. European Union's Horizon 2020 Framework Programme for Research and Innovation [785907, 945539]
  2. Helmholtz Association Initiative and Networking Fund [SO-092]
  3. Deutsche Forschungsgemeinschaft (DFG) Excellence Cluster BrainLinks-BrainTools Grant [EXC 1086]
  4. state of BadenWurttemberg through bwHPC
  5. DFG [INST 39/963-1 FUGG]

向作者/读者索取更多资源

The article introduces a web-based Graphical User Interface (GUI) for simulation software of spiking neuronal network models, reducing the entry barrier for students and early career scientists in computational neuroscience. The NEST Desktop tool, with graphical elements for creating, configuring, running, and analyzing network models, enhances the quality and intensity of teaching in computational neuroscience. The availability of this tool on public resources contributes to equal opportunities in the field.
Simulation software for spiking neuronal network models matured in the past decades regarding performance and flexibility. But the entry barrier remains high for students and early career scientists in computational neuroscience since these simulators typically require programming skills and a complex installation. Here, we describe an installation-free Graphical User Interface (GUI) running in the web browser, which is distinct from the simulation engine running anywhere, on the student's laptop or on a supercomputer. This architecture provides robustness against technological changes in the software stack and simplifies deployment for self-education and for teachers. Our new open-source tool, NEST Desktop, comprises graphical elements for creating and configuring network models, running simulations, and visualizing and analyzing the results. NEST Desktop allows students to explore important concepts in computational neuroscience without the need to learn a simulator control language before. Our experiences so far highlight that NEST Desktop helps advancing both quality and intensity of teaching in computational neuroscience in regular university courses. We view the availability of the tool on public resources like the European ICT infrastructure for neuroscience EBRAINS as a contribution to equal opportunities.

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