AutoPI grid cell decoding

Explanation of the decoding method used for the autopi project

Table of contents

Installation

Notebooks for method explanation:

1.Simulating grid cell spike trains

2.Estimating grid orientation and spacing

3.Transforming 2D Cartesian coordinates into 2D toroidal coordinates

4.Predicting toroidal location based on grid cell activity

5.Reconstructing movement path from sequences of predicted toroidal locations

Installation

1. Python environment

Here's a step by step guide to implement the method:

Make sure you have Anaconda or Miniconda installed

First create your conda environment:

conda create -n torch python=3.8

conda activate torch

2. SpikeA package

Install the SpikeA package

cd ~/repo
git clone https://github.com/kevin-allen/spikeA.git
cd ~/repo/spikeA
pip install -e ~/repo/spikeA
cd ~/repo/spikeA/spikeA/
python setup.py build_ext --inplace

3. Pytorch

Install Pytorch

If you have GPU on your computer:

conda install pytorch torchvision torchaudio pytorch-cuda -c pytorch -c nvidia

If not:

conda install pytorch torchvision torchaudio cpuonly -c pytorch

4. Jupyter notebook

conda install -c conda-forge notebook