bna-data-analysis / extract-brain-network

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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

Requirements

External Dependencies

Setup

  1. Install numpy, os, shutil, glob, dcm2niix, nilearn, scipy modules for python programming
  2. Install Docker/Singularity and fMRIPrep

Steps to preprocess neuroimages:

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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

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

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