Last modified by jfioril1 on 2022/05/23 22:36
From version 47.1
edited by jfioril1
on 2020/04/15 14:22
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To version 66.1
edited by denker
on 2020/04/21 15:47
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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^^
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24 24  (((
25 25  (% class="col-xs-12 col-sm-8" %)
26 26  (((
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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47 47  
48 48  == 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. Please note that the example data is preliminary and might contain inaccuracies in event timestamps. This current version is therefore only meant for demonstration and validation purposes.
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.
51 51  
52 -[[image:https://i.creativecommons.org/l/by/4.0/88x31.png||style="float:left"]]
50 +[[image:88x31.png]]
53 53  
54 -== ==
55 55  
56 56  == Acknowledgments ==
57 57  
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