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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 copulate1,2. 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 female3,4. 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. In Drosophila melanogaster, female mating decisions are governed by female-specific descending neurons that integrate input from auditory neurons that respond to features of the song of a conspecific male and central neurons that encode the mating status of the female.

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 Drosophila melanogaster. 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’s brain., eLife digest Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons – compared to some 86 billion in humans – the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map – or connectome – the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

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 Drosophila melanogaster. 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’s brain.

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions.Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

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 laying1. Sex peptide is detected by sensory neurons in the uterus2–4, and silences these neurons and their postsynaptic ascending neurons in the abdominal ganglion5. 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. Neuron-tracing and labelling experiments in Drosophila females reveal the neural circuitry that coordinates mating and egg laying, and the role of sex peptide from male seminal fluid in triggering these neurons.

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'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.