Changes for page Elephant Tutorials

Last modified by denker on 2025/04/09 07:02
From version 48.1
edited by denker
on 2023/03/17 10:39
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To version 27.1
edited by denker
on 2021/04/16 21:38
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Summary

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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" %)**~-~- in beta  ~-~-**
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 -
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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33 33  
34 34  In this collaborative space, we provide hands on video tutorials based on Jupyter notebooks that showcase various types of data analysis, from simple to advanced. Most notebooks are based on a common dataset published at [[https:~~/~~/gin.g-node.org/INT/multielectrode_grasp>>https://gin.g-node.org/INT/multielectrode_grasp]] (for details cf. Brochier et al (2018) Scientific Data 5, 180055. [[https:~~/~~/doi.org/10.1038/sdata.2018.55>>url:https://doi.org/10.1038/sdata.2018.55]]). All video tutorials are approximately 30 minutes in length.
35 35  
36 -In addition, tutorials presented at various workshops and schools are collected in this collab.
37 37  
38 -
39 39  == Access to the tutorials ==
40 40  
41 41  To access the tutorials, check out the drive space of this collab. The Jupyter notebooks are available in the (% style="color:#f39c12" %)notebooks(%%) folder, and links to the (% style="color:#f39c12" %)videos(%%) are embedded within each notebook. Notebooks can either be run directly on the EBRAINS Collaboratory's JupyterLab service (currently limited to HBP-affiliated members), or downloaded and run locally. For local execution, please use the provided (% style="color:#f39c12" %)requirements.txt(%%) file to generate an appropriate Python environment.
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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**"}}
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