BRANT: A Versatile and Extendable Resting-state fMRI Toolkit
- 1Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China
- 2Institute of Automation, Chinese Academy of Sciences, China
- 3CAS Center for Excellence in Brain Science, Institute of Automation, Chinese Academy of Sciences, China
- 4Sino Danish Centre for Education and Research (SDC), China
- 5Sino-Danish College, University of Chinese Academy of Sciences (UCAS), China
- 6University of Chinese Academy of Sciences (UCAS), China
- 7School of Biomedical Engineering, Southern Medical University, China
- 8Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, China
- 9Queensland Brain Institute, The University of Queensland, Australia
Data processing toolboxes for resting-state functional MRI (rs-fMRI) have provided us with a variety of functions and user friendly graphic user interfaces (GUIs). However, many toolboxes only cover a certain range of functions, and use exclusively designed GUIs. To facilitate data processing and alleviate the burden of manually drawing GUIs, we have developed a versatile and extendable MATLAB-based toolbox, BRANT (BRAinNetome fmri Toolkit), with a wide range of rs-fMRI data processing functions and code-generated GUIs. During the implementation, we have also empowered the toolbox with parallel computing techniques, efficient file handling methods for compressed file format, and one-line scripting. With BRANT, users can find rs-fMRI batch processing functions for preprocessing, brain spontaneous activity analysis, functional connectivity analysis, complex network analysis, statistical analysis, and results visualization, while developers can quickly publish scripts with code-generated GUIs.
Keywords: brant, Resting-state fMRI, code-generated GUI, preprocessing, visualization
Received: 13 Jan 2018;
Accepted: 24 Jul 2018.
Edited by:Pedro A. Valdes-Sosa, Clinical Hospital of Chengdu Brain Science Institute, China
Reviewed by:Jiaojian Wang, University of Electronic Science and Technology of China, China
Feng Shi, Cedars-Sinai Medical Center, United States
Ye Tian, The University of Melbourne, Australia
Copyright: © 2018 Xu, Liu, Zhan, Ren and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Yong Liu, Chinese Academy of Sciences, Brainnetome Center, Institute of Automation, Beijing, 100190, China, email@example.com