https://github.com/themattinthehatt/rlvm

MATLAB implementation of a rectified latent variable model for analysis of neural time series data.
https://github.com/themattinthehatt/rlvm

latent-variable-models neural-data-analysis neuroscience

Last synced: about 1 year ago
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MATLAB implementation of a rectified latent variable model for analysis of neural time series data.

• Host: GitHub
• URL: https://github.com/themattinthehatt/rlvm
• Owner: themattinthehatt
• License: gpl-3.0
• Created: 2016-07-18T02:26:48.000Z (almost 10 years ago)
• Default Branch: v2.0
• Last Pushed: 2017-09-26T18:50:38.000Z (almost 9 years ago)
• Last Synced: 2025-02-15T23:28:18.891Z (over 1 year ago)
• Topics: latent-variable-models, neural-data-analysis, neuroscience
• Language: Matlab
• Size: 212 KB
• Stars: 3
• Watchers: 4
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
## Rectified Latent Variable Model (RLVM) 

The RLVM is a latent variable model developed to study large populations of simultaneously recorded neurons. 

For more information regarding the mathematical formulation of the model, see the preprint on [bioRxiv](http://biorxiv.org/content/early/2016/08/29/072173). The `doc` directory contains scripts that show how to use the model on several simulated datasets. 

The RLVM optimizes model parameters using [Mark Schmidt's](http://www.cs.ubc.ca/~schmidtm/) minFunc package, which is located in the `lib` directory and should work out of the box. If not you may need to run the mexAll.m file from the `lib/minFunc_2012` directory.

### Update!

This is the branch for version 2.0, which contains the following new features:

- autoencoder can now contain an arbitrary number of layers

- refactoring of model structure makes managing large models easier

- stimulus subunits can now be shared across cells

v2.0 is still not fully tested or documented. See the master branch for the most recent stable version.