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4	4	(((
5	5	= Temporal Structure in Recorded Ensemble Activity =
6	6
7		-**Use Case SGA2-SP3-003: Pipeline for analyzing Temporal structure in recorded Ensemble Activity and related Systems Neuroscience data in association with behavior, cognitive processing and modeling**
	7	+**Contribution to Use Case SGA2-SP3-003: Pipeline for analyzing Temporal structure in recorded Ensemble Activity and related Systems Neuroscience data in association with behavior, cognitive processing and modeling**
8	8
9		-To be discussed Author order, contributions,...:
10		-
11	11	Experiments: Julien Fiorilli^^2^^
12	12
13	13	Implementation: Regimantas Jurkus^^1^^, Julien Fiorilli^^2^^, Pietro Marchesi^^2^^, Thijs Ruikes^^2^^
14	14
15		-Lead: Michael Denker^^1^^, Sonja Grün^^1^^, Cyril Pennartz^^2^^
	13	+Lead: Michael Denker^^1^^, Sonja Grün^^1^^, Cyriel Pennartz^^2^^
16	16
17	17	,,1) Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany,,
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25	25	(% class="col-xs-12 col-sm-8" %)
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27		-== Demonstration of the analysis of electrophysiological data ==
	25	+== Analysis of temporal correlations in electrophysiological data using Neo and Elephant ==
28	28
29		-A notebook that demonstrates how to apply the pipeline to a complex dataset.
30		-\\The aim of this note-book is twofold. Firstly,we aim to demonstrate the advantage of a common and shared data representation format for a challenging and complex electrophysiology dataset. The second aim is to showcase the first part of a pipeline for analysing for population-level data, including parallel spiking activity, paired with and behavioural and cognitive state variables.
	27	+This notebook, aimed at experimental and computational neuroscientists, demonstrates the principles of performing analysis of activity data on a complex dataset using the Neo and Elephant tools. We demonstrate the advantage of a common and shared data representation format for a challenging and complex electrophysiology dataset. Also, we showcase the first part of a pipeline for analysing for population-level data, including parallel spiking activity, paired with and behavioural and cognitive state variables.
31	31
32		-This Collab is aimed at experimental and computational neuroscientists interested in the usage of the Neo and Elephant tools in performing data analysis of spiking data.
	29	+A detailed description is found in the interactive Jupyter notebook.
33	33
34	34	== Executing the analysis notebook ==
35	35
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45	45	In the Jupyter Hub, navigate to `drive/My Libraries/My Library/Demonstrator_Use_Case_SGA2-SP3-003.ipynb`, and run the notebook.
46	46
47	47
48		-== License (to discuss) ==
	45	+== License ==
49	49
50		-All text and example data in this collab is licensed under Creative Commons CC-BY 4.0 license. Software code is licensed under a modified BSD license.
	47	+All text and example data in this collab is licensed under under a [[Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License>>url:https://creativecommons.org/licenses/by-nc-nd/4.0/]]. Software code is licensed under [[a modified BSD license>>https://opensource.org/licenses/BSD-3-Clause]].
	48	+Please note that the data in this Collab is preliminary and might therefore still contain inaccuracies in specific event timestamps.
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52		-[[image:https://i.creativecommons.org/l/by/4.0/88x31.png||style="float:left"]]
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54		-(% class="wikigeneratedid" %)
55		-== ==
56	56
57	57	== Acknowledgments ==
58	58

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