Jingpeng Wu

This paper develops a deep learning method to correct non-uniform milling artifacts in FIB-SEM images using unsupervised cross-plane image-to-image translation.

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.

GCTransNet improves mitochondrial segmentation in vEM images using 3D Global Context Vision Transformers, achieving state-of-the-art results in the MitoEM challenge.

The paper investigates how different types of binocular disparities affect neural responses in mouse primary visual cortex, finding distinct circuit mechanisms for phase and orientation conflicts.

UniSPAC improves neuronal segmentation in connectomics by combining 2D interactive proofreading and 3D tracing, reducing manual effort and enabling semi-automatic labeling.

The paper uses a larval zebrafish connectome to predict neural coding of behavior and shows statistical matches with calcium imaging data.

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

The paper develops an image-processing pipeline to restore VEM images with high fidelity while preserving relative contrast, tested on Microwasp head 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.

The paper predicts MET-type identities from EM data and shows they have distinct connectivity patterns and synapse targets.

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 maps synaptic connectivity between cortical pyramidal neurons and shows synapse size is modeled by a combination of binary and analog variables.

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.

This study identifies pC1-Alpha neurons in Drosophila females that drive persistent behaviors through recurrent neural connectivity.

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 maps chandelier cell synapses onto pyramidal neurons and finds variability in synaptic input correlated with target neuron features, while showing functional correlation with arousal state.

The paper introduces EASE, a method that matches calcium imaging signals to EM-derived cell segments in mouse visual cortex, enabling dendritic functional analysis and denoising.