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https://www.youtube.com/watch?v=BZB7xKUK8Vc (14 minutes) |
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-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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+In this tutorial, you will learn how to install PyNN, together with the Brian 2, NEST and NEURON simulators, on Linux. [More information] |
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== Building and simulating a simple model == |
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https://www.youtube.com/watch?v=zBLNfJiEvRc (16 minutes) |
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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. ~[[[More information>>doc:.Building and simulating a simple model.WebHome]]] |
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-== Planned tutorials == |
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-* [[1. Introduction to PyNN>>doc:.Introduction to PyNN.WebHome]] |
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-* [[2. Installing PyNN>>doc:.Installing PyNN.WebHome]] |
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-** b) on Mac OS |
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-** c) on Windows |
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-** d) in the EBRAINS Jupyter Lab |
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-* [[4. Recording and data handling>>doc:.Recording and data handling.WebHome]] |
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-* [[5. Structuring larger models>>doc:.Structuring larger models.WebHome]] |
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-* [[6. Models with spatial structure>>doc:.Models with spatial structure.WebHome]] |
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-* [[7. Synaptic plasticity>>doc:.Synaptic plasticity.WebHome]] |
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-* [[8. Randomness and reproducibility>>doc:.Randomness and reproducibility.WebHome]] |
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-* [[9. Running parallel simulations>>doc:.Running parallel simulations.WebHome]] |
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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. [More information] |
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