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1		-PyNN (//pronounced 'pine'//) is a simulator-independent language for building neuronal network models.
	1	+This collab is currently being used to plan tutorials for PyNN. Once we have completed at least one of the "Installing PyNN" tutorials and the "Building and simulating a simple model" tutorial, we will make it public.
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3		-In other words, you can write the code for a model once, using the PyNN API and the Python programming language, and then run it without modification on any simulator that PyNN supports (currently [[NEURON>>url:http://www.neuron.yale.edu/neuron/]], [[NEST>>url:http://www.nest-initiative.org/?page=Software]], and [[Brian>>url:http://briansimulator.org/]]), and on the [[SpiNNaker>>url:http://apt.cs.manchester.ac.uk/projects/SpiNNaker/]] and [[BrainScaleS>>url:https://www.humanbrainproject.eu/en/silicon-brains/]] neuromorphic hardware systems.
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5		-== (% class="mark" %)[[Tutorials>>Tutorials]](%%)   [[Documentation>>https://neuralensemble.org/docs/PyNN/]] [[Homepage>>http://neuralensemble.org/PyNN/]] ==
	4	+== Planned tutorials ==
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7		-== [[Source code>>https://github.com/NeuralEnsemble/PyNN]] [[Issue tracker>>https://github.com/NeuralEnsemble/PyNN/issues]]   [[Community>>https://neuralensemble.org/community]] ==
	6	+The first three tutorials should be followed in sequence. Following this, the remaining, more advanced, tutorials can be followed in any order.
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	8	+* [[Introduction to PyNN>>doc:.Tutorials.Introduction to PyNN.WebHome]]
	9	+* [[Installing PyNN>>Installing PyNN]]
	10	+** on Linux
	11	+** on Mac OS
	12	+** on Windows
	13	+** in the EBRAINS Jupyter Lab
	14	+* Building and simulating a simple model
	15	+* Recording and data handling
	16	+* Structuring larger models
	17	+* Models with spatial structure
	18	+* Synaptic plasticity
	19	+* Randomness and reproducibility
	20	+* Running parallel simulations
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