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

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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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Acknowledgments

The authors appreciate the editorial assistance and support of Dr. Francisco X. Castellanos. Dr. Zuo acknowledges the funding support from the National Basic Research (973) Program (2015CB351702). Dr. Yan and Dr. Zuo acknowledge the support of the Hundred Talents Program of the Chinese Academy of Sciences (CGY: Y5CX072006; XNZ: Y2CS112006) and Beijing Municipal Science & Technology Commission. Dr. Yan and Dr. Zuo are also members of the international collaboration team (under its trial stage with PI: Dr. Xun Liu) supported by the CAS K.C. Wong Education Foundation. Dr. Zang is partly supported by “Qian Jiang Distinguished Professor” program.

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Authors and Affiliations

  1. 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

    Chao-Gan Yan & Xi-Nian Zuo

  2. Department of Child and Adolescent Psychiatry, NYU Langone Medical Center School of Medicine, New York, NY, USA

    Chao-Gan Yan

  3. State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China

    Xin-Di Wang

  4. Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China

    Yu-Feng Zang

  5. Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China

    Yu-Feng Zang

  6. Department of Psychology, College of Education, Hangzhou Normal University, Hangzhou, China

    Yu-Feng Zang

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  1. Chao-Gan Yan
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  2. Xin-Di Wang
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  3. Xi-Nian Zuo
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  4. Yu-Feng Zang
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Correspondence to Chao-Gan Yan.

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DPABI is hosted at the R-fMRI Network (http://rfmri.org), which is a non-commercial resource for the R-fMRI community.

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Yan, CG., Wang, XD., Zuo, XN. et al. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. Neuroinform 14, 339–351 (2016). https://doi.org/10.1007/s12021-016-9299-4

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