The synaptic connectome of the Drosophila larval visual circuit is the first case of a completely reconstructed visual network in a genetically fully tractable model organism.
A first principles, neuro-computational framework proposes a path for the experimental dissection of neural circuit mechanisms of competitive selection across brain areas and animal species.
Transcriptomes of cells in the Drosophila visual system combined with anatomy and other information reveal new functional insight into the visual circuit.
A bright and stochastic multicolor labeling method, Tetbow, facilitates millimeters-scale reconstructions of neuronal circuits at a large scale using tissue clearing.
A recurrent reward circuit in Drosophila, comprised of specific dopamine neurons and a single class of mushroom body output neurons, transforms a nascent memory trace into a stable long-term memory.
Anatomical and physiological analyses identified an inhibitory interneuron that is an integral part of the rod bipolar cell pathway, the circuit for night vision, of the mammalian retina.
A novel experimental method and analysis is conceived, based on perturbation and sparse recording, to elucidate the circuit structure and mechanisms underlying the responses of grid cells.
Light-seeking strategies in Zebrafish larvae are dissected using a virtual-reality assay, and these data are used to establish minimal stochastic and neural-circuits models that quantitatively capture this behavior.
