Decoding Pain: Uncovering the Factors that Affect Performance of Neuroimaging-Based Pain Models

This repository contains the codes and data which are used in the following paper.

Dong Hee Lee, Sungwoo Lee, Choong-Wan Woo, Decoding Pain: Uncovering the Factors that Affect Performance of Neuroimaging-Based Pain Models, 2023, bioRxiv (link)

Dependencies

1. CanlabCore toolbox (link)
2. Mediation toolbox (link)
3. SPM12 (link)
4. MATLAB Statistics and Machine Learning Toolbox (link)

Usage

Below are the codes that allow you to generate the main figures in the manuscript.

• fig_3_litearture_survey.m
• fig_4_literature_survey.R
• fig_5_litearture_survey.m
• fig_7_benchmarking_analysis.m
• fig_8_benchmarking_analysis.m
• fig_9_benchmarking_analysis.m
• fig_10_benchmarking_analysis.m

To use these scripts, download all files and unzip the zipfile (i.e. data.zip). Open the script that you want to run in Matlab or R and set the current folder to the  working directory. Add the paths for the dependencies. The other functions (e.g., lpp_plot_boxplot.m) are necessary to create the main figures. Make sure that the functions have to be saved in the same directory with the main scripts.