Last modified by jfioril1 on 2022/05/23 22:36
From version 55.1
edited by jfioril1
on 2020/04/15 14:37
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To version 75.1
edited by denker
on 2020/05/08 15:19
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1 -XWiki.jfioril1
1 +XWiki.denker
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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 9  Experiments: Julien Fiorilli^^2^^
10 10  
11 11  Implementation: Regimantas Jurkus^^1^^, Julien Fiorilli^^2^^, Pietro Marchesi^^2^^, Thijs Ruikes^^2^^
12 12  
13 -Lead: Michael Denker^^1^^, Sonja Grün^^1^^, Cyriel Pennartz^^2^^
13 +Lead: Michael Denker^^1^^, Sonja Grün^^1,3^^, Cyriel Pennartz^^2^^
14 14  
15 15  ,,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,,
16 16  
17 17  ,,2) Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands,,
18 +
19 +,,3) Theoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany,,
18 18  )))
19 19  )))
20 20  
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22 22  (((
23 23  (% class="col-xs-12 col-sm-8" %)
24 24  (((
25 -== Demonstration of the analysis of electrophysiological data ==
27 +== Synopsis of this demonstration ==
26 26  
27 -A notebook that demonstrates how to apply the pipeline to a complex dataset.
28 -\\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.
29 +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.
29 29  
30 -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.
31 +A detailed description is found in the interactive Jupyter notebook.
31 31  
32 32  == Executing the analysis notebook ==
33 33  
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45 45  
46 46  == License ==
47 47  
48 -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. 
49 +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]].
49 49  Please note that the data in this Collab is preliminary and might therefore still contain inaccuracies in specific event timestamps.
50 50  
51 -[[image:https://i.creativecommons.org/l/by/4.0/88x31.png||style="float:left"]]
52 +[[image:88x31.png]]
52 52  
53 -== ==
54 54  
55 55  == Acknowledgments ==
56 56  
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1 -This collaboration space is created to showcase examples of the progress made for the SP3 Use Case 3, highlight the tools used and outline the next steps to be taken.
1 +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