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22	22	The tutorial is composed of three parts in which the user learns to simulate with NEST step by step.
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25		-==== Time schedule ====
	25	+=== Time schedule ===
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27	27	|(% style="width:84px" %)9 - 11|(% style="width:235px" %)NEST Desktop|(% style="width:541px" %)[[https:~~/~~/nest-desktop.readthedocs.org/>>https://nest-desktop.readthedocs.org/]]
28	28	|(% style="width:84px" %)12 - 15|(% style="width:235px" %)NEST Simulator|(% style="width:541px" %)[[https:~~/~~/nest-simulator.readthedocs.org/>>https://nest-simulator.readthedocs.org/]]
29	29	|(% style="width:84px" %)15 - 18|(% style="width:235px" %)NESTML|(% style="width:541px" %)[[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]]
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	31	+=== ===
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32		-==== Descriptions ====
	33	+=== 1) NEST Desktop ===
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34		-1) The first part of the tutorial, we look at NEST Desktop.  As a goal we will create and analyze a balanced two-population network.
	35	+The first part of the tutorial, we look at NEST Desktop.  As a goal we will create and analyze a balanced two-population network.
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36	36	* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nest-desktop>>https://wiki.ebrains.eu/bin/view/Collabs/nest-desktop]]
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39		-2) The tutorial will then turn to Jupyter (Python) notebooks where we will start by creating a spiking neurons. Here, we learn advanced steps to write code with NEST Simulation syntax. The scripting codes allow us to customize sophisticated use cases with NEST simulations. Examples are:
	40	+=== 2) NEST Simulator ===
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	42	+The tutorial will then turn to Jupyter (Python) notebooks where we will start by creating a spiking neurons. Here, we learn advanced steps to write code with NEST Simulation syntax. The scripting codes allow us to customize sophisticated use cases with NEST simulations. Examples are:
	43	+
41	41	* neuronal dynamics
42	42	* large scale networks,
43	43	* networks of spatial neurons
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44	44	* using plasticity
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	50	+=== 3) NESTML ===
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48		-3) The last part is using NESTML to create custom neuron and synapse models for NEST Simulator. A functional plasticity rule will then be introduced into the balanced E/I network to implement a biologically realistic version of reinforcement learning. This will be done by formulating the learning model in the NESTML language syntax, and using the associated toolchain to generate code for NEST [4].
	52	+The last part is using NESTML to create custom neuron and synapse models for NEST Simulator. A functional plasticity rule will then be introduced into the balanced E/I network to implement a biologically realistic version of reinforcement learning. This will be done by formulating the learning model in the NESTML language syntax, and using the associated toolchain to generate code for NEST [4].
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50	50	* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials>>https://wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials]]
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