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Neuroinformatics

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01.07.2016 | Software Original Article

DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging

verfasst von: Chao-Gan Yan, Xin-Di Wang, Xi-Nian Zuo, Yu-Feng Zang

Erschienen in: Neuroinformatics | Ausgabe 3/2016

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Abstract

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.

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Titel: DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging
verfasst von: Chao-Gan Yan
Xin-Di Wang
Xi-Nian Zuo
Yu-Feng Zang
Publikationsdatum: 01.07.2016
Verlag: Springer US
Erschienen in: Neuroinformatics / Ausgabe 3/2016
Print ISSN: 1539-2791
Elektronische ISSN: 1559-0089
DOI: https://doi.org/10.1007/s12021-016-9299-4

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