Wiki source code of Swedish Node 2025: NEST Tutorials
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11.1 | 5 | = NEST Tutorials = |
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11.1 | 7 | EBRAINS Swedish Node, Stockholm, 25/08/25 - 27/08/25 |
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14.1 | 15 | == From single-cell modeling to large-scale network dynamics with NEST Simulator == |
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14.2 | 17 | **Instructor**: Sebastian Spreizer, PhD, University of Trier and Research Center Jülich |
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14.2 | 19 | - [[Abstract>>url:https://wiki.ebrains.eu/bin/view/Collabs/swedish-node-nest-tutorials/About/]] |
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14.2 | 22 | The tutorial is composed of three parts in which the user learns to model neuronal networks step by step. |
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| 25 | |(% style="width:84px" %)9 - 11|(% style="width:235px" %)NEST Desktop|(% style="width:541px" %)[[https:~~/~~/nest-desktop.readthedocs.org/>>https://nest-desktop.readthedocs.org/]] | ||
| 26 | |(% style="width:84px" %)12 - 15|(% style="width:235px" %)NEST in Jupyter Lab|(% style="width:541px" %)[[https:~~/~~/nest-simulator.readthedocs.org/>>https://nest-simulator.readthedocs.org/]] | ||
| 27 | |(% style="width:84px" %)15 - 17|(% style="width:235px" %)NESTML|(% style="width:541px" %)[[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]] | ||
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| 30 | 1) 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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| 33 | 2) The tutorial will then turn to Jupyter (Python) notebooks where we will start by creating a spiking network. 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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| 35 | - large scale networks, | ||
| 36 | - networks of spatial neurons | ||
| 37 | - using plasticity | ||
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| 40 | 3) 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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| 49 | {{box title="**Contents**"}} | ||
| 50 | {{toc/}} | ||
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