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Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, twoDrosophilaspecies, including the widely studiedD. melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such ‘anti-directional turning’ is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show thatDrosophilaoptomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

International audience; Genetically encoded voltage indicators are emerging tools for monitoring voltage dynamics with cell-type specificity. However, current indicators enable a narrow range of applications due to poor performance under two-photon microscopy, a method of choice for deep-tissue recording. To improve indicators, we developed a multiparameter high-throughput platform to optimize voltage indicators for two-photon microscopy. Using this system, we identified JEDI-2P, an indicator that is faster, brighter, and more sensitive and photostable than its predecessors. We demonstrate that JEDI-2P can report light-evoked responses in axonal termini of Drosophila interneurons and the dendrites and somata of amacrine cells of isolated mouse retina. JEDI-2P can also optically record the voltage dynamics of individual cortical neurons in awake behaving mice for more than 30 min using both resonant-scanning and ULoVE random-access microscopy. Finally, ULoVE recording of JEDI-2P can robustly detect spikes at depths exceeding 400 μm and report voltage correlations in pairs of neurons.

SummaryWalking is a fundamental mode of locomotion, yet its neural correlates are unknown at brain-wide scale in any animal. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We detect locomotor signals in approximately 40% of the brain, identify a global signal associated with the transition from rest to walking, and define clustered neural signals selectively associated with changes in forward or angular velocity. These networks span functionally diverse brain regions, and include regions that have not been previously linked to locomotion. We also identify time-varying trajectories of neural activity that anticipate future movements, and that represent sequential engagement of clusters of neurons with different behavioral selectivity. These motor maps suggest a dynamical systems framework for constructing walking maneuvers reminiscent of models of forelimb reaching in primates and set a foundation for understanding how local circuits interact across large-scale networks.

SummaryStructural plasticity in the brain often necessitates dramatic remodeling of neuronal processes and attendant reorganization of the cytoskeleton and membranes. While cytoskeletal restructuring has been studied extensively, how lipids might orchestrate structural plasticity remains unclear. We show that specific glial cells in Drosophila produce Glucocerebrosidase (GBA) to locally catabolize sphingolipids. Sphingolipid accumulation drives lysosomal dysfunction, causing gba1b mutants to harbor protein aggregates that cycle across circadian time and are regulated by neural activity, the circadian clock, and sleep. While the vast majority of membrane lipids are stable across the day, a specific subset, highly enriched in sphingolipids, cycles daily in a gba1b-dependant fashion. In parallel, circadian clock neurons remodel their neurites, growing and shrinking across the day to shape circadian behavior. Remarkably, this neuronal remodeling relies on a cycle of temporally offset sphingolipid biosynthesis and catabolism. Thus, dynamic sphingolipid regulation by glia enables diurnal circuit remodeling and proper circadian behavior.

Structural plasticity in the brain often necessitates dramatic remodeling of neuronal processes, with attendant reorganization of the cytoskeleton and membranes. Although cytoskeletal restructuring has been studied extensively, how lipids might orchestrate structural plasticity remains unclear. We show that specific glial cells in Drosophila produce glucocerebrosidase (GBA) to locally catabolize sphingolipids. Sphingolipid accumulation drives lysosomal dysfunction, causing gba1b mutants to harbor protein aggregates that cycle across circadian time and are regulated by neural activity, the circadian clock, and sleep. Although the vast majority of membrane lipids are stable across the day, a specific subset that is highly enriched in sphingolipids cycles daily in a gba1b-dependent fashion. Remarkably, both sphingolipid biosynthesis and degradation are required for the diurnal remodeling of circadian clock neurites, which grow and shrink across the day. Thus, dynamic sphingolipid regulation by glia enables diurnal circuit remodeling and proper circadian behavior.

Neuronal spiking activity is routinely recorded using genetically encoded calcium indicators (GECIs), but calcium imaging is limited in temporal resolution and does not report subthreshold voltage changes. Genetically encoded voltage indicators (GEVIs) offer better temporal resolution and subthreshold sensitivity, but spike detection with fast GEVIs has required specialized imaging equipment. Here, we report the ASAP4 subfamily of genetically encoded voltage indicators (GEVIs) that brighten in response to membrane depolarization, inverting the fluorescence-voltage relationship of previous ASAP GEVIs. Two variants, ASAP4b and ASAP4e, feature 128% and 178% fluorescence increases over 100-mV of depolarization, respectively, facilitating spike detection in single trials in vivo with standard 1 and 2-photon imaging systems. Simultaneous voltage and calcium imaging confirms improved temporal resolution and spike discernment by ASAP4 GEVIs. Thus, positively tuned ASAP4 voltage indicators enable recording of neuronal spiking activity using similar equipment as calcium imaging, while providing higher temporal resolution.One Sentence SummaryUpward ASAPs increase detection capability of GEVIs in vivo.

In visual systems, neurons adapt both to the mean light level and to the range of light levels, or the contrast. Contrast adaptation has been studied extensively, but it remains unclear how it is distributed among neurons in connected circuits, and how early adaptation affects subsequent computations. Here, we investigated temporal contrast adaptation in neurons across Drosophila’s visual motion circuitry. Several ON-pathway neurons showed strong adaptation to changes in contrast over time. One of these neurons, Mi1, showed almost complete adaptation on fast timescales, and experiments ruled out several potential mechanisms for its adaptive properties. When contrast adaptation reduced the gain in ON pathway cells, it was accompanied by decreased motion responses in downstream direction-selective cells. Simulations show that contrast adaptation can substantially improve motion estimates in natural scenes. The benefits are larger for ON-pathway adaptation, which helps explain the heterogeneous distribution of contrast adaptation in these circuits.

Neural circuits must both execute the behavioral repertoire of individuals and account for behavioral variation across species. Understanding how this variation emerges over evolutionary time requires large-scale phylogenetic comparisons of behavioral repertoires. Here, we describe the evolution of walking in fruit flies by capturing high-resolution, unconstrained movement from 13 species and 15 strains of drosophilids. We find that walking can be captured in a universal behavior space, the structure of which is evolutionarily conserved. However, the occurrence of and transitions between specific movements have evolved rapidly, resulting in repeated convergent evolution in the temporal structure of locomotion. Moreover, a meta-analysis demonstrates that many behaviors evolve more rapidly than other traits. Thus, the architecture and physiology of locomotor circuits can execute precise individual movements in one species and simultaneously support rapid evolutionary changes in the temporal ordering of these modular elements across clades.

Neural activity sculpts circuit wiring in many animals. In vertebrates, patterned spontaneous network activity (PaSNA) generates sensory maps and establishes local circuits. However, it remains unclear how PaSNA might shape neuronal circuits and behavior in invertebrates. Previous work in the developing Drosophila embryo discovered spontaneous muscle activity that did not require synaptic transmission, and hence was myogenic, preceding PaSNA. These studies, however, monitored muscle movement, not neural activity, and were therefore unable to observe how myogenic activity might relate to subsequent neural network engagement. Here we use calcium imaging to directly record neural activity and characterize the emergence of PaSNA. We demonstrate that the spatiotemporal properties of PaSNA are highly stereotyped across embryos, arguing for genetic programming. Consistent with previous observations, we observe neural activity well before it becomes patterned, initially emerging during the myogenic stage. Remarkably, inhibition of mechanosensory input results in excessive PaSNA, demonstrating that muscle movement serves as a brake. Finally, using an optogenetic strategy to selectively disrupt mechanosensory inputs during PaSNA, followed by quantitative modeling of larval behavior, we demonstrate that mechanosensory modulation during development is required for proper larval foraging. This work thus provides a foundation for using the Drosophila embryo to study the role of PaSNA in circuit formation, provides mechanistic insight into how PaSNA is entrained by motor activity, and demonstrates that spontaneous network activity is essential for locomotor behavior . These studies argue that sensory feedback during the earliest stages of circuit formation can sculpt locomotor behaviors through innate motor learning.

Summary Anatomical connectivity can constrain both a neural circuit’s function and its underlying computation. This principle has been demonstrated for many small, defined neural circuits. For example, connectome reconstructions have informed models for direction selectivity in the vertebrate retina 1 , 2 as well as the Drosophila visual system. 3 In these cases, the circuit in question is relatively compact, well-defined, and has known functions. However, how the connectome constrains global properties of large-scale networks, across multiple brain regions or the entire brain, is incompletely understood. As the availability of partial or complete connectomes expands to more systems and species 4 , 5 , 6 , 7 , 8 it becomes critical to understand how this detailed anatomical information can inform our understanding of large-scale circuit function. 9 , 10 Here, we use data from the Drosophila connectome 4 in conjunction with whole-brain in vivo imaging 11 to relate structural and functional connectivity in the central brain. We find a strong relationship between resting-state functional correlations and direct region-to-region structural connectivity. We find that the relationship between structure and function varies across the brain, with some regions displaying a tight correspondence between structural and functional connectivity whereas others, including the mushroom body, are more strongly dependent on indirect connections. Throughout this work, we observe features of structural and functional networks in Drosophila that are strikingly similar to those seen in mammalian cortex, including in the human brain. Given the vast anatomical and functional differences between Drosophila and mammalian nervous systems, these observations suggest general principles that govern brain structure, function, and the relationship between the two.

Uncovering relationships between neural activity and behavior represents a critical challenge, one that would benefit from facile tools that can capture complex structures within large datasets. Here we demonstrate a generalizable strategy for capturing such structures across diverse behaviors: Time-REsolved BehavioraL Embedding (TREBLE). Using data from synthetic trajectories, adult and larval Drosophila, and mice we show how TREBLE captures both continuous and discrete behavioral dynamics, can uncover variation across individuals, detect the effects of optogenetic perturbation in unbiased fashion, and reveal structure in pose estimation data. By applying TREBLE to moving mice, and medial entorhinal cortex (MEC) recordings, we show that nearly all MEC neurons encode information relevant to specific movement patterns, expanding our understanding of how navigation is related to the execution of locomotion. Thus, TREBLE provides a flexible framework for describing the structure of complex behaviors and their relationships to neural activity.

Coordinated activity across networks of neurons is a hallmark of both resting and active behavioral states in many species, including worms, flies, fish, mice and humans1–5. These global patterns alter energy metabolism in the brain over seconds to hours, making oxygen consumption and glucose uptake widely used proxies of neural activity6,7. However, whether changes in neural activity are causally related to changes in metabolic flux in intact circuits on the sub-second timescales associated with behavior, is unknown. Moreover, it is unclear whether transitions between rest and action are associated with spatiotemporally structured changes in neuronal energy metabolism. Here, we combine two-photon microscopy of the entire fruit fly brain with sensors that allow simultaneous measurements of neural activity and metabolic flux, across both resting and active behavioral states. We demonstrate that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across large-scale brain networks. Further, these studies reveal that the initiation of even minimal behavioral movements causes large-scale changes in the pattern of neural activity and energy metabolism, revealing unexpected structure in the functional architecture of the brain. The relationship between neural activity and energy metabolism is likely evolutionarily ancient. Thus, these studies provide a critical foundation for using metabolic proxies to capture changes in neural activity and reveal that even minimal behavioral movements are associated with changes in large-scale brain network activity.

Coordinated activity across networks of neurons is a hallmark of both resting and active behavioural states in many species1–5. These global patterns alter energy metabolism over seconds to hours, which underpins the widespread use of oxygen consumption and glucose uptake as proxies of neural activity6,7. However, whether changes in neural activity are causally related to metabolic flux in intact circuits on the timescales associated with behaviour is unclear. Here we combine two-photon microscopy of the fly brain with sensors that enable the simultaneous measurement of neural activity and metabolic flux, across both resting and active behavioural states. We demonstrate that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across brain networks. Using local optogenetic perturbation, we demonstrate that even transient increases in neural activity result in rapid and persistent increases in cytosolic ATP, which suggests that neuronal metabolism predictively allocates resources to anticipate the energy demands of future activity. Finally, our studies reveal that the initiation of even minimal behavioural movements causes large-scale changes in the pattern of neural activity and energy metabolism, which reveals a widespread engagement of the brain. As the relationship between neural activity and energy metabolism is probably evolutionarily ancient and highly conserved, our studies provide a critical foundation for using metabolic proxies to capture changes in neural activity. Two-photon microscopy across the fly brain using sensors that permit simultaneous measurement of neural activity and metabolic flux reveals global and local coordination of neural activity and energy metabolism.

Motion in the visual world provides critical information to guide the behavior of sighted animals. Furthermore, as visual motion estimation requires comparisons of signals across inputs and over time, it represents a paradigmatic and generalizable neural computation. Focusing on the Drosophila visual system, where an explosion of technological advances has recently accelerated experimental progress, we review our understanding of how, algorithmically and mechanistically, motion signals are first computed.

SummaryNeural activity sculpts circuit wiring in many animals. In vertebrates, patterned spontaneous network activity (PaSNA) generates sensory maps and establishes local circuits 1–3. However, it remains unclear how PaSNA might shape neuronal circuits and behavior in invertebrates. Previous work in the developing Drosophila embryo discovered spontaneous muscle activity that did not require synaptic transmission, and hence was myogenic, preceding PaSNA 4–6. These studies, however, monitored muscle movement, not neural activity, and were therefore unable to observe how myogenic activity might relate to subsequent neural network engagement. Here we use calcium imaging to directly record neural activity and characterize the emergence of PaSNA. We demonstrate that the spatiotemporal properties of PaSNA are highly stereotyped across embryos, arguing for genetic programming. Consistent with previous observations, we observe neural activity well before it becomes patterned, initially emerging during the myogenic stage. Remarkably, inhibition of mechanosensory input as well as inhibition of muscle contractions results in premature and excessive PaSNA, demonstrating that muscle movement serves as a brake on this process. Finally, using an optogenetic strategy to selectively disrupt mechanosensory inputs during PaSNA, followed by quantitative modeling of larval behavior, we demonstrate that mechanosensory modulation during development is required for proper larval foraging. This work thus provides a foundation for using the Drosophila embryo to study the role of PaSNA in circuit formation, provides mechanistic insight into how PaSNA is entrained by motor activity, and demonstrates that spontaneous network activity is essential for locomotor behavior. These studies argue that sensory feedback during the earliest stages of circuit formation can sculpt locomotor behaviors through innate motor learning.HighlightsPaSNA in the Drosophila embryonic CNS is spatiotemporally stereotypedMechanosensory neurons negatively modulate PaSNAEmbryonic PaSNA is required for larval locomotor behavior

Retinotopic maps represent a fundamental organizing principle of visual system wiring. A recent study illustrates how careful coordination of developmental strategies can simultaneously create a diverse array of cell types and establish a complex wiring diagram.

Many experimental approaches rely on controlling gene expression in select subsets of cells within an individual animal. However, reproducibly targeting transgene expression to specific fractions of a genetically-defined cell-type is challenging. We developedSparsePredictiveActivity throughRecombinaseCompetition (SPARC), a generalizable toolkit that can express any effector in precise proportions of post-mitotic cells inDrosophila. Using this approach, we demonstrate targeted expression of many effectors and apply these tools to calcium imaging of individual neurons and optogenetic manipulation of sparse cell populationsin vivo.

A new study has mapped the connectome - the shapes and connections of all the neurons- of the visual system of a Drosophila larva, providing a structural basis for understanding the neural circuitry of larval vision.

The activity and maintenance of neurons requires substantial metabolic energy, resulting in selective pressure to decrease resource consumption by the nervous system. The wiring economy principle proposes that animals have evolved mechanisms that wire circuits efficiently by minimizing neurite length. Computational modeling of neuronal morphology, microcircuit organization, and neural networks reveals that wiring economy is a significant determinant of nervous system layout. The strategies for reducing wiring costs are shared across phyla and point to the possibility of generalizable rules that specify the development of efficient nervous systems. As the developmental mechanisms underpinning wiring economy are only now being elucidated, whether the molecular basis of this phenomenon is the result of conserved genetic programs or convergent evolution remains to be determined.

Intracellular Ca(2+) is a widely used neuronal activity indicator. Here we describe a transcriptional reporter of intracellular Ca(2+) (TRIC) in Drosophila that uses a binary expression system to report Ca(2+)-dependent interactions between calmodulin and its target peptide. We found that in vitro assays predicted in vivo properties of TRIC and that TRIC signals in sensory systems depend on neuronal activity. TRIC was able to quantitatively monitor neuronal responses that changed slowly, such as those of neuropeptide F-expressing neurons to sexual deprivation and neuroendocrine pars intercerebralis cells to food and arousal. Furthermore, TRIC-induced expression of a neuronal silencer in nutrient-activated cells enhanced stress resistance, providing a proof of principle that TRIC can be used for circuit manipulation. Thus, TRIC facilitates the monitoring and manipulation of neuronal activity, especially those reflecting slow changes in physiological states that are poorly captured by existing methods. TRIC's modular design should enable optimization and adaptation to other organisms.

We present an imaging system for pan-neuronal recording in crawling Caenorhabditis elegans. A spinning disk confocal microscope, modified for automated tracking of the C. elegans head ganglia, simultaneously records the activity and position of ∼80 neurons that coexpress cytoplasmic calcium indicator GCaMP6s and nuclear localized red fluorescent protein at 10 volumes per second. We developed a behavioral analysis algorithm that maps the movements of the head ganglia to the animal's posture and locomotion. Image registration and analysis software automatically assigns an index to each nucleus and calculates the corresponding calcium signal. Neurons with highly stereotyped positions can be associated with unique indexes and subsequently identified using an atlas of the worm nervous system. To test our system, we analyzed the brainwide activity patterns of moving worms subjected to thermosensory inputs. We demonstrate that our setup is able to uncover representations of sensory input and motor output of individual neurons from brainwide dynamics. Our imaging setup and analysis pipeline should facilitate mapping circuits for sensory to motor transformation in transparent behaving animals such as C. elegans and Drosophila larva.

Background Drosophila melanogaster has served as a powerful model system for genetic studies of courtship songs. To accelerate research on the genetic and neural mechanisms underlying courtship song, we have developed a sensitive recording system to simultaneously capture the acoustic signals from 32 separate pairs of courting flies as well as software for automated segmentation of songs. Results Our novel hardware design enables recording of low amplitude sounds in most laboratory environments. We demonstrate the power of this system by collecting, segmenting and analyzing over 18 hours of courtship song from 75 males from five wild-type strains of Drosophila melanogaster. Our analysis reveals previously undetected modulation of courtship song features and extensive natural genetic variation for most components of courtship song. Despite having a large dataset with sufficient power to detect subtle modulations of song, we were unable to identify previously reported periodic rhythms in the inter-pulse interval of song. We provide detailed instructions for assembling the hardware and for using our open-source segmentation software. Conclusions Analysis of a large dataset of acoustic signals from Drosophila melanogaster provides novel insight into the structure and dynamics of species-specific courtship songs. Our new system for recording and analyzing fly acoustic signals should therefore greatly accelerate future studies of the genetics, neurobiology and evolution of courtship song.

In this chapter we will discuss the application of genetics to the interrogation of neuronal function in fruit flies from a historical and modern perspective. We will review the current state-of-the-art tool kit for circuit dissection including neuronal measurements, manipulation and quantitative behavioral assessment. We will then discuss how these approaches can be productively applied to the interrogation of circuit computation by discussing recent discoveries in visual circuitry. Due to dramatic progress in recent years, these new tools have greatly expanded our understanding of the cell types and algorithmic transformations that underpin the detection of visual motion.

The algorithms and neural circuits that process spatio-temporal changes in luminance to extract visual motion cues have been the focus of intense research. An influential model, the Hassenstein-Reichardt correlator, relies on differential temporal filtering of two spatially separated input channels, delaying one input signal with respect to the other. Motion in a particular direction causes these delayed and non-delayed luminance signals to arrive simultaneously at a subsequent processing step in the brain; these signals are then nonlinearly amplified to produce a direction-selective response. Recent work in Drosophila has identified two parallel pathways that selectively respond to either moving light or dark edges. Each of these pathways requires two critical processing steps to be applied to incoming signals: differential delay between the spatial input channels, and distinct processing of brightness increment and decrement signals. Here we demonstrate, using in vivo patch-clamp recordings, that four medulla neurons implement these two processing steps. The neurons Mi1 and Tm3 respond selectively to brightness increments, with the response of Mi1 delayed relative to Tm3. Conversely, Tm1 and Tm2 respond selectively to brightness decrements, with the response of Tm1 delayed compared with Tm2. Remarkably, constraining Hassenstein-Reichardt correlator models using these measurements produces outputs consistent with previously measured properties of motion detectors, including temporal frequency tuning and specificity for light versus dark edges. We propose that Mi1 and Tm3 perform critical processing of the delayed and non-delayed input channels of the correlator responsible for the detection of light edges, while Tm1 and Tm2 play analogous roles in the detection of moving dark edges. Our data show that specific medulla neurons possess response properties that allow them to implement the algorithmic steps that precede the correlative operation in the Hassenstein-Reichardt correlator, revealing elements of the long-sought neural substrates of motion detection in the fly.

Summary Background Neuronal circuits in worms, flies, and mammals are organized so as to minimize wiring length for a functional number of synaptic connections, a phenomenon called wiring optimization. However, the molecular mechanisms that establish optimal wiring during development are unknown. We addressed this question by studying the role of N-cadherin in the development of optimally wired neurite fascicles in the peripheral visual system of Drosophila . Results Photoreceptor axons surround the dendrites of their postsynaptic targets, called lamina cells, within a concentric fascicle called a cartridge. N-cadherin is expressed at higher levels in lamina cells than in photoreceptors, and all genetic manipulations that invert these relative differences displace lamina cells to the periphery and relocate photoreceptor axon terminals into the center. Conclusions Differential expression of a single cadherin is both necessary and sufficient to determine cartridge structure because it positions the most-adhesive elements that make the most synapses at the core and the less-adhesive elements that make fewer synapses at the periphery. These results suggest a general model by which differential adhesion can be utilized to determine the relative positions of axons and dendrites to establish optimal wiring.

Understanding the mechanisms that link sensory stimuli to animal behavior is a central challenge in neuroscience. The quantitative description of behavioral responses to defined stimuli has led to a rich understanding of different behavioral strategies in many species. One important navigational cue perceived by many vertebrates and insects is the e-vector orientation of linearly polarized light. Drosophila manifests an innate orientation response to this cue ('polarotaxis'), aligning its body axis with the e-vector field. We have established a population-based behavioral paradigm for the genetic dissection of neural circuits guiding polarotaxis to both celestial as well as reflected polarized stimuli. However, the behavioral mechanisms by which flies align with a linearly polarized stimulus remain unknown. Here, we present a detailed quantitative description of Drosophila polarotaxis, systematically measuring behavioral parameters that are modulated by the stimulus. We show that angular acceleration is modulated during alignment, and this single parameter may be sufficient for alignment. Furthermore, using monocular deprivation, we show that each eye is necessary for modulating turns in the ipsilateral direction. This analysis lays the foundation for understanding how neural circuits guide these important visual behaviors.

Summary Neurons can maintain stable synaptic connections across adult life. However, the signals that regulate expression of synaptic proteins in the mature brain are incompletely understood. Here, we describe a transcriptional feedback loop between the biosynthesis and repertoire of specific phospholipids and the synaptic vesicle pool in adult Drosophila photoreceptors. Mutations that disrupt biosynthesis of a subset of phospholipids cause degeneration of the axon terminal and loss of synaptic vesicles. Although degeneration of the axon terminal is dependent on neural activity, activation of sterol regulatory element binding protein (SREBP) is both necessary and sufficient to cause synaptic vesicle loss. Our studies demonstrate that SREBP regulates synaptic vesicle levels by interacting with tetraspanins, critical organizers of membranous organelles. SREBP is an evolutionarily conserved regulator of lipid biosynthesis in non-neuronal cells; our studies reveal a surprising role for this feedback loop in maintaining synaptic vesicle pools in the adult brain.

Summary Background: Chemotaxis, the ability to direct movements according to chemical cues in the environment, is important for the survival of most organisms. The vinegar fly, Drosophila melanogaster, displays robust olfactory aversion and attraction, but how these behaviors are executed via changes in locomotion remains poorly understood. In particular, it is not clear whether aversion and attraction bidirectionally modulate a shared circuit or recruit distinct circuits for execution. Results:Using a quantitative behavioral assay, we determined that both aversive and attractive odorants modulate the initiation and direction of turns but display distinct kinematics. Using genetic tools to perturb these behaviors, we identified specific populations of neurons required for aversion, but not for attraction. Inactivation of these populations of cells affected the completion of aversive turns, but not their initiation. Optogenetic activation of the same populations of cells triggered a locomotion pattern resembling aversive turns. Perturbations in both the ellipsoid body and the ventral nerve cord, two regions involved in motor control, resulted in defects in aversion. Conclusions: Aversive chemotaxis in vinegar flies triggers ethologically appropriate kinematics distinct from those of attractive chemotaxis and requires specific motor-related neurons.

Across animal phyla, motion vision relies on neurons that respond preferentially to stimuli moving in one, preferred direction over the opposite, null direction. In the elementary motion detector of Drosophila , direction selectivity emerges in two neuron types, T4 and T5, but the computational algorithm underlying this selectivity remains unknown. We find that the receptive fields of both T4 and T5 exhibit spatiotemporally offset light-preferring and dark-preferring subfields, each obliquely oriented in spacetime. In a linear-nonlinear modeling framework, the spatiotemporal organization of the T5 receptive field predicts the activity of T5 in response to motion stimuli. These findings demonstrate that direction selectivity emerges from the enhancement of responses to motion in the preferred direction, as well as the suppression of responses to motion in the null direction. Thus, remarkably, T5 incorporates the essential algorithmic strategies used by the Hassenstein–Reichardt correlator and the Barlow–Levick detector. Our model for T5 also provides an algorithmic explanation for the selectivity of T5 for moving dark edges: our model captures all two- and three-point spacetime correlations relevant to motion in this stimulus class. More broadly, our findings reveal the contribution of input pathway visual processing, specifically center-surround, temporally biphasic receptive fields, to the generation of direction selectivity in T5. As the spatiotemporal receptive field of T5 in Drosophila is common to the simple cell in vertebrate visual cortex, our stimulus-response model of T5 will inform efforts in an experimentally tractable context to identify more detailed, mechanistic models of a prevalent computation. SIGNIFICANCE STATEMENT Feature selective neurons respond preferentially to astonishingly specific stimuli, providing the neurobiological basis for perception. Direction selectivity serves as a paradigmatic model of feature selectivity that has been examined in many species. While insect elementary motion detectors have served as premiere experimental models of direction selectivity for 60 years, the central question of their underlying algorithm remains unanswered. Using in vivo two-photon imaging of intracellular calcium signals, we measure the receptive fields of the first direction-selective cells in the Drosophila visual system, and define the algorithm used to compute the direction of motion. Computational modeling of these receptive fields predicts responses to motion and reveals how this circuit efficiently captures many useful correlations intrinsic to moving dark edges.

A mechanistic understanding of neural computation requires determining how information is processed as it passes through neurons and across synapses. However, it has been challenging to measure membrane potential changes in axons and dendrites in vivo. We use in vivo, two-photon imaging of novel genetically encoded voltage indicators, as well as calcium imaging, to measure sensory stimulus-evoked signals in the Drosophila visual system with subcellular resolution. Across synapses, we find major transformations in the kinetics, amplitude, and sign of voltage responses to light. We also describe distinct relationships between voltage and calcium signals in different neuronal compartments, a substrate for local computation. Finally, we demonstrate that ON and OFF selectivity, a key feature of visual processing across species, emerges through the transformation of membrane potential into intracellular calcium concentration. By imaging voltage and calcium signals to map information flow with subcellular resolution, we illuminate where and how critical computations arise.

Classifying sensory experiences as either novel or familiar represents a fundamental challenge to neural processing. In this issue of Cell, Hattori et al. describe a circuit mechanism by which a novel stimulus that initially interests a fruit fly turns into a familiar one.