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.

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.

Animals flexibly switch between different actions by changing neural activity patterns for motor control. Courting Drosophila melanogaster males produce two different acoustic signals, pulse and sine song, each of which can be promoted by artificial activation of distinct neurons. However, how the activity of these neurons implements flexible song production is unknown. Here, we developed an assay to record neuronal calcium signals in the ventral nerve cord, which contains the song motor circuit, in singing flies. We found that sine-promoting neurons, but not pulse-promoting neurons, show strong activation during sine song. In contrast, both pulse- and sine-promoting neurons are active during pulse song. Furthermore, population calcium imaging in the song circuit suggests that sine song involves activation of a subset of neurons that are also active during pulse song. Thus, differential activation of overlapping, rather than distinct, neural populations underlies flexible motor actions during acoustic communication in D. melanogaster.

Animals exhibit innate behaviours to a variety of sensory stimuli including olfactory cues. In , one higher olfactory centre, the lateral horn (LH), is implicated in innate behaviour. However, our structural and functional understanding of the LH is scant, in large part due to a lack of sparse neurogenetic tools for this region. We generate a collection of split-GAL4 driver lines providing genetic access to 82 LH cell types. We use these to create an anatomical and neurotransmitter map of the LH and link this to EM connectomics data. We find ~30% of LH projections converge with outputs from the mushroom body, site of olfactory learning and memory. Using optogenetic activation, we identify LH cell types that drive changes in valence behavior or specific locomotor programs. In summary, we have generated a resource for manipulating and mapping LH neurons, providing new insights into the circuit basis of innate and learned olfactory behavior.

Animals employ diverse learning rules and synaptic plasticity dynamics to record temporal and statistical information about the world. However, the molecular mechanisms underlying this diversity are poorly understood. The anatomically defined compartments of the insect mushroom body function as parallel units of associative learning, with different learning rates, memory decay dynamics and flexibility (Aso & Rubin 2016). Here we show that nitric oxide (NO) acts as a neurotransmitter in a subset of dopaminergic neurons in . NO's effects develop more slowly than those of dopamine and depend on soluble guanylate cyclase in postsynaptic Kenyon cells. NO acts antagonistically to dopamine; it shortens memory retention and facilitates the rapid updating of memories. The interplay of NO and dopamine enables memories stored in local domains along Kenyon cell axons to be specialized for predicting the value of odors based only on recent events. Our results provide key mechanistic insights into how diverse memory dynamics are established in parallel memory systems.

Memory guides the choices an animal makes across widely varying conditions in dynamic environments. Consequently, the most adaptive choice depends on the options available. How can a single memory support optimal behavior across different sets of choice options? We address this using olfactory learning in Drosophila. Even when we restrict an odor-punishment association to a single set of synapses using optogenetics, we find that flies still show choice behavior that depends on the options it encounters. Here we show that how the odor choices are presented to the animal influences memory recall itself. Presenting two similar odors in sequence enabled flies to not only discriminate them behaviorally but also at the level of neural activity. However, when the same odors were encountered as solitary stimuli, no such differences were detectable. These results show that memory recall is not simply a comparison to a static learned template, but can be adaptively modulated by stimulus dynamics.

Natural behaviors are a coordinated symphony of motor acts which drive self-induced or reafferent sensory activation. Single sensors only signal presence and magnitude of a sensory cue; they cannot disambiguate exafferent (externally-induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to make appropriate decisions and initiate adaptive behavioral outcomes. This is mediated by predictive motor signaling mechanisms, which emanate from motor control pathways to sensory processing pathways, but how predictive motor signaling circuits function at the cellular and synaptic level is poorly understood. We use a variety of techniques, including connectomics from both male and female electron microscopy volumes, transcriptomics, neuroanatomical, physiological and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs), which putatively provide predictive motor signals to several sensory and motor neuropil. Both AHN pairs receive input primarily from an overlapping population of descending neurons, many of which drive wing motor output. The two AHN pairs target almost exclusively non-overlapping downstream neural networks including those that process visual, auditory and mechanosensory information as well as networks coordinating wing, haltere, and leg motor output. These results support the conclusion that the AHN pairs multi-task, integrating a large amount of common input, then tile their output in the brain, providing predictive motor signals to non-overlapping sensory networks affecting motor control both directly and indirectly.

The Drosophila mushroom body (MB) is a key associative memory center that has also been implicated in the control of sleep. However, the identity of MB neurons underlying homeostatic sleep regulation, as well as the types of sleep signals generated by specific classes of MB neurons, has remained poorly understood. We recently identified two MB output neuron (MBON) classes whose axons convey sleep control signals from the MB to converge in the same downstream target region: a cholinergic sleep-promoting MBON class and a glutamatergic wake-promoting MBON class. Here, we deploy a combination of neurogenetic, behavioral, and physiological approaches to identify and mechanistically dissect sleep-controlling circuits of the MB. Our studies reveal the existence of two segregated excitatory synaptic microcircuits that propagate homeostatic sleep information from different populations of intrinsic MB "Kenyon cells" (KCs) to specific sleep-regulating MBONs: sleep-promoting KCs increase sleep by preferentially activating the cholinergic MBONs, while wake-promoting KCs decrease sleep by preferentially activating the glutamatergic MBONs. Importantly, activity of the sleep-promoting MB microcircuit is increased by sleep deprivation and is necessary for homeostatic rebound sleep (i.e., the increased sleep that occurs after, and in compensation for, sleep lost during deprivation). These studies reveal for the first time specific functional connections between subsets of KCs and particular MBONs and establish the identity of synaptic microcircuits underlying transmission of homeostatic sleep signals in the MB.

The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.

To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great diversity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their function. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse driver lines targeting 198 individual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neural circuits and connectivity of premotor circuits while linking them to behavioral outputs.