joel-shor / Context-Classifier

Thesis work - computational neuroscience, ML, bioinformatics

Joel Shor, 5-26-2014 [e-mail]

1.0 Introduction

The goal of this project is to train a classifier that takes a sequence of spike data returns the value of the latent variable 'context' of each moment. The spike data are unpublished data from Dmitriy Aronov (Tank Lab, Princeton) taken from rats running spatial tasks in virtual reality. Recordings are LFPs taken from 8 tetrodes. Data is organized by animal, session, and tetrode.

See Docs/Thesis.pdf for more background on the neuroscience, data, and ML algorithms.

Drivers are

python LocationAnimation.py

python MakeFig.py [fig_name]

python RunScript.py [script_name]

python RunScript.py {number_of_folds}