Learning objectives
In this tutorial, you will learn how to install PyNN, together with the NEST, NEURON and Brian2 simulators, on Linux / Mac OS / Windows / in EBRAINS Jupyter Lab.
Audience
This tutorial is intended for people with at least a basic knowledge of neuroscience (high school level or above) and basic familiarity with the Python programming language. It should also be helpful for people who already have advanced knowledge of neuroscience and neural simulation, who simply wish to learn how to use PyNN, and how it differs from other simulation tools they know.
Prerequisites
To follow this tutorial, you will need a computer with [Linux/Mac OS/Windows] and a good network connection. You will need to know how to open the terminal application for your operating system.
OR
To follow this tutorial, you will need an EBRAINS account. You should know how to create and use Jupyter notebooks in the EBRAINS Jupyter Lab.
Format
These tutorials will be screencasts, in which the presenter runs commands in a terminal (or in a Jupyer notebook), and the viewer is expected to follow along. The intended duration is 10 minutes. For the Jupyter version of the tutorial, the final notebook will also be made available.
Script
Hello, my name is X.
This video is one of a series of tutorials for PyNN, which is Python software for modelling and simulating spiking neural networks.
For a list of the other tutorials in this series, you can visit ebrains.eu/service/pynn, that's p-y-n-n.
In this tutorial, I will guide you through setting up PyNN, together with the NEST, NEURON and Brian2 simulators, in a Linux environment. Note that we have a dedicated version of this tutorial for other environments, such as Mac OS, Windows and EBRAINS Jupyter Lab.
I shall be demonstrating the installation on a computer with Ubuntu 18.04 OS installed. The steps are likely to remain very similar for other versions of Ubuntu OS, and also not expected to vary significantly for other Linux distributions. In the latter case, you will find on the Internet about how to carry out the equivalent of the tasks demonstrated here using Ubuntu OS.
We shall make use of virtualenv (virtual environment) in this tutorial. This allows multiple Python projects to coexist on the same computer, even when they might have different, and even conflicting, requirements. It helps isolate projects and thereby preventing unrequested changes in others, when any one of them is updated.
That is the end of this tutorial, in which I've demonstrated how to install PyNN, and other required simulators, in a Linux system. You are now ready to start modeling! To learn about model development in PyNN, do take a look at our next tutorial.
Als, we will be releasing a series of tutorials, throughout the rest of 2021 and 2022, to introduce these more advanced features of PyNN, so keep an eye on the EBRAINS website.
PyNN has been developed by many different people, with financial support from several different organisations. I'd like to mention in particular the CNRS and the European Commission, through the FACETS, BrainScaleS and Human Brain Project grants.
For more information visit neuralensemble.org/PyNN. If you have questions you can contact us through the PyNN Github project, the NeuralEnsemble forum, EBRAINS support, or the EBRAINS Community.