Multi-area Multi-sensory Representations in Freely Moving Rats
Use Case SGA2-SP3-003: Analysis pipeline for representation and analysis of electrophysiological data
To be discussed Author order, contributions,...:
Experiments: Julien Fiorilli2
Implementation: Regimantas Jurkus1, Julien Fiorilli2, Pietro Marchesi2, Thijs Ruikes2
Lead: Michael Denker1, Sonja Grün1, Cyril Pennartz2
1) Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany
2) Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
Demonstration of the analysis of electrophysiological data
A notebook that demonstrates how to apply the pipeline to a complex dataset.
The aim of this note-book is twofold. Firstly,we aim to demonstrate the advantage of a common and shared data representation format for a challenging and complex electrophysiology dataset. The second aim is to showcase the first part of a pipeline for analysing for population-level data, including parallel spiking activity, paired with and behavioural and cognitive state variables.
This Collab is aimed at experimental and computational neuroscientists interested in the usage of the Neo and Elephant tools in performing data analysis of spiking data.
Executing the analysis notebook
- Copy the collab drive to your drive space
- Open the Drive from the left menu
- Select "Demonstrator_Use_Case_SGA2-SP3-003.ipynb", the "Figures" folder, and the "Data" folder
- Copy the selected items, and select the destination 'My Library' from the dropdown 'Other Libraries'
- Start a Jupyter Hub instance
In another browser, open https://lab.ebrains.eu
- Run the notebook
In the Jupyter Hub, navigate to `drive/My Libraries/My Library/Demonstrator_Use_Case_SGA2-SP3-003.ipynb`, and run the notebook.
License (to discuss)
All text and example data in this collab is licensed under Creative Commons CC-BY 4.0 license. Software code is licensed under a modified BSD license.
Acknowledgments
This open source software code was developed in part or in whole in the Human Brain Project, funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2).