Changes for page Elephant Tutorials

Last modified by denker on 2025/04/09 07:02
From version 6.1
edited by denker
on 2021/02/01 17:24
Change comment: There is no comment for this version
To version 12.1
edited by denker
on 2021/02/01 18:27
Change comment: There is no comment for this version

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2 2  (((
3 3  (% class="container" %)
4 4  (((
5 -= Elephant Tutorial Space =
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 -Video tutorials on data analysis using Elephant
7 +(% style="color:#4e5f70" %)Interactive video tutorials on
8 +neuronal data analysis using Elephant
8 8  )))
9 9  )))
10 10  
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23 23  
24 24  To access the tutorials, check out the drive space of this Collab. Video are available for download in the (% style="color:#f39c12" %)videos(%%) section, whereas the corresponding Jupyter notebooks are available in the (% style="color:#f39c12" %)notebooks(%%) folder. Notebooks can either be run directly on the EBRAINS Collaboratory (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.
25 25  
26 -==== Execution on the EBRAINS Collaboratory ====
27 +=== Execution on the EBRAINS Collaboratory ===
27 27  
28 28  * Open the EBRAINS lab by selecting the corresponding (% style="color:#f39c12" %)Lab(%%) menu entry on the left.
29 29  //Please note: Jupyterlab functionality is currently in beta and not yet available to non-HBP-affiliated Collaboratory users. Please check back in the near future.//
30 30  * In the lab, navigate to a particular notebook and open and execute it. To save changes you may want to make, please create a copy of the notebook in a Collab of your own (i.e., where you have write permissions).
31 31  
32 -==== Local execution ====
33 +=== Local execution ===
33 33  
34 34  * Open the EBRAINS drive by selecting the corresponding (% style="color:#f39c12" %)Drive(%%) menu entry on the left.
35 35  * Download a particular notebook and the (% style="color:#f39c12" %)requirements.txt(%%) to your computer.
36 36  * Create a Python environment based on the (% style="color:#f39c12" %)requirements.txt(%%) file. The details will depend on your particular Python setup.
37 37  
38 -
39 39  == List of available tutorials ==
40 40  
41 41  
42 42  (% style="margin-right:auto" %)
43 43  |=(% style="width: 300px;" %)Tutorial|=(% style="width: 267px;" %)Hosts and Authors|=(% style="width: 626px;" %)Content
44 -|(% style="width:300px" %)Elephant_Tutorial_-_LFP_analysis|(% style="width:267px" %)Robin Gutzen|(% style="width:626px" %)Apply basic LFP analysis techniques, such as power spectra.
45 -|(% style="width:300px" %)Elephant_Tutorial_-_Spike_analysis|(% style="width:267px" %)(((
44 +|(% style="width:300px" %)LFP_analysis|(% style="width:267px" %)Robin Gutzen|(% style="width:626px" %)Apply basic LFP analysis techniques, such as power spectra.
45 +|(% style="width:300px" %)Spike_analysis|(% style="width:267px" %)(((
46 46  Cristiano Köhler
47 47  Alexander Kleinjohann
48 48  )))|(% style="width:626px" %)Perform basic statistical analysis of spike trains from rate profiles to pair-wise correlations.
49 -|(% style="width:300px" %)Elephant_Tutorial_-_Spatio-temporal_spike_patterns|(% style="width:267px" %)Regimatas Jurkus
49 +|(% style="width:300px" %)Spatio-temporal_spike_patterns|(% style="width:267px" %)Regimatas Jurkus
50 50  Alessandra Stella|(% style="width:626px" %)Highlights two methods for detecting hidden spatio-temporal patterns in spike data.
51 -|(% style="width:300px" %)Elephant_Tutorial_-_GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
52 -|(% style="width:300px" %)Elephant_Tutorial_-_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.
51 +|(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
52 +|(% 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.
53 53  
54 54  
55 55  )))
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