The R-fMRI Course V3.0 Is Released

Dear Colleagues, 
We are pleased to announce the release of The R-fMRI Course V3.0 (!
The R-fMRI Course V3.0 is a major update since V2.1. The R-fMRI Course V3.0 systematically introduces the principles of resting-state fMRI (R-fMRI), current research, methodological issues, computational platform and its applications to brain disorders. More importantly, The R-fMRI Course V3.0 explains the data processing details for DPABI/DPABISurf/DPARSF, including data conversion, data preprocessing, temporal dynamic analysis, quality control, statistical analysis and results viewing.
A key point of The R-fMRI Course V3.0 is the video course for DPABISurf V1.1. DPABISurf is a surface-based resting-state fMRI data analysis toolbox evolved from DPABI/DPARSF, as easy-to-use as DPABI/DPARSF. DPABISurf is based on fMRIPprep 1.4.1 (Esteban et al., 2018)(RRID:SCR_016216), and based on FreeSurfer 6.0.1 (Dale et al., 1999)(RRID:SCR_001847), ANTs 2.2.0 (Avants et al., 2008)(RRID:SCR_004757), FSL 5.0.9 (Jenkinson et al., 2002)(RRID:SCR_002823), AFNI 20160207 (Cox, 1996)(RRID:SCR_005927), SPM12 (Ashburner, 2012)(RRID:SCR_007037), PALM alpha112 (Winkler et al., 2016), GNU Parallel (Tange, 2011), MATLAB (The MathWorks Inc., Natick, MA, US) (RRID:SCR_001622), Docker ( (RRID:SCR_016445), and DPABI V4.1 (Yan et al., 2016)(RRID:SCR_010501). DPABISurf provides user-friendly graphical user interface (GUI) for pipeline surface-based preprocessing, statistical analyses and results viewing, while requires no programming/scripting skills from the users.
DPABISurf is designed to make surface-based data analysis require minimum manual operations and almost no programming/scripting experience. We anticipate The R-fMRI Course V3.0 will guide users to be skilled at how to use this open-source toolbox.
The R-fMRI Course V3.0 English Version (
(Mostly recorded at The R-fMRI Workshop, July 30~31, 2019)
1. Resting-State fMRI: Current Research, Methodological Issues and Computational Platform             
2. Resting-State fMRI: Applications to Brain Disorders             
3. The REST-meta-MDD Project: towards a Neuroimaging Biomarker of Major Depressive Disorder             
4. Data Processing of Resting-State fMRI: DPARSF             
5. The R-fMRI Maps Project             
6. Surface-Based Brain Imaging Analysis and DPABISurf            
7. DPABI Animal Data Processing            
8. Temporal Dynamic Analysis            
9. DPABI: Quality Control, Statistical Analysis and Results Viewing            
10. DPABISurf: A Surface-Based Resting-State fMRI Data Analysis Toolbox            
11. Output structure of DPARSF            
12. Output structure of DPABISurf            
13. Verification of Reproducibility of R-fMRI Metrics and Reproducible Network Underpinnings of Rumination            
14. DPABI: Utilities            
15. DPABISurf Advanced: More about FreeSurfer            
The R-fMRI Course was firstly released on July 15, 2009. During the past 10 years, the course was kept updating, and received 291,425 views. We hope this major update will further help advancing R-fMRI methodology and its application to clinical translational studies.

Chao-Gan YAN, Ph.D.
Professor, Principal Investigator
Director, International Big-Data Center for Depression Research
Deputy Director, Magnetic Resonance Imaging Research Center
Institute of Psychology, Chinese Academy of Sciences
16 Lincui Road, Chaoyang District, Beijing 100101, China