Changes for page Elephant Tutorials

Last modified by denker on 2026/01/22 10:27
From version 62.1
edited by denker
on 2026/01/22 10:27
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To version 25.1
edited by denker
on 2021/02/03 11:35
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2 2  (((
3 3  (% class="container" %)
4 4  (((
5 -= (% style="color:#f39c12" %)Elephant Tutorial Space[[image:https://elephant.readthedocs.io/en/latest/_static/elephant_logo_sidebar.png||alt="Elephant logo" data-xwiki-image-style-alignment="end"]](%%) =
5 += (% style="color:#f39c12" %)Elephant Tutorial Space[[image:https://elephant.readthedocs.io/en/latest/_static/elephant_logo_sidebar.png||alt="Elephant logo" style="float:right"]](%%) =
6 6  
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 for the HBP Student Conference workshop ~-~-**
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 -March 17, 2026: Elephant Training as part of the **[[//EduBrains Training Series//>>https://foldercase.com/proext.php?pid=466]]**
22 -\\June 15-July 31, 2026 **Advanced Neural Data Analysis and Neuroinformatics ANDA-NI (Jülich, Germany)**
23 -Website: [[https:~~/~~/andani.info>>https://andani.info]]
24 -{{/info}}
25 -
26 26  == A resource for kick-starting work with the Elephant library ==
27 27  
28 28  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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29 29  
30 30  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.
31 31  
32 -In addition, tutorials presented at various workshops and schools are collected in this collab.
33 33  
34 -
35 35  == Access to the tutorials ==
36 36  
37 37  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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54 54  == List of available tutorials ==
55 55  
56 56  
57 -(% style="margin-right:auto; width:1429.5px" %)
58 -|=(% style="width: 300px;" %)Tutorial|=(% style="width: 267px;" %)Hosts and Authors|=(% style="width: 848px;" %)Content
59 -|(% style="width:300px" %)LFP_analysis|(% style="width:267px" %)Robin Gutzen|(% style="width:848px" %)Apply basic LFP analysis techniques, such as power spectra.
47 +(% style="margin-right:auto" %)
48 +|=(% style="width: 300px;" %)Tutorial|=(% style="width: 267px;" %)Hosts and Authors|=(% style="width: 626px;" %)Content
49 +|(% style="width:300px" %)LFP_analysis|(% style="width:267px" %)Robin Gutzen|(% style="width:626px" %)Apply basic LFP analysis techniques, such as power spectra.
60 60  |(% style="width:300px" %)Spike_analysis|(% style="width:267px" %)(((
61 61  Cristiano Köhler
62 62  Alexander Kleinjohann
63 -)))|(% style="width:848px" %)Perform basic statistical analysis of spike trains from rate profiles to pair-wise correlations.
53 +)))|(% style="width:626px" %)Perform basic statistical analysis of spike trains from rate profiles to pair-wise correlations.
64 64  |(% style="width:300px" %)Spatio-temporal_spike_patterns|(% style="width:267px" %)Regimatas Jurkus
65 -Alessandra Stella|(% style="width:848px" %)Highlights two methods for detecting hidden spatio-temporal patterns in spike data.
66 -|(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:848px" %)Extract low-dimensional rate trajectories from the population spike activity.
67 -|(% style="width:300px" %)Surrogate_techniques|(% style="width:267px" %)Peter Bouss|(% style="width:848px" %)Learn how to use different surrogate methods for spike trains to assist in formulating statistical null hypotheses in the presence of non-stationarity.
68 -|(% style="width:300px" %)NEST-Elephant|(% style="width:267px" %)(((
69 -Jessica Mitchell
70 -Moritz Kern
71 -)))|(% style="width:848px" %)Learn how to simulate a neural network with NEST, analyse data with Elephant and visualize results with Viziphant.
55 +Alessandra Stella|(% style="width:626px" %)Highlights two methods for detecting hidden spatio-temporal patterns in spike data.
56 +|(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
57 +|(% 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 external teaching and training resources ==
74 -
75 -* **IBOTS Code** offers a wealth of teaching and training material, including Neo and Elephant training, at: [[https:~~/~~/ibots-bonn.de/teaching/>>https://ibots-bonn.de/teaching/]]
76 -
77 -== ==
78 -
79 -== List of past events ==
80 -
81 -
82 -August 25-26, 2025 **INCF-SeRC-EBRAINS-Sweden workshop on FAIR neuroscience 2025 on Managing and Analyzing electrophysiology data using Neo and Elephant (Stockholm, Sweden)**
83 -Program: [[https:~~/~~/www.ebrains.eu/news-and-events/tutorials-and-users-day-2025>>https://www.ebrains.eu/news-and-events/tutorials-and-users-day-2025]]
84 -
85 -
86 -March 12, 2025 **Accelerate Your Neuroscience Research with EBRAINS** **(Heidelberg, Germany)**
87 -Program: [[https:~~/~~/www.ebrains.eu/news-and-events/tutorials-and-users-day-2025>>https://www.ebrains.eu/news-and-events/tutorials-and-users-day-2025]]
88 -
89 -
90 -Sept. 24-Nov. 8, 2024 **Advanced Neural Data Analysis and Neuroinformatics ANDA-NI (Jülich, Germany)**
91 -Website: [[https:~~/~~/andani.info>>https://andani.info]]
92 -
93 -
94 -July 15, 2023 **CNS 2023, 32nd Annual Computational Neuroscience Meeting (Leipzig)**
95 -Program: [[https:~~/~~/www.cnsorg.org/cns-2023-meeting-program>>https://www.cnsorg.org/cns-2023-meeting-program]]
96 -
97 -
98 -April 5, 2023 **Data Analysis using Elephant (Hybrid), SMHB General Assembly (Jülich, Germany)**
99 -
100 -
101 -(((
102 -November 10, 2022** Simulate with EBRAINS (Online)**
103 -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]]
104 -
105 -
106 -July 1, 2022 **Satellite tutorial at the annual CNS meeting (Online)**
107 -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]]
108 -
109 -
110 -June 13-15, 2022 **BASSES workshop (Rome, Italy)**
111 -Program: [[https:~~/~~/www.humanbrainproject.eu/en/education/ebrains- workshops/basses/>>https://www.humanbrainproject.eu/en/education/ebrains-workshops/basses/]]
112 -
113 -
114 114  
115 115  )))
116 -)))
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119 119  (((
120 120  {{box title="**Contents**"}}
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