Test-retest reliability of functional connectivity in depressed adolescents

Access the preprint here

Authors

Chris C. Camp, Stephanie Noble, Dustin Scheinost, Argyris Stringaris, Dylan M. Nielson

Abstract

This repository contains the code and data used in Test-retest reliability of functional connectivity in depressed adolescents. This work investigates the reliability of fMRI functional connectivity in a longitudinal dataset of adolescents with and without major depressive disorder. We leverage univariate (intraclass correlation coefficient) and multivariate (fingerprinting and discriminability) reliability metrics to conduct a comprehensive analysis of reliability over a one year period. We did not find strong evidence for an association between depression and reliability; both groups had low univariate reliability and high multivariate reliability.
Preprocessing was conducted in Python, and most analyses were conducted in R. Please reach out to the corresponding author (Chris C. Camp) with any questions.

Where/how to get the data

Connectomes are available on OSF Imaging data is available on OpenNeuro

How to install dependencies

R Code: Install renv.lock using Renv

List of steps to reproduce results

Preprocessing

Filename	Description	Input	Output
notebooks/run_fmriprepv21.0.0.ipynb	Run fmriprep	bids data	fmripreped derivatives
fmriprep group report	Run fmriprep group report command line tool	fmripreped derivatives
notebooks/add_additional_confounds.ipynb	Add additional confounds to fmriprep files	fmripreped derivatives	fmripreped derivatives
notebooks/prep_tables.ipynb	Create tables for subsequent processing	fmripreped derivatives	summary tables
notebooks/extract_all_timeseries.ipynb	Extract all the timeseries	fmripreped derivatives, summary tables, atlas	extracted timeseries (OpenNeuro)
notebooks/rs_connectivity.ipynb	Generate connectivity matrices	subject dataframe with paths to timeseries (OpenNeuro)	connectivity matrices, updated subject dataframe
notebooks/prep_icc_clean.ipynb	Create dataframe of vectorized connectivity matrices	connectivity matrices (OSF)	[connectivity dataframe]

Analysis

Filename	Description	Input	Output
icc_bootstrap_main.R	Creates slurm commands for bootstrapped ICCs using bootrun script	subject dataframe, vectorized connectomes	slurm command file
run_icc_stats.ipynb	Maps ICCs to brain atlas	all ICC dataframe	Figure 1
markdown/reliability_analysis.R	Run analyses	subject dataframe, vectorized connectomes, all ICC dataframe, MDD ICC dataframe, HV ICC dataframe, MDD 4mo ICCs, bootstrapped FI data, bootstrapped discriminability data, differential power, group consistency	figures 2-3, SI tables 1-3, SI figures 1-3