@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} }