Changes for page EBRAINS Swedish Node Workshop 2025: NEST Tutorials
Last modified by spreizer on 2025/08/26 09:19
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... ... @@ -25,15 +25,16 @@ 25 25 ==== Time schedule ==== 26 26 27 27 |(% style="width:84px" %)9 - 11|(% style="width:235px" %)NEST Desktop|(% style="width:541px" %)[[https:~~/~~/nest-desktop.readthedocs.org/>>https://nest-desktop.readthedocs.org/]] 28 -|(% style="width:84px" %)12 - 1 4|(% style="width:235px" %)NEST Simulator|(% style="width:541px" %)[[https:~~/~~/nest-simulator.readthedocs.org/>>https://nest-simulator.readthedocs.org/]]29 -|(% style="width:84px" %)1 4- 17|(% style="width:235px" %)NESTML|(% style="width:541px" %)[[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]]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/]] 30 30 31 - 32 32 ==== Descriptions ==== 33 33 34 34 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. 35 35 35 +* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nest-desktop>>https://wiki.ebrains.eu/bin/view/Collabs/nest-desktop]] 36 36 37 + 37 37 2) The tutorial will then turn to Jupyter (Python) notebooks where we will start by creating a 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: 38 38 39 39 * neuronal dynamics ... ... @@ -41,12 +41,10 @@ 41 41 * networks of spatial neurons 42 42 * using plasticity 43 43 44 - 45 45 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]. 46 46 47 47 * [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials>>https://wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials]] 48 48 49 - 50 50 51 51 ))) 52 52