@article {68955, title = {A competitive disinhibitory network for robust optic flow processing in Drosophila}, journal = {Nat Neurosci.}, year = {2025}, month = {2025 may 1}, abstract = {

Many animals navigate using optic flow, detecting rotational image velocity differences between their eyes to adjust direction. Forward locomotion produces strong symmetric translational optic flow that can mask these differences, yet the brain efficiently extracts these binocular asymmetries for course control. In Drosophila melanogaster, monocular horizontal system neurons facilitate detection of binocular asymmetries and contribute to steering. To understand these functions, we reconstructed horizontal system cells{\textquoteright} central network using electron microscopy datasets, revealing convergent visual inputs, a recurrent inhibitory middle layer and a divergent output layer projecting to the ventral nerve cord and deeper brain regions. Two-photon imaging, GABA receptor manipulations and modeling, showed that lateral disinhibition reduces the output{\textquoteright}s translational sensitivity while enhancing its rotational selectivity. Unilateral manipulations confirmed the role of interneurons and descending outputs in steering. These findings establish competitive disinhibition as a key circuit mechanism for detecting rotational motion during translation, supporting navigation in dynamic environments.

Preprint:\ https://doi.org/10.1101/2023.08.06.552150

}, doi = {10.1038/s41593-025-01948-9}, url = {https://doi.org/10.1038/s41593-025-01948-9}, author = {Mert Erginkaya and Tom{\'a}s Cruz and Margarida Brotas and Kathrin Steck and Aljoscha Nern and Filipa Torr{\~a}o and N{\'e}lia Varela and Davi Bock and Michael Reiser and M Eugenia Chiappe} } @article {68656, title = {Connectome-constrained networks predict neural activity across the fly visual system}, journal = {Nature}, year = {2024}, month = {2024 Sep 11}, abstract = {

We can now measure the connectivity of every neuron in a neural circuit, but we cannot measure other biological details, including the dynamical characteristics of each neuron. The degree to which measurements of connectivity alone can inform the understanding of neural computation is an open question. Here we show that with experimental measurements of only the connectivity of a biological neural network, we can predict the neural activity underlying a specified neural computation. We constructed a model neural network with the experimentally determined connectivity for 64 cell types in the motion pathways of the fruit fly optic lobe but with unknown parameters for the single-neuron and single-synapse properties. We then optimized the values of these unknown parameters using techniques from deep learning, to allow the model network to detect visual motion. Our mechanistic model makes detailed, experimentally testable predictions for each neuron in the connectome. We found that model predictions agreed with experimental measurements of neural activity across 26 studies. Our work demonstrates a strategy for generating detailed hypotheses about the mechanisms of neural circuit function from connectivity measurements. We show that this strategy is more likely to be successful when neurons are sparsely connected-a universally observed feature of biological neural networks across species and brain regions.

}, doi = {10.1038/s41586-024-07939-3}, url = {https://doi.org/10.1038/s41586-024-07939-3}, author = {Janne K. Lappalainen and Fabian D. Tschopp and Sridhama Prakhya and Mason McGill and Aljoscha Nern and Kazunori Shinomiya and Shin-ya Takemura and Eyal Gruntman and Jakob H. Macke and Srinivas C. Turaga} } @article {69373, title = {Connectome-driven neural inventory of a complete visual system}, journal = {Nature}, year = {2024}, month = {2025 Mar 26}, 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{\textquoteright}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{\textquoteright}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.

}, doi = {10.1038/s41586-025-08746-0}, url = {https://doi.org/10.1038/s41586-025-08746-0}, author = {Aljoscha Nern and Frank Loesche and Shin-ya Takemura and Laura E Burnett and Marisa Dreher and Eyal Gruntman and Judith Hoeller and Gary B Huang and Michal Januszewski and Nathan C Klapoetke and Sanna Koskela and Kit D Longden and Zhiyuan Lu and Stephan Preibisch and Wei Qiu and Edward M Rogers and Pavithraa Seenivasan and Arthur Zhao and John Bogovic and Brandon S Canino and Jody Clements and Michael Cook and Samantha Finley-May and Miriam A Flynn and Imran Hameed and Kenneth J Hayworth and Gary Patrick Hopkins and Philip M Hubbard and William T Katz and Julie Kovalyak and Shirley A Lauchie and Meghan Leonard and Alanna Lohff and Charli A Maldonado and Caroline Mooney and Nneoma Okeoma and Donald J Olbris and Christopher Ordish and Tyler Paterson and Emily M Phillips and Tobias Pietzsch and Jennifer Rivas Salinas and Patricia K Rivlin and Ashley L Scott and Louis A Scuderi and Satoko Takemura and Iris Talebi and Alexander Thomson and Eric T Trautman and Lowell Umayam and Claire Walsh and John J Walsh and C Shan Xu and Emily A Yakal and Tansy Yang and Ting Zhao and Jan Funke and Reed George and Harald F Hess and Gregory S X E Jefferis and Christopher Knecht and Wyatt Korff and Stephen M Plaza and Sandro Romani and Stephan Saalfeld and Louis K Scheffer and Stuart Berg and Gerald M Rubin and Michael B Reiser} } @article {69296, title = {Social state gates vision using three circuit mechanisms in Drosophila}, journal = {Nature}, year = {2024}, month = {2024 Nov 20}, abstract = {

Animals are often bombarded with visual information and must prioritize specific visual features based on their current needs. The neuronal circuits that detect and relay visual features have been well studied. Much less is known about how an animal adjusts its visual attention as its goals or environmental conditions change. During social behaviours, flies need to focus on nearby flies. Here we study how the flow of visual information is altered when female Drosophila enter an aggressive state. From the connectome, we identify three state-dependent circuit motifs poised to modify the response of an aggressive female to fly-sized visual objects: convergence of excitatory inputs from neurons conveying select visual features and internal state; dendritic disinhibition of select visual feature detectors; and a switch that toggles between two visual feature detectors. Using cell-type-specific genetic tools, together with behavioural and neurophysiological analyses, we show that each of these circuit motifs is used during female aggression. We reveal that features of this same switch operate in male Drosophila during courtship pursuit, suggesting that disparate social behaviours may share circuit mechanisms. Our study provides a compelling example of using the connectome to infer circuit mechanisms that underlie dynamic processing of sensory signals.

}, doi = {10.1038/s41586-024-08255-6}, url = {https://doi.org/10.1038/s41586-024-08255-6}, author = {Catherine E. Schretter and Tom Hindmarsh Sten and Nathan Klapoetke and Mei Shao and Aljoscha Nern and Marisa Dreher and Daniel Bushey and Alice A. Robie and Adam L. Taylor and Kristin M. Branson and Adriane Otopalik and Vanessa Ruta and Gerald M. Rubin} } @article {69329, title = {A split-GAL4 driver line resource for Drosophila CNS cell types}, journal = {bioRxiv}, year = {2024}, month = {2024 Jan 10}, abstract = {

Techniques that enable precise manipulations of subsets of neurons in the fly central nervous system have greatly facilitated our understanding of the neural basis of behavior. Split-GAL4 driver lines allow specific targeting of cell types in Drosophila melanogaster and other species. We describe here a collection of 3060 lines targeting a range of cell types in the adult Drosophila central nervous system and 1373 lines characterized in third-instar larvae. These tools enable functional, transcriptomic, and proteomic studies based on precise anatomical targeting. NeuronBridge and other search tools relate light microscopy images of these split-GAL4 lines to connectomes reconstructed from electron microscopy images. The collections are the result of screening over 77,000 split hemidriver combinations. In addition to images and fly stocks for these well-characterized lines, we make available 300,000 new 3D images of other split-GAL4 lines.

}, doi = {10.1101/2024.01.09.574419}, url = {https://www.biorxiv.org/content/early/2024/04/01/2024.01.09.574419}, author = {Geoffrey W Meissner and Allison Vannan and Jennifer Jeter and Kari Close and Gina M DePasquale and Zachary Dorman and Kaitlyn Forster and Jaye Anne Beringer and Theresa V Gibney and Joanna H Hausenfluck and Yisheng He and Kristin Henderson and Lauren Johnson and Rebecca M Johnston and Gudrun Ihrke and Nirmala Iyer and Rachel Lazarus and Kelley Lee and Hsing-Hsi Li and Hua-Peng Liaw and Brian Melton and Scott Miller and Reeham Motaher and Alexandra Novak and Omotara Ogundeyi and Alyson Petruncio and Jacquelyn Price and Sophia Protopapas and Susana Tae and Jennifer Taylor and Rebecca Vorimo and Brianna Yarbrough and Kevin Xiankun Zeng and Christopher T Zugates and Heather Dionne and Claire Angstadt and Kelly Ashley and Amanda Cavallaro and Tam Dang and Guillermo A Gonzalez III and Karen L Hibbard and Cuizhen Huang and Jui-Chun Kao and Todd Laverty and Monti Mercer and Brenda Perez and Scarlett Pitts and Danielle Ruiz and Viruthika Vallanadu and Grace Zhiyu Zheng and Cristian Goina and Hideo Otsuna and Konrad Rokicki and Robert R Svirskas and Han SJ Cheong and Michael-John Dolan and Erica Ehrhardt and Kai Feng and Basel El Galfi and Jens Goldammer and Stephen J Huston and Nan Hu and Masayoshi Ito and Claire McKellar and Ryo Minegishi and Shigehiro Namiki and Aljoscha Nern and Catherine E Schretter and Gabriella R Sterne and Lalanti Venkatasubramanian and Kaiyu Wang and Tanya Wolff and Ming Wu and Reed George and Oz Malkesman and Yoshinori Aso and Gwyneth M Card and Barry J Dickson and Wyatt Korff and Kei Ito and James W Truman and Marta Zlatic and Gerald M Rubin and FlyLight Project Team} } @article {69039, title = {A comprehensive neuroanatomical survey of the Drosophila Lobula Plate Tangential Neurons with predictions for their optic flow sensitivity.}, journal = {bioRxiv}, year = {2023}, month = {2023 Oct 17}, abstract = {

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of {\textquoteright}optic-flow{\textquoteright} sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.

}, doi = {10.1101/2023.10.16.562634}, url = {https://doi.org/10.1101/2023.10.16.562634}, author = {Arthur Zhao and Aljoscha Nern and Sanna Koskela and Marisa Dreher and Mert Erginkaya and Connor W Laughland and Henrique DF Ludwig and Alex G Thomson and Judith Hoeller and Ruchi Parekh and Sandro Romani and Davi D Bock and Eugenia Chiappe and Michael B Reiser} } @article {68697, title = {Identifying determinants of synaptic specificity by integrating connectomes and transcriptomes}, journal = {bioRxiv}, year = {2023}, month = {2023 Apr 04}, abstract = {

How do developing neurons select their synaptic partners? To identify molecules matching synaptic partners, we integrated the synapse-level connectome of neural circuits with the developmental expression patterns and binding specificities of cell adhesion molecules (CAMs) on pre- and postsynaptic neurons. We focused on parallel synaptic pathways in the Drosophila visual system, in which closely related neurons form synapses onto closely related target neurons. We show that the choice of synaptic partners correlates with the matching expression of receptor-ligand pairs of Beat and Side proteins of the immunoglobulin superfamily (IgSF) CAMs. Genetic analysis demonstrates that these proteins determine the choice between alternative synaptic targets. Combining transcriptomes, connectomes, and protein interactome maps provides a framework to uncover the molecular logic of synaptic connectivity.

}, doi = {10.1101/2023.04.03.534791}, url = {https://doi.org/10.1101/2023.04.03.534791}, author = {Juyoun Yoo and Mark Dombrovski and Parmis Mirshahidi and Aljoscha Nern and Samuel A. LoCascio and S. Lawrence Zipursky and Yerbol Z. Kurmangaliyev} } @article {68838, title = {Small-field visual projection neurons detect translational optic flow and support walking control}, journal = {bioRxiv}, year = {2023}, month = {2023 Jun 22}, abstract = {

Animals rely on visual motion for navigating the world, and research in flies has clarified how neural circuits extract information from moving visual scenes. However, the major pathways connecting these patterns of optic flow to behavior remain poorly understood. Using a high-throughput quantitative assay of visually guided behaviors and genetic neuronal silencing, we discovered a region in\ Drosophila{\textquoteright}s protocerebrum critical for visual motion following. We used neuronal silencing, calcium imaging, and optogenetics to identify a single cell type, LPC1, that innervates this region, detects translational optic flow, and plays a key role in regulating forward walking. Moreover, the population of LPC1s can estimate the travelling direction, such as when gaze direction diverges from body heading. By linking specific cell types and their visual computations to specific behaviors, our findings establish a foundation for understanding how the nervous system uses vision to guide navigation.

}, doi = {10.1101/2023.06.21.546024}, url = {https://doi.org/10.1101/2023.06.21.546024}, author = {Mathew D. Isaacson and Jessica L. M. Eliason and Aljoscha Nern and Edward M. Rogers and Gus K. Lott and Tanya Tabachnik and William J. Rowell and Austin W. Edwards and Wyatt L. Korff and Gerald M. Rubin and Kristin Branson and Michael B. Reiser} } @article {68570, title = {Eye structure shapes neuron function in Drosophila motion vision}, journal = {bioRxiv}, year = {2022}, month = {2022 Dec 15}, abstract = {

Many animals rely on vision to navigate through their environment. The pattern of changes in the visual scene induced by self-motion is the\ optic flow1, which is first estimated in local patches by directionally selective (DS) neurons2{\textendash}4. But how should the arrays of DS neurons, each responsive to motion in a preferred direction at a specific retinal position, be organized to support robust decoding of optic flow by downstream circuits? Understanding this global organization is challenging because it requires mapping fine, local features of neurons across the animal{\textquoteright}s field of view3. In\ Drosophila, the asymmetric dendrites of the T4 and T5 DS neurons establish their preferred direction, making it possible to predict DS responses from anatomy4,5. Here we report that the preferred directions of fly DS neurons vary at different retinal positions and show that this spatial variation is established by the anatomy of the compound eye. To estimate the preferred directions across the visual field, we reconstructed hundreds of T4 neurons in a full brain EM volume6\ and discovered unexpectedly stereotypical dendritic arborizations that are independent of location. We then used whole-head μCT scans to map the viewing directions of all compound eye facets and found a non-uniform sampling of visual space that explains the spatial variation in preferred directions. Our findings show that the organization of preferred directions in the fly is largely determined by the compound eye, exposing an intimate and unexpected connection between the peripheral structure of the eye, functional properties of neurons deep in the brain, and the control of body movements.

}, doi = {10.1101/2022.12.14.520178}, url = {https://doi.org/10.1101/2022.12.14.520178}, author = {Arthur Zhao and Eyal Gruntman and Aljoscha Nern and Nirmala A. Iyer and Edward M. Rogers and Sanna Koskela and Igor Siwanowicz and Marisa Dreher and Miriam A. Flynn and Connor W. Laughland and Henrique D.F. Ludwig and Alex G. Thomson and Cullen P. Moran and Bruck Gezahegn and Davi D. Bock and Michael B. Reiser} } @article {68294, title = {Visual projection neuron convergence and compensation in developing sensorimotor circuits in the Drosophila optic glomeruli}, month = {2022 Aug 22}, abstract = {

Visual features detected by the early visual system must be combined into higher order representations to guide behavioral decision. Although key developmental mechanisms that enable the separation of visual feature channels in early visual circuits have been discovered, relatively little is known about the mechanisms that underlie their convergence in later stages of visual processing. Here we explore the development of a functionally well-characterized sensorimotor circuit in\ Drosophila melanogaster, the convergence of visual projection neurons (VPNs) onto the dendrites of a large descending neuron called the giant fiber (GF). We find two VPNs encoding different visual features that target the same giant fiber dendrite establish their territories on the dendrite, in part, through sequential axon arrival during development prior to synaptogenesis. Physical occupancy is important to maintain territories, as we find the ablation of one VPN results in expanded dendrite territory of the remaining VPN, and that this compensation enables the GF to remain responsive to ethologically relevant visual stimuli. Our data highlight temporal mechanisms for visual feature convergence and promote the GF circuit, and the\ Drosophila\ optic glomeruli where VPN to GF connectivity resides, as an ideal developmental model for investigating complex wiring programs and plasticity in visual feature convergence.

}, doi = {10.1101/2022.08.20.504653}, url = {https://doi.org/10.1101/2022.08.20.504653}, author = {Brennan W. McFarland and HyoJong Jang and Natalie Smolin and Tanja A. Godenschwege and Aljoscha Nern and Yerbol Z. Kurmangaliyev and Catherine R. von Reyn} }