@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 {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 {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} } @article {67771, title = {A connectome of the central complex reveals network motifs suitable for flexible navigation and context-dependent action selection.}, journal = {eLife}, volume = {10}, year = {2021}, month = {2021 Oct 26}, abstract = {

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly{\textquoteright}s head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

}, issn = {2050-084X}, doi = {10.7554/eLife.66039}, author = {Hulse, Brad K and Haberkern, Hannah and Franconville, Romain and Turner-Evans, Daniel B and Takemura, Shin-ya and Wolff, Tanya and Noorman, Marcella and Dreher, Marisa and Dan, Chuntao and Parekh, Ruchi and Hermundstad, Ann M and Rubin, Gerald M and Jayaraman, Vivek} } @article {65859, title = {Neural circuit mechanisms of sexual receptivity in Drosophila females.}, journal = {Nature}, volume = {589}, year = {2021}, month = {2021 Jan 01}, pages = {577-81}, abstract = {

Choosing a mate is one of the most consequential decisions a female will make during her lifetime. A female fly signals her willingness to mate by opening her vaginal plates, allowing a courting male to copulate. Vaginal plate opening (VPO) occurs in response to the male courtship song and is dependent on the mating status\ of the female. How these exteroceptive (song) and interoceptive (mating status) inputs are integrated to regulate VPO remains unknown. Here we characterize the neural circuitry that implements mating decisions in the brain of female Drosophila melanogaster. We show that VPO is controlled by a pair of female-specific descending neurons (vpoDNs). The vpoDNs receive excitatory input from auditory neurons (vpoENs), which are tuned to specific features of the D. melanogaster song, and from pC1 neurons, which encode the mating status\ of the female. The song responses of vpoDNs, but not vpoENs, are attenuated upon mating, accounting for the reduced receptivity of mated females. This modulation is mediated by pC1 neurons. The vpoDNs thus directly integrate the external and internal signals that control the mating decisions of Drosophila females.

}, issn = {1476-4687}, doi = {10.1038/s41586-020-2972-7}, author = {Wang, Kaiyu and Wang, Fei and Forknall, Nora and Yang, Tansy and Patrick, Christopher and Parekh, Ruchi and Dickson, Barry J} } @article {65816, title = {Cell types and neuronal circuitry underlying female aggression in Drosophila.}, journal = {eLife}, volume = {9}, year = {2020}, month = {2020 Nov 03}, abstract = {

Aggressive social interactions are used to compete for limited resources and are regulated by complex sensory cues and the organism{\textquoteright}s internal state. While both sexes exhibit aggression, its neuronal underpinnings are understudied in females. Here, we identify a population of sexually dimorphic aIPg neurons in the adult central brain whose optogenetic activation increased, and genetic inactivation reduced, female aggression. Analysis of GAL4 lines identified in an unbiased screen for increased female chasing behavior revealed the involvement of another sexually dimorphic neuron, pC1d, and implicated aIPg and pC1d neurons as core nodes regulating female aggression. Connectomic analysis demonstrated that aIPg neurons and pC1d are interconnected and suggest that aIPg neurons may exert part of their effect by gating the flow of visual information to descending neurons. Our work reveals important regulatory components of the neuronal circuitry that underlies female aggressive social interactions and provides tools for their manipulation.

}, issn = {2050-084X}, doi = {10.7554/eLife.58942}, author = {Schretter, Catherine E and Aso, Yoshi and Robie, Alice A and Dreher, Marisa and Dolan, Michael-John and Chen, Nan and Ito, Masayoshi and Yang, Tansy and Parekh, Ruchi and Branson, Kristin M and Rubin, Gerald M} } @article {65683, title = {Circuit and behavioral mechanisms of sexual rejection by drosophila females.}, journal = {Current Biology}, volume = {30}, year = {2020}, month = {2020 Oct 05}, abstract = {

The mating decisions of Drosophila melanogaster females are primarily revealed through either of two discrete actions: opening of the vaginal plates to allow copulation, or extrusion of the ovipositor to reject the male. Both actions are triggered by the male courtship song, and both are dependent upon the female{\textquoteright}s mating status. Virgin females are more likely to open their vaginal plates in response to song; mated females are more likely to extrude their ovipositor. Here, we examine the neural cause and behavioral consequence of ovipositor extrusion. We show that the DNp13 descending neurons act as command-type neurons for ovipositor extrusion, and that ovipositor extrusion is an effective deterrent only when performed by females that have previously mated. The DNp13 neurons respond to male song via direct synaptic input from the pC2l auditory neurons. Mating status does not modulate the song responses of DNp13 neurons, but rather how effectively they can engage the motor circuits for ovipositor extrusion. We present evidence that mating status information is mediated by ppk sensory neurons in the uterus, which are activated upon ovulation. Vaginal plate opening and ovipositor extrusion are thus controlled by anatomically and functionally distinct circuits, highlighting the diversity of neural decision-making circuits even in the context of closely related behaviors with shared exteroceptive and interoceptive inputs.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2020.07.083}, author = {Wang, Fei and Wang, Kaiyu and Forknall, Nora and Parekh, Ruchi and Dickson, Barry J} } @article {68507, title = {A connectome and analysis of the adult Drosophila central brain.}, journal = {Elife}, volume = {9}, year = {2020}, month = {2020 Sep 07}, abstract = {

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly . Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly{\textquoteright}s brain.

}, keywords = {Animals, Brain, Connectome, Drosophila melanogaster, Female, Male, Neurons, Synapses}, issn = {2050-084X}, doi = {10.7554/eLife.57443}, author = {Scheffer, Louis K and Xu, C Shan and Januszewski, Michal and Lu, Zhiyuan and Takemura, Shin-ya and Hayworth, Kenneth J and Huang, Gary B and Shinomiya, Kazunori and Maitlin-Shepard, Jeremy and Berg, Stuart and Clements, Jody and Hubbard, Philip M and Katz, William T and Umayam, Lowell and Zhao, Ting and Ackerman, David and Blakely, Tim and Bogovic, John and Dolafi, Tom and Kainmueller, Dagmar and Kawase, Takashi and Khairy, Khaled A and Leavitt, Laramie and Li, Peter H and Lindsey, Larry and Neubarth, Nicole and Olbris, Donald J and Otsuna, Hideo and Trautman, Eric T and Ito, Masayoshi and Bates, Alexander S and Goldammer, Jens and Wolff, Tanya and Svirskas, Robert and Schlegel, Philipp and Neace, Erika and Knecht, Christopher J and Alvarado, Chelsea X and Bailey, Dennis A and Ballinger, Samantha and Borycz, Jolanta A and Canino, Brandon S and Cheatham, Natasha and Cook, Michael and Dreher, Marisa and Duclos, Octave and Eubanks, Bryon and Fairbanks, Kelli and Finley, Samantha and Forknall, Nora and Francis, Audrey and Hopkins, Gary Patrick and Joyce, Emily M and Kim, SungJin and Kirk, Nicole A and Kovalyak, Julie and Lauchie, Shirley A and Lohff, Alanna and Maldonado, Charli and Manley, Emily A and McLin, Sari and Mooney, Caroline and Ndama, Miatta and Ogundeyi, Omotara and Okeoma, Nneoma and Ordish, Christopher and Padilla, Nicholas and Patrick, Christopher M and Paterson, Tyler and Phillips, Elliott E and Phillips, Emily M and Rampally, Neha and Ribeiro, Caitlin and Robertson, Madelaine K and Rymer, Jon Thomson and Ryan, Sean M and Sammons, Megan and Scott, Anne K and Scott, Ashley L and Shinomiya, Aya and Smith, Claire and Smith, Kelsey and Smith, Natalie L and Sobeski, Margaret A and Suleiman, Alia and Swift, Jackie and Takemura, Satoko and Talebi, Iris and Tarnogorska, Dorota and Tenshaw, Emily and Tokhi, Temour and Walsh, John J and Yang, Tansy and Horne, Jane Anne and Li, Feng and Parekh, Ruchi and Rivlin, Patricia K and Jayaraman, Vivek and Costa, Marta and Jefferis, Gregory Sxe and Ito, Kei and Saalfeld, Stephan and George, Reed and Meinertzhagen, Ian A and Rubin, Gerald M and Hess, Harald F and Jain, Viren and Plaza, Stephen M} } @article {65899, title = {The connectome of the adult mushroom body provides insights into function.}, journal = {eLife}, volume = {9}, year = {2020}, month = {2020 Dec 14}, abstract = {

Making inferences about the computations performed by neuronal circuits from synapse-level connectivity maps is an emerging opportunity in neuroscience. The mushroom body (MB) is well positioned for developing and testing such an approach due to its conserved neuronal architecture, recently completed dense connectome, and extensive prior experimental studies of its roles in learning, memory and activity regulation. Here we identify new components of the MB circuit in , including extensive visual input and MB output neurons (MBONs) with direct connections to descending neurons. We find unexpected structure in sensory inputs, in the transfer of information about different sensory modalities to MBONs, and in the modulation of that transfer by dopaminergic neurons (DANs). We provide insights into the circuitry used to integrate MB outputs, connectivity between the MB and the central complex and inputs to DANs, including feedback from MBONs. Our results provide a foundation for further theoretical and experimental work.

}, issn = {2050-084X}, doi = {10.7554/eLife.62576}, author = {Li, Feng and Lindsey, Jack W and Marin, Elizabeth C and Otto, Nils and Dreher, Marisa and Dempsey, Georgia and Stark, Ildiko and Bates, Alexander S and Pleijzier, Markus William and Schlegel, Philipp and Nern, Aljoscha and Takemura, Shin-ya and Eckstein, Nils and Yang, Tansy and Francis, Audrey and Braun, Amalia and Parekh, Ruchi and Costa, Marta and Scheffer, Louis K and Aso, Yoshi and Jefferis, Gregory Sxe and Abbott, Larry F and Litwin-Kumar, Ashok and Waddell, Scott and Rubin, Gerald M} } @article {65317, title = {Neural circuitry linking mating and egg laying in Drosophila females.}, journal = {Nature}, volume = {579}, year = {2020}, month = {2020 Mar 02}, pages = {101-105}, abstract = {

Mating and egg laying are tightly cooordinated events in the reproductive life of\ all oviparous females. Oviposition is typically rare in virgin females but is initiated after copulation. Here we identify the neural circuitry that links egg laying to mating status in Drosophila melanogaster. Activation of female-specific oviposition descending neurons (oviDNs) is necessary and sufficient for egg laying, and is equally potent in virgin and mated females. After mating, sex peptide-a protein from the male seminal fluid-triggers many behavioural and physiological changes in the female, including the onset of egg laying. Sex peptide is detected by sensory neurons in the uterus, and silences these neurons and their postsynaptic ascending neurons in the abdominal ganglion. We show that these\ abdominal ganglion neurons directly activate the female-specific pC1 neurons. GABAergic (γ-aminobutyric-acid-releasing) oviposition inhibitory neurons (oviINs) mediate feed-forward inhibition from pC1 neurons to both oviDNs and their major excitatory input, the oviposition excitatory neurons (oviENs). By attenuating the abdominal ganglion inputs to pC1 neurons and oviINs, sex peptide disinhibits oviDNs to enable egg laying after mating. This circuitry thus coordinates the two key events in female reproduction: mating and egg laying.

}, issn = {1476-4687}, doi = {10.1038/s41586-020-2055-9}, author = {Wang, Fei and Wang, Kaiyu and Forknall, Nora and Patrick, Christopher and Yang, Tansy and Parekh, Ruchi and Bock, Davi and Dickson, Barry J} } @article {64825, title = {Neural basis for looming size and velocity encoding in the Drosophila giant fiber escape pathway.}, journal = {Current Biology : CB}, volume = {29}, year = {2019}, month = {2019 Feb 28}, pages = {1073}, abstract = {

Identified neuron classes in vertebrate cortical [1-4] and subcortical [5-8] areas and invertebrate peripheral [9-11] and central [12-14] brain neuropils encode specific visual features of a panorama. How downstream neurons integrate these features to control vital behaviors, like escape, is unclear [15]. In Drosophila, the timing of a single spike in the giant fiber (GF) descending neuron [16-18] determines whether a fly uses a short or long takeoff when escaping a looming predator [13]. We previously proposed that GF spike timing results from summation of two visual features whose detection is highly conserved across animals [19]: an object{\textquoteright}s subtended angular size and its angular velocity [5-8, 11, 20, 21]. We attributed velocity encoding to input from lobula columnar type 4 (LC4) visual projection neurons, but the size-encoding\ source remained unknown. Here, we show that lobula plate/lobula columnar, type 2 (LPLC2) visual projection neurons anatomically specialized to detect looming [22] provide the entire GF size component. We find LPLC2 neurons to be necessary for GF-mediated escape and show that LPLC2 and LC4 synapse directly onto the GF via reconstruction in a fly brain electron microscopy (EM) volume [23]. LPLC2 silencing eliminates the size component of the GF looming response in patch-clamp recordings, leaving only the velocity component. A model summing a linear function of angular velocity (provided by LC4) and a Gaussian function of angular size (provided by LPLC2) replicates GF looming response dynamics and predicts the peak response time. We thus present an identified circuit in which information from looming feature-detecting neurons is combined by a common post-synaptic target to determine behavioral output.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2019.01.079}, author = {Ache, Jan M and Polsky, Jason and Alghailani, Shada and Parekh, Ruchi and Breads, Patrick and Peek, Martin Y and Bock, Davi D and von Reyn, Catherine R and Card, Gwyneth M} }