Quanxin Wang

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 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 maps the cell-type-specific afferent and efferent projections of the mouse claustrum using viral tracing and single-neuron reconstruction, revealing its widespread connections and regional specificity.

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 provides a guide to the BRAIN Initiative Cell Census Network (BICCN) data ecosystem, its tools, and resources for analyzing brain cell types across species.

The paper provides a detailed cellular-resolution map of the mouse primary motor cortex, defining cell types and their connectivity.

Complete morphologies of 1,708 neurons, sparsely labelled and imaged whole-brain with fMOST, expose region-specific long-range projection rules and finer diversity than current transcriptomic subtypes capture.

The paper analyzes the hierarchical organization of the mouse visual cortex using laminar patterns of interareal axonal projections and identifies both canonical and noncanonical hierarchical network motifs.

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.

NeuroInfo automatically registers experimental mouse brain sections with a 3D atlas to accurately identify brain regions, improving navigation and reducing observer error.

The paper develops a biophysically detailed in silico model of layer 4 of the mouse primary visual cortex, showing how functional synaptic connectivity reproduces experimental observations of neuronal responses to visual stimuli.