Rachel A. Dalley

This study uses single-nucleus RNA-seq, ATAC-seq, and Multiome to analyze Alzheimer's disease across multiple brain regions, revealing shared and region-specific cellular vulnerabilities.

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 creates a cross-species consensus atlas of primate basal ganglia cell types using multiomic data from human, macaque, and marmoset, identifying 61 conserved cell types and a novel hybrid medium spiny neuron type.

The paper demonstrates the use of ANTsX for precise spatial mapping of the mouse brain using standardized coordinate systems and presents novel workflows for longitudinal trajectory analysis and automated morphological measurements.

This study integrates molecular and morphological data to classify cortical neurons and map their connectomes, revealing organizational principles of brain-wide networks at the single-cell level.

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 investigates the synaptic connectivity of thick tufted layer 5 pyramidal neurons in the mouse visual cortex, revealing their local inhibitory and long-range excitatory connections.

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 predicts MET-type identities from EM data and shows they have distinct connectivity patterns and synapse targets.

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 analyzes dendritic and axonal arbors of inhibitory neurons to identify transcriptomic correlates of neuroanatomy.

The paper compares cellular diversity in the primary motor cortex across human, marmoset, and mouse using single-nucleus transcriptomics and epigenomics, finding conserved cell types and species-specific adaptations.

This study creates two high-resolution anatomical atlases of prenatal human brains at PCW 15 and 21, annotated with gene expression and cytoarchitecture to identify developmental features.

The paper identifies conserved and divergent morpho-electric and transcriptomic properties of human and rodent layer 5 extratelencephalic-projecting neurons using patch-seq in human brain slices.

The paper describes an optimized Patch-seq technique for high-quality electrophysiological, morphological, and transcriptomic characterization of neurons, along with software tools for data acquisition and analysis.

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.