Publications by authors named "M R Heitmeier"

The ventral pallidum (VP) is critical for motivated behaviors. While contemporary work has begun to elucidate the functional diversity of VP neurons, the molecular heterogeneity underlying this functional diversity remains incompletely understood. We used single-nucleus RNA sequencing and in situ hybridization to define the transcriptional taxonomy of VP cell types in mice, macaques, and baboons.

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CRISPR/Cas9 gene editing represents an exciting avenue to study genes of unknown function and can be combined with genetically encoded tools such as fluorescent proteins, channelrhodopsins, DREADDs, and various biosensors to more deeply probe the function of these genes in different cell types. However, current strategies to also manipulate or visualize edited cells are challenging due to the large size of Cas9 proteins and the limited packaging capacity of adeno-associated viruses (AAVs). To overcome these constraints, we developed an alternative gene editing strategy using a single AAV vector and mouse lines that express Cre-dependent Cas9 to achieve efficient cell-type specific editing across the nervous system.

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Unlabelled: The ventral pallidum (VP) is critical for motivated behaviors. While contemporary work has begun to elucidate the functional diversity of VP neurons, the molecular heterogeneity underlying this functional diversity remains incompletely understood. We used snRNA-seq and hybridization to define the transcriptional taxonomy of VP cell types in mice, macaques, and baboons.

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Single-cell multiomic techniques have sparked immense interest in developing a comprehensive multi-modal map of diverse neuronal cell types and their brain wide projections. However, investigating the spatial organization, transcriptional and epigenetic landscapes of brain wide projection neurons is hampered by the lack of efficient and easily adoptable tools. Here we introduce Projection-TAGs, a retrograde AAV platform that allows multiplex tagging of projection neurons using RNA barcodes.

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Word frequency is a strong predictor in most lexical processing tasks. Thus, any model of word recognition needs to account for how word frequency effects arise. The Discriminative Lexicon Model (DLM) models lexical processing with mappings between words' forms and their meanings.

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