REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing

Xiao-Wei Song,Xiang-Yu Long,Su-Fang Li,Zhang-Ye Dong,Chao-Gan Yan,Yong He,Xi-Nian Zuo,Chao-Zhe Zhu,Yu-Feng Zang,Ben J Harrison

doi:10.1371/journal.pone.0025031

Abstract

Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST). REST was developed in MATLAB with graphical user interface (GUI). After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF), and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.). REST is an open-source package and is freely available at http://www.restfmri.net.

Highlights

Most functional magnetic resonance imaging studies focus on task-state conditions
Algorithms we introduce the three main algorithms in RESting-state functional magnetic resonance imaging (fMRI) data analysis Toolkit (REST): functional connectivity, regional homogeneity (ReHo), and amplitude of low frequency fluctuation (ALFF). 1.1
The default masks in REST were made from the a priori templates found in Statistical Parametric Mapping (SPM) as follows: the whole brain mask was from brainmask.nii with a threshold at 50% probability, the white matter mask was from white.nii with a threshold at 90% probability, and the cerebrospinal fluid (CSF) mask was from csf.nii with a threshold at 70% probability

Summary

Introduction

Most functional magnetic resonance imaging (fMRI) studies focus on task-state conditions. Two measures of local features for RS-fMRI signal analysis, ReHo and ALFF, were implemented as core features in the current version of REST. Some additional functions were implemented in REST, including DICOM sorter, linear trend removal, bandpass filtering, regression of covariates, time course extraction, statistical analysis, image calculator, and slice viewer (for result visualization, multiple comparison correction, etc.).

Results

Conclusion