Understanding brain cell type diversity across spatial and functional scales

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Recent technology advances have enabled neuroscientists to collect massive amounts of data on how brain cells function. These data types include neuron electrical activity, detailed dendrite and axon shapes, and mRNA expression patterns for every gene in the genome. Despite these advances in collecting data, our ability to organize and analyze these complex datasets has not kept up. This proposal is to support my research program focused on furthering our knowledge of how healthy brain cells function and how these functions are altered in aging and disease. My research program has several inter-related aspects: Aspect 1) Building web databases to organize, store, and visualize neuron electrical activity patterns. Our efforts include enhancing NeuroElectro.org, our public web resource and database for intracellular electrophysiology. Aspect 2) Understanding how gene expression drives brain cell structure and function. This includes developing tools for processing powerful new data types like PatchSeq, that combine intracellular electrophysiology with single-cell RNA sequencing. Aspect 3) Discovering how evolution has contributed to the specialization of neuron function across the mammalian lineage. By collaborating with experimental colleagues, we have unique access to datasets on neuron physiology and gene expression profiles from mice, monkeys, and humans. Aspect 4) Identifying how brain cell types, like inhibitory neuron subtypes and astrocytes, change over healthy human aging, are altered in neuropsychiatric disease, and are affected by common genetic variants. My research program is unique in its integration of basic and clinical neuroscience with neuroinformatics and data science. We work closely with multiple experimental groups and these interactions often shape our specific research questions. A key focus for our lab is developing open source tools and resources that can be broadly applied by researchers throughout the world. This award would be used to fund the training of graduate and undergraduate students and post-docs working on each of the aspects listed above. These trainees represent the next generation of neuroscientists who are equally versed in neurobiology and genetics as well as computer science and data science.