Data-Driven Network Neuroscience: On Data Collection and Benchmark

This repository contains a package of scripts and codes used in the paper to convert raw functional images to connectivity matrices using fMRIPrep (https://fmriprep.org/en/stable/)

Samples of the raw MRI / preprocessed outputs / matrices

• A sample TaoWu subject can be accessed here: https://figshare.com/s/dfadce2aaf5d0d94d403?file=36742629
• The fMRIPrep outputs of the same subject fully preprocessed can be accessed here: https://figshare.com/s/dfadce2aaf5d0d94d403?file=36742644
• The set of connectivity matrices (using correlation) generated for the same subject can be accessed here: https://figshare.com/s/dfadce2aaf5d0d94d403?file=36742722

Requirements

• Containerized execution environment:
  • Docker (https://www.nipreps.org/apps/docker/) or
  • Singularity (https://www.nipreps.org/apps/singularity/)

External Dependencies

• fMRIPrep (version 20.2.3 - https://fmriprep.org/en/stable/index.html)
• dcm2niix (https://github.com/rordenlab/dcm2niix)
• nilearn (https://nilearn.github.io/stable/index.html)

Setup

1. Install numpy, os, shutil, glob, dcm2niix, nilearn, scipy modules for python programming
2. Install Docker/Singularity and fMRIPrep
   • Installing fMRIPrep requires several steps and sorting out dependencies and a freesurfer license (free to acquire). We recommend following this guide (https://andysbrainbook.readthedocs.io/en/latest/OpenScience/OS/fMRIPrep.html)

Steps to preprocess neuroimages:

Step A: Data Collection and Selection

Access Link for Neurocon and TaoWu Dataset : http://fcon_1000.projects.nitrc.org/indi/retro/parkinsons.html A sample TaoWu subject can be accessed here: https://figshare.com/s/dfadce2aaf5d0d94d403?file=36742629

Access Link for ABIDE/ADNI/PPMI : https://ida.loni.usc.edu/login.jsp.

• Each fMRI image needs to be accompanied with a structural T1-weighted (T1w) image acquired from the same subject (ideally) in the same scan session

Step B: BIDS Format Conversion

Raw T1w/fMRI data are in DICOM or NifTi format

• This step is to convert raw MRI data in either DICOM or NifTi into BIDS format (https://bids.neuroimaging.io/)
  • ABIDE_Nifti2BIDS.py - To convert raw MRI data (NifTi format) to BIDS - For ABIDE dataset
  • ADNI_PPMI_DCM2BIDS.py - To convert raw MRI data (DICOM format) to BIDS - For PPMI and ADNI dataset
  • Neurocon and TaoWu dataset are NifTi files and are already BIDS formatted

Step C: fMRIPrep Preprocessing

Make sure you have installed fMRIPrep correctly using the information and guides from the links above.

• Preprocess BIDS formatted neuroimages (1 T1w image and 1 fMRI BOLD image) using fMRIPrep
  • fmriprep_shellscript.sh - Script to execute fmriprep preprocessing
• fMRIPrep outputs a number of BIDS Derivative compliant files
  • For details on each file: https://fmriprep.org/en/stable/outputs.html

A sample of a fully preprocessed TaoWu subject (and its outputs) can be accessed here: https://figshare.com/s/dfadce2aaf5d0d94d403?file=36742644

Steps D, E, and F: Parcellation and ROI Definition, Connectivity Matrix Extraction, and Graphical Brain Network

• Convert preprocessed Nifti images into connectivity matrices
  • ConnectivityMatrices.py - Code to generate connectivity matrices

Perform Experimental Analysis

• The codes we used to run our empirical analysis
  • NIPS_paper_gridsearch_experiments.py
  • EdgeWeightsStatistics.py

Note: Input/Output location and the required modification are detailed within the python codes