Changes for page EBRAINS Swedish Node Workshop 2025: NEST Tutorials
Last modified by spreizer on 2025/08/26 09:19
Summary
-
Page properties (2 modified, 0 added, 0 removed)
Details
- Page properties
-
- Title
-
... ... @@ -1,1 +1,1 @@ 1 -EBRAINS Swedish Node Workshop 2025: NEST Tutorials1 +NEST Tutorials for EBRAINS Swedish Node - Content
-
... ... @@ -2,9 +2,9 @@ 2 2 ((( 3 3 (% class="container" %) 4 4 ((( 5 -= NEST Tutorials=5 += From single-cell modeling to large-scale network dynamics with NEST Simulator = 6 6 7 -EBRAINS Swedish Node , Stockholm, 25/08/25 - 27/08/257 +NEST Tutorials for EBRAINS Swedish Node 8 8 ))) 9 9 ))) 10 10 ... ... @@ -12,45 +12,28 @@ 12 12 ((( 13 13 (% class="col-xs-12 col-sm-8" %) 14 14 ((( 15 -== From single-cell modeling to large-scale network dynamics with NEST Simulator == 15 +(% class="wikigeneratedid" %) 16 +**Instructor**: Sebastian Spreizer, PhD University of Trier and Research Center Jülich 16 16 17 -**Instructor**: Sebastian Spreizer, PhD, University of Trier and Research Center Jülich 18 18 19 -- [[Abstract>>url:https://wiki.ebrains.eu/bin/view/Collabs/swedish-node-nest-tutorials/About/]] 19 +(% class="wikigeneratedid" id="HWhatcanIfindhere3F" %) 20 +NEST is an established, open-source simulator for spiking neuronal networks, which can capture a high degree of detail of biological network structures while retaining high performance and scalability from laptops to HPC [1]. This tutorial offers hands-on experience in building and simulating neuron, synapse, and network models. It introduces several tools and front-ends to implement modeling ideas most effectively. Participants do not have to install software as all tools are accessible via the cloud. 20 20 22 +First, we look at NEST Desktop [2], a web-based graphical user interface (GUI), which allows the exploration of essential concepts in computational neuroscience without the need to learn a programming language. This advances both the quality and speed of teaching in computational neuroscience. To get acquainted with the GUI, we will create and analyze a balanced two-population network. 21 21 22 -The tutorial i scomposedofthreepartsinwhichtheuser learns tosimulate with NEST stepbystep.24 +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 explore sophisticated use cases with NEST simulations. I will let the audience pick one or few of the provided examples, e.g. large scale networks, networks of spatial neurons or using plasticity [3]. 23 23 26 +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]. 24 24 25 -=== Time schedule === 28 +[1] [[https:~~/~~/nest-simulator.readthedocs.org/>>https://nest-simulator.readthedocs.org/]] 29 +[2] [[https:~~/~~/nest-desktop.readthedocs.org/>>https://nest-desktop.readthedocs.org/]] 30 +[3] [[https:~~/~~/nest-simulator.readthedocs.io/en/latest/examples/index.html>>https://nest-simulator.readthedocs.io/en/latest/examples/index.html]] 31 +[4] [[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]] 26 26 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 - 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 34 +**Requirements**: Laptop with access to Internet. An account on EBRAINS would be optimal, otherwise I will create guest accounts for participants. 31 31 32 -=== 1) NEST Desktop === 33 - 34 -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 - 36 -* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nest-desktop>>https://wiki.ebrains.eu/bin/view/Collabs/nest-desktop]] 37 - 38 -=== 2) NEST Simulator === 39 - 40 -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: 41 - 42 -* neuronal dynamics 43 -* large scale networks, 44 -* networks of spatial neurons 45 -* using plasticity 46 - 47 -=== 3) NESTML === 48 - 49 -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]. 50 - 51 -* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials>>https://wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials]] 52 - 53 - 36 +**Target audience**: Students and researchers who are interesting in computational neuroscience 54 54 ))) 55 55 56 56