MDMA Amygdala Subtype Paper

This repository contains the main scripts and code required to replicate the analyses presented in the manuscript entitled: "Negative affect circuit subtypes predict acute neural, behavioral, and affective responses to MDMA in humans."

The scripts are organized according to the main analysis steps described in the manuscript's Results section.

Repository Structure

• RMD/: Contains the main R Markdown files that perform all analysis and produce figures and tables for the paper.

  • MDMA_baseline_amy_stratification_paper_figure_forupload.Rmd: R Markdown file that runs the main analyses and produces the figures and tables for the paper, including:
    • Baseline amygdala stratification (Fig. 2b).
    • Baseline demographic and symptom characteristics by baseline stratification (Table 1, Fig. 2c, Suppl. Fig. 1).
    • MDMA of 120mg vs placebo induced acute neural, behavioral, and affective response. (Fig. 3a-3h, Suppl. Fig. 2a-2h, and Suppl. Table 1)
    • MDMA of 120mg vs placebo induced acute neural, behavioral, and affective response, with multiple imputations (Suppl. Table 2 and 3)
    • Blinding analysis (Suppl. Table 4)

• R/: Contains R scripts used for data preprocessing and loading different datasets required for the analysis.

  • MDMA_read_biotype_forupload.R: Script to load and filter biotype data.
  • mdma_read_redcap_data_forupload.R: Script to load and preprocess data from REDCap collected questionnaire data, including 5D-ASC, VAS, and face likability.
  • mdma_read_webneuro_data_forupload.R: Script to load and filter data from WebNeuro, a neurocognitive assessment tool.

Installation and Setup

1. Clone the repository:

   git clone https://github.com/WilliamsPanLab/MDMA-Amygdala-subtype.git
   cd MDMA-Amygdala-subtype

Running the Analysis

Main Analysis and Figure Generation:

• Open and run the R Markdown file in the RMD/ folder:
  • MDMA_baseline_amy_stratification_paper_figure_forupload.Rmd
• This file will run the full analysis and generate all tables and figures required for the manuscript.
• If you encounter any errors during knitting, ensure all the source files are correctly linked and accessible.

Notes

• Data Accessibility: The scripts assume you have access to the raw datasets required for analysis. Please contact the authors if you need more information about the datasets.
• Troubleshooting: If you encounter issues during knitting, particularly related to loading functions or missing columns, double-check that all source scripts in the R/ directory are correctly referenced in the R Markdown file.