Shang Mu

CAVE enables reproducible connectome analysis in large-scale datasets during ongoing annotation and proofreading.

NEURD automates proofreading and feature extraction from connectomics data to improve accuracy and accessibility of neural morphology analyses.

The paper presents a functional connectomics dataset of mouse visual cortex, combining calcium imaging with EM reconstruction to study neural circuits and their connectivity.

Functionally similar neurons in mouse visual cortex connect preferentially across layers and areas, including feedback, and feature tuning, not receptive-field position, predicts synapses beyond axon-dendrite proximity.

The paper uses graph-based machine learning to analyze dendritic morphology of excitatory neurons in mouse visual cortex, finding a continuous morphological landscape rather than discrete types.

This study shows that remote ischemic conditioning (RIC) improves stroke recovery by altering monocyte composition and CD36-mediated efferocytosis in macrophages, which reduces transneuronal degeneration.

This study shows human glioblastoma cells integrate into brain-wide neuronal circuits, exhibit diverse connectivity, and respond to neuromodulatory inputs like acetylcholine, which promotes invasion and survival.

The paper presents the first neuronal wiring diagram of a whole adult Drosophila brain, revealing synaptic connections and circuit mechanisms underlying sensorimotor behaviors.

This study develops a high-throughput in vivo Perturb-seq platform to analyze gene function across diverse cell types in the brain and peripheral nervous system, identifying cell type-specific transcriptional networks.

The paper introduces a pipeline for aligning serial section electron microscopy images, improving accuracy and scalability for large datasets.

The paper investigates the synaptic connectivity of thick tufted layer 5 pyramidal neurons in the mouse visual cortex, revealing their local inhibitory and long-range excitatory connections.

Electron microscopy of 1352 neurons in a mouse visual cortex column reveals widespread cell-type-specific inhibition, a basket-cell-targeting disinhibitory class, and interneuron motif groups sharing excitatory targets.

The paper identifies novel nuclear layer contacts between starburst amacrine cells in the mouse retina through detailed morphological analysis of electron microscopic data.

The paper uses electron microscopy data to classify cell types in the neocortex based on perisomatic features, showing that these features are sufficient for accurate classification even in large datasets.

FlyWire enables collaborative proofreading of whole-brain connectomes through an online platform, demonstrating its utility in reconstructing and analyzing mechanosensory neuron circuits.

The paper reconstructs 3D cell nuclei in a Drosophila brain, identifying over 133,000 nuclei, mostly neurons, and highlights differences in nuclear size and cell density across brain regions.

Cloud-run convolutional nets aligned 19,939 serial EM sections of mouse visual cortex despite cracks and folds, segmented neurons and detected 523 million synapses; code and the reconstruction are public.

The paper identifies oligodendrocyte precursor cells (OPCs) as major contributors to axon pruning in the mouse neocortex through phagocytic activity.

The paper presents a semi-automated reconstruction of mouse primary visual cortex from electron microscopy data, revealing structural and functional relationships in cortical circuits.

The paper presents a digital resource of mouse retinal ganglion cell dendritic arbors and visual responses, identifies sublaminae, clusters cells, and finds sustained responses in one sublamina.