https://github.com/mouseland/kesa-et-al-2019

https://github.com/mouseland/kesa-et-al-2019

Last synced: about 1 year ago
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• Host: GitHub
• URL: https://github.com/mouseland/kesa-et-al-2019
• Owner: MouseLand
• Created: 2019-10-02T15:26:42.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-11-06T00:24:27.000Z (over 6 years ago)
• Last Synced: 2024-12-25T17:27:22.753Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 67.6 MB
• Stars: 0
• Watchers: 5
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# EnsemblePursuit-- a sparse matrix factorization algorithm for extracting co-activating neurons from large-scale recordings

Ensemble Pursuit is a matrix factorization algorithm that extracts sparse neural components of co-activating cells. 



The matrix U is a sparse matrix (because of an L0 penalty in the cost function) that encodes which neurons belong to a component. V is an average timecourse of these neurons, e.g. component time course.

For more details see the  [wiki](https://github.com/mariakesa/EnsemblePursuit/wiki) and our [Statistical Analysis of Neural Data 2019 workshop poster](https://github.com/mariakesa/EnsemblePursuit/blob/master/SAND9Poster/kesa.pptx%20(1).pdf)

![Alt Text](https://github.com/MouseLand/EnsemblePursuit/blob/master/Figures/my_gif.gif)

Ensembles learned using EnsemblePursuit from recordings in V1 have Gabor receptive fields. 

![alt text](https://github.com/mariakesa/EnsemblePursuit/blob/master/Figures/ep_rec_fields.png)

Some ensembles are well explained by behavior PC's extracted from mouse orofacial movies.

![alt text](https://github.com/mariakesa/EnsemblePursuit/blob/master/Figures/Behavior.png)