/landscape_of_pain_prediction

Primary LanguageMATLABMIT LicenseMIT

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

  • CanlabCore toolbox (link)
  • Mediation toolbox (link)
  • SPM12 (link)
  • 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.