Human Brain Data Sharing Initiative (HBDSI)

Dear colleagues,

We are pleased to announce the launch of the Human Brain Data Sharing Initiative (HBDSI).

The aim of the HBDSI is to help improve our understanding of the human brain function and associations with various clinical conditions to brain disorders, by building an unprecedented big data open resource of brain imaging across a wide variety of individuals: including healthy people with different traits as well as different neurological and psychiatric diseases.

The first stage of HBDSI consists of 4 key components:

1.     The R-fMRI Maps Project  

Share a broad array of the resting-state fMRI (R-fMRI) indices of various open R-fMRI data (through a standard processing pipeline built in DPABI/DPARSF), as well as structural maps (through DPABI’s VBM analysis), and encourage researchers from both basic research and clinical fields to share their processed R-fMRI maps to public.

2.     The 3C Brain Project  

Through the predefined systematic Connectome Computation System (CCS) for multimodal image analysis, this project targets an open resource of intensively processed longitudinal cortical surface maps of the public data from the Consortium for Reliability and Reproducibility (CoRR). It serves a testbed for developing novel algorithms of longitudinal brain images as well as test-retest reliability evaluation, together with well-designed longitudinal samples of the Chinese Color Nest Project (CCNP), eventually models the normative brain developmental trajectories across the human lifespan.

3.     The Standardized Cognitive Tasks Project

The aim of this project is to create a platform to share standardized psychological paradigms (e.g., Stroop task in cognitive control) and data. Standardized tasks of each cognitive category would be collected from the mostly used paradigms. For better generalization, different versions of paradigms would be provided to adapt to different software platforms, including the system in mobile devices. Collected data with the standard paradigms would be shared.

4.     The Variability Insights Project

Provides a full view of inter-individual variability among open or user-uploaded functional and/or structural maps, and suggests potential sub-groups among the participants. These pieces of information help users to generate insights for interpreting variability in their neuroimaging data and to identify neuroimaging-based markers for participant classification.

Project 1 builds a lightweight R-fMRI analysis toolkit (DPARSF) and an easy-to-join sharing database of wide range of individuals, including extensive brain disorders. Project 2 focuses on deep data analysis on specific datasets (life-span), to build the normal developing curve of brain functions. With such a curve, aberrant developing which results into brain disorders could be identified. Such identifications and innovative data analysis methods would be adapted into Project 1 to spread to a wider community. Project 3 goes beyond intrinsic brain activity, by developing standardized paradigms of cognitive processing. Such paradigms could be applied for a wide variety of brain disorders, to identify the disorder-specific alterations in cognitive brain activities. Based on data shared by Projects 1~3, as well as user-uploaded functional and/or structural maps, Project 4 provides a full view of inter-individual variability and suggestions regarding potential subgroups of human population, thus help us to oversee the patterns of individual variability and interpret the variability in neuroimaging data.

Together, the 4 HBDSI projects would provide a further understanding on aberrant brain activities in brain disorders. We hope more exciting neuroscience findings could be fostered by such an initiative, and future innovative model could be inspired by it.

Please join us with the HBDSI, and utilize the shared data to explore the profound brain. Further questions are encouraged to discuss at http://rfmri.org/HBDSIDiscussion.

Sincerely,

Chao-Gan Yan, Ph.D.

Xi-Nian Zuo, Ph.D.

Xun Liu, Ph.D.

Zhi Yang, Ph.D.

MRI Research Center

Institute of Psychology, Chinese Academy of Sciences

16 Lincui Road, Chaoyang District, Beijing 100101, China