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Connectome-driven neural inventory of a complete visual system

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bioRxiv. 2024 Apr 18;. doi: 10.1101/2024.04.16.589741
Connectome-driven neural inventory of a complete visual system Reiser LabRubin LabFlyEM
Nern Aljoscha, Loesche Frank, Takemura Shin-ya, Burnett Laura, Dreher Marisa, Gruntman Eyal, Hoeller Judith, Huang Gary, Januszewski Michal, Klapoetke Nathan, Koskela Sanna, Longden Kit, Lu Zhiyuan, Preibisch Stephan, Qiu Wei, Rogers Edward, Seenivasan Pavithraa, Zhao Arthur, Bogovic John, Canino Brandon, Clements Jody, Cook Michael, Finley-May Samantha, Flynn Miriam, Hameed Imran, Hayworth Kenneth, Hopkins Gary, Hubbard Philip, Katz William, Kovalyak Julie, Lauchie Shirley, Leonard Meghan, Lohff Alanna, Maldonado Charli, Mooney Caroline, Okeoma Nneoma, Olbris Donald, Ordish Christopher, Paterson Tyler, Phillips Emily, Pietzsch Tobias, Salinas Jennifer, Rivlin Patricia, Scott Ashley, Scuderi Louis, Takemura Satoko, Talebi Iris, Thomson Alexander, Trautman Eric, Umayam Lowell, Walsh Claire, Walsh John, Xu Shan, Yakal Emily, Yang Tansy, Zhao Ting, Funke Jan, George Reed, Hess Harald, Jefferis Gregory, Knecht Christopher, Korff Wyatt, Plaza Stephen, Romani Sandro, Saalfeld Stephan, Scheffer Louis, Berg Stuart, Rubin Gerald, Reiser Michael
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Abstract

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain’s volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly’s visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the 53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

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