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To survive, animals must convert sensory information into appropriate behaviours1,2. Vision is a common sense for locating ethologically relevant stimuli and guiding motor responses3–5. How circuitry converts object location in retinal coordinates to movement direction in body coordinates remains largely unknown. Here we show through behaviour, physiology, anatomy and connectomics in Drosophila that visuomotor transformation occurs by conversion of topographic maps formed by the dendrites of feature-detecting visual projection neurons (VPNs)6,7 into synaptic weight gradients of VPN outputs onto central brain neurons. We demonstrate how this gradient motif transforms the anteroposterior location of a visual looming stimulus into the fly’s directional escape. Specifically, we discover that two neurons postsynaptic to a looming-responsive VPN type promote opposite takeoff directions. Opposite synaptic weight gradients onto these neurons from looming VPNs in different visual field regions convert localized looming threats into correctly oriented escapes. For a second looming-responsive VPN type, we demonstrate graded responses along the dorsoventral axis. We show that this synaptic gradient motif generalizes across all 20 primary VPN cell types and most often arises without VPN axon topography. Synaptic gradients may thus be a general mechanism for conveying spatial features of sensory information into directed motor outputs.

Summary: Sparse manipulation of neuron excitability during free behavior is critical for identifying neural substrates of behavior. Genetic tools for precise neuronal manipulation exist in the fruit fly, Drosophila melanogaster, but behavioral tools are still lacking to identify potentially subtle phenotypes only detectible using high-throughput and high spatiotemporal resolution. We developed three assay components that can be used modularly to study natural and optogenetically induced behaviors. FlyGate automatically releases flies one at a time into an assay. FlyDetect tracks flies in real time, is robust to severe occlusions, and can be used to track appendages, such as the head. GlobeDisplay is a spherical projection system covering the fly’s visual receptive field with a single projector. We demonstrate the utility of these components in an integrated system, FlyPEZ, by comprehensively modeling the input-output function for directional looming-evoked escape takeoffs and describing a millisecond-timescale phenotype from genetic silencing of a single visual projection neuron type. : Williamson et al. developed a high-throughput device to automatically isolate individual flies and record their behavior with high-speed video. They demonstrate the system’s utility for studying the Drosophila brain using modern genetic tools by discovering behavioral phenotypes that result from manipulation of small groups of neurons. Keywords: neuroscience, Drosophila, behavior, neural substrates, high throughput, neural circuits, high-speed video, visual stimulation, neural activation, escape, machine vision

Startle behaviors are rapid, high-performance motor responses to threatening stimuli. Startle responses have been identified in a broad range of species across animal diversity. For investigations of neural circuit structure and function, these behaviors offer a number of benefits, including that they are driven by large and identifiable neurons and their neural control is simple in comparison to other behaviors. Among vertebrates, the best-known startle circuit is the Mauthner cell circuit of fishes. In recent years, genetic approaches in zebrafish have provided key tools for morphological and physiological dissection of circuits and greatly extended understanding of their architecture. Here we discuss the startle circuit of fishes, with a focus on the Mauthner cells and associated interneurons called spiral fiber neurons and we add new observations on hindbrain circuit organization. We also briefly review and compare startle circuits of several other taxa, paying particular attention to how movement direction is controlled.

In contrast to larger species, little is known about the flight of the smallest flying insects, such as thrips and fairyflies. These tiny animals range from 300 to 1000 microns in length and fly at Reynolds numbers ranging from about 4 to 60. Previous work with numerical and physical models have shown that the aerodynamics of these diminutive insects is significantly different from that of larger animals, but most of these studies have relied on two-dimensional approximations. There can, however, be significant differences between two- and three-dimensional flows, as has been found for larger insects. To better understand the flight of the smallest insects, we have performed a systematic study of the forces and flow structures around a three-dimensional revolving elliptical wing. We used both a dynamically scaled physical model and a three-dimensional computational model at Reynolds numbers ranging from 1 to 130 and angles of attacks ranging from 0&deg, to 90&deg, The results of the physical and computational models were in good agreement and showed that dimensionless drag, aerodynamic efficiency, and spanwise flow all decrease with decreasing Reynolds number. In addition, both the leading and trailing edge vortices remain attached to the wing over the scales relevant to the smallest flying insects. Overall, these observations suggest that there are drastic differences in the aerodynamics of flight at the scale of the smallest flying animals.

Nervous systems combine lower-level sensory signals to detect higher-order stimulus features critical to survival, such as the visual looming motion created by an imminent collision or approaching predator. Looming-sensitive neurons have been identified in diverse animal species. Different large-scale visual features such as looming often share local cues, which means loom-detecting neurons face the challenge of rejecting confounding stimuli. Here we report the discovery of an ultra-selective looming detecting neuron, lobula plate/lobula columnar, type II (LPLC2) in Drosophila, and show how its selectivity is established by radial motion opponency. In the fly visual system, directionally selective small-field neurons called T4 and T5 form a spatial map in the lobula plate, where they each terminate in one of four retinotopic layers, such that each layer responds to motion in a different cardinal direction. Single-cell anatomical analysis reveals that each arm of the LPLC2 cross-shaped primary dendrites ramifies in one of these layers and extends along that layer's preferred motion direction. In vivo calcium imaging demonstrates that, as their shape predicts, individual LPLC2 neurons respond strongly to outward motion emanating from the centre of the neuron's receptive field. Each dendritic arm also receives local inhibitory inputs directionally selective for inward motion opposing the excitation. This radial motion opponency generates a balance of excitation and inhibition that makes LPLC2 non-responsive to related patterns of motion such as contraction, wide-field rotation or luminance change. As a population, LPLC2 neurons densely cover visual space and terminate onto the giant fibre descending neurons, which drive the jump muscle motor neuron to trigger an escape take off. Our findings provide a mechanistic description of the selective feature detection that flies use to discern and escape looming threats.

Summary Identified neuron classes in vertebrate cortical [ 1 , 2 , 3 , 4 ] and subcortical [ 5 , 6 , 7 , 8 ] areas and invertebrate peripheral [ 9 , 10 , 11 ] and central [ 12 , 13 , 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 , 17 , 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’s subtended angular size and its angular velocity [ 5 , 6 , 7 , 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.

Neural circuits mediating visually evoked escape behaviors are promising systems in which to dissect the neural basis of behavior. Behavioral responses to predator-like looming stimuli, and their underlying neural computations, are remarkably similar across species. Recently, genetic tools have been applied in this classical paradigm, revealing novel non-cortical pathways that connect loom processing to defensive behaviors in mammals and demonstrating that loom encoding models from locusts also fit vertebrate neural responses. In both invertebrates and vertebrates, relative spike-timing in descending pathways is a mechanism for escape behavior choice. Current findings suggest that experimentally tractable systems, such as Drosophila, may be applicable models for sensorimotor processing and persistent states in higher organisms.

We discovered a bimodal behavior in the genetically tractable organism Drosophila melanogaster that allowed us to directly probe the neural mechanisms of an action selection process. When confronted by a predator-mimicking looming stimulus, a fly responds with either a long-duration escape behavior sequence that initiates stable flight or a distinct, short-duration sequence that sacrifices flight stability for speed. Intracellular recording of the descending giant fiber (GF) interneuron during head-fixed escape revealed that GF spike timing relative to parallel circuits for escape actions determined which of the two behavioral responses was elicited. The process was well described by a simple model in which the GF circuit has a higher activation threshold than the parallel circuits, but can override ongoing behavior to force a short takeoff. Our findings suggest a neural mechanism for action selection in which relative activation timing of parallel circuits creates the appropriate motor output.