03. Building and simulating a simple model

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tutorial under development

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== Learning objectives ==

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In this tutorial, you will learn how to build a simple network of integrate-and-fire neurons using PyNN, how to run simulation experiments with this network using different simulators, and how to visualize the data generated by these experiments.

== 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 need a basic knowledge of neuroscience (high-school level or greater), basic familiarity with the Python programming language, and either a computer with PyNN, NEST, NEURON and Brian 2 installed, or an EBRAINS account and basic familiarity with Jupyter notebooks. If you don't have these tools installed, see one of our previous tutorials which guide you through the installation.

== Format ==

This tutorial will be a video combining slides, animations, and screencast elements. The intended duration is 10 minutes.

== Script ==

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(% class="small" %)**Introduce yourself**

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.

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For a list of the other tutorials in this series, you can visit ebrains.eu/service/pynn, that's p-y-n-n.

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(% class="small" %)**State the learning objectives**

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In this tutorial, you will learn the basics of PyNN: how to build a simple network of integrate-and-fire neurons using PyNN, how to run simulation experiments with this network using different simulators, and how to visualize the data generated by these experiments.

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(% class="small" %)**State prerequisites**

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To follow this tutorial, you need a basic knowledge of neuroscience (high-school level or greater), basic familiarity with the Python programming language, and you should have already followed our earlier tutorial video which guides you through the installation process.

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This video covers PyNN 0.10. If you've installed a more recent version of PyNN, you might want to look for an updated version of this video.

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(% class="small" %)**Description, explanation, and practice**

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