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2	2	(((
3	3	(% class="container" %)
4	4	(((
5		-= Elephant Tutorial Space =
	5	+= Elephant Tutorial Space[[image:https://elephant.readthedocs.io/en/latest/_static/elephant_logo_sidebar.png||alt="Elephant logo" style="float:right"]] =
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7		-Video tutorials on data analysis using Elephant
	7	+Video tutorials on neuronal data analysis using Elephant
8	8	)))
9	9	)))
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19	19	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.
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	21	+
21	21	== Access to the tutorials ==
22	22
23		-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 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.
	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.
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	26	+=== Execution on the EBRAINS Collaboratory ===
	27	+
	28	+* Open the EBRAINS lab by selecting the corresponding (% style="color:#f39c12" %)Lab(%%) menu entry on the left.
	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	+* 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	+
	32	+=== Local execution ===
	33	+
	34	+* Open the EBRAINS drive by selecting the corresponding (% style="color:#f39c12" %)Drive(%%) menu entry on the left.
	35	+* Download a particular notebook and the (% style="color:#f39c12" %)requirements.txt(%%) to your computer.
	36	+* Create a Python environment based on the (% style="color:#f39c12" %)requirements.txt(%%) file. The details will depend on your particular Python setup.
	37	+
25	25	== List of available tutorials ==
26	26
	40	+
27	27	(% style="margin-right:auto" %)
28	28	|=(% style="width: 300px;" %)Tutorial|=(% style="width: 267px;" %)Hosts and Authors|=(% style="width: 626px;" %)Content
29		-|(% style="width:300px" %)Elephant_Tutorial_-_LFP_analysis|(% style="width:267px" %)Robin Gutzen|(% style="width:626px" %)Apply basic LFP analysis techniques, such as power spectra.
30		-|(% style="width:300px" %)Elephant_Tutorial_-_Spike_analysis|(% style="width:267px" %)(((
	43	+|(% style="width:300px" %)LFP_analysis|(% style="width:267px" %)Robin Gutzen|(% style="width:626px" %)Apply basic LFP analysis techniques, such as power spectra.
	44	+|(% style="width:300px" %)Spike_analysis|(% style="width:267px" %)(((
31	31	Cristiano Köhler
32	32	Alexander Kleinjohann
33	33	)))|(% style="width:626px" %)Perform basic statistical analysis of spike trains from rate profiles to pair-wise correlations.
34		-|(% style="width:300px" %)Elephant_Tutorial_-_Spatio-temporal_spike_patterns|(% style="width:267px" %)Regimatas Jurkus
	48	+|(% style="width:300px" %)Spatio-temporal_spike_patterns|(% style="width:267px" %)Regimatas Jurkus
35	35	Alessandra Stella|(% style="width:626px" %)Highlights two methods for detecting hidden spatio-temporal patterns in spike data.
36		-|(% style="width:300px" %)Elephant_Tutorial_-_GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
37		-|(% 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.
	50	+|(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity.
	51	+|(% 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.
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40	40	)))