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Changes for page Elephant Tutorials

Last modified by denker on 2025/04/09 07:02
From version 47.2
edited by moritzkern
on 2023/01/12 14:51
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

Summary

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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 -**Intermediate Data Analysis in Python (Hybrid)**
22 -**Session: Using Neo and Elephant for neural activity analysis**
23 -Date: Tuesday, December 6, 2022
24 -Time: tba
25 -Registration & Agenda: tba
26 -
27 -
28 -{{/info}}
29 -
30 30  == A resource for kick-starting work with the Elephant library ==
31 31  
32 32  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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70 70  |(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
71 71  |(% 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 72  
73 -== List of past events ==
74 -
75 -(((
76 -November 10, 2022** Simulate with EBRAINS (Online)**
77 -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]]
78 -
79 -
80 -July 1, 2022 **Satellite tutorial at the annual CNS meeting (Online)**
81 -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]]
82 -
83 -
84 -June 13-15, 2022 **BASSES workshop (Rome, Italy)**
85 -Program: [[https:~~/~~/www.humanbrainproject.eu/en/education/ebrains- workshops/basses/>>https://www.humanbrainproject.eu/en/education/ebrains-workshops/basses/]]
86 -
87 -
88 88  
89 89  )))
90 -)))
91 91  
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92 92  (% class="col-xs-12 col-sm-4" %)
93 93  (((
94 94  {{box title="**Contents**"}}