DPABI Training Camp

English edition with DPABI / DPABISurf / DPARSF

December 14–18, 2026  | Monday–Friday

09:00–12:00 daily, Beijing time (UTC+8)

Live online  • English instruction  •  Five sessions over 15 scheduled hours

We invite you to join a five-day online training camp on the foundations of resting-state functional magnetic resonance imaging (R‑fMRI) and practical data analysis with DPABI, DPABISurf and DPARSF. Led by Dr. Chao‑Gan Yan, the camp will connect the principles behind the methods with guided software practice, helping you build an analysis workflow for your own research.

The programme covers both volume-based analysis with DPARSF and cortical surface-based analysis with DPABISurf, followed by quality control, statistical analysis and results visualization. Participants are encouraged to bring research questions and their own data for discussion.

What you will learn

• Understand the principles of R‑fMRI and its applications in psychology, cognitive neuroscience and brain disorders.
• Organize imaging data, work through preprocessing and assess data quality using the DPABI software suite.
• Explore cortical reconstruction and surface-based functional and structural measures with DPABISurf.
• Perform group-level statistical analyses, apply multiple-comparison correction and display results.
• Recognize key methodological choices and discuss how to apply the workflow to a research project.

Who should attend

Researchers, clinicians, graduate students and advanced undergraduates in psychology, neuroscience, biomedical engineering, medicine and related fields are welcome. The camp is suitable for beginners in brain imaging. Prior programming experience is not required for the core graphical-interface exercises.

Lecturer

Chao‑Gan Yan, PhD

Dr. Chao-Gan Yan is a Professor in the Department of Psychological and Cognitive Sciences and the Director of the Research Center for Culture and Psychology at Tsinghua University. He has been recognized as an Elsevier Highly Cited Chinese Researcher (2019–2025) and one of Stanford’s World’s Top 2% Scientists. His honors include the 2021 OHBM Early Career Investigator Award and the Second Prize of the Beijing Municipal Natural Science Award as first recipient. Dr. Yan develops brain-imaging technologies and precision approaches to diagnosing and treating depression. He created widely used, standardized neuroimaging platforms—including DPARSF, DPABI, DPABISurf, DPABIFiber, and DPABINet—collectively cited over 8,000 times. He is also leading RESTING, an initiative to establish reference models of brain imaging for the Chinese population and detect individualized abnormalities in brain disorders. To address the heterogeneity of small-sample depression studies, he founded the Depression Imaging REsearch ConsorTium (DIRECT), which uses large-scale multicenter data to identify reliable neuroimaging patterns of depression. He proposed a default-network intervention hypothesis for depressive rumination and developed an imaging-guided algorithm for personalized transcranial magnetic stimulation. Through the “Mind Flower” Initiative, he explores integrated psychological and physiological interventions for depression. He also pioneered the Think-Aloud fMRI paradigm, combining neuroimaging with deep-learning language models to decode spontaneous thought and model brain activity. Dr. Yan has published over 130 academic papers in prestigious journals such as Nature Mental Health, PNAS, Science Bulletin, and Molecular Psychiatry, with more than 60 as the first or corresponding author. His work has garnered significant attention from the international scientific community, with over 30,000 citations and an h-index of 55 (Google Scholar). Five of his first or corresponding author papers have been listed as ESI Highly Cited Papers, with one ranking in the top 0.01%, and one in the top 0.1%, while 4 have been cited over 1,000 times individually. He currently serves as an Handling Editor of Imaging Neuroscience.

Lecturer profile

 

Course programme

All five sessions run from 09:00 to 12:00 Beijing time (UTC+8). The daily topics are listed below in teaching order.

Date in Beijing

Course content

Monday
December 14

1. Camp opening ceremony
2. Resting-state fMRI principles and data analysis
3. Applications of resting-state fMRI in psychology and brain disorders
4. Participant project introductions
5. Software installation

Tuesday
December 15

1. Data organization starting from the MRI scanner
2. R‑fMRI preprocessing with DPARSF
3. Introduction to surface-based brain imaging analysis and DPABISurf
4. Guided hands-on practice

Wednesday
December 16

1. R‑fMRI quality control and The R‑fMRI Maps Project
2. Animal data processing with DPABI
3. Statistical analysis, multiple-comparison correction and results visualization

Thursday
December 17

1. Data processing with DPABISurf
2. Hands-on statistical analysis with DPABI
3. Processing participants’ own datasets

Friday
December 18

1. Harmonization of multisite R‑fMRI data to reduce site effects
2. Gradient analysis
3. Advanced DPABISurf
4. Participant presentations of project results

 

International session times

The Beijing schedule is the reference. North American sessions fall on the previous calendar day.

Location and time zone

Daily local time

Local dates in 2026

Beijing / Singapore  UTC+8

09:00–12:00

December 14–18

UTC / London   GMT

01:00–04:00

December 14–18

Rome / Berlin   CET

02:00–05:00

December 14–18

New York   EST

20:00–23:00

December 13–17

Los Angeles   PST

17:00–20:00

December 13–17

Sydney   AEDT

12:00–15:00

December 14–18

 

 

Training format and preparation

The planned format is a small online class with live lectures, software demonstrations and project discussions. Teaching support from The R‑fMRI Lab will focus on guided practice and troubleshooting. Details of the meeting platform, teaching-assistant sessions and any cloud computing access will be announced with registration.

Before the camp

• Prepare a computer with a stable internet connection and sufficient resources for the practical exercises. A machine with at least 16 GB of RAM is recommended; check the current installation guidance for operating-system requirements.
• Install the required software and download the example data in advance. Use the course setup instructions to select the software version and confirm that your environment works before the first session.
• Review the freely available English R‑fMRI Course if you would like an introduction before joining the live sessions.
• Prepare a short description of your research question. Example data can be used for practice; you are also welcome to bring your own appropriately de-identified data for project-specific discussion.

Full preprocessing can take longer than a live session. Plan for independent practice between sessions; demonstrations and prepared outputs will support learning during the scheduled class time.

Registration

Please add to cart and pay to enroll.