Nadezhda I. Dotson

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