/r21-cardgame

Code, data, and results from Aim 1 of our R21 grant.

Primary LanguageHTMLMIT LicenseMIT

Alpha-tACS and Reward-Related Corticostriatal Connectivity

This project has been carried out in collaboration with Bart Krekelberg (Rutgers-Newark). This repository contains much of the imaging code related to our project and will be merged with Bart's code prior to publication. Imaging data will be shared via OpenNeuro when the manuscript is posted on bioRxiv or accepted for publication.

A few prerequisites and recommendations

  • Understand BIDS and be comfortable navigating Linux
  • Install FSL
  • Install miniconda or anaconda
  • Make singularity container for fmriprep (version: 20.1.0).

Notes on repository organization and files

  • Some of the contents of this repository are not tracked (.gitignore) because the files are large and we do not yet have a nice workflow for datalad. These folders include derivatives/fsl and derivatives/fmriprep.
  • Tracked folders and their contents:
    • code: analysis code
    • templates: fsf template files used for FSL analyses
    • masks: images used as masks, networks, and seed regions in analyses
    • logs: various logs and notes created by some of our analysis code

Basic commands to reproduce our analyses

# get code and data (TBD)
git clone https://github.com/DVS-Lab/r21-cardgame
cd r21-cardgame
datalad install <TBD url> # get bids data (will need to rename to bids to match script)

# run preprocessing and generate confounds and timing files for analyses
bash code/run_fmriprep.sh
python code/MakeConfounds.py --fmriprepDir="derivatives/fmriprep"
bash code/run_gen3colfiles.sh

# run statistics
bash code/run_L1stats.sh
bash code/run_L2stats.sh
bash code/run_L3stats.sh

Acknowledgments

This work was supported, in part, by a grant from the National Institutes of Health (R21-MH113917). DVS was a Research Fellow of the Public Policy Lab at Temple University during the course of this project (2019-2020 academic year).