An Array of Descending Visual Interneurons Encoding Self-Motion in Drosophila

Comparative connectomics of the descending and ascending neurons of the Drosophila nervous system: stereotypy and sexual dimorphism

In most complex nervous systems there is a clear anatomical separation between the nerve cord, which contains most of the final motor outputs necessary for behaviour, and the brain. In insects, the neck connective is both a physical and information bottleneck connecting the brain and the ventral nerve cord (VNC, spinal cord analogue) and comprises diverse populations of descending (DN), ascending (AN) and sensory ascending neurons, which are crucial for sensorimotor signalling and control. Integrating three separate EM datasets, we now provide a complete connectomic description of the ascending and descending neurons of the female nervous system of Drosophila and compare them with neurons of the male nerve cord. Proofread neuronal reconstructions have been matched across hemispheres, datasets and sexes. Crucially, we have also matched 51% of DN cell types to light level data defining specific driver lines as well as classifying all ascending populations. We use these results to reveal the general architecture, tracts, neuropil innervation and connectivity of neck connective neurons. We observe connected chains of descending and ascending neurons spanning the neck, which may subserve motor sequences. We provide a complete description of sexually dimorphic DN and AN populations, with detailed analysis of circuits implicated in sex-related behaviours, including female ovipositor extrusion (DNp13), male courtship (DNa12/aSP22) and song production (AN hemilineage 08B). Our work represents the first EM-level circuit analyses spanning the entire central nervous system of an adult animal.

Asynchronous haltere input drives specific wing and head movements in Drosophila

Halteres are multifunctional mechanosensory organs unique to the true flies (Diptera). A set of reduced hindwings, the halteres beat at the same frequency as the lift-generating forewings and sense inertial forces via mechanosensory campaniform sensilla. Though haltere ablation makes stable flight impossible, the specific role of wing-synchronous input has not been established. Using small iron filings attached to the halteres of tethered flies and an alternating electromagnetic field, we experimentally decoupled the wings and halteres of flying Drosophila and observed the resulting changes in wingbeat amplitude and head orientation. We find that asynchronous haltere input results in fast amplitude changes in the wing (hitches), but does not appreciably move the head. In multi-modal experiments, we find that wing and gaze optomotor responses are disrupted differently by asynchronous input. These effects of wing-asynchronous haltere input suggest that specific sensory information is necessary for maintaining wing amplitude stability and adaptive gaze control.

Descending networks transform command signals into population motor control

To convert intentions into actions, movement instructions must pass from the brain to downstream motor circuits through descending neurons (DNs). These include small sets of command-like neurons that are sufficient to drive behaviours1-the circuit mechanisms for which remain unclear. Here we show that command-like DNs in Drosophila directly recruit networks of additional DNs to orchestrate behaviours that require the active control of numerous body parts. Specifically, we found that command-like DNs previously thought to drive behaviours alone2-4 in fact co-activate larger populations of DNs. Connectome analyses and experimental manipulations revealed that this functional recruitment can be explained by direct excitatory connections between command-like DNs and networks of interconnected DNs in the brain. Descending population recruitment is necessary for behavioural control: DNs with many downstream descending partners require network co-activation to drive complete behaviours and drive only simple stereotyped movements in their absence. These DN networks reside within behaviour-specific clusters that inhibit one another. These results support a mechanism for command-like descending control in which behaviours are generated through the recruitment of increasingly large DN networks that compose behaviours by combining multiple motor subroutines.

Multisensory integration in Anopheles mosquito swarms: The role of visual and acoustic information in mate tracking and collision avoidance

Male mosquitoes form aerial aggregations, known as swarms, to attract females and maximize their chances of finding a mate. Within these swarms, individuals must be able to recognize potential mates and navigate the dynamic social environment to successfully intercept a mating partner. Prior research has almost exclusively focused on the role of acoustic cues in mediating the male mosquito's ability to recognize and pursue flying females. However, the role of other sensory modalities in this behavior has not been explored. Moreover, how males avoid collisions with one another in the dense swarm while pursuing females remains poorly understood. In this study, we combined free-flight and tethered flight simulator experiments to demonstrate that swarming Anopheles coluzzii mosquitoes integrate visual and acoustic information to track conspecifics and avoid collisions. Our tethered experiments revealed that acoustic stimuli gated mosquito steering responses to visual objects simulating nearby mosquitoes, especially in males that exhibited attraction to visual objects in the presence of female flight tones. Additionally, we observed that visual cues alone could trigger changes in mosquitoes' wingbeat amplitude and frequency. These findings were corroborated by our free-flight experiments, which revealed that mosquitoes modulate their flight responses to nearby conspecifics in a similar manner to tethered animals, allowing for collision avoidance within swarms. Together, these results demonstrate that both males and females integrate multiple sensory inputs to mediate swarming behavior, and for males, the change in flight kinematics in response to multimodal cues allows them to simultaneously track females while avoiding collisions.

Machine learning reveals the control mechanics of an insect wing hinge

Insects constitute the most species-rich radiation of metazoa, a success that is due to the evolution of active flight. Unlike pterosaurs, birds and bats, the wings of insects did not evolve from legs1, but are novel structures that are attached to the body via a biomechanically complex hinge that transforms tiny, high-frequency oscillations of specialized power muscles into the sweeping back-and-forth motion of the wings2. The hinge consists of a system of tiny, hardened structures called sclerites that are interconnected to one another via flexible joints and regulated by the activity of specialized control muscles. Here we imaged the activity of these muscles in a fly using a genetically encoded calcium indicator, while simultaneously tracking the three-dimensional motion of the wings with high-speed cameras. Using machine learning, we created a convolutional neural network3 that accurately predicts wing motion from the activity of the steering muscles, and an encoder-decoder4 that predicts the role of the individual sclerites on wing motion. By replaying patterns of wing motion on a dynamically scaled robotic fly, we quantified the effects of steering muscle activity on aerodynamic forces. A physics-based simulation incorporating our hinge model generates flight manoeuvres that are remarkably similar to those of free-flying flies. This integrative, multi-disciplinary approach reveals the mechanical control logic of the insect wing hinge, arguably among the most sophisticated and evolutionarily important skeletal structures in the natural world.

Mapping the neural dynamics of locomotion across the Drosophila brain

Locomotion engages widely distributed networks of neurons. However, our understanding of the spatial architecture and temporal dynamics of the networks that underpin walking remains incomplete. We use volumetric two-photon imaging to map neural activity associated with walking across the entire brain of Drosophila. We define spatially clustered neural signals selectively associated with changes in either forward or angular velocity, demonstrating that neurons with similar behavioral selectivity are clustered. These signals reveal distinct topographic maps in diverse brain regions involved in navigation, memory, sensory processing, and motor control, as well as regions not previously linked to locomotion. We identify temporal trajectories of neural activity that sweep across these maps, including signals that anticipate future movement, representing the sequential engagement of clusters with different behavioral specificities. Finally, we register these maps to a connectome and identify neural networks that we propose underlie the observed signals, setting a foundation for subsequent circuit dissection. Overall, our work suggests a spatiotemporal framework for the emergence and execution of complex walking maneuvers and links this brain-wide neural activity to single neurons and local circuits.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of locomotion, selecting for a common search motif in which straight movements through resource-poor regions alternate with zig-zag exploration in resource-rich domains. For example, during local search, flying flies spontaneously execute rapid flight turns, called body saccades, but suppress these maneuvers during long-distance dispersal or when surging upstream toward an attractive odor. Here, we describe the key cellular components of a neural network in flies that generate spontaneous turns as well as a specialized pair of neurons that inhibits the network and suppresses turning. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional units-one for right turns and one for left-with each unit consisting of an excitatory (DNae014) and an inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly, we identified a pair of large, distinct interneurons (VES041) that form inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As predicted by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it promotes straight flight to regulate the transition between local search and long-distance dispersal. These results thus identify the key elements of a network that may play a crucial role in foraging ecology.

Descending control of motor sequences in Drosophila

The descending neurons connecting the fly's brain to its ventral nerve cord respond to sensory stimuli and evoke motor programs of varying complexity. Anatomical characterization of the descending neurons and their synaptic connections suggests how these circuits organize movements, while optogenetic manipulation of their activity reveals what behaviors they can induce. Monitoring their responses to sensory stimuli or during behavior performance indicates what information they may encode. Recent advances in all three approaches make the descending neurons an excellent place to better understand the sensorimotor integration and transformation required for nervous systems to govern the motor sequences that constitute animal behavior.

Neurons with names: Descending control and sensorimotor processing in insect motor control

Technical and methodological advances in recent years have brought new ways to tackle major classical questions in insect motor control. Particularly, significant advancements were achieved in comprehending brain descending control by characterizing descending neurons, their targets in the ventral nerve cord (VNC), and how local networks there integrate sensory information. While physiological experiments in larger insects brought us a better understanding of how sensory modalities are processed locally in the VNC, the development and improvement of genetic tools, principally in Drosophila, opened the door to individually characterize actors at these three levels of information flow in behavioral control. This brief review brings together the names and roles of some of those actors, by highlighting the most significant findings from our perspective.

Fine-grained descending control of steering in walking Drosophila

Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream from distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Notably, a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from brain cells that drive specific, coordinated modulations of low-level patterns.

Flies adaptively control flight to compensate for added inertia

Animal locomotion is highly adaptive, displaying a large degree of flexibility, yet how this flexibility arises from the integration of mechanics and neural control remains elusive. For instance, animals require flexible strategies to maintain performance as changes in mass or inertia impact stability. Compensatory strategies to mechanical loading are especially critical for animals that rely on flight for survival. To shed light on the capacity and flexibility of flight neuromechanics to mechanical loading, we pushed the performance of fruit flies (Drosophila) near its limit and implemented a control theoretic framework. Flies with added inertia were placed inside a virtual reality arena which permitted free rotation about the vertical (yaw) axis. Adding inertia increased the fly's response time yet had little influence on overall gaze stabilization performance. Flies maintained stability following the addition of inertia by adaptively modulating both visuomotor gain and damping. By contrast, mathematical modelling predicted a significant decrease in gaze stabilization performance. Adding inertia altered saccades, however, flies compensated for the added inertia by increasing saccade torque. Taken together, in response to added inertia flies increase reaction time but maintain flight performance through adaptive neural control. Overall, adding inertia decreases closed-loop flight robustness. Our work highlights the flexibility and capacity of motor control in flight.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of life, selecting for a common locomotor search motif in which straight movements through resource-poor regions alternate with zig -zag exploration in resource-rich domains. For example, flies execute rapid changes in flight heading called body saccades during local search, but suppress these turns during long-distance dispersal or when surging upwind after encountering an attractive odor plume. Here, we describe the key cellular components of a neural network in flies that generates spontaneous turns as well as a specialized neuron that inhibits the network to promote straight flight. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional couplets-one for right turns and one for left-with each couplet consisting of an excitatory (DNae014) and inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly brain, we identified a large, unique interneuron (VES041) that forms inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As suggested by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it regulates the transition between local search and long-distance dispersal. These results thus identify the critical elements of a network that not only structures the locomotor behavior of flies, but may also play a crucial role in their natural foraging ecology.

Multilevel visuomotor control of locomotion in Drosophila

Vision is critical for the control of locomotion, but the underlying neural mechanisms by which visuomotor circuits contribute to the movement of the body through space are yet not well understood. Locomotion engages multiple control systems, forming distinct interacting "control levels" driven by the activity of distributed and overlapping circuits. Therefore, a comprehensive understanding of the mechanisms underlying locomotion control requires the consideration of all control levels and their necessary coordination. Due to their small size and the wide availability of experimental tools, Drosophila has become an important model system to study this coordination. Traditionally, insect locomotion has been divided into studying either the biomechanics and local control of limbs, or navigation and course control. However, recent developments in tracking techniques, and physiological and genetic tools in Drosophila have prompted researchers to examine multilevel control coordination in flight and walking.

Neuronal wiring diagram of an adult brain

Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×107 chemical synapses between ~130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.

Single-cell type analysis of wing premotor circuits in the ventral nerve cord of Drosophila melanogaster

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.

Visual processing in the fly, from photoreceptors to behavior

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.

Optic flow based spatial vision in insects

The optic flow, i.e., the displacement of retinal images of objects in the environment induced by self-motion, is an important source of spatial information, especially for fast-flying insects. Spatial information over a wide range of distances, from the animal's immediate surroundings over several hundred metres to kilometres, is necessary for mediating behaviours, such as landing manoeuvres, collision avoidance in spatially complex environments, learning environmental object constellations and path integration in spatial navigation. To facilitate the processing of spatial information, the complexity of the optic flow is often reduced by active vision strategies. These result in translations and rotations being largely separated by a saccadic flight and gaze mode. Only the translational components of the optic flow contain spatial information. In the first step of optic flow processing, an array of local motion detectors provides a retinotopic spatial proximity map of the environment. This local motion information is then processed in parallel neural pathways in a task-specific manner and used to control the different components of spatial behaviour. A particular challenge here is that the distance information extracted from the optic flow does not represent the distances unambiguously, but these are scaled by the animal's speed of locomotion. Possible ways of coping with this ambiguity are discussed.

Neuromuscular embodiment of feedback control elements in Drosophila flight

While insects such as Drosophila are flying, aerodynamic instabilities require that they make millisecond time scale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons. Here, we show that the b1 and b2 motor units-prominent components of the fly's steering muscle system-modulate specific elements of the PI controller: the angular displacement (integral) and angular velocity (proportional), respectively. Moreover, these effects are observed only during the stabilization of pitch. Our results provide evidence for an organizational principle in which each muscle contributes to a specific functional role in flight control, a finding that highlights the power of using top-down behavioral modeling to guide bottom-up cellular manipulation studies.

Flies trade off stability and performance via adaptive compensation to wing damage

Physical injury often impairs mobility, which can have dire consequences for survival in animals. Revealing mechanisms of robust biological intelligence to prevent system failure can provide critical insights into how complex brains generate adaptive movement and inspiration to design fault-tolerant robots. For flying animals, physical injury to a wing can have severe consequences, as flight is inherently unstable. Using a virtual reality flight arena, we studied how flying fruit flies compensate for damage to one wing. By combining experimental and mathematical methods, we show that flies compensate for wing damage by corrective wing movement modulated by closed-loop sensing and robust mechanics. Injured flies actively increase damping and, in doing so, modestly decrease flight performance but fly as stably as uninjured flies. Quantifying responses to injury can uncover the flexibility and robustness of biological systems while informing the development of bio-inspired fault-tolerant strategies.

Experimental Verification on Steering Flight of Honeybee by Electrical Stimulation

The artificial locomotion control strategy is the fundamental technique to ensure the accomplishment of the preset assignments for cyborg insects. The existing research has recognized that the electrical stimulation applied to the optic lobes was an appropriate flight control strategy for small insects represented by honeybee. This control technique has been confirmed to be effective for honeybee flight initiation and cessation. However, its regulation effect on steering locomotion has not been fully verified. Here, we investigated the steering control effect of honeybee by applying electrical stimulation signals with different duty cycles and frequencies on the unilateral optic lobes and screened the stimulus parameters with the highest response successful rate. Moreover, we confirmed the effectiveness of steering control by verifying the presence of rotation torque on tethered honeybees and the body orientation change of crawling honeybees. Our study will contribute some reliable parameter references to the motion control of cyborg honeybees.

Impact of walking speed and motion adaptation on optokinetic nystagmus-like head movements in the blowfly Calliphora

The optokinetic nystagmus is a gaze-stabilizing mechanism reducing motion blur by rapid eye rotations against the direction of visual motion, followed by slower syndirectional eye movements minimizing retinal slip speed. Flies control their gaze through head turns controlled by neck motor neurons receiving input directly, or via descending neurons, from well-characterized directional-selective interneurons sensitive to visual wide-field motion. Locomotion increases the gain and speed sensitivity of these interneurons, while visual motion adaptation in walking animals has the opposite effects. To find out whether flies perform an optokinetic nystagmus, and how it may be affected by locomotion and visual motion adaptation, we recorded head movements of blowflies on a trackball stimulated by progressive and rotational visual motion. Flies flexibly responded to rotational stimuli with optokinetic nystagmus-like head movements, independent of their locomotor state. The temporal frequency tuning of these movements, though matching that of the upstream directional-selective interneurons, was only mildly modulated by walking speed or visual motion adaptation. Our results suggest flies flexibly control their gaze to compensate for rotational wide-field motion by a mechanism similar to an optokinetic nystagmus. Surprisingly, the mechanism is less state-dependent than the response properties of directional-selective interneurons providing input to the neck motor system.

Generating spatiotemporal patterns of linearly polarised light at high frame rates for insect vision research

Polarisation vision is commonplace among invertebrates; however, most experiments focus on determining behavioural and/or neurophysiological responses to static polarised light sources rather than moving patterns of polarised light. To address the latter, we designed a polarisation stimulation device based on superimposing polarised and non-polarised images from two projectors, which can display moving patterns at frame rates exceeding invertebrate flicker fusion frequencies. A linear polariser fitted to one projector enables moving patterns of polarised light to be displayed, whilst the other projector contributes arbitrary intensities of non-polarised light to yield moving patterns with a defined polarisation and intensity contrast. To test the device, we measured receptive fields of polarisation-sensitive Argynnis paphia butterfly photoreceptors for both non-polarised and polarised light. We then measured local motion sensitivities of the optic flow-sensitive lobula plate tangential cell H1 in Calliphora vicina blowflies under both polarised and non-polarised light, finding no polarisation sensitivity in this neuron.

Summary: Design of a versatile visual stimulation device for presenting moving patterns of polarised light, and demonstration of its use to characterise polarisation sensitivity in butterfly photoreceptors and blowfly motion-sensitive interneurons.

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.

A population of descending neurons that regulates the flight motor of Drosophila

Like 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 length³, 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 both the damaged and intact wings⁴. 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 neuron (DNg02) that projects directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike many 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.

Using an activation screen in flying flies, Namiki et al. identify a population of descending neurons that regulates wing amplitude over a large dynamic range. Via functional imaging and activation of different numbers of cells, they show that this population is a core component of the flight circuit, allowing the fly to steer and fly straight.

Stimulus-dependent orientation strategies in monarch butterflies

Insects are well-known for their ability to keep track of their heading direction based on a combination of skylight cues and visual landmarks. This allows them to navigate back to their nest, disperse throughout unfamiliar environments, as well as migrate over large distances between their breeding and non-breeding habitats. The monarch butterfly (Danaus plexippus) for instance is known for its annual southward migration from North America to certain trees in Central Mexico. To maintain a constant flight route, these butterflies use a time-compensated sun compass for orientation which is processed in a region in the brain, termed the central complex. However, to successfully complete their journey, the butterflies’ brain must generate a multitude of orientation strategies, allowing them to dynamically switch from sun-compass orientation to a tactic behavior toward a certain target. To study if monarch butterflies exhibit different orientation modes and if they can switch between them, we observed the orientation behavior of tethered flying butterflies in a flight simulator while presenting different visual cues to them. We found that the butterflies’ behavior depended on the presented visual stimulus. Thus, while a dark stripe was used for flight stabilization, a bright stripe was fixated by the butterflies in their frontal visual field. If we replaced a bright stripe by a simulated sun stimulus, the butterflies switched their behavior and exhibited compass orientation. Taken together, our data show that monarch butterflies rely on and switch between different orientation modes, allowing the animal to adjust orientation to its actual behavioral demands.

Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors

Deciphering how the brain regulates motor circuits to control complex behaviors is an important, long-standing challenge in neuroscience. In the fly, Drosophila melanogaster, this is coordinated by a population of ~ 1100 descending neurons (DNs). Activating only a few DNs is known to be sufficient to drive complex behaviors like walking and grooming. However, what additional role the larger population of DNs plays during natural behaviors remains largely unknown. For example, they may modulate core behavioral commands or comprise parallel pathways that are engaged depending on sensory context. We evaluated these possibilities by recording populations of nearly 100 DNs in individual tethered flies while they generated limb-dependent behaviors, including walking and grooming. We found that the largest fraction of recorded DNs encode walking while fewer are active during head grooming and resting. A large fraction of walk-encoding DNs encode turning and far fewer weakly encode speed. Although odor context does not determine which behavior-encoding DNs are recruited, a few DNs encode odors rather than behaviors. Lastly, we illustrate how one can identify individual neurons from DN population recordings by using their spatial, functional, and morphological properties. These results set the stage for a comprehensive, population-level understanding of how the brain’s descending signals regulate complex motor actions.

The impulse response of optic flow-sensitive descending neurons to roll m-sequences

When animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow-sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensorimotor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. Therefore, here we used m-sequences to quantify the impulse responses of optic flow-sensitive descending neurons in male Eristalis tenax hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5–18.0 ms. This is similar to the impulse response time to peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift.

Summary: The impulse response of hoverfly optic flow-sensitive descending neurons to roll m-sequences reaches its time to peak within 20 ms and slowly returns to baseline over the next 100 ms.

Mechanisms of punctuated vision in fly flight

To guide locomotion, animals control gaze via movements of their eyes, head, and/or body, but how the nervous system controls gaze during complex motor tasks remains elusive. In many animals, shifts in gaze consist of periods of smooth movement punctuated by rapid eye saccades. Notably, eye movements are constrained by anatomical limits, which requires resetting eye position. By studying tethered, flying fruit flies (Drosophila), we show that flies perform stereotyped head saccades to reset gaze, analogous to optokinetic nystagmus in primates. Head-reset saccades interrupted head smooth movement for as little as 50 ms-representing less than 5% of the total flight time-thereby enabling punctuated gaze stabilization. By revealing the passive mechanics of the neck joint, we show that head-reset saccades leverage the neck's natural elastic recoil, enabling mechanically assisted redirection of gaze. The consistent head orientation at saccade initiation, the influence of the head's angular position on saccade rate, the decrease in wing saccade frequency in head-fixed flies, and the decrease in head-reset saccade rate in flies with their head range of motion restricted together implicate proprioception as the primary trigger of head-reset saccades. Wing-reset saccades were influenced by head orientation, establishing a causal link between neck sensory signals and the execution of body saccades. Head-reset saccades were abolished when flies switched to a landing state, demonstrating that head movements are gated by behavioral state. We propose a control architecture for active vision systems with limits in sensor range of motion. VIDEO ABSTRACT.

Insect inspired vision-based velocity estimation through spatial pooling of optic flow during linear motion

Insects rely on the perception of image motion, or optic flow, to estimate their velocity relative to nearby objects. This information provides important sensory input for avoiding obstacles. However, certain behaviors, such as estimating the absolute distance to a landing target, accurately measuring absolute distance traveled, and estimating the ambient wind speed require decoupling optic flow into its component parts: absolute ground velocity and distance to nearby objects. Behavioral experiments suggest that insects perform these calculations, but their mechanism for doing so remains unknown. Here we present a novel algorithm that combines the geometry of dynamic forward motion with known features of insect visual processing to provide a hypothesis for how insects mightdirectlyestimate absolute ground velocity from a combination of optic flow and acceleration information. Our robotics-inspired-biology approach reveals three critical requirements. First, absolute ground velocity can only be directly estimated from optic flow during times of active acceleration and deceleration. Second, spatial pooling of optic flow across a receptive field helps to alleviate the effects of noise and/or low resolution visual systems. Third, averaging velocity estimates from multiple receptive fields further helps to reject noise. Our algorithm provides a hypothesis for how insects might estimate absolute velocity from vision during active maneuvers, and also provides a theoretical framework for designing fast analog circuitry for efficient state estimation that can be applied to insect-sized robots.

Spherical arena reveals optokinetic response tuning to stimulus location, size, and frequency across entire visual field of larval zebrafish

Many animals have large visual fields, and sensory circuits may sample those regions of visual space most relevant to behaviours such as gaze stabilisation and hunting. Despite this, relatively small displays are often used in vision neuroscience. To sample stimulus locations across most of the visual field, we built a spherical stimulus arena with 14,848 independently controllable LEDs. We measured the optokinetic response gain of immobilised zebrafish larvae to stimuli of different steradian size and visual field locations. We find that the two eyes are less yoked than previously thought and that spatial frequency tuning is similar across visual field positions. However, zebrafish react most strongly to lateral, nearly equatorial stimuli, consistent with previously reported spatial densities of red, green, and blue photoreceptors. Upside-down experiments suggest further extra-retinal processing. Our results demonstrate that motion vision circuits in zebrafish are anisotropic, and preferentially monitor areas with putative behavioural relevance.

Haltere and visual inputs sum linearly to predict wing (but not gaze) motor output in tethered flying Drosophila

In the true flies (Diptera), the hind wings have evolved into specialized mechanosensory organs known as halteres, which are sensitive to gyroscopic and other inertial forces. Together with the fly's visual system, the halteres direct head and wing movements through a suite of equilibrium reflexes that are crucial to the fly's ability to maintain stable flight. As in other animals (including humans), this presents challenges to the nervous system as equilibrium reflexes driven by the inertial sensory system must be integrated with those driven by the visual system in order to control an overlapping pool of motor outputs shared between the two of them. Here, we introduce an experimental paradigm for reproducibly altering haltere stroke kinematics and use it to quantify multisensory integration of wing and gaze equilibrium reflexes. We show that multisensory wing-steering responses reflect a linear superposition of haltere-driven and visually driven responses, but that multisensory gaze responses are not well predicted by this framework. These models, based on populations, extend also to the responses of individual flies.

Timing precision in fly flight control: integrating mechanosensory input with muscle physiology

Animals rapidly collect and act on incoming information to navigate complex environments, making the precise timing of sensory feedback critical in the context of neural circuit function. Moreover, the timing of sensory input determines the biomechanical properties of muscles that undergo cyclic length changes, as during locomotion. Both of these issues come to a head in the case of flying insects, as these animals execute steering manoeuvres at timescales approaching the upper limits of performance for neuromechanical systems. Among insects, flies stand out as especially adept given their ability to execute manoeuvres that require sub-millisecond control of steering muscles. Although vision is critical, here I review the role of rapid, wingbeat-synchronous mechanosensory feedback from the wings and structures unique to flies, the halteres. The visual system and descending interneurons of the brain employ a spike rate coding scheme to relay commands to the wing steering system. By contrast, mechanosensory feedback operates at faster timescales and in the language of motor neurons, i.e. spike timing, allowing wing and haltere input to dynamically structure the output of the wing steering system. Although the halteres have been long known to provide essential input to the wing steering system as gyroscopic sensors, recent evidence suggests that the feedback from these vestigial hindwings is under active control. Thus, flies may accomplish manoeuvres through a conserved hindwing circuit, regulating the firing phase-and thus, the mechanical power output-of the wing steering muscles.

Multi-regional circuits underlying visually guided decision-making in Drosophila

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.

Better Sleep at Night: How Light Influences Sleep in Drosophila

Sleep-like states have been described in Drosophila and the mechanisms and factors that generate and define sleep-wake profiles in this model organism are being thoroughly investigated. Sleep is controlled by both circadian and homeostatic mechanisms, and environmental factors such as light, temperature, and social stimuli are fundamental in shaping and confining sleep episodes into the correct time of the day. Among environmental cues, light seems to have a prominent function in modulating the timing of sleep during the 24 h and, in this review, we will discuss the role of light inputs in modulating the distribution of the fly sleep-wake cycles. This phenomenon is of growing interest in the modern society, where artificial light exposure during the night is a common trait, opening the possibility to study Drosophila as a model organism for investigating shift-work disorders.

Active vision shapes and coordinates flight motor responses in flies

Animals use active sensing to respond to sensory inputs and guide future motor decisions. In flight, flies generate a pattern of head and body movements to stabilize gaze. How the brain relays visual information to control head and body movements and how active head movements influence downstream motor control remains elusive. Using a control theoretic framework, we studied the optomotor gaze stabilization reflex in tethered flight and quantified how head movements stabilize visual motion and shape wing steering efforts in fruit flies (Drosophila). By shaping visual inputs, head movements increased the gain of wing steering responses and coordination between stimulus and wings, pointing to a tight coupling between head and wing movements. Head movements followed the visual stimulus in as little as 10 ms-a delay similar to the human vestibulo-ocular reflex-whereas wing steering responses lagged by more than 40 ms. This timing difference suggests a temporal order in the flow of visual information such that the head filters visual information eliciting downstream wing steering responses. Head fixation significantly decreased the mechanical power generated by the flight motor by reducing wingbeat frequency and overall thrust. By simulating an elementary motion detector array, we show that head movements shift the effective visual input dynamic range onto the sensitivity optimum of the motion vision pathway. Taken together, our results reveal a transformative influence of active vision on flight motor responses in flies. Our work provides a framework for understanding how to coordinate moving sensors on a moving body.

Two Brain Pathways Initiate Distinct Forward Walking Programs in Drosophila

An animal at rest or engaged in stationary behaviors can instantaneously initiate goal-directed walking. How descending brain inputs trigger rapid transitions from a non-walking state to an appropriate walking state is unclear. Here, we identify two neuronal types, P9 and BPN, in the Drosophila brain that, upon activation, initiate and maintain two distinct coordinated walking patterns. P9 drives forward walking with ipsilateral turning, receives inputs from central courtship-promoting neurons and visual projection neurons, and is necessary for a male to pursue a female during courtship. In contrast, BPN drives straight, forward walking and is not required during courtship. BPN is instead recruited during and required for fast, straight, forward walking bouts. Thus, this study reveals separate brain pathways for object-directed walking and fast, straight, forward walking, providing insight into how the brain initiates context-appropriate walking programs.

Persistent Firing and Adaptation in Optic-Flow-Sensitive Descending Neurons

A general principle of sensory systems is that they adapt to prolonged stimulation by reducing their response over time. Indeed, in many visual systems, including higher-order motion sensitive neurons in the fly optic lobes and the mammalian visual cortex, a reduction in neural activity following prolonged stimulation occurs. In contrast to this phenomenon, the response of the motor system controlling flight maneuvers persists following the offset of visual motion. It has been suggested that this gap is caused by a lingering calcium signal in the output synapses of fly optic lobe neurons. However, whether this directly affects the responses of the post-synaptic descending neurons, leading to the observed behavioral output, is not known. We use extracellular electrophysiology to record from optic-flow-sensitive descending neurons in response to prolonged wide-field stimulation. We find that, as opposed to most sensory and visual neurons, and in particular to the motion vision sensitive neurons in the brains of both flies and mammals, the descending neurons show little adaption during stimulus motion. In addition, we find that the optic-flow-sensitive descending neurons display persistent firing, or an after-effect, following the cessation of visual stimulation, consistent with the lingering calcium signal hypothesis. However, if the difference in after-effect is compensated for, subsequent presentation of stimuli in a test-adapt-test paradigm reveals adaptation to visual motion. Our results thus show a combination of adaptation and persistent firing in the neurons that project to the thoracic ganglia and thereby control behavioral output.

Visual motion sensitivity in descending neurons in the hoverfly

Many animals use motion vision information to control dynamic behaviors. For example, flying insects must decide whether to pursue a prey or not, to avoid a predator, to maintain their current flight trajectory, or to land. The neural mechanisms underlying the computation of visual motion have been particularly well investigated in the fly optic lobes. However, the descending neurons, which connect the optic lobes with the motor command centers of the ventral nerve cord, remain less studied. To address this deficiency, we describe motion vision sensitive descending neurons in the hoverfly Eristalis tenax. We describe how the neurons can be identified based on their receptive field properties, and how they respond to moving targets, looming stimuli and to widefield optic flow. We discuss their similarities with previously published visual neurons, in the optic lobes and ventral nerve cord, and suggest that they can be classified as target-selective, looming sensitive and optic flow sensitive, based on these similarities. Our results highlight the importance of using several visual stimuli as the neurons can rarely be identified based on only one response characteristic. In addition, they provide an understanding of the neurophysiology of visual neurons that are likely to affect behavior.

The olfactory basis of orchid pollination by mosquitoes

Nectar feeding by mosquitoes is important for survival and reproduction, and hence disease transmission. However, we know little about the sensory mechanisms that mediate mosquito attraction to sources of nectar, like those of flowers, or how this information is processed in the mosquito brain. Using a unique mutualism between Aedes mosquitoes and Platanthera obtusata orchids, we reveal that the orchid’s scent mediates this mutualism. Furthermore, lateral inhibition in the mosquito’s antennal (olfactory) lobe—via the neurotransmitter GABA—is critical for the representation of the scent. These results have implications for understanding the olfactory basis of mosquito nectar-seeking behaviors.

Mosquitoes are important vectors of disease and require sources of carbohydrates for reproduction and survival. Unlike host-related behaviors of mosquitoes, comparatively less is understood about the mechanisms involved in nectar-feeding decisions, or how this sensory information is processed in the mosquito brain. Here we show that Aedes spp. mosquitoes, including Aedes aegypti, are effective pollinators of the Platanthera obtusata orchid, and demonstrate this mutualism is mediated by the orchid’s scent and the balance of excitation and inhibition in the mosquito’s antennal lobe (AL). The P. obtusata orchid emits an attractive, nonanal-rich scent, whereas related Platanthera species—not visited by mosquitoes—emit scents dominated by lilac aldehyde. Calcium imaging experiments in the mosquito AL revealed that nonanal and lilac aldehyde each respectively activate the LC2 and AM2 glomerulus, and remarkably, the AM2 glomerulus is also sensitive to N,N-diethyl-meta-toluamide (DEET), a mosquito repellent. Lateral inhibition between these 2 glomeruli reflects the level of attraction to the orchid scents. Whereas the enriched nonanal scent of P. obtusata activates the LC2 and suppresses AM2, the high level of lilac aldehyde in the other orchid scents inverts this pattern of glomerular activity, and behavioral attraction is lost. These results demonstrate the ecological importance of mosquitoes beyond operating as disease vectors and open the door toward understanding the neural basis of mosquito nectar-seeking behaviors.

Mechanisms of vision in the fruit fly

Vision is essential to maximize the efficiency of daily tasks such as feeding, avoiding predators or finding mating partners. An advantageous model is Drosophila melanogaster, since it offers tools that allow genetic and neuronal manipulation with high spatial and temporal resolution, which can be combined with behavioral, anatomical and physiological assays. Recent advances have expanded our knowledge on the neural circuitry underlying such important behaviors as color vision (role of reciprocal inhibition to enhance color signal at the level of the ommatidia); motion vision (motion-detection neurones receive both excitatory and inhibitory input), and sensory processing (role of the central complex in spatial navigation, and in orchestrating the information from other senses and the inner state). Research on synergies between pathways is shaping the field.

The diversity of lobula plate tangential cells (LPTCs) in the Drosophila motion vision system

To navigate through the environment, animals rely on visual feedback to control their movements relative to their surroundings. In dipteran flies, visual feedback is provided by the wide-field motion-sensitive neurons in the visual system called lobula plate tangential cells (LPTCs). Understanding the role of LPTCs in fly behaviors can address many fundamental questions on how sensory circuits guide behaviors. The blowfly was estimated to have ~ 60 LPTCs, but only a few have been identified in Drosophila. We conducted a Gal4 driver screen and identified five LPTC subtypes in Drosophila, based on their morphological characteristics: LPTCs have large arborizations in the lobula plate and project to the central brain. We compared their morphologies to the blowfly LPTCs and named them after the most similar blowfly cells: CH, H1, H2, FD1 and FD3, and V1. We further characterized their pre- and post-synaptic organizations, as well as their neurotransmitter profiles. These anatomical features largely agree with the anatomy and function of their likely blowfly counterparts. Nevertheless, several anatomical details indicate the Drosophila LPTCs may have more complex functions. Our characterization of these five LPTCs in Drosophila will facilitate further functional studies to understand their roles in the visual circuits that instruct fly behaviors.

Sensory processing by motoneurons: a numerical model for low-level flight control in flies

Rhythmic locomotor behaviour in animals requires exact timing of muscle activation within the locomotor cycle. In rapidly oscillating motor systems, conventional control strategies may be affected by neural delays, making these strategies inappropriate for precise timing control. In flies, wing control thus requires sensory processing within the peripheral nervous system, circumventing the central brain. The underlying mechanism, with which flies integrate graded depolarization of visual interneurons and spiking proprioceptive feedback for precise muscle activation, is under debate. Based on physiological parameters, we developed a numerical model of spike initiation in flight muscles of a blowfly. The simulated Hodgkin–Huxley neuron reproduces multiple experimental findings and explains on the cellular level how vision might control wing kinematics. Sensory processing by single motoneurons appears to be sufficient for control of muscle power during flight in flies and potentially other flying insects, reducing computational load on the central brain during body posture reflexes and manoeuvring flight.

Flies Regulate Wing Motion via Active Control of a Dual-Function Gyroscope

Flies execute their remarkable aerial maneuvers using a set of wing steering muscles, which are activated at specific phases of the stroke cycle [1-3]. The activation phase of these muscles-which determines their biomechanical output [4-6]-arises via feedback from mechanoreceptors at the base of the wings and structures unique to flies called halteres [7-9]. Evolved from the hindwings, the tiny halteres oscillate at the same frequency as the wings, although they serve no aerodynamic function [10] and are thought to act as gyroscopes [10-15]. Like the wings, halteres possess minute control muscles whose activity is modified by descending visual input [16], raising the possibility that flies control wing motion by adjusting the motor output of their halteres, although this hypothesis has never been directly tested. Here, using genetic techniques possible in Drosophila melanogaster, we tested the hypothesis that visual input during flight modulates haltere muscle activity and that this, in turn, alters the mechanosensory feedback that regulates the wing steering muscles. Our results suggest that rather than acting solely as a gyroscope to detect body rotation, halteres also function as an adjustable clock to set the spike timing of wing motor neurons, a specialized capability that evolved from the generic flight circuitry of their four-winged ancestors. In addition to demonstrating how the efferent control loop of a sensory structure regulates wing motion, our results provide insight into the selective scenario that gave rise to the evolution of halteres.

Modulation of Host Learning in Aedes aegypti Mosquitoes

How mosquitoes determine which individuals to bite has important epidemiological consequences. This choice is not random; most mosquitoes specialize in one or a few vertebrate host species, and some individuals in a host population are preferred over others. Mosquitoes will also blood feed from other hosts when their preferred is no longer abundant, but the mechanisms mediating these shifts between hosts, and preferences for certain individuals within a host species, remain unclear. Here, we show that olfactory learning may contribute to Aedes aegypti mosquito biting preferences and host shifts. Training and testing to scents of humans and other host species showed that mosquitoes can aversively learn the scent of specific humans and single odorants and learn to avoid the scent of rats (but not chickens). Using pharmacological interventions, RNAi, and CRISPR gene editing, we found that modification of the dopamine-1 receptor suppressed their learning abilities. We further show through combined electrophysiological and behavioral recordings from tethered flying mosquitoes that these odors evoke changes in both behavior and antennal lobe (AL) neuronal responses and that dopamine strongly modulates odor-evoked responses in AL neurons. Not only do these results provide direct experimental evidence that olfactory learning in mosquitoes can play an epidemiological role, but collectively, they also provide neuroanatomical and functional demonstration of the role of dopamine in mediating this learning-induced plasticity, for the first time in a disease vector insect.

State-dependent decoupling of sensory and motor circuits underlies behavioral flexibility in Drosophila

An approaching predator and self-motion towards 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 likely 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.

Encoding of Wind Direction by Central Neurons in Drosophila

Wind is a major navigational cue for insects, but how wind direction is decoded by central neurons in the insect brain is unknown. Here we find that walking flies combine signals from both antennae to orient to wind during olfactory search behavior. Movements of single antennae are ambiguous with respect to wind direction, but the difference between left and right antennal displacements yields a linear code for wind direction in azimuth. Second-order mechanosensory neurons share the ambiguous responses of a single antenna and receive input primarily from the ipsilateral antenna. Finally, we identify novel "wedge projection neurons" that integrate signals across the two antennae and receive input from at least three classes of second-order neurons to produce a more linear representation of wind direction. This study establishes how a feature of the sensory environment-wind direction-is decoded by neurons that compare information across two sensors.

Fast near-whole-brain imaging in adult Drosophila during responses to stimuli and behavior

Whole-brain recordings give us a global perspective of the brain in action. In this study, we describe a method using light field microscopy to record near-whole brain calcium and voltage activity at high speed in behaving adult flies. We first obtained global activity maps for various stimuli and behaviors. Notably, we found that brain activity increased on a global scale when the fly walked but not when it groomed. This global increase with walking was particularly strong in dopamine neurons. Second, we extracted maps of spatially distinct sources of activity as well as their time series using principal component analysis and independent component analysis. The characteristic shapes in the maps matched the anatomy of subneuropil regions and, in some cases, a specific neuron type. Brain structures that responded to light and odor were consistent with previous reports, confirming the new technique's validity. We also observed previously uncharacterized behavior-related activity as well as patterns of spontaneous voltage activity.