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Changes for page Elephant Tutorials

Last modified by denker on 2025/04/09 07:02
From version 31.1
edited by denker
on 2022/06/29 11:31
Change comment: There is no comment for this version
To version 49.1
edited by moritzkern
on 2023/03/21 11:30
Change comment: There is no comment for this version

Summary

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1 +XWiki.moritzkern
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7 7  (% style="color:#4e5f70" %)Interactive video tutorials on
8 8  neuronal data analysis using Elephant
9 9  
10 -(% style="color:#e74c3c" %)**Upcoming: CNS 2022**
10 +
11 11  )))
12 12  )))
13 13  
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15 15  (((
16 16  (% class="col-xs-12 col-sm-8" %)
17 17  (((
18 +== Upcoming training events ==
19 +
20 +{{info}}
21 +**Data Analysis using Elephant (Hybrid)**
22 +**SMHB General Assembly**
23 +Date: Wednesday, April 5, 2023
24 +Location: Forschungszentrum Juelich, Germany
25 +
26 +
27 +
28 +{{/info}}
29 +
18 18  == A resource for kick-starting work with the Elephant library ==
19 19  
20 20  The Python library [[Electrophysiology Analysis Toolkit (Elephant)>>https://python-elephant.org||rel="noopener noreferrer" target="_blank"]] provides tools for the analysis of neuronal activity data, such as spike trains, local field potentials and intracellular data. In addition to providing a platform for sharing analysis codes from different laboratories, Elephant provides a consistent and homogeneous framework for data analysis, built on a modular foundation. The underlying data model is the Neo library, a framework which easily captures a wide range of neuronal data types and methods, including dozens of file formats and network simulation tools. A common data description, as provided by the Neo library, is essential for developing interoperable analysis workflows.
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57 57  Alessandra Stella|(% style="width:626px" %)Highlights two methods for detecting hidden spatio-temporal patterns in spike data.
58 58  |(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
59 59  |(% style="width:300px" %)Surrogate_techniques|(% style="width:267px" %)Peter Bouss|(% style="width:626px" %)Learn how to use different surrogate methods for spike trains to assist in formulating statistical null hypotheses in the presence of non-stationarity.
72 +|(% style="width:300px" %)NEST-Elephant|(% style="width:267px" %)(((
73 +Jessica Mitchell
60 60  
75 +Moritz Kern
76 +)))|(% style="width:626px" %)Learn how to simulate a neural network with NEST, analyse the results with Elephant and visualize results with Viziphant.
77 +
78 +== List of past events ==
79 +
80 +(((
81 +November 10, 2022** Simulate with EBRAINS (Online)**
82 +Agenda: [[https:~~/~~/flagship.kip.uni-heidelberg.d/jss/HBPm?m=showAgenda&meetingID=242>>https://flagship.kip.uni-heidelberg.de/jss/HBPm?m=showAgenda&meetingID=242]]
83 +
84 +
85 +July 1, 2022 **Satellite tutorial at the annual CNS meeting (Online)**
86 +Program: [[https:~~/~~/ocns.github.io/SoftwareWG/pages/software-wg-satellite-tutorials-at-cns-2022.html>>https://ocns.github.io/SoftwareWG/pages/software-wg-satellite-tutorials-at-cns-2022.html]]
87 +
88 +
89 +June 13-15, 2022 **BASSES workshop (Rome, Italy)**
90 +Program: [[https:~~/~~/www.humanbrainproject.eu/en/education/ebrains- workshops/basses/>>https://www.humanbrainproject.eu/en/education/ebrains-workshops/basses/]]
91 +
92 +
61 61  
62 62  )))
95 +)))
63 63  
64 -
65 65  (% class="col-xs-12 col-sm-4" %)
66 66  (((
67 67  {{box title="**Contents**"}}