With the rapid development of software and hardware platforms, the spatial and temporal resolution of various brain imaging technologies is getting higher and higher, leading to the rapid growth of the capacity of brain imaging data in geometric progression, which brings great challenges to the subsequent storage and calculation of massive data, and has become one of the technical barriers in the field of brain cognition and brain medicine. In view of the increasing big data of brain imaging, the State Key Laboratory has specially built a high-performance computing platform for brain imaging data. The hardware computing resources of the platform are mainly composed of two blade servers, four rack servers and eight rack servers. The CPU processor is over 2000 core, the total memory capacity is 7.2TB, and the theoretical floating point computing capacity is 33.4 trillion times/second. Storage resources consist of a large-scale parallel file system and a backup storage system. The parallel file system has a storage space of 540 TB and the backup storage system has a storage space of 460 TB. Computing platform software resources include software platforms developed by internationally famous laboratories (such as MATLAB, FSL, SPM, REST, FreeSurfer, Python, DPABI, AFNI, Anaconda, Tracula, CIVET), along with independently developed software platforms for brain image big data analysis and visualization (such as PANDA, GRETNA and BrainNetViewer), which provide support for brain image big data computation and storage for members of the State Key Laboratories.