Rachel Enstrom

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 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 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.