/timecorr-paper

Paper and code for High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns

Primary LanguageJupyter NotebookMIT LicenseMIT

What is the neural code?

DOI

This repository contains data and code used to produce the paper High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns by Lucy L.W. Owen, Thomas H. Chang, and Jeremy R. Manning. You may also be interested in our timecorr Python toolbox for calculating high-order dynamic correlations in timeseries data; the methods implemented in our timecorr toolbox feature prominently in our paper.

This repository is organized as follows:

root
└── code : all code used in the paper
    ├── notebooks : jupyter notebooks for paper analyses and instructions for downloading the data
    └── scripts : python scripts used to run analyses on a computing cluster
    └── figs : pdf and png copies of figures
└── data : create this folder by extracting the following zip archive into your clone of this repository's folder: https://drive.google.com/file/d/1CZYe8eyAkZFuLqfwwlKoeijgkjdW6vFs
└── paper : all files to generate paper
    └── figs : pdf copies of each figure

Content of the data folder is provided here. We also include a Dockerfile to reproduce our computational environment. Instruction for use are below:

Docker setup

  1. Install Docker on your computer using the appropriate guide below:
  2. Launch Docker and adjust the preferences to allocate sufficient resources (e.g. > 4GB RAM)
  3. Build the docker image by opening a terminal in this repo folder and enter docker build -t timecorr_paper .
  4. Use the image to create a new container
    • The command below will create a new container that will map your local copy of the repository to /mnt within the container, so that location is shared between your host OS and the container. The command will also share port 9999 with your host computer so any jupyter notebooks launched from within the container will be accessible in your web browser.
    • docker run -it -p 9999:9999 --name Timecorr_paper -v $PWD:/mnt timecorr_paper
    • You should now see the root@ prefix in your terminal, if so you've successfully created a container and are running a shell from inside!
  5. To launch any of the notebooks: jupyter notebook

Using the container after setup

  1. You can always fire up the container by typing the following into a terminal
    • docker start --attach Timecorr_paper
    • When you see the root@ prefix, you're inside the container
  2. Stop a running jupyter notebook server with ctrl + c
  3. Close a running container with ctrl + d or exit from the same terminal window you used to launch the container, or docker stop Timecorr_paper from any other terminal window