Project Summary (Abstract) Gaining a comprehensive understanding of brain-wide cellular organization in the human brain has long been recognized as a critical foundation for understanding complex brain functions, including who we are as humans. In this project we propose to take on this challenge and establish a pipeline capable of imaging the entire human brain at cellular resolution. We believe that the convergence of our novel technologies for tissue processing and clearing, ultra-fast 3D microscopy and highly efficient analysis will make this problem tractable and scalable, marking a new paradigm in human brain research. As part of BICCN, the Osten and Wu labs, have already made significant progress towards deciphering the cell type and three-dimensional organizational logic of the mouse brain, using both genetic and molecular labeling in combination with whole mouse brain imaging. However, scaling efforts ~2,000x from mouse to human brain requires both technical and conceptual innovation to extract maximum information and ensure high efficiency. Our approach will center on a new Human brain Optimized Light-Sheet HOLiS microscopy platform developed by the Hillman lab, whose speed, efficiency and multiplexing capabilities are expected to enable cellular- resolution imaging across the entire human brain in only a few days. The HOLiS platform is complemented by a new optimized tissue preparation method for human brain developed by the Wu lab, named HuB.Clear, optimized for multiplexed staining and clearing of highly tractable 5 mm thick, full human brain slabs. Our computational data analysis pipelines developed by the Osten lab will leverage deep learning-based data analysis and permit every cell in the brain to be registered within the whole brain 7T MRI volume. Our new human brain common coordinate framework will include cellular diversity analysis based on multiplex protein profiling and precise spatial characterization. The following benchmarks will be achieved during the 3-year project: Our tissue preparation method will provide: 1) complete tissue clearing while preserving morphology to allow faithful data production and integration with MRI, and 2) reliable and quantitative whole mount immunolabeling with diverse targets to allow multiplex molecular profiling across the entire brain. Our imaging technology will provide: 1) sufficient resolution and multiplexing capacity, and 2) high-throughput speed to allow exhaustive analyses across multiple whole human brains. Our data analysis methods will provide: 1) infrastructure capable of processing whole human brain imaging data, and 2) algorithms optimized for HOLiS to extract and interpret rich molecular and cellular information with the latest advances in computer science. The resulting pipeline will be easily scalable and sharable with maximized benefit-cost ratio, opening the door to imaging 100's or even 1,000's of human brains in coming years. Our results will link cellular diversity and morphology with molecular signatures across the entire human brain at a sufficient cellular resolution and to facilitate further functional investigations and cross-species comparisons in synergy with other BICCN efforts.

Narrative Over the past decade, many techniques have been developed for mapping the brains of mice in exquisite detail, revealing the organization patterns of different types of cells and their connections with each other. However, we have yet to gain similar knowledge about the human brain, and have never before been able to evaluate an entire human brain in-toto at cellular resolution. Such data could teach us for the first time how the organization and structure of the human brain gives rise to behavior, emotion and cognition. In this project, we will leverage the latest technologies for tissue clearing, labeling, high-speed imaging and big-data analysis to establish a pipeline for imaging entire human brains rapidly and efficiently enough to permit wide-spread analysis and comparison of 100's of human brains with rich cellular and anatomical details in near future.