Yan Chao-Gan, Wang Xin-Di, Zuo Xi-Nian, Zang Yu-Feng
Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, 16 Lincui Road, Chaoyang District, Beijing, 100101, China.
Department of Child and Adolescent Psychiatry, NYU Langone Medical Center School of Medicine, New York, NY, USA.
Neuroinformatics. 2016 Jul;14(3):339-51. doi: 10.1007/s12021-016-9299-4.
Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.
脑成像研究正越来越多地致力于解码人类大脑的功能。在神经成像技术中,静息态功能磁共振成像(R-fMRI)目前正呈指数级增长。除了一般的神经成像分析软件包(如SPM、AFNI和FSL)外,还开发了REST和DPARSF以满足对R-fMRI数据处理的用户友好型工具箱日益增长的需求。为应对最近发现的R-fMRI方法学挑战,我们推出了新开发的工具箱DPABI,它是从REST和DPARSF演变而来的。DPABI纳入了头部运动控制和测量标准化方面的最新研究进展,从而允许用户使用严格的控制策略来评估结果。DPABI还强调重测信度和数据处理的质量控制。此外,DPABI为大鼠/猴子的R-fMRI数据分析提供了一个用户友好的流水线分析工具包,以反映动物成像的快速进展。此外,DPABI包括用于基于任务的功能磁共振成像、基于体素的形态计量学分析、统计分析和结果查看的预处理模块。DPABI旨在使数据分析需要更少的手动操作、耗时更少、技能要求更低、无意出错的风险更小,并且在不同研究之间更具可比性。我们预计这个开源工具箱将帮助新手和专家用户,并继续支持推进R-fMRI方法及其在临床转化研究中的应用。