Changes for page Elephant Tutorials

Last modified by denker on 2025/04/09 07:02
From version 51.1
edited by moritzkern
on 2023/04/19 18:02
Change comment: There is no comment for this version
To version 31.1
edited by denker
on 2022/06/29 11:31
Change comment: There is no comment for this version

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1 -XWiki.moritzkern
1 +XWiki.denker
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7 7  (% style="color:#4e5f70" %)Interactive video tutorials on
8 8  neuronal data analysis using Elephant
9 9  
10 -
10 +(% style="color:#e74c3c" %)**Upcoming: CNS 2022**
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 -
23 -
24 -
25 -{{/info}}
26 -
27 27  == A resource for kick-starting work with the Elephant library ==
28 28  
29 29  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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66 66  Alessandra Stella|(% style="width:626px" %)Highlights two methods for detecting hidden spatio-temporal patterns in spike data.
67 67  |(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
68 68  |(% 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.
69 -|(% style="width:300px" %)NEST-Elephant|(% style="width:267px" %)(((
70 -Jessica Mitchell
71 71  
72 -Moritz Kern
73 -)))|(% style="width:626px" %)Learn how to simulate a neural network with NEST, analyse data with Elephant and visualize results with Viziphant.
74 -
75 -== List of past events ==
76 -
77 -
78 -April 5, 2023 **Data Analysis using Elephant (Hybrid), SMHB General Assembly**
79 -Location: Forschungszentrum Juelich, Germany
80 -
81 -
82 -(((
83 -November 10, 2022** Simulate with EBRAINS (Online)**
84 -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]]
85 -
86 -
87 -July 1, 2022 **Satellite tutorial at the annual CNS meeting (Online)**
88 -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]]
89 -
90 -
91 -June 13-15, 2022 **BASSES workshop (Rome, Italy)**
92 -Program: [[https:~~/~~/www.humanbrainproject.eu/en/education/ebrains- workshops/basses/>>https://www.humanbrainproject.eu/en/education/ebrains-workshops/basses/]]
93 -
94 -
95 95  
96 96  )))
97 -)))
98 98  
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99 99  (% class="col-xs-12 col-sm-4" %)
100 100  (((
101 101  {{box title="**Contents**"}}