Krissy Brouner

The paper integrates transcriptomic, morphological, and electrophysiological data to define neuron types in mouse visual cortex and predict their projection targets.

This study uses multimodal Patch-seq data to show that gene expression gradients in mouse basal ganglia neurons correlate with spatial location, physiology, and morphology.

The paper analyzes multi-modal Patch-seq data from macaque striatum to reveal morphoelectric diversity and functional specialization of neuronal cell types, highlighting primate-specific features and differences from rodents.

The paper integrates multimodal data to characterize human neocortical glutamatergic neurons, revealing morphoelectric properties that distinguish transcriptomic subclasses and highlight species-specific differences.

The paper presents an enhancer AAV toolbox for targeting and perturbing striatal cell types and circuits in mice, with validated specificity and cross-species applicability.

The paper develops a toolkit of transgenic mouse lines and enhancer AAVs for selective targeting of cortical cell populations using transcriptomic and epigenomic data.

The paper introduces MerQuaCo, an open-source tool to automatically detect and quantify imperfections in spatial transcriptomics data, improving quality assessment.

This study creates an integrated multimodal cell atlas of Alzheimer's disease by analyzing single nuclei transcriptomes, epigenomes, and spatial coordinates across AD stages.

The paper identifies transcriptomic and morpho-electric diversity in human neocortical layer 1 interneurons, revealing greater subclass distinction compared to mouse.

The paper uses viral labeling and Patch-seq to define morpho-electric properties of GABAergic interneurons in human neocortex, revealing functional insights and reclassifying some SST neurons into PVALB subclass.

The paper develops AAV-based genetic tools to specifically target astrocytes and oligodendrocytes across species, revealing functional roles in reward-dependent acetylcholine responses.

The paper maps brain-wide monosynaptic inputs to specific neuron classes in mouse visual cortex using an improved rabies virus tracing strategy and identifies connectivity patterns within and between visual areas.

The paper presents a synaptic physiology dataset and analysis platform to study cortical microcircuit structure and synaptic properties in mouse and human neocortex, revealing layer-dependent connectivity and subclass-specific dynamics.

The paper characterizes transcriptomic and physiological properties of GABAergic cortical neurons in mice, identifying 20 interneuron met-types with consistent features across modalities.

The paper identifies transcriptomic diversity in human supragranular neurons and links it to functional specialization and disease vulnerability.

The paper compares cell types in human and mouse cortex using single nucleus RNA-sequencing, finding conserved architecture with species-specific differences.

The paper classifies neurons in mouse visual cortex into 17 electrophysiological and 35 morphological types using unsupervised methods and links them to transcriptomic types.