@article {69881, title = {Comparative connectomics of Drosophila descending and ascending neurons.}, journal = {Nature}, year = {2025}, month = {2025 Apr 30}, abstract = {

In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and an information bottleneck connecting the brain and the ventral nerve cord (an analogue of the spinal cord) and comprises diverse populations of descending neurons (DNs), ascending neurons (ANs) and sensory ascending neurons, which are crucial for sensorimotor signalling and control. Here, by integrating three separate electron microscopy (EM) datasets, we provide a complete connectomic description of the ANs and DNs of the Drosophila female nervous system and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions are matched across hemispheres, datasets and sexes. Crucially, we also match 51\% of DN cell types to light-level data defining specific driver lines, as well as classifying all ascending populations. We use these results to reveal the anatomical and circuit logic of neck connective neurons. We observe connected chains of DNs and ANs spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analyses of selected circuits for reproductive behaviours, including male courtship (DNa12; also known as aSP22) and song production (AN neurons from hemilineage 08B) and female ovipositor extrusion (DNp13). Our work provides EM-level circuit analyses that span the entire central nervous system of an adult animal.

}, issn = {1476-4687}, doi = {10.1038/s41586-025-08925-z}, url = {https://doi.org/10.1038/s41586-025-08925-z}, author = {St{\"u}rner, Tomke and Brooks, Paul and Serratosa Capdevila, Laia and Morris, Billy J and Javier, Alexandre and Fang, Siqi and Gkantia, Marina and Cachero, Sebastian and Beckett, Isabella R and Marin, Elizabeth C and Schlegel, Philipp and Champion, Andrew S and Moitra, Ilina and Richards, Alana and Klemm, Finja and Kugel, Leonie and Namiki, Shigehiro and Cheong, Han S J and Kovalyak, Julie and Tenshaw, Emily and Parekh, Ruchi and Phelps, Jasper S and Mark, Brandon and Dorkenwald, Sven and Bates, Alexander S and Matsliah, Arie and Yu, Szi-Chieh and McKellar, Claire E and Sterling, Amy and Seung, H Sebastian and Murthy, Mala and Tuthill, John C and Lee, Wei-Chung Allen and Card, Gwyneth M and Costa, Marta and Jefferis, Gregory S X E and Eichler, Katharina} } @article {70047, title = {Distributed control circuits across a brain-and-cord connectome}, journal = {bioRxiv}, year = {2025}, month = {2025 Aug 02}, abstract = {

Just as genomes revolutionized molecular genetics, connectomes (maps of neurons and synapses) are transforming neuroscience. To date, the only species with complete connectomes are worms\ and sea squirts\ (103-104 synapses). By contrast, the fruit fly is more complex (108 synaptic connections), with a brain that supports learning and spatial memory and an intricate ventral nerve cord analogous to the vertebrate spinal cord. Here we report the first adult fly connectome that unites the brain and ventral nerve cord, and we leverage this resource to investigate principles of neural control. We show that effector cells (motor neurons, endocrine cells and efferent neurons targeting the viscera) are primarily influenced by local sensory cells in the same body part, forming local feedback loops. These local loops are linked by long-range circuits involving ascending and descending neurons organized into behavior-centric modules. Single ascending and descending neurons are often positioned to influence the voluntary movements of multiple body parts, together with endocrine cells or visceral organs that support those movements. Brain regions involved in learning and navigation supervise these circuits. These results reveal an architecture that is distributed, parallelized and embodied (tightly connected to effectors), reminiscent of distributed control architectures in engineered systems.

}, doi = {10.1101/2025.07.31.667571}, url = {https://www.biorxiv.org/content/early/2025/08/02/2025.07.31.667571}, author = {Bates, Alexander Shakeel and Phelps, Jasper S. and Kim, Minsu and Yang, Helen H. and Matsliah, Arie and Ajabi, Zaki and Perlman, Eric and Delgado, Kevin M. and Osman, Mohammed Abdal Monium and Salmon, Christopher K. and Gager, Jay and Silverman, Benjamin and Renauld, Sophia and Collie, Matthew F. and Fan, Jingxuan and Pacheco, Diego A. and Zhao, Yunzhi and Patel, Janki and Zhang, Wenyi and Serratosa Capdevilla, Laia and Roberts, Ruair{\'\i} J.V. and Munnelly, Eva J. and Griggs, Nina and Langley, Helen and Moya-Llamas, Borja and Maloney, Ryan T. and Yu, Szi-Chieh and Sterling, Amy R. and Sorek, Marissa and Kruk, Krzysztof and Serafetinidis, Nikitas and Dhawan, Serene and St{\"u}rner, Tomke and Klemm, Finja and Brooks, Paul and Lesser, Ellen and Jones, Jessica M. and Pierce-Lundgren, Sara E. and Lee, Su-Yee and Luo, Yichen and Cook, Andrew P. and McKim, Theresa H. and Kophs, Emily C. and Falt, Tjalda and Negr{\'o}n Morales, Alexa M. and Burke, Austin and Hebditch, James and Willie, Kyle P. and Willie, Ryan and Popovych, Sergiy and Kemnitz, Nico and Ih, Dodam and Lee, Kisuk and Lu, Ran and Halageri, Akhilesh and Bae, J. Alexander and Jourdan, Ben and Schwartzman, Gregory and Demarest, Damian D. and Behnke, Emily and Bland, Doug and Kristiansen, Anne and Skelton, Jaime and Stocks, Tom and Garner, Dustin and Salman, Farzaan and Daly, Kevin C. and Hernandez, Anthony and Kumar, Sandeep and The BANC-FlyWire Consortium and Dorkenwald, Sven and Collman, Forrest and Suver, Marie P. and Fenk, Lisa M. and Pankratz, Michael J. and Jefferis, Gregory S.X.E. and Eichler, Katharina and Seeds, Andrew M. and Hampel, Stefanie and Agrawal, Sweta and Zandawala, Meet and Macrina, Thomas and Adjavon, Diane-Yayra and Funke, Jan and Tuthill, John C. and Azevedo, Anthony and Seung, H. Sebastian and de Bivort, Benjamin L. and Murthy, Mala and Drugowitsch, Jan and Wilson, Rachel I. and Lee, Wei-Chung Allen} } @article {70012, title = {Sexually-dimorphic neurons in the Drosophila whole-brain connectome}, journal = {Research Square}, year = {2025}, month = {2025 Jun 26}, abstract = {

Sexual dimorphisms are present across brains. Male and female brains contain sets of cell types with differences in cell number, morphology, or synaptic connectivity between the two sexes. These differences are driven by differentially-expressed transcription factors, which set the stage for disparate sexual and social behaviors observed between males and females, such as courtship, aggression, receptivity, and mating. In the Drosophila brain, sexual dimorphisms result from differential expression of two transcription factors, Fruitless (Fru) and Doublesex (Dsx), and genetic reagents driven by enhancers for Fru and Dsx label sexually-dimorphic neurons in both male and female brains. The recent release of the first whole-brain connectome for Drosophila provides a unique opportunity to study the connectivity between these neurons as well as their integration into the larger brain network. Here, we identify 91 putative Fru or Dsx cell types, comprising ~1400 neurons, within the whole-brain connectome, using morphological similarity between electron microscopic (EM) reconstructions and light microscopic (LM) images of known Fru and Dsx neurons. We discover that while Fru and Dsx neurons are highly interconnected, each cell type typically receives more inputs from and sends more outputs to non-Fru/Dsx neurons. We characterize the connectivity in the Fru/Dsx networks to predict the function of cell types not previously characterized, we measure distances to the sensory periphery and uncover multisensory interactions, and we map connections to descending neurons that drive behavior. All Fru and Dsx labels reported here are shared within FlyWire Codex (codex.flywire.ai; gene==Fruitless or Doublesex); this work is a critical first step towards deciphering the neural basis of sexually-dimorphic behaviors and for making comparisons with future connectomes of the male brain.

}, doi = {10.21203/rs.3.rs-6881911/v1}, url = {https://doi.org/10.21203/rs.3.rs-6881911/v1}, author = {Deutsch, David and Matsliah, Arie and Wang, Kaiyu and Dorkenwald, Sven and Mondal, Arpita and Burke, Austin and Hebditch, James and Gager, Jay and Yu, Szi-Chieh and Sterling, Amy and McKellar, Amy and Schlegel, Philipp and Gerhard, Stephan and Sterne, Gabriella and Costa, Marta and Eichler, Katharina and Yin, Yijie and Jefferis, Gregory and Dickson, Barry and Seung, H Sebastian and Murthy, Mala} } @article {69489, title = {Comparative connectomics of the descending and ascending neurons of the Drosophila nervous system: stereotypy and sexual dimorphism}, journal = {bioRxiv}, year = {2024}, month = {2024 Jun 06}, abstract = {

In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and information bottleneck connecting the brain and the ventral nerve cord (VNC, spinal cord analogue) and comprises diverse populations of descending (DN), ascending (AN) and sensory ascending neurons, which are crucial for sensorimotor signalling and control.Integrating three separate EM datasets, we now provide a complete connectomic description of the ascending and descending neurons of the female nervous system of Drosophila and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions have been matched across hemispheres, datasets and sexes. Crucially, we have also matched 51\% of DN cell types to light level data defining specific driver lines as well as classifying all ascending populations.We use these results to reveal the general architecture, tracts, neuropil innervation and connectivity of neck connective neurons. We observe connected chains of descending and ascending neurons spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analysis of circuits implicated in sex-related behaviours, including female ovipositor extrusion (DNp13), male courtship (DNa12/aSP22) and song production (AN hemilineage 08B). Our work represents the first EM-level circuit analyses spanning the entire central nervous system of an adult animal.

}, doi = {10.1101/2024.06.04.596633}, url = {https://www.biorxiv.org/content/early/2024/06/06/2024.06.04.596633}, author = {St{\"u}rner, Tomke and Brooks, Paul and Serratosa Capdevila, Laia and Morris, Billy J. and Javier, Alexandre and Fang, Siqi and Gkantia, Marina and Cachero, Sebastian and Beckett, Isabella R. and Champion, Andrew S. and Moitra, Ilina and Richards, Alana and Klemm, Finja and Kugel, Leonie and Namiki, Shigehiro and Cheong, Han S.J. and Kovalyak, Julie and Tenshaw, Emily and Parekh, Ruchi and Schlegel, Philipp and Phelps, Jasper S. and Mark, Brandon and Dorkenwald, Sven and Bates, Alexander S. and Matsliah, Arie and Yu, Szi-Chieh and McKellar, Claire E. and Sterling, Amy and Seung, Sebastian and Murthy, Mala and Tuthill, John and Lee, Wei-Chung A. and Card, Gwyneth M. and Costa, Marta and Jefferis, Gregory S.X.E. and Eichler, Katharina} } @article {69633, title = {A Drosophila computational brain model reveals sensorimotor processing.}, journal = {Nature}, volume = {634}, year = {2024}, month = {2024 Oct 02}, pages = {210-219}, abstract = {

The recent assembly of the adult Drosophila melanogaster central brain connectome, containing more than 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here we create a leaky integrate-and-fire computational model of the entire Drosophila brain, on the basis of neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviours. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation. In addition, using the model to activate neurons in the feeding region of the Drosophila brain predicts those that elicit motor neuron firing-a testable hypothesis that we validate by optogenetic activation and behavioural studies. Activating different classes of gustatory neurons in the model makes accurate predictions of how several taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modelling brain circuits using only synapse-level connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can describe complete sensorimotor transformations.

}, keywords = {Animals, Brain, Computer Simulation, Connectome, Drosophila melanogaster, Feeding Behavior, Female, Grooming, Male, Models, Neurological, Motor Neurons, Optogenetics, Synapses, Taste}, issn = {1476-4687}, doi = {10.1038/s41586-024-07763-9}, url = {https://doi.org/10.1038/s41586-024-07763-9}, author = {Shiu, Philip K and Sterne, Gabriella R and Spiller, Nico and Franconville, Romain and Sandoval, Andrea and Zhou, Joie and Simha, Neha and Kang, Chan Hyuk and Yu, Seongbong and Kim, Jinseop S and Dorkenwald, Sven and Matsliah, Arie and Schlegel, Philipp and Yu, Szi-Chieh and McKellar, Claire E and Sterling, Amy and Costa, Marta and Eichler, Katharina and Bates, Alexander Shakeel and Eckstein, Nils and Funke, Jan and Jefferis, Gregory S X E and Murthy, Mala and Bidaye, Salil S and Hampel, Stefanie and Seeds, Andrew M and Scott, Kristin} } @article {68889, title = {Neuronal wiring diagram of an adult brain.}, journal = {Nature}, volume = {634}, year = {2024}, month = {2024 Oct 02}, pages = {124-138}, abstract = {

Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 {\texttimes} 107 chemical synapses between 139,255 neurons reconstructed from an adult female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages and predictions of neurotransmitter identities. Data products are available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources. We derive a projectome-a map of projections between regions-from the connectome and report on tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine and descending neurons) across both hemispheres and between the central brain and the optic lobes. Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours. The technologies and open ecosystem reported here set the stage for future large-scale connectome projects in other species.

}, doi = {10.1038/s41586-024-07558-y}, url = {https://doi.org/10.1038/s41586-024-07558-y}, author = {Dorkenwald, Sven and Matsliah, Arie and Sterling, Amy R and Schlegel, Philipp and Yu, Szi-Chieh and McKellar, Claire E and Lin, Albert and Costa, Marta and Eichler, Katharina and Yin, Yijie and Silversmith, Will and Schneider-Mizell, Casey and Jordan, Chris S and Brittain, Derrick and Halageri, Akhilesh and Kuehner, Kai and Ogedengbe, Oluwaseun and Morey, Ryan and Gager, Jay and Kruk, Krzysztof and Perlman, Eric and Yang, Runzhe and Deutsch, David and Bland, Doug and Sorek, Marissa and Lu, Ran and Macrina, Thomas and Lee, Kisuk and Bae, J Alexander and Mu, Shang and Nehoran, Barak and Mitchell, Eric and Popovych, Sergiy and Wu, Jingpeng and Jia, Zhen and Castro, Manuel and Kemnitz, Nico and Ih, Dodam and Bates, Alexander Shakeel and Eckstein, Nils and Funke, Jan and Collman, Forrest and Bock, Davi D and Jefferis, Gregory S X E and Seung, H Sebastian and Murthy, Mala} } @article {69439, title = {Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster}, journal = {Cell}, volume = {187}, year = {2024}, month = {2024 May 09}, pages = {2574-2594.e23}, abstract = {

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87\% for individual synapses, 94\% for neurons, and 91\% for known cell types across a D.\ melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

}, keywords = {Animals, Brain, Connectome, Drosophila melanogaster, gamma-Aminobutyric Acid, Microscopy, Electron, Neural Networks, Computer, Neurons, Neurotransmitter Agents, Synapses}, issn = {1097-4172}, doi = {10.1016/j.cell.2024.03.016}, author = {Eckstein, Nils and Bates, Alexander Shakeel and Champion, Andrew and Du, Michelle and Yin, Yijie and Schlegel, Philipp and Lu, Alicia Kun-Yang and Rymer, Thomson and Finley-May, Samantha and Paterson, Tyler and Parekh, Ruchi and Dorkenwald, Sven and Matsliah, Arie and Yu, Szi-Chieh and McKellar, Claire and Sterling, Amy and Eichler, Katharina and Costa, Marta and Seung, Sebastian and Murthy, Mala and Hartenstein, Volker and Jefferis, Gregory S X E and Funke, Jan} }