Changes for page Elephant Tutorials
Last modified by denker on 2025/04/09 07:02
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... ... @@ -2,9 +2,10 @@ 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 ... ... @@ -21,35 +21,36 @@ 21 21 22 22 == Access to the tutorials == 23 23 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 HBP25 +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'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. 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 -//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). 30 +//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.// 31 +* In the lab, navigate to a particular notebook and open and execute it. 32 +** Please note that in some instances, you may need to restart the kernel for the notebooks to run (e.g., when new packages are installed by the notebook, or in case of low memory). 33 +** To save changes you may want to make to a notebook, please create a copy of the notebook in a collab of your own (i.e., a collab where you have write permissions). 31 31 32 -=== =Local execution ====35 +=== 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" %)(((46 +|(% style="width:300px" %)LFP_analysis|(% style="width:267px" %)Robin Gutzen|(% style="width:626px" %)Apply basic LFP analysis techniques, such as power spectra. 47 +|(% 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 Jurkus51 +|(% 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.53 +|(% style="width:300px" %)GPFA|(% style="width:267px" %)Simon Essink|(% style="width:626px" %)Extract low-dimensional rate trajectories from the population spike activity. 54 +|(% 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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