The BRAIN Initiative seeks to accelerate the development and application of innovative technologies that ultimately will revolutionize our understanding of the human brain. A central current focus of the brain initiative is to enable a swift and comprehensive survey of all brain cell types and circuits. Recently, single cell transcriptomics is helping to classify cell types by their expression patterns. Transcriptomic analysis is currently unique in that it scales to the entire mouse brain and all cell types. However, the correspondence between transcriptomic clusters and cell types, as defined by connectivity or physiology, is not clear. Classification of cell types will require integrative analysis of at least two data elements at the cellular level: (1) molecular signature (e.g., transcriptome), (2) anatomy (e.g., location, morphology, connectivity). We therefore propose here to elevate the complete reconstruction of the morphology of molecularly defined neurons from a small-scale artisanal method to a technology that scales to the analysis of all neuron types across the entire brain thereby providing critical information about cell types, neuronal structure and connectivity. To achieve this goal, we will build on an existing research partnership between the Departments of Neuroscience and Biomedial Engineering at Johns Hopkins University and Janelia Research Campus to develop novel tools for the reconstruction of molecularly defined neuronal subtypes. We will develop scalable imaging technology and neuro-informatics tools for morpho-molecular analysis that will be made available to researchers for a community wide effort of the mapping of all neuronal cell types and connections at and unprecedented scale and depth. Preliminary data demonstrate the feasibility of our approach that will be further developed to enhance speed on a generally usable platform. We will also develop affordable tools for data storage and retrieval. Molecular identification of neurons is designed to take advantage of information from the BRAIN Initiative Cell Census Network (BICCN) to integrate data across platforms into a common Brain Atlas. Data collected in this proposal will be integrated into the searchable BICCN database at the Allen Brain Institute.
The goal of this proposal is to develop scalable and affordable imaging and neuro-informatics tools for the reconstruction of the morphology of molecularly defined neurons across the entire brain. The technology will be made available to neuroscience researchers for a community wide effort of the mapping of neuronal connectivity at and unprecedented scale and depth. Molecular identification of neurons is designed to take advantage of information from the BRAIN Initiative Cell Census Network (BICCN) to integrate data across platforms into a common Brain Atlas.
