Version 21.1 by spreizer on 2025/07/30 11:10
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spreizer 11.1 5 = NEST Tutorials =
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spreizer 11.1 7 EBRAINS Swedish Node, Stockholm, 25/08/25 - 27/08/25
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spreizer 14.1 15 == From single-cell modeling to large-scale network dynamics with NEST Simulator ==
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spreizer 14.2 17 **Instructor**: Sebastian Spreizer, PhD, University of Trier and Research Center Jülich
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spreizer 20.2 19 - [[Tutorial abstract>>url:https://wiki.ebrains.eu/bin/view/Collabs/swedish-node-nest-tutorials/About/]]
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spreizer 16.3 22 The tutorial is composed of three parts in which the user learns to simulate with NEST step by step.
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spreizer 18.1 25 === Time schedule ===
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spreizer 14.2 27 |(% style="width:84px" %)9 - 11|(% style="width:235px" %)NEST Desktop|(% style="width:541px" %)[[https:~~/~~/nest-desktop.readthedocs.org/>>https://nest-desktop.readthedocs.org/]]
spreizer 16.5 28 |(% style="width:84px" %)12 - 15|(% style="width:235px" %)NEST Simulator|(% style="width:541px" %)[[https:~~/~~/nest-simulator.readthedocs.org/>>https://nest-simulator.readthedocs.org/]]
29 |(% style="width:84px" %)15 - 18|(% style="width:235px" %)NESTML|(% style="width:541px" %)[[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]]
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spreizer 18.2 31 === 1) NEST Desktop ===
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spreizer 18.1 33 The first part of the tutorial, we look at NEST Desktop.  As a goal we will create and analyze a balanced two-population network.
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spreizer 16.6 35 * [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nest-desktop>>https://wiki.ebrains.eu/bin/view/Collabs/nest-desktop]]
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spreizer 18.2 37 === 2) NEST Simulator ===
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spreizer 21.1 39 The tutorial will then turn to Jupyter (Python) notebooks where we will start by creating spiking neurons. Here, we learn advanced steps to write code with NEST Simulation syntax. The scripting codes allow us to customize sophisticated use cases with NEST simulations. Examples are:
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spreizer 16.4 41 * neuronal dynamics
42 * large scale networks,
43 * networks of spatial neurons
44 * using plasticity
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spreizer 18.2 46 === 3) NESTML ===
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spreizer 18.1 48 The last part is using NESTML to create custom neuron and synapse models for NEST Simulator. A functional plasticity rule will then be introduced into the balanced E/I network to implement a biologically realistic version of reinforcement learning. This will be done by formulating the learning model in the NESTML language syntax, and using the associated toolchain to generate code for NEST [4].
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spreizer 16.3 50 * [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials>>https://wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials]]
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58 {{box title="**Contents**"}}
59 {{toc/}}
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