Amy Bernard

This paper describes the construction and usage of the Human Reference Atlas (HRA) v2.0, which integrates multiscale data across 36 organs and provides tools for analysis and visualization.

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.

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 uses single-cell RNA-seq to analyze relay neurons in the dLGN across species, finding subtle transcriptomic differences compared to morphological and functional distinctions.

The paper presents a dataset and analysis of spiking activity across multiple mouse visual areas, revealing that functional connectivity mirrors anatomical hierarchy.

The paper identifies von Economo neurons as a regionally specialized subtype of extratelencephalic-projecting excitatory neurons using single nucleus RNA-sequencing and cross-species comparisons.

The paper presents a large-scale dataset of neural activity in the mouse visual cortex and shows that responses to different stimuli are largely independent, suggesting multi-layer hierarchical computation.

The paper expands the Allen Mouse Brain Connectivity Atlas by analyzing intracortical connections at the layer and cell class level, revealing modular organization and distinct projection patterns.

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.

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.