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3.1 | 1 | == Installing PyNN on Linux == |
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| 3 | https://www.youtube.com/watch?v=BZB7xKUK8Vc (14 minutes) | ||
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4.1 | 5 | In this tutorial, you will learn how to install PyNN, together with the Brian 2, NEST and NEURON simulators, on Linux. ~[[[More information>>doc:.Installing PyNN.WebHome]]] |
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3.1 | 6 | |
| 7 | == Building and simulating a simple model == | ||
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| 9 | https://www.youtube.com/watch?v=zBLNfJiEvRc (16 minutes) | ||
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5.1 | 10 | \\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. ~[[[More information>>doc:.Building and simulating a simple model.WebHome]]] |
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6.1 | 11 | |
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| 13 | == Planned tutorials == | ||
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| 15 | Tutorials 1-3 should be followed in sequence. Following this, the remaining, more advanced, tutorials can be followed in any order. | ||
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7.1 | 17 | * [[1. Introduction to PyNN>>doc:.Introduction to PyNN.WebHome]] |
| 18 | * [[2. Installing PyNN>>doc:.Installing PyNN.WebHome]] | ||
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6.1 | 19 | ** b) on Mac OS |
| 20 | ** c) on Windows | ||
| 21 | ** d) in the EBRAINS Jupyter Lab | ||
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7.1 | 22 | * [[4. Recording and data handling>>doc:.Recording and data handling.WebHome]] |
| 23 | * [[5. Structuring larger models>>doc:.Structuring larger models.WebHome]] | ||
| 24 | * [[6. Models with spatial structure>>doc:.Models with spatial structure.WebHome]] | ||
| 25 | * [[7. Synaptic plasticity>>doc:.Synaptic plasticity.WebHome]] | ||
| 26 | * [[8. Randomness and reproducibility>>doc:.Randomness and reproducibility.WebHome]] | ||
| 27 | * [[9. Running parallel simulations>>doc:.Running parallel simulations.WebHome]] | ||
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