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19	19	- [[Abstract>>url:https://wiki.ebrains.eu/bin/view/Collabs/swedish-node-nest-tutorials/About/]]
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22		-The tutorial is composed of three parts in which the user learns to simulate with NEST step by step.
	22	+The tutorial is composed of three parts in which the user learns to model neuronal networks step by step.
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25		-==== Time schedule ====
26		-
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		-|(% style="width:84px" %)12 - 15|(% style="width:235px" %)NEST Simulator|(% style="width:541px" %)[[https:~~/~~/nest-simulator.readthedocs.org/>>https://nest-simulator.readthedocs.org/]]
29		-|(% style="width:84px" %)15 - 18|(% style="width:235px" %)NESTML|(% style="width:541px" %)[[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]]
	26	+|(% style="width:84px" %)12 - 15|(% style="width:235px" %)NEST in Jupyter Lab|(% style="width:541px" %)[[https:~~/~~/nest-simulator.readthedocs.org/>>https://nest-simulator.readthedocs.org/]]
	27	+|(% style="width:84px" %)15 - 17|(% style="width:235px" %)NESTML|(% style="width:541px" %)[[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]]
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31		-==== Descriptions ====
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33	33	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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35		-* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nest-desktop>>https://wiki.ebrains.eu/bin/view/Collabs/nest-desktop]]
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	33	+2) The tutorial will then turn to Jupyter (Python) notebooks where we will start by creating a spiking network. 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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38		-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:
	35	+- large scale networks,
	36	+- networks of spatial neurons
	37	+- using plasticity
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40		-* neuronal dynamics
41		-* large scale networks,
42		-* networks of spatial neurons
43		-* using plasticity
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45	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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47		-* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials>>https://wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials]]
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50	50	)))