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 53.1
edited by moritzkern
on 2023/08/25 13:33
Change comment: There is no comment for this version

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1 -XWiki.denker
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 +
22 +{{/info}}
23 +
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.
66 +|(% style="width:300px" %)NEST-Elephant|(% style="width:267px" %)(((
67 +Jessica Mitchell
60 60  
69 +Moritz Kern
70 +)))|(% style="width:626px" %)Learn how to simulate a neural network with NEST, analyse data with Elephant and visualize results with Viziphant.
71 +
72 +== List of past events ==
73 +
74 +
75 +July 15, 2022 **CNS 2023, 32nd Annual Computational Neuroscience Meeting** (Leipzig)
76 +Program: [[https:~~/~~/www.cnsorg.org/cns-2023-meeting-program>>https://www.cnsorg.org/cns-2023-meeting-program]]
77 +
78 +
79 +April 5, 2023 **Data Analysis using Elephant (Hybrid), SMHB General Assembly**
80 +Location: Forschungszentrum Juelich, Germany
81 +
82 +
83 +(((
84 +November 10, 2022** Simulate with EBRAINS (Online)**
85 +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]]
86 +
87 +
88 +July 1, 2022 **Satellite tutorial at the annual CNS meeting (Online)**
89 +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]]
90 +
91 +
92 +June 13-15, 2022 **BASSES workshop (Rome, Italy)**
93 +Program: [[https:~~/~~/www.humanbrainproject.eu/en/education/ebrains- workshops/basses/>>https://www.humanbrainproject.eu/en/education/ebrains-workshops/basses/]]
94 +
95 +
61 61  
62 62  )))
98 +)))
63 63  
64 -
65 65  (% class="col-xs-12 col-sm-4" %)
66 66  (((
67 67  {{box title="**Contents**"}}