Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -19,18 +19,14 @@
19	19	- [[Abstract>>url:https://wiki.ebrains.eu/bin/view/Collabs/swedish-node-nest-tutorials/About/]]
20	20
21	21
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.
23	23
24	24
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	28	|(% 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/]]
29	29	|(% style="width:84px" %)15 - 17|(% style="width:235px" %)NESTML|(% style="width:541px" %)[[https:~~/~~/nestml.readthedocs.org/>>https://nestml.readthedocs.org/]]
30	30
31	31
32		-==== Descriptions ====
33		-
34	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	35
36	36
...	...	@@ -43,9 +43,7 @@
43	43
44	44	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].
45	45
46		-* [[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials>>https://wiki.ebrains.eu/bin/view/Collabs/nestml-tutorials]]
47	47
48		-
49	49
50	50	)))
51	51