Amy Robinson Sterling

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.

Eyewire II provides a large-scale EM dataset of the mouse retina, enabling cell type annotation and connectivity mapping through human-in-the-loop deep learning and functional alignment.

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.

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

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 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 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.

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

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