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The code for the Hidden Markov Model Generalized Linear Model used to model discrete complex behavior profiles of mice using neural activity

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Introduction

This repository contains the code for the Hidden Markov Model Generalized Linear Model (HMM GLM) developed in the Tye Lab for the modeling of complex behavior profiles in mice using neural activity. The code is completely written in MATLAB, and is optimized to be utilize multiple cores on a CPU. It has not yet been optimized to run on a GPU.

Tips for usage

The primary functions used for training and testing are "train" and "predict_likelihood_onestep". There are multiple other functions for likelihood comptutation, training and predictions. However, these are all currently experimental.

  • The document will be updated further post publication.

Citation

If you use this code, please cite:
Nancy Padilla-Coreano, Kanha Batra, Makenzie Patarino et al. A cortical-hypothalamic circuit decodes social rank and promotes dominance behavior, 04 November 2020, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-94115/v1]

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The code for the Hidden Markov Model Generalized Linear Model used to model discrete complex behavior profiles of mice using neural activity

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