Brain Research & Artificial Intelligence Nexus (B.R.A.I.N.)

B.R.A.I.N. center seeks to develop a multimodal multiscale connectome and cell-type map of the mammalian brain using advanced tracing, imaging, and computational methods. Our cross-disciplinary group develops neuroanatomic and neuroinformatic approaches to understand connectivity patterns in both health and disease. 




Alzheimer’s Disease Mouse Brain Cell Atlas (AD-U01)

Leveraging the most advanced BRAIN Initiative neurotechnologies in circuit tracing, sparse neuronal labeling, single-cell molecular profiling, and informatics, we will identify cell-type-specific connectional and molecular disruptions across age and in two AD mouse models, and will develop an integrated informatics pipeline and web-based visualization portal for data sharing. Together, our study will provide a rich resource to study selective molecular, cellular, and circuitry vulnerabilities in AD, and to provide novel readouts in two next-generation AD mouse models to study disease mechanisms and to test candidate therapeutics.



The Mouse Connectome Project (MCP)

MCP is an NIH-funded venture that aims to create a complete mesoscale connectivity atlas of the mouse brain and to subsequently generate its global neural networks. Using fluorescent dyes as tracers and novel computational informatics tools for analysis, the project will provide researchers with a better understanding of how various brain structures organize into networks and communicate with one another. The MCP team includes neuroanatomists, computer scientists, and web programmers.



The Brain Initiative Cell Census Network (BICCN)

BICCN is an arm of the BRAIN Initiative that seeks to create a comprehensive list of cell types in the brain. B.R.A.I.N. center is working to create a cell-type atlas of the mouse brain, leading the anatomical analysis by documenting and describing the structure and connections of various brain cells. The institute is also contributing to other components of the project that analyze connectivity, transcriptomes and epigenomics.