Christine Rimorin

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 presents a barcoded multiplex strategy to screen enhancer AAVs using single-cell RNA sequencing and taxonomy mapping, but finds significant technical and biological noise complicates accurate expression pattern analysis.

The paper reveals the external globus pallidus (GPe) as a basal ganglia output hub with distinct subpopulations that mediate specific behaviors through projection-specific circuits.

The paper develops a cross-species enhancer-AAV toolkit for targeting specific cell types in the basal ganglia across species, validated in mouse and macaque.

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 creates a cross-species spinal cord cell type atlas integrating data from mouse, macaque, and human, identifying conserved and species-specific features.

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

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

This paper creates a high-resolution transcriptomic and spatial cell type atlas of the whole adult mouse brain, revealing spatial organization and transcription factor codes for cell types.

The paper uses single nucleus RNA-sequencing to analyze human cortical areas, revealing cell type proportions and gene expression patterns that correlate with functional connectivity and areal specialization.

This study uses single nucleus transcriptomics to compare human and non-human primate cortical tissues, identifying human-specific gene expression patterns and their potential functional roles.

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 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.

The paper generates a multimodal cell census and atlas of the mammalian primary motor cortex, revealing a unified molecular genetic landscape and cross-species taxonomy of cell types.

The paper creates a comprehensive atlas of mouse primary motor cortex cell types using integrated transcriptomic and epigenomic data from over 600,000 samples.

This study defines a comprehensive transcriptomic cell type taxonomy of the adult mouse isocortex and hippocampal formation using single-cell RNA-sequencing.

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 shows that single-nucleus and single-cell RNA-seq can equally identify neuronal cell types in mouse visual cortex when intronic sequences are included.

The paper identifies shared and distinct transcriptomic cell types in two mouse neocortical regions using scRNA-seq, showing most excitatory types are region-specific while inhibitory types are shared.