Szi-chieh Yu

The paper automatically aligns Drosophila connectomes to classify neurons and identify sex-specific and sexually dimorphic cell types in the ventral nerve cord.

The paper presents the first densely reconstructed adult fruit fly connectome integrating the brain and ventral nerve cord, revealing distributed control circuits involving local and long-range neural connections.

The paper improves synapse detection in Drosophila brain connectomes using new neural networks, achieving better performance in challenging regions and improved neuron clustering.

The paper maps large-scale neuronal connections in mouse hippocampal CA3, revealing spatially graded mossy fiber inputs and a feedforward inhibitory circuit targeting specific pyramidal cells.

The paper identifies and analyzes sexually dimorphic neurons in the Drosophila brain using connectome data to understand their connectivity and functional roles in behavior.

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.

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 creates a computational model of the Drosophila brain connectome to study sensorimotor processing and validates predictions through experiments.

The paper completes the list of cell types in the Drosophila optic lobe and identifies connectivity rules, revealing new families and clusters related to visual functions.

The paper analyzes the network properties of the Drosophila whole-brain connectome, identifying rich club organization and signal integration/broadcasting neurons.

The paper investigates how RIM and RIM-binding proteins regulate synaptic transmission by localizing Cav2 channels in C. elegans neuromuscular junctions, showing differential effects on cholinergic and GABAergic transmission.

The paper provides a connectomic description of ascending and descending neurons in the Drosophila nervous system, revealing sexual dimorphism and motor-related circuits.

The paper uses artificial neural networks to classify neurotransmitters from electron microscopy images of Drosophila melanogaster synapses, achieving high accuracy and revealing ultrastructural differences.

The paper introduces a method to learn a causal model of the fly brain using a connectome and optogenetic perturbation data, revealing that global brain dynamics arise from small, localized circuits.

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.

Annotating the 127,978-neuron FlyWire fly connectome yields 4,552 cell types, 3,094 cross-validated against the hemibrain; cell-type edges above 10 synapses or 1.1% of input recur over 90% across hemispheres.

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.

This study shows that synapsin SNN-1 is required for cAMP-dependent neuropeptide release in C. elegans motor neurons by capturing dense core vesicles at synapses.

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