Huanxiang Lu

The paper creates a detailed computational model of rat somatosensory cortex anatomy, including 4.2 million neurons and 14.2 billion synapses, and identifies limitations in connectivity prediction from morphology.

The paper presents a full-scale in silico model of rat hippocampal CA1 integrating diverse experimental data and validates it through simulations of theta rhythm and other experiments.

The paper enhances brain atlases with laminar coordinate systems and flatmaps to better represent layered brain regions, enabling improved visualization and modeling of structures like the barrel cortex.

The paper builds a statistical model of the mouse whole-neocortex micro-connectome using region-to-region connectivity and axon reconstructions, revealing a novel targeting principle for predicting individual axon innervation.