Last modified by jfioril1 on 2022/05/23 22:36
From version 66.1
edited by denker
on 2020/04/21 15:47
Change comment: There is no comment for this version
To version 88.1
edited by jfioril1
on 2020/05/08 17:51
Change comment: There is no comment for this version

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1 -XWiki.denker
1 +XWiki.jfioril1
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4 4  (((
5 5  = Temporal Structure in Recorded Ensemble Activity =
6 6  
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**
7 +**Contribution to Use Case SGA2-SP3-003: Pipeline for analyzing the 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 -== Analysis of temporal correlations in electrophysiological data using Neo and Elephant ==
27 +== Synopsis of this demonstration ==
26 26  
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.
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 behavioural and cognitive state variables.
28 28  
29 29  A detailed description is found in the interactive Jupyter notebook.
30 30  
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34 34  ** Open the Drive from the left menu
35 35  ** Select "Demonstrator_Use_Case_SGA2-SP3-003.ipynb", the "Figures" folder, and the "Data" folder
36 36  ** Copy the selected items, and select the destination 'My Library' from the dropdown 'Other Libraries'
37 -
39 +\\
38 38  * **Start a Jupyter Hub instance **
39 39  In another browser, open [[https:~~/~~/lab.ebrains.eu>>url:https://lab.ebrains.eu]]
40 40  
41 41  * **Run the notebook**
42 42  In the Jupyter Hub, navigate to `drive/My Libraries/My Library/Demonstrator_Use_Case_SGA2-SP3-003.ipynb`, and run the notebook.
43 -
44 44  
46 +
47 +Users without an ebrains account can access the notebook by opening: [[https:~~/~~/drive.ebrains.eu/d/26ee91ed433049278d0e/>>url:https://drive.ebrains.eu/d/26ee91ed433049278d0e/]]
48 +
45 45  == License ==
46 46  
47 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]].
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Description
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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
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