Search

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.

Visually guided decision-making requires integration of information from distributed brain areas, necessitating a brain-wide approach to examine its neural mechanisms. New tools in Drosophila melanogaster enable circuits spanning the brain to be charted with single cell-type resolution. Here, we highlight recent advances uncovering the computations and circuits that transform and integrate visual information across the brain to make behavioral choices. Visual information flows from the optic lobes to three primary central brain regions: a sensorimotor mapping area and two 'higher' centers for memory or spatial orientation. Rapid decision-making during predator evasion emerges from the spike timing dynamics in parallel sensorimotor cascades. Goal-directed decisions may occur through memory, navigation and valence processing in the central complex and mushroom bodies.

The representation of contextual information peripheral to a salient stimulus is central to an animal's ability to correctly interpret and flexibly respond to that stimulus. While the computations and circuits underlying the context-dependent modulation of stimulus-response pairings have typically been studied in vertebrates, the genetic tractability, numeric simplification, and well-characterized connectivity patterns of the Drosophila melanogaster brain have facilitated circuit-level insights into contextual processing. Recent studies in flies reveal the neuronal mechanisms that create flexible context-dependent behavioral responses to sensory events in conditions of predation threat, feeding regulation, and social interaction.

SummaryLike many insect species, Drosophila melanogaster are capable of maintaining a stable flight trajectory for periods lasting up to several hours(1, 2). Because aerodynamic torque is roughly proportional to the fifth power of wing length(3), even small asymmetries in wing size require the maintenance of subtle bilateral differences in flapping motion to maintain a stable path. Flies can even fly straight after losing half of a wing, a feat they accomplish via very large, sustained kinematic changes to the both damaged and intact wings(4). Thus, the neural network responsible for stable flight must be capable of sustaining fine-scaled control over wing motion across a large dynamic range. In this paper, we describe an unusual type of descending neurons (DNg02) that project directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike most descending neurons, which exist as single bilateral pairs with unique morphology, there is a population of at least 15 DNg02 cell pairs with nearly identical shape. By optogenetically activating different numbers of DNg02 cells, we demonstrate that these neurons regulate wingbeat amplitude over a wide dynamic range via a population code. Using 2-photon functional imaging, we show that DNg02 cells are responsive to visual motion during flight in a manner that would make them well suited to continuously regulate bilateral changes in wing kinematics. Collectively, we have identified a critical set of DNs that provide the sensitivity and dynamic range required for flight control.

An approaching predator and self-motion toward an object can generate similar looming patterns on the retina, but these situations demand different rapid responses. How central circuits flexibly process visual cues to activate appropriate, fast motor pathways remains unclear. Here we identify two descending neuron (DN) types that control landing and contribute to visuomotor flexibility in Drosophila. For each, silencing impairs visually evoked landing, activation drives landing, and spike rate determines leg extension amplitude. Critically, visual responses of both DNs are severely attenuated during non-flight periods, effectively decoupling visual stimuli from the landing motor pathway when landing is inappropriate. The flight-dependence mechanism differs between DN types. Octopamine exposure mimics flight effects in one, whereas the other probably receives neuronal feedback from flight motor circuits. Thus, this sensorimotor flexibility arises from distinct mechanisms for gating action-specific descending pathways, such that sensory and motor networks are coupled or decoupled according to the behavioral state.

Topographic maps, the systematic spatial ordering of neurons by response tuning, are common across species. In Drosophila, the lobula columnar (LC) neuron types project from the optic lobe to the central brain, where each forms a glomerulus in a distinct position. However, the advantages of this glomerular arrangement are unclear. Here, we examine the functional and spatial relationships of 10 glomeruli using single-neuron calcium imaging. We discover novel detectors for objects smaller than the lens resolution (LC18) and for complex line motion (LC25). We find that glomeruli are spatially clustered by selectivity for looming versus drifting object motion and ordered by size tuning to form a topographic visual feature map. Furthermore, connectome analysis shows that downstream neurons integrate from sparse subsets of possible glomeruli combinations, which are biased for glomeruli encoding similar features. LC neurons are thus an explicit example of distinct feature detectors topographically organized to facilitate downstream circuit integration.

To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception.

Precise, repeatable genetic access to specific neurons via the GAL4/UAS system and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which mostly lack the single-cell resolution required for reliable cell type identification. Here we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 27,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between electron microscopy-identified neurons and light microscopy-based intersectional genetic approaches such as the split-GAL4 system. Identifying the individual neurons that make up each GAL4 expression pattern improves the prediction of which GAL4 enhancer fragments best combine via split-GAL4 to target neurons of interest. To this end we have developed the NeuronBridge search tool, which matches these light microscope neuronal images to neurons in the recently published FlyEM hemibrain. This work thus provides a resource and search tool that will significantly enhance both the efficiency and efficacy of split-GAL4 targeting of EM-identified neurons and further advance Drosophila neuroscience.

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

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

SUMMARY To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception., In brief To understand how diverse proprioceptive signals from the Drosophila leg are integrated by downstream circuits, Chen et al. use optogenetics and calcium imaging to map functional connectivity between sensory and central neurons. This work identifies parallel neural pathways for processing leg vibration vs. joint position and movement., Graphical abstract

The fruit fly, Drosophila melanogaster, is an established and powerful model system for neuroscience research with wide relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognising this problem, the Insect Brain Name Working Group produced an authoritative hierarchical nomenclature system for the adult insect brain, using Drosophila melanogaster as the reference framework, with other taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Here, we extend this nomenclature system to the sub-gnathal regions of the adult Drosophila nervous system, thus providing a systematic anatomical description of the ventral nervous system (VNS). This portion of the nervous system includes the thoracic and abdominal neuromeres that were not included in the original work and contains the motor circuits that play essential roles in most fly behaviours.

SUMMARYIn most animals, the brain controls the body via a set of descending neurons (DNs) that traverse the neck and terminate in post-cranial regions of the nervous system. This critical neural population is thought to activate, maintain and modulate locomotion and other behaviors. Although individual members of this cell class have been well-studied across species ranging from insects to primates, little is known about the overall connectivity pattern of DNs as a population. We undertook a systematic anatomical investigation of descending neurons in the fruit fly,Drosophila melanogaster, and created a collection of over 100 transgenic lines targeting individual cell types. Our methods allowed us to describe the morphology of roughly half of an estimated 400 DNs and create a comprehensive map of connectivity between the sensory neuropils in the brain and the motor neuropils in the ventral nerve cord. Like the vertebrate spinal cord, our results show that the fly nerve cord is a highly organized, layered system of neuropils, an organization that reflects the fact that insects are capable of two largely independent means of locomotion – walking and fight – using distinct sets of appendages. Our results reveal the basic functional map of descending pathways in flies and provide tools for systematic interrogation of sensory-motor circuits.

In most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how descending neurons control an insect’s movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrial D. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies, and we associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a large collection of descending neurons, we found that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically activated behaviors were often dependent on the behavioral state prior to activation.

SummaryThe most fundamental choice an animal has to make when it detects a predator, or other threats, is whether to freeze, reducing its chances of being noticed, or to flee to safety. Here we show thatDrosophila melanogasterexposed to looming stimuli in a confined arena either froze or fled. The probability of freezing versus fleeing was modulated by the fly’s walking speed at the time of threat, demonstrating that freeze/flee decisions were context dependent. We describe a pair of descending neurons crucially implicated in freezing. Genetic silencing of DNp09 descending neurons disrupted freezing yet did not prevent fleeing. Optogenetic activation of both DNp09 neurons induced running and freezing in a state-dependent manner. Our findings establish walking speed as a key factor in defensive response choices and reveal a pair of descending neurons as a critical component in the circuitry mediating selection and execution of freezing or fleeing behaviors.

In most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how these neurons control an insect’s movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrialD. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies and associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a population of descending neurons, we found, that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically-activated behaviors were often dependent on the behavioral state prior to activation.

Assigning behavioral functions to neural structures has long been a central goal in neuroscience and is a necessary first step toward a circuit-level understanding of how the brain generates behavior. Here, we map the neural substrates of locomotion and social behaviors for Drosophila melanogaster using automated machine-vision and machine-learning techniques. From videos of 400,000 flies, we quantified the behavioral effects of activating 2,204 genetically targeted populations of neurons. We combined a novel quantification of anatomy with our behavioral analysis to create brain-behavior correlation maps, which are shared as browsable web pages and interactive software. Based on these maps, we generated hypotheses of regions of the brain causally related to sensory processing, locomotor control, courtship, aggression, and sleep. Our maps directly specify genetic tools to target these regions, which we used to identify a small population of neurons with a role in the control of walking.

The fruit fly,Drosophila melanogaster, is an established and powerful model system for neuroscience research with wide relevance in biology and medicine. Until recently, research on theDrosophilabrain was hindered by the lack of a complete and uniform nomenclature. Recognising this problem, the Insect Brain Name Working Group produced an authoritative hierarchical nomenclature system for the adult insect brain, usingDrosophila melanogasteras the reference framework, with other taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Here, we extend this nomenclature system to the sub-gnathal regions of the adultDrosophilanervous system, thus providing a systematic anatomical description of the ventral nervous system (VNS). This portion of the nervous system includes the thoracic and abdominal neuromeres that were not included in the original work and contains the motor circuits that play essential roles in most fly behaviours.

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.

Visual projection neurons (VPNs) provide an anatomical connection between early visual processing and higher brain regions. Here we characterize lobula columnar (LC) cells, a class of Drosophila VPNs that project to distinct central brain structures called optic glomeruli. We anatomically describe 22 different LC types and show that, for several types, optogenetic activation in freely moving flies evokes specific behaviors. The activation phenotypes of two LC types closely resemble natural avoidance behaviors triggered by a visual loom. In vivo two-photon calcium imaging reveals that these LC types respond to looming stimuli, while another type does not, but instead responds to the motion of a small object. Activation of LC neurons on only one side of the brain can result in attractive or aversive turning behaviors depending on the cell type. Our results indicate that LC neurons convey information on the presence and location of visual features relevant for specific behaviors. DOI: http://dx.doi.org/10.7554/eLife.21022.001, eLife digest Many animals rely heavily on what they can see to interact with the world around them. But how does the brain use such visual information to guide behavior? Light-sensitive neurons in the eye cannot distinguish between the visual signals associated with, say, an approaching predator or a source of food. Yet the brain can make this distinction. Networks of neurons in the brain perform computations to extract information from a visual scene that indicates the need for a particular behavior, such as an escape response. These networks are found in regions of the brain that communicate closely with the eyes. Cells known as visual projection neurons then relay the output of these networks to more central parts of the brain. By studying visual projection neurons, it is possible to work out what the eye tells the brain, and how the brain uses this information to control behavior. The fruit fly Drosophila is a suitable model organism in which to study these phenomena. This insect shows a range of behavioral responses to visual stimuli, and can be studied using sophisticated genetic tools. Wu, Nern et al. set out to explore how a group of visual projection neurons known as lobula columnar cells help fruit flies respond appropriately to visual stimuli. Experiments revealed that individual subtypes of lobula columnar cells convey information about the presence and general location of specific visual features. Wu, Nern et al. identified a number of lobular columnar subtypes involved in triggering escape responses to specific stimuli – such as walking backwards or taking off in flight – as well as others that can trigger the flies to approach a target. A next step is to map the circuits of neurons that act upstream and downstream of lobula columnar cells. This can help to reveal how these neurons detect specific visual features and how the fly then chooses and executes an appropriate behavior in response. Such studies in flies can provide insights into general principles of how brains use sensory information to guide behavior. DOI: http://dx.doi.org/10.7554/eLife.21022.002

Summary Animals rely on dedicated sensory circuits to extract and encode environmental features. How individual neurons integrate and translate these features into behavioral responses remains a major question. Here, we identify a visual projection neuron type that conveys predator approach information to the Drosophila giant fiber (GF) escape circuit. Genetic removal of this input during looming stimuli reveals that it encodes angular expansion velocity, whereas other input cell type(s) encode angular size. Motor program selection and timing emerge from linear integration of these two features within the GF. Linear integration improves size detection invariance over prior models and appropriately biases motor selection to rapid, GF-mediated escapes during fast looms. Our findings suggest feature integration, and motor control may occur as simultaneous operations within the same neuron and establish the Drosophila escape circuit as a model system in which these computations may be further dissected at the circuit level. Video Abstract

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.

Escape behaviors are, by necessity, fast and robust, making them excellent systems with which to study the neural basis of behavior. This is especially true in insects, which have comparatively tractable nervous systems and members who are amenable to manipulation with genetic tools. Recent technical developments in high-speed video reveal that, despite their short duration, insect escape behaviors are more complex than previously appreciated. For example, before initiating an escape jump, a fly performs sophisticated posture and stimulus-dependent preparatory leg movements that enable it to jump away from a looming threat. This newfound flexibility raises the question of how the nervous system generates a behavior that is both rapid and flexible. Recordings from the cricket nervous system suggest that synchrony between the activity of specific interneuron pairs may provide a rapid cue for the cricket to detect the direction of an approaching predator and thus which direction it should run. Technical advances make possible wireless recording from neurons while locusts escape from a looming threat, enabling, for the first time, a direct correlation between the activity of multiple neurons and the time-course of an insect escape behavior.

Interindividual differences in neuronal wiring may contribute to behavioral individuality and affect susceptibility to neurological disorders. To investigate the causes and potential consequences of wiring variation in Drosophila melanogaster, we focused on a hemilineage of ventral nerve cord interneurons that exhibits morphological variability. We find that late-born subclasses of the 12A hemilineage are highly sensitive to genetic and environmental variation. Neurons in the second thoracic segment are particularly variable with regard to two developmental decisions, whereas its segmental homologs are more robust. This variability “hotspot” depends on Ultrabithorax expression in the 12A neurons, indicating variability is cell-intrinsic and under genetic control. 12A development is more variable and sensitive to temperature in long-established laboratory strains than in strains recently derived from the wild. Strains with a high frequency of one of the 12A variants also showed a high frequency of animals with delayed spontaneous flight initiation, whereas other wing-related behaviors did not show such a correlation and were thus not overtly affected by 12A variation. These results show that neurodevelopmental robustness is variable and under genetic control in Drosophila and suggest that the fly may serve as a model for identifying conserved gene pathways that stabilize wiring in stressful developmental environments. Moreover, some neuronal lineages are variation hotspots and thus may be more amenable to evolutionary change.

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.