NEST Tutorials
EBRAINS Swedish Node, Stockholm, 25/08/25 - 27/08/25
From single-cell modeling to large-scale network dynamics with NEST Simulator
Instructor: Sebastian Spreizer, PhD, University of Trier and Research Center Jülich
The tutorial is composed of three parts in which the user learns to simulate with NEST step by step.
Time schedule
| 9 - 11 | NEST Desktop | https://nest-desktop.readthedocs.org/ |
| 12 - 15 | NEST Simulator | https://nest-simulator.readthedocs.org/ |
| 15 - 18 | NESTML | https://nestml.readthedocs.org/ |
1) NEST Desktop
The first part of the tutorial, we look at NEST Desktop. As a goal we will create and analyze a balanced two-population network.
2) NEST Simulator
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:
- neuronal dynamics
- large scale networks,
- networks of spatial neurons
- using plasticity
3) NESTML
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].