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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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33		-=== 1) NEST Desktop ===
	32	+==== Descriptions ====
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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.
	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.
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37		-* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nest-desktop>>https://wiki.ebrains.eu/bin/view/Collabs/nest-desktop]]
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	37	+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:
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40		-=== 2) NEST Simulator ===
41		-
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:
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44	44	* neuronal dynamics
45	45	* large scale networks,
46	46	* networks of spatial neurons
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47	47	* using plasticity
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50		-=== 3) NESTML ===
	45	+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].
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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].
53		-
54	54	* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials>>https://wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials]]
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	49	+
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57	57	)))
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