The Brain Imaging Sharing Initiative (BISI) platform (http://bisi.org.cn or http://bisi.cstcloud.cn:8080) is funded by the 13th Five-year Informatization Plan of Chinese Academy of Sciences (grant number: XXH13505), supported by the Computer Network Information Center, Chinese Academy of Sciences and China Science & Technology Cloud. The platform was constructed and maintained by the R-fMRI Lab led by Dr. Chao-Gan Yan in the Institute of Psychology, Chinese Academy of Sciences.
BISI is evolved from the R-fMRI Maps Project (http://rfmri.org/maps), a brain imaging data sharing project launched by Dr. Chao-Gan Yan in January 2016. Up to now, there have been over 3,000 independent users downloaded or shared brain imaging data through the database of the R-fMRI Maps Project, and a dozen studies published based on the shared data in the database. In February 2021, the R-fMRI Maps Project platform was officially upgraded to the BISI platform, providing support to Chinese and international users for sharing brain imaging data when publishing papers.
The BISI platform supports the sharing of raw data (in BIDS format), as well as the sharing of results which were preprocessed by DPARSF or DPABISurf standardized protocol. The raw data sharing has promoted the big data research in the field of brain imaging and has led to huge achievements. However, raw data sharing requires intensive coordinating efforts, huge manpower demand and large-amount data storing/management facilities. Furthermore, sharing raw data is mired with privacy concerns arising from possibility of being able to identify participants from high dimensional raw data. These concerns, together with the demands of data organization and the limit of large data uploading, prevents a wider imaging community to share their valuable brain imaging datasets to public. Therefore, the BISI platform inherits the result sharing mode from the R-fMRI Maps Project where users can selectively share only final result files processed by DPARSF or DPABISurf. By sharing the processed R-fMRI indices, the projects removed the barriers of computational resources as well as analytic knowledge for the users, thus allows a wider scientific community (especially for machine learning experts) to join in the endeavor of understanding the brain. In addition, BISI was developed based on XNAT, a widely used open-source platform in the medical imaging field. Thus, data retrieval and package downloading are very simple and convenient to use in BISI.
With the BISI platform, we hope to build an unprecedented big data of brain imaging across a wide variety of individuals: including different neurological and psychiatric disease, as well as healthy people with different traits. We hope such a big data could help us better understand the brain and improve the diagnosis and treatment of brain diseases.
We sincerely hope you could join us, either downloading and utilizing the shared data, or sharing your data with BISI. If you have further questions, please refer to http://rfmri.org/BISIDiscussion to discuss.
Please see here for a 16min tutorial video or PPT (strongly recommend). 
Sincerely,
Chao-Gan Yan, Ph.D.
Professor, Principal Investigator
Director, International Big-Data Center for Depression Research
Director, Magnetic Resonance Imaging Research Center
Institute of Psychology, Chinese Academy of Sciences
16 Lincui Road, Chaoyang District, Beijing 100101, China
Institute of Psychology, Chinese Academy of Sciences
16 Lincui Road, Chaoyang District, Beijing 100101, China
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Initiator