Abstract Recent advances in single‐cell transcriptomics in dissociated cells have permitted the unbiased classification of unique, molecularly‐defined cell types in many brain regions. However, linking these molecularly‐defined cell types to their corresponding morphological, physiological, and functional phenotypes remains a major chal‐ lenge in the field. We have assembled an interdisciplinary team capable of combining and further optimizing cutting‐edge technologies including Patch‐seq (a method we developed that combines whole‐cell patch‐clamp recordings and single‐cell RNA sequencing), multi‐photon calcium imaging, multiplexed fluorescent in situ hy‐ bridization (MERFISH), and state‐of‐art machine learning to address this gap in knowledge. In aim 1, during the first two years, we will provide a comprehensive census of the cell types that comprise the mouse primary visual cortex circuitry by linking single cell RNA‐seq, morphological, and in vitro electrophysiological data. During the last three years, we will define the cell types of higher order visual areas. In addition, we will characterize a distributed network of five subcortical regions involved in the control of innate social behaviors, including the ventromedial hypothalamic nucleus, medial preoptic nucleus, anterior hypothalamic nucleus, posterior bed nu‐ cleus of the stria terminalis, and posterior medial amygdala. By studying both cortical and subcortical brain regions, we will be able to compare similarities and differences across those regions, as well as compare princi‐ ples of cell type organization between evolutionarily ancient subcortical and more recently evolved cortical re‐ gions of the brain. In aim 2, we will study the functional properties of transcriptomically‐defined cell types in the visual cortex of the mouse (areas V1, LM, PM and AM). We will perform multi‐photon calcium imaging in behaving mice during the presentation of a variety of visual stimuli to characterize in detail the receptive field properties of these neurons followed by MERFISH to identify the genetic profile of the recorded neurons. We will employ this to both Cre lines that label known broad classes of neurons as well as dense imaging of cortical populations to provide a complete, specific (i.e. in the same animal) characterization of both cell type function and molecular profiling. The combined data from these two specific aims promise to provide the most complete understanding of cell types to date, including expression profiles (e.g. ion channel and receptor levels) morphol‐ ogy, single‐cell electrophysiology, and in vivo functional properties. The methods and pipelines that will be op‐ timized in this section of the proposal will also lay the foundation to further apply these methods in different parts of the brain as well as study animal models of diseases.