Multiplexing of motor information in the discharge of a collision detecting neuron during escape behaviors

Recent advances in insect vision in a 3D world: looming stimuli and escape behaviour

Detecting looming motion directly towards the insect is vital to its survival. Looming detection in two insects, flies and locusts, is described and contrasted. Pathways using looming detectors to trigger action and their topographical layout in the brain is explored in relation to facilitating behavioural selection. Similar visual stimuli, such as looming motion, are processed by nearby glomeruli in the brain. Insect-inspired looming motion detectors are combined to detect and avoid collision in different scenarios by robots, vehicles and unmanned aerial vehicle (UAV)s.

Escape behaviors in prey and the evolution of pennaceous plumage in dinosaurs

Numerous non-avian dinosaurs possessed pennaceous feathers on their forelimbs (proto-wings) and tail. Their functions remain unclear. We propose that these pennaceous feathers were used in displays to flush hiding prey through stimulation of sensory-neural escape pathways in prey, allowing the dinosaurs to pursue the flushed prey. We evaluated the escape behavior of grasshoppers to hypothetical visual flush-displays by a robotic dinosaur, and we recorded neurophysiological responses of grasshoppers' escape pathway to computer animations of the hypothetical flush-displays by dinosaurs. We show that the prey of dinosaurs would have fled more often when proto-wings were present, especially distally and with contrasting patterns, and when caudal plumage, especially of a large area, was used during the hypothetical flush-displays. The reinforcing loop between flush and pursue functions could have contributed to the evolution of larger and stiffer feathers for faster running, maneuverability, and stronger flush-displays, promoting foraging based on the flush-pursue strategy. The flush-pursue hypothesis can explain the presence and distribution of the pennaceous feathers, plumage color contrasts, as well as a number of other features observed in early pennaraptorans. This scenario highlights that sensory-neural processes underlying prey's antipredatory reactions may contribute to the origin of major evolutionary innovations in predators.

An Angular Acceleration Based Looming Detector for Moving UAVs

Visual perception equips unmanned aerial vehicles (UAVs) with increasingly comprehensive and instant environmental perception, rendering it a crucial technology in intelligent UAV obstacle avoidance. However, the rapid movements of UAVs cause significant changes in the field of view, affecting the algorithms' ability to extract the visual features of collisions accurately. As a result, algorithms suffer from a high rate of false alarms and a delay in warning time. During the study of visual field angle curves of different orders, it was found that the peak times of the curves of higher-order information on the angular size of looming objects are linearly related to the time to collision (TTC) and occur before collisions. This discovery implies that encoding higher-order information on the angular size could resolve the issue of response lag. Furthermore, the fact that the image of a looming object adjusts to meet several looming visual cues compared to the background interference implies that integrating various field-of-view characteristics will likely enhance the model's resistance to motion interference. Therefore, this paper presents a concise A-LGMD model for detecting looming objects. The model is based on image angular acceleration and addresses problems related to imprecise feature extraction and insufficient time series modeling to enhance the model's ability to rapidly and precisely detect looming objects during the rapid self-motion of UAVs. The model draws inspiration from the lobula giant movement detector (LGMD), which shows high sensitivity to acceleration information. In the proposed model, higher-order information on the angular size is abstracted by the network and fused with multiple visual field angle characteristics to promote the selective response to looming objects. Experiments carried out on synthetic and real-world datasets reveal that the model can efficiently detect the angular acceleration of an image, filter out insignificant background motion, and provide early warnings. These findings indicate that the model could have significant potential in embedded collision detection systems of micro or small UAVs.

Neuromuscular basis of Drosophila larval rolling escape behavior

When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larva's circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression leads to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response.

Convergent escape behaviour from distinct visual processing of impending collision in fish and grasshoppers

In animal species ranging from invertebrate to mammals, visually guided escape behaviours have been studied using looming stimuli, the two-dimensional expanding projection on a screen of an object approaching on a collision course at constant speed. The peak firing rate or membrane potential of neurons responding to looming stimuli often tracks a fixed threshold angular size of the approaching stimulus that contributes to the triggering of escape behaviours. To study whether this result holds more generally, we designed stimuli that simulate acceleration or deceleration over the course of object approach on a collision course. Under these conditions, we found that the angular threshold conveyed by collision detecting neurons in grasshoppers was sensitive to acceleration whereas the triggering of escape behaviours was less so. In contrast, neurons in goldfish identified through the characteristic features of the escape behaviours they trigger, showed little sensitivity to acceleration. This closely mirrored a broader lack of sensitivity to acceleration of the goldfish escape behaviour. Thus, although the sensory coding of simulated colliding stimuli with non-zero acceleration probably differs in grasshoppers and goldfish, the triggering of escape behaviours converges towards similar characteristics. Approaching stimuli with non-zero acceleration may help refine our understanding of neural computations underlying escape behaviours in a broad range of animal species. KEY POINTS: A companion manuscript showed that two mathematical models of collision-detecting neurons in grasshoppers and goldfish make distinct predictions for the timing of their responses to simulated objects approaching on a collision course with non-zero acceleration. Testing these experimental predictions showed that grasshopper neurons are sensitive to acceleration while goldfish neurons are not, in agreement with the distinct models proposed previously in these species using constant velocity approaches. Grasshopper and goldfish escape behaviours occurred after the stimulus reached a fixed angular size insensitive to acceleration, suggesting further downstream processing in grasshopper motor circuits to match what was observed in goldfish. Thus, in spite of different sensory processing in the two species, escape behaviours converge towards similar solutions. The use of object acceleration during approach on a collision course may help better understand the neural computations implemented for collision avoidance in a broad range of species.

Neuromuscular Basis of Drosophila larval rolling escape behavior

When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally-Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, the muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larval circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression lead to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior, and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response.

Motor state changes escape behavior of crickets

Animals change their behavior depending on external circumstances, internal factors, and their interactions. Locomotion state is a crucial internal factor that profoundly affects sensory perception and behavior. However, studying the behavioral impacts of locomotion state in free-moving animals has been challenging due to difficulty in reproducing quantitatively identical stimuli in freely moving animals. We utilized a closed-loop controlled servosphere treadmill system, enabling unrestricted confinement and orientation of small animals, and investigated wind-induced escape behavior in freely moving crickets. When stimulated during locomotion, the crickets quickly stopped before initiating escape behavior. Moving crickets exhibited a higher probability of escape response compared to stationary crickets. The threshold for pausing response in moving crickets was also much lower than the escape response threshold. Moving crickets had delayed reaction times for escape and greater variance in movement direction compared to stationary crickets. The locomotion-related response delay may be compensated by an elevated sensitivity to airflow.

A rise-to-threshold process for a relative-value decision

Whereas progress has been made in the identification of neural signals related to rapid, cued decisions1-3, less is known about how brains guide and terminate more ethologically relevant decisions in which an animal's own behaviour governs the options experienced over minutes4-6. Drosophila search for many seconds to minutes for egg-laying sites with high relative value7,8 and have neurons, called oviDNs, whose activity fulfills necessity and sufficiency criteria for initiating the egg-deposition motor programme9. Here we show that oviDNs express a calcium signal that (1) dips when an egg is internally prepared (ovulated), (2) drifts up and down over seconds to minutes-in a manner influenced by the relative value of substrates-as a fly determines whether to lay an egg and (3) reaches a consistent peak level just before the abdomen bend for egg deposition. This signal is apparent in the cell bodies of oviDNs in the brain and it probably reflects a behaviourally relevant rise-to-threshold process in the ventral nerve cord, where the synaptic terminals of oviDNs are located and where their output can influence behaviour. We provide perturbational evidence that the egg-deposition motor programme is initiated once this process hits a threshold and that subthreshold variation in this process regulates the time spent considering options and, ultimately, the choice taken. Finally, we identify a small recurrent circuit that feeds into oviDNs and show that activity in each of its constituent cell types is required for laying an egg. These results argue that a rise-to-threshold process regulates a relative-value, self-paced decision and provide initial insight into the underlying circuit mechanism for building this process.

Neural Circuit Mechanisms Involved in Animals' Detection of and Response to Visual Threats

Evading or escaping from predators is one of the most crucial issues for survival across the animal kingdom. The timely detection of predators and the initiation of appropriate fight-or-flight responses are innate capabilities of the nervous system. Here we review recent progress in our understanding of innate visually-triggered defensive behaviors and the underlying neural circuit mechanisms, and a comparison among vinegar flies, zebrafish, and mice is included. This overview covers the anatomical and functional aspects of the neural circuits involved in this process, including visual threat processing and identification, the selection of appropriate behavioral responses, and the initiation of these innate defensive behaviors. The emphasis of this review is on the early stages of this pathway, namely, threat identification from complex visual inputs and how behavioral choices are influenced by differences in visual threats. We also briefly cover how the innate defensive response is processed centrally. Based on these summaries, we discuss coding strategies for visual threats and propose a common prototypical pathway for rapid innate defensive responses.

Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models

The processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Specifically, in goldfish, the [Formula: see text] model has been proposed to describe the Mauthner cell, an identified neuron involved in startle escape responses. In the vinegar fly, a third model was developed for the giant fiber neuron, which triggers last resort escapes immediately before an impending collision. One key property of these models is their prediction that peak neuronal responses occur at a fixed delay after the simulated approaching object reaches a threshold angular size on the retina. This prediction is valid for simulated objects approaching at a constant speed. We tested whether it remains valid when approaching objects accelerate. After characterizing and comparing the models' responses to accelerating and constant speed stimuli, we find that the prediction holds true for the [Formula: see text] and the giant fiber model, but not for the [Formula: see text] model. These results suggest that acceleration in the approach trajectory of an object may help distinguish and further constrain the neuronal computations required for collision avoidance in grasshoppers, fish and vinegar flies.

Neural circuits underlying habituation of visually evoked escape behaviors in larval zebrafish

Larval zebrafish that are exposed repeatedly to dark looming stimuli will quickly habituate to these aversive signals and cease to respond with their stereotypical escape swims. A dark looming stimulus can be separated into two independent components: one that is characterized by an overall spatial expansion, where overall luminance is maintained at the same level, and a second, that represents an overall dimming within the whole visual field in the absence of any motion energy. Using specific stimulation patterns that isolate these independent components, we first extracted the behavioral algorithms that dictate how these separate information channels interact with each other and across the two eyes during the habituation process. Concurrent brain wide imaging experiments then permitted the construction of circuit models that suggest the existence of two separate neural pathways. The first is a looming channel which responds specifically to expanding edges presented to the contralateral eye and relays that information to the brain stem escape network to generate directed escapes. The second is a dimming-specific channel that could be either monocular or binocularly responsive, and that appears to specifically inhibit escape response when activated. We propose that this second channel is under strong contextual modulation and that it is primarily responsible for the incremental silencing of successive dark looming-evoked escapes.

Contrast polarity-specific mapping improves efficiency of neuronal computation for collision detection

Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cell's dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. The lack of retinotopic synaptic arrangement results in the neuron's inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animal's escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.

Roles of neural communication between the brain and thoracic ganglia in the selection and regulation of the cricket escape behavior

To survive a predator's attack, prey animals must exhibit escape responses that are appropriately regulated in terms of their moving speed, distance, and direction. Insect locomotion is considered to be controlled by an interaction between the brain, which is involved in behavioral decision-making, and the thoracic ganglia (TG), which are primary motor centers. However, it remains unknown which descending and ascending signals between these neural centers are involved in the regulation of the escape behavior. We addressed the distinct roles of the brain and TG in the wind-elicited escape behavior of crickets by assessing the effects of partial ablation of the intersegmental communications on escape responses. We unilaterally cut the ventral nerve cord (VNC) at different locations, between the brain and TG, or between the TG and terminal abdominal ganglion (TAG), a primary sensory center of the cercal system. The partial ablation of ascending signals to the brain greatly reduced the jumping response rather than running, indicating that sensory information processing in the brain is essential for the choice of escape responses. The ablation of descending signals from the brain to the TG impaired locomotor performance and directional control of the escape responses, suggesting that locomotion in the escape behavior largely depends on the descending signals from the brain. Finally, the extracellular recording from the cervical VNC indicated a difference in the descending activities preceding the escape responses between running and jumping. Our results demonstrated that the brain sends the descending signals encoding the behavioral choice and locomotor regulation to the TG, while the TG seem to have other specific roles, such as in the preparation of escape movement.

Wireless and battery-free platforms for collection of biosignals

Recent progress in biosensors have quantitively expanded current capabilities in exploratory research tools, diagnostics and therapeutics. This rapid pace in sensor development has been accentuated by vast improvements in data analysis methods in the form of machine learning and artificial intelligence that, together, promise fantastic opportunities in chronic sensing of biosignals to enable preventative screening, automated diagnosis, and tools for personalized treatment strategies. At the same time, the importance of widely accessible personal monitoring has become evident by recent events such as the COVID-19 pandemic. Progress in fully integrated and chronic sensing solutions is therefore increasingly important. Chronic operation, however, is not truly possible with tethered approaches or bulky, battery-powered systems that require frequent user interaction. A solution for this integration challenge is offered by wireless and battery-free platforms that enable continuous collection of biosignals. This review summarizes current approaches to realize such device architectures and discusses their building blocks. Specifically, power supplies, wireless communication methods and compatible sensing modalities in the context of most prevalent implementations in target organ systems. Additionally, we highlight examples of current embodiments that quantitively expand sensing capabilities because of their use of wireless and battery-free architectures.

Takeoff diversity in Diptera

The order Diptera (true flies) are named for their two wings because their hindwings have evolved into specialized mechanosensory organs called halteres. Flies use halteres to detect body rotations and maintain stability during flight and other behaviours. The most recently diverged dipteran monophyletic subsection, the Calyptratae, is highly successful, accounting for approximately 12% of dipteran diversity, and includes common families like house flies. These flies move their halteres independently from their wings and oscillate their halteres during walking. Here, we demonstrate that this subsection of flies uses their halteres to stabilize their bodies during takeoff, whereas non-Calyptratae flies do not. We find that flies of the Calyptratae are able to take off more rapidly than non-Calyptratae flies without sacrificing stability. Haltere removal decreased both velocity and stability in the takeoffs of Calyptratae, but not other flies. The loss of takeoff velocity following haltere removal in Calyptratae (but not other flies) is a direct result of a decrease in leg extension speed. A closely related non-Calyptratae species (D. melanogaster) also has a rapid takeoff, but takeoff duration and stability are unaffected by haltere removal. Haltere use thus allows for greater speed and stability during fast escapes, but only in the Calyptratae clade.

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.

Molecular characterization and distribution of the voltage-gated sodium channel, Para, in the brain of the grasshopper and vinegar fly

Voltage-gated sodium (NaV) channels, encoded by the gene para, play a critical role in the rapid processing and propagation of visual information related to collision avoidance behaviors. We investigated their localization by immunostaining the optic lobes and central brain of the grasshopper Schistocerca americana and the vinegar fly Drosophila melanogaster with an antibody that recognizes the channel peptide domain responsible for fast inactivation gating. NaV channels were detected at high density at all stages of development. In the optic lobe, they revealed stereotypically repeating fascicles consistent with the regular structure of the eye. In the central brain, major axonal tracts were strongly labeled, particularly in the grasshopper olfactory system. We used the NaV channel sequence of Drosophila to identify an ortholog in the transcriptome of Schistocerca. The grasshopper, vinegar fly, and human NaV channels exhibit a high degree of conservation at gating and ion selectivity domains. Comparison with three species evolutionarily close to Schistocerca identified splice variants of Para and their relation to those of Drosophila. The anatomical distribution of NaV channels molecularly analogous to those of humans in grasshoppers and vinegar flies provides a substrate for rapid signal propagation and visual processing in the context of visually-guided collision avoidance.

Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve discrimination of input synchrony

How neurons filter and integrate their complex patterns of synaptic inputs is central to their role in neural information processing. Synaptic filtering and integration are shaped by the frequency-dependent neuronal membrane impedance. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the membrane impedance of a collision detection neuron in the grasshopper Schistocerca americana. This neuron, the lobula giant movement detector (LGMD), exhibits consistent impedance properties across frequencies and membrane potentials. Two common active conductances g_H and g_M, mediated respectively by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels and by muscarine-sensitive M-type K⁺ channels, promote broadband integration with high temporal precision over the LGMD's natural range of membrane potentials and synaptic input frequencies. Additionally, we found that a model based on the LGMD's branching morphology increased the gain and decreased the delay associated with the mapping of synaptic input currents to membrane potential. More generally, this was true for a wide range of model neuron morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings show the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration.NEW & NOTEWORTHY Neuronal filtering and integration of synaptic input patterns depend on the electrochemical properties of dendrites. We used an identified collision detection neuron in grasshoppers to examine how its morphology and two conductances affect its membrane impedance in relation to the computations it performs. The neuronal properties examined are ubiquitous and therefore promote a general understanding of neuronal computations, including those in the human brain.

Encoding lateralization of jump kinematics and eye use in a locust via bio-robotic artifacts

The effect of previous exposure to lateral sensory stimuli in shaping the response to subsequent symmetric stimuli represents an important overlooked issue in neuroethology, with special reference to arthropods. In this research, we investigated the hypothesis to 'programme' jumping escape direction as well as surveillance orientation in young and adult individuals of Locusta migratoria as an adaptive consequence of prior exposure to directional-biased predator approaches generated by a robotic leopard gecko representing Eublepharis macularius The manipulation of the jumping escape direction was successfully achieved in young locusts, although young L. migratoria did not exhibit innately lateralized jumping escapes. Jumping escape direction was also successfully manipulated in adult locusts, which exhibited innate lateralized jumping escape at the individual level. The innate lateralization of each instar of L. migratoria in using a preferential eye during surveillance was not affected by prior lateralized exposure to the robotic gecko. Our results indicate a high plasticity of the escape motor outputs that are occurring almost in real time with the perceived stimuli, making them greatly adaptable and compliant to environmental changes in order to be effective and reliable. In addition, surveillance lateralization innately occurs at population level in each instar of L. migratoria Therefore, its low forgeability by environmental factors would avoid disorganization at swarm level and improve swarm coordination during group tasks. These findings are consistent with the fact that, as in vertebrates, in insects the right hemisphere is specialized in controlling fear and escape functions.

Integration of Small- and Wide-Field Visual Features in Target-Selective Descending Neurons of both Predatory and Nonpredatory Dipterans

For many animals, target motion carries high ecological significance as this may be generated by a predator, prey, or potential mate. Indeed, animals whose survival depends on early target detection are often equipped with a sharply tuned visual system, yielding robust performance in challenging conditions. For example, many fast-flying insects use visual cues for identifying targets, such as prey (e.g., predatory dragonflies and robberflies) or conspecifics (e.g., nonpredatory hoverflies), and can often do so against self-generated background optic flow. Supporting these behaviors, the optic lobes of insects that pursue targets harbor neurons that respond robustly to the motion of small moving objects, even when displayed against syn-directional background clutter. However, in diptera, the encoding of target information by the descending neurons, which are more directly involved in generating the behavioral output, has received less attention. We characterized target-selective neurons by recording in the ventral nerve cord of male and female predatory Holcocephala fusca robberflies and of male nonpredatory Eristalis tenax hoverflies. We show that both species have dipteran target-selective descending neurons that only respond to target motion if the background is stationary or moving slowly, moves in the opposite direction, or has un-naturalistic spatial characteristics. The response to the target is suppressed when background and target move at similar velocities, which is strikingly different to the response of target neurons in the optic lobes. As the neurons we recorded from are premotor, our findings affect our interpretation of the neurophysiology underlying target-tracking behaviors.

SIGNIFICANCE STATEMENT Many animals use sensory cues to detect moving targets that may represent predators, prey, or conspecifics. For example, birds of prey show superb sensitivity to the motion of small prey, and intercept these at high speeds. In a similar manner, predatory insects visually track moving prey, often against cluttered backgrounds. Accompanying this behavior, the brains of insects that pursue targets contain neurons that respond exclusively to target motion. We here show that dipteran insects also have target-selective descending neurons in the part of their nervous system that corresponds to the vertebrate spinal cord. Surprisingly, and in contrast to the neurons in the brain, these premotor neurons are inhibited by background patterns moving in the same direction as the target.

Three-dimensional shape and velocity changes affect responses of a locust visual interneuron to approaching objects

Adaptive collision avoidance behaviours require accurate detection of complex spatiotemporal properties of an object approaching in an animal's natural, three-dimensional environment. Within the locust, the lobula giant movement detector and its postsynaptic partner, the descending contralateral movement detector (DCMD), respond robustly to images that emulate an approaching two-dimensional object and exhibit firing rate modulation correlated with changes in object trajectory. It is not known how this pathway responds to visual expansion of a three-dimensional object or an approaching object that changes velocity, both of which represent natural stimuli. We compared DCMD responses with images that emulate the approach of a sphere with those elicited by a two-dimensional disc. A sphere evoked later peak firing and decreased sensitivity to the ratio of the half size of the object to the approach velocity, resulting in an increased threshold subtense angle required to generate peak firing. We also presented locusts with an approaching sphere that decreased or increased in velocity. A velocity decrease resulted in transition-associated peak firing followed by a firing rate increase that resembled the response to a constant, slower velocity. A velocity increase resulted in an earlier increase in the firing rate that was more pronounced with an earlier transition. These results further demonstrate that this pathway can provide motor circuits for behaviour with salient information about complex stimulus dynamics.

Optogenetic manipulation of medullary neurons in the locust optic lobe

The locust is a widely used animal model for studying sensory processing and its relation to behavior. Due to the lack of genomic information, genetic tools to manipulate neural circuits in locusts are not yet available. We examined whether Semliki Forest virus is suitable to mediate exogenous gene expression in neurons of the locust optic lobe. We subcloned a channelrhodopsin variant and the yellow fluorescent protein Venus into a Semliki Forest virus vector and injected the virus into the optic lobe of locusts ( Schistocerca americana). Fluorescence was observed in all injected optic lobes. Most neurons that expressed the recombinant proteins were located in the first two neuropils of the optic lobe, the lamina and medulla. Extracellular recordings demonstrated that laser illumination increased the firing rate of medullary neurons expressing channelrhodopsin. The optogenetic activation of the medullary neurons also triggered excitatory postsynaptic potentials and firing of a postsynaptic, looming-sensitive neuron, the lobula giant movement detector. These results indicate that Semliki Forest virus is efficient at mediating transient exogenous gene expression and provides a tool to manipulate neural circuits in the locust nervous system and likely other insects. NEW & NOTEWORTHY Using Semliki Forest virus, we efficiently delivered channelrhodopsin into neurons of the locust optic lobe. We demonstrate that laser illumination increases the firing of the medullary neurons expressing channelrhodopsin and elicits excitatory postsynaptic potentials and spiking in an identified postsynaptic target neuron, the lobula giant movement detector neuron. This technique allows the manipulation of neuronal activity in locust neural circuits using optogenetics.

Single mechanosensory neurons encode lateral displacements using precise spike timing and thresholds

During locomotion, animals rely on multiple sensory modalities to maintain stability. External cues may guide behaviour, but they must be interpreted in the context of the animal's own body movements. Mechanosensory cues that can resolve dynamic internal and environmental conditions, like those from vertebrate vestibular systems or other proprioceptors, are essential for guided movement. How do afferent proprioceptor neurons transform movement into a neural code? In flies, modified hindwings known as halteres detect forces produced by body rotations and are essential for flight. However, the mechanisms by which haltere neurons transform forces resulting from three-dimensional body rotations into patterns of neural spikes are unknown. We use intracellular electrodes to record from haltere primary afferent neurons during a range of haltere motions. We find that spike timing activity of individual neurons changes with displacement and propose a mechanism by which single neurons can encode three-dimensional haltere movements during flight.

M current regulates firing mode and spike reliability in a collision-detecting neuron

All animals must detect impending collisions to escape and reliably discriminate them from nonthreatening stimuli, thus preventing false alarms. Therefore, it is no surprise that animals have evolved highly selective and sensitive neurons dedicated to such tasks. We examined a well-studied collision-detection neuron in the grasshopper ( Schistocerca americana) using in vivo electrophysiology, pharmacology, and computational modeling. This lobula giant movement detector (LGMD) neuron is excitable by inputs originating from each ommatidia of the compound eye. It possesses many intrinsic properties that increase its selectivity to objects approaching on a collision course, including switching between burst and nonburst firing. In this study, we demonstrate that the LGMD neuron exhibits a large M current, generated by noninactivating K⁺ channels, that shortens the temporal window of dendritic integration, regulates a firing mode switch between burst and isolated spiking, increases the precision of spike timing, and increases the reliability of spike propagation to downstream motor centers. By revealing how the M current increases the LGMD's ability to detect impending collisions, our results suggest that similar channels may play an analogous role in other collision detection circuits. NEW & NOTEWORTHY The ability to reliably detect impending collisions is a critical survival skill. The nervous systems of many animals have developed dedicated neurons for accomplishing this task. We used a mix of in vivo electrophysiology and computational modeling to investigate the role of M potassium channels within one such collision-detecting neuron and show that through regulation of burst firing and enhancement of spiking reliability, the M current increases the ability to detect impending collisions.

Feedforward Inhibition Conveys Time-Varying Stimulus Information in a Collision Detection Circuit

Feedforward inhibition is ubiquitous as a motif in the organization of neuronal circuits. During sensory information processing, it is traditionally thought to sharpen the responses and temporal tuning of feedforward excitation onto principal neurons. As it often exhibits complex time-varying activation properties, feedforward inhibition could also convey information used by single neurons to implement dendritic computations on sensory stimulus variables. We investigated this possibility in a collision-detecting neuron of the locust optic lobe that receives both feedforward excitation and inhibition. We identified a small population of neurons mediating feedforward inhibition, with wide visual receptive fields and whose responses depend both on the size and speed of moving stimuli. By studying responses to simulated objects approaching on a collision course, we determined that they jointly encode the angular size of expansion of the stimulus. Feedforward excitation, on the other hand, encodes a function of the angular velocity of expansion and the targeted collision-detecting neuron combines these two variables non-linearly in its firing output. Thus, feedforward inhibition actively contributes to the detailed firing-rate time course of this collision-detecting neuron, a feature critical to the appropriate execution of escape behaviors. These results suggest that feedforward inhibition could similarly convey time-varying stimulus information in other neuronal circuits.

Biophysics of object segmentation in a collision-detecting neuron

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. Here, we demonstrate that a collision-detecting neuron can detect the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation. Pharmacological block of HCN channels abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Additionally, our results suggest that the interaction of HCN and inactivating K⁺ channels within active dendrites produces neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.

Characterization and modelling of looming-sensitive neurons in the crab Neohelice

Looming-sensitive neurons (LSNs) are motion-sensitive neurons tuned for detecting imminent collision. Their main characteristic is the selectivity to looming (a 2D representation of an object approach), rather than to receding stimuli. We studied a set of LSNs by performing surface extracellular recordings in the optic nerve of Neohelice granulata crabs, and characterized their response against computer-generated visual stimuli with different combinations of moving edges, highlighting different components of the optical flow. In addition to their selectivity to looming stimuli, we characterized other properties of these neurons, such as low directionality; reduced response to sustained excitement; and an inhibition phenomenon in response to visual stimuli with dense optical flow of expansion, contraction, and translation. To analyze the spatio-temporal processing of these LSNs, we proposed a biologically plausible computational model which was inspired by previous computational models of the locust lobula giant motion detector (LGMD) neuron. The videos seen by the animal during electrophysiological experiments were applied as an input to the model which produced a satisfactory fit to the measured responses, suggesting that the computation performed by LSNs in a decapod crustacean appears to be based on similar physiological processing previously described for the LGMD in insects.

Feature Integration Drives Probabilistic Behavior in the Drosophila Escape Response

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.

Complex object motion represented by context-dependent correlated activity of visual interneurones

Accurate and adaptive encoding of complex, dynamic visual information is critical for the survival of many animals. Studies across a range of taxa have investigated behavioral and neuronal responses to objects that represent a threat, such as a looming object approaching along a direct collision course. By investigating neural mechanisms of avoidance behaviors through recording multineuronal activity, it is possible to better understand how complex visual information is represented in circuits that ultimately drive behaviors. We used multichannel electrodes to record from the well-studied locust nervous system to explore how object motion is reflected in activity of correlated neural activity. We presented locusts (Locusta migratoria) with objects that moved along one of 11 unique trajectories and recorded from descending interneurons within the ventral nerve cord. Spike sorting resulted in 405 discriminated units across 20 locusts and we found that 75% of the units responded to some form of object motion. Dimensionality reduction through principal component (PCA) and dynamic factor (DFA) analyses revealed population vector responses within individuals and common firing trends across the pool of discriminated units, respectively. Population vector composition (PCA) varied with the stimulus and common trends (DFA) showed unique tuning related to changes in the visual size and trajectory of the object through time. These findings demonstrate that this well-described collision detection system is more complex than previously envisioned and will drive future experiments to explore fundamental principles of how visual information is processed through context-dependent dynamic ensembles of neurons to initiate and control complex behavior.

Interaction of compass sensing and object-motion detection in the locust central complex

Goal-directed behavior is often complicated by unpredictable events, such as the appearance of a predator during directed locomotion. This situation requires adaptive responses like evasive maneuvers followed by subsequent reorientation and course correction. Here we study the possible neural underpinnings of such a situation in an insect, the desert locust. As in other insects, its sense of spatial orientation strongly relies on the central complex, a group of midline brain neuropils. The central complex houses sky compass cells that signal the polarization plane of skylight and thus indicate the animal's steering direction relative to the sun. Most of these cells additionally respond to small moving objects that drive fast sensory-motor circuits for escape. Here we investigate how the presentation of a moving object influences activity of the neurons during compass signaling. Cells responded in one of two ways: in some neurons, responses to the moving object were simply added to the compass response that had adapted during continuous stimulation by stationary polarized light. By contrast, other neurons disadapted, i.e., regained their full compass response to polarized light, when a moving object was presented. We propose that the latter case could help to prepare for reorientation of the animal after escape. A neuronal network based on central-complex architecture can explain both responses by slight changes in the dynamics and amplitudes of adaptation to polarized light in CL columnar input neurons of the system.NEW & NOTEWORTHY Neurons of the central complex in several insects signal compass directions through sensitivity to the sky polarization pattern. In locusts, these neurons also respond to moving objects. We show here that during polarized-light presentation, responses to moving objects override their compass signaling or restore adapted inhibitory as well as excitatory compass responses. A network model is presented to explain the variations of these responses that likely serve to redirect flight or walking following evasive maneuvers.

Food deprivation and prior anoxic coma have opposite effects on the activity of a visual interneuron in the locust

We compared how different metabolic stressors, anoxic coma and food deprivation, affected signaling in neural tissue. We used the locust's Descending Contralateral Movement Detector (DCMD) interneuron because its large axon, high firing frequencies, and rapid conduction velocity make it energetically expensive. We exposed locusts to a 30min anoxic coma or 1day of food deprivation and found contrasting effects on signaling within the axon. After a prior anoxic coma, the DCMD fired fewer high-frequency (>200Hz) action potentials (APs) (Control: 12.4±1.6; Coma: 6.3±0.9) with a reduction in axonal conduction velocity (CV) at all frequencies (∼4-8%) when presented with a standard looming visual stimulus. Prior anoxic coma was also associated with a loss of supernormal conduction by reducing both the number of supernormal APs and the firing frequency with the highest CV. Initially, food deprivation caused a significant increase in the number of low- and high-frequency APs with no differences observed in CV. After controlling for isolation, food deprivation resulted in an increase in high-frequency APs (>200Hz: Control: 17.1±1.7; Food-deprived: 19.9±1.3) and an increase in relative conduction velocity for frequencies >150Hz (∼2%). Action potentials of food-deprived animals had a smaller half-width (Control: 0.45±0.02ms; Food-deprived: 0.40±0.01ms) and decay time (Control: 0.62±0.03ms; Food-deprived: 0.54±0.02ms). Our data indicate that the effects of metabolic stress on neural signaling can be stressor-dependent.

Visual projection neurons in the Drosophila lobula link feature detection to distinct behavioral programs

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.

Emergence of Selectivity to Looming Stimuli in a Spiking Network Model of the Optic Tectum

The neural circuits in the optic tectum of Xenopus tadpoles are selectively responsive to looming visual stimuli that resemble objects approaching the animal at a collision trajectory. This selectivity is required for adaptive collision avoidance behavior in this species, but its underlying mechanisms are not known. In particular, it is still unclear how the balance between the recurrent spontaneous network activity and the newly arriving sensory flow is set in this structure, and to what degree this balance is important for collision detection. Also, despite the clear indication for the presence of strong recurrent excitation and spontaneous activity, the exact topology of recurrent feedback circuits in the tectum remains elusive. In this study we take advantage of recently published detailed cell-level data from tadpole tectum to build an informed computational model of it, and investigate whether dynamic activation in excitatory recurrent retinotopic networks may on its own underlie collision detection. We consider several possible recurrent connectivity configurations and compare their performance for collision detection under different levels of spontaneous neural activity. We show that even in the absence of inhibition, a retinotopic network of quickly inactivating spiking neurons is naturally selective for looming stimuli, but this selectivity is not robust to neuronal noise, and is sensitive to the balance between direct and recurrent inputs. We also describe how homeostatic modulation of intrinsic properties of individual tectal cells can change selectivity thresholds in this network, and qualitatively verify our predictions in a behavioral experiment in freely swimming tadpoles.

Two identified looming detectors in the locust: ubiquitous lateral connections among their inputs contribute to selective responses to looming objects

In locusts, two lobula giant movement detector neurons (LGMDs) act as looming object detectors. Their reproducible responses to looming and their ethological significance makes them models for single neuron computation. But there is no comprehensive picture of the neurons that connect directly to each LGMD. We used high-through-put serial block-face scanning-electron-microscopy to reconstruct the network of input-synapses onto the LGMDs over spatial scales ranging from single synapses and small circuits, up to dendritic branches and total excitatory input. Reconstructions reveal that many trans-medullary-afferents (TmAs) connect the eye with each LGMD, one TmA per facet per LGMD. But when a TmA synapses with an LGMD it also connects laterally with another TmA. These inter-TmA synapses are always reciprocal. Total excitatory input to the LGMD 1 and 2 comes from 131,000 and 186,000 synapses reaching densities of 3.1 and 2.6 synapses per μm² respectively. We explored the computational consequences of reciprocal synapses between each TmA and 6 others from neighbouring columns. Since any lateral interactions between LGMD inputs have always been inhibitory we may assume these reciprocal lateral connections are most likely inhibitory. Such reciprocal inhibitory synapses increased the LGMD’s selectivity for looming over passing objects, particularly at the beginning of object approach.

Background visual motion affects responses of an insect motion-sensitive neuron to objects deviating from a collision course

Stimulus complexity affects the response of looming sensitive neurons in a variety of animal taxa. The Lobula Giant Movement Detector/Descending Contralateral Movement Detector (LGMD/DCMD) pathway is well-characterized in the locust visual system. It responds to simple objects approaching on a direct collision course (i.e., looming) as well as complex motion defined by changes in stimulus velocity, trajectory, and transitions, all of which are affected by the presence or absence of background visual motion. In this study, we focused on DCMD responses to objects transitioning away from a collision course, which emulates a successful locust avoidance behavior. We presented each of 20 locusts with a sequence of complex three-dimensional visual stimuli in simple, scattered, and progressive flow field backgrounds while simultaneously recording DCMD activity extracellularly. DCMD responses to looming stimuli were generally characteristic irrespective of stimulus background. However, changing background complexity affected, peak firing rates, peak time, and caused changes in peak rise and fall phases. The DCMD response to complex object motion also varied with the azimuthal approach angle and the dynamics of object edge expansion. These data fit with an existing correlational model that relates expansion properties to firing rate modulation during trajectory changes.

Ionic mechanisms maintaining action potential conduction velocity at high firing frequencies in an unmyelinated axon

The descending contralateral movement detector (DCMD) is a high‐performance interneuron in locusts with an axon capable of transmitting action potentials (AP) at more than 500 Hz. We investigated biophysical mechanisms for fidelity of high‐frequency transmission in this axon. We measured conduction velocities (CVs) at room temperature during exposure to 10 mmol/L cadmium, a calcium current antagonist, and found significant reduction in CV with reduction at frequencies >200 Hz of ~10%. Higher temperatures induced greater CV reductions during exposure to cadmium across all frequencies of ~20–30%. Intracellular recordings during 15 min of exposure to cadmium or nickel, also a calcium current antagonist, revealed an increase in the magnitude of the afterhyperpolarization potential (AHP) and the time to recover to baseline after the AHP (Medians for Control: −19.8%; Nickel: 167.2%; Cadmium: 387.2%), that could be due to a T‐type calcium current. However, the removal of extracellular calcium did not mimic divalent cation exposure suggesting calcium currents are not the cause of the AHP increase. Computational modeling showed that the effects of the divalent cations could be modeled with a persistent sodium current which could be blocked by high concentrations of divalent cations. Persistent sodium current shortened the AHP duration in our models and increased CV for high‐frequency APs. We suggest that faithful, high‐frequency axonal conduction in the DCMD is enabled by a mechanism that shortens the AHP duration like a persistent or resurgent sodium current.

Avoidance of a moving threat in the common chameleon (Chamaeleo chamaeleon): rapid tracking by body motion and eye use

A chameleon (Chamaeleo chamaeleon) on a perch responds to a nearby threat by moving to the side of the perch opposite the threat, while bilaterally compressing its abdomen, thus minimizing its exposure to the threat. If the threat moves, the chameleon pivots around the perch to maintain its hidden position. How precise is the body rotation and what are the patterns of eye movement during avoidance? Just-hatched chameleons, placed on a vertical perch, on the side roughly opposite to a visual threat, adjusted their position to precisely opposite the threat. If the threat were moved on a horizontal arc at angular velocities of up to 85°/s, the chameleons co-rotated smoothly so that (1) the angle of the sagittal plane of the head relative to the threat and (2) the direction of monocular gaze, were positively and significantly correlated with threat angular position. Eye movements were role-dependent: the eye toward which the threat moved maintained a stable gaze on it, while the contralateral eye scanned the surroundings. This is the first description, to our knowledge, of such a response in a non-flying terrestrial vertebrate, and it is discussed in terms of possible underlying control systems.

Predation risk modifies behaviour by shaping the response of identified brain neurons

Interpopulation comparisons in species that show behavioural variations associated with particular ecological disparities offer good opportunities for assessing how environmental factors may foster specific functional adaptations in the brain. Yet, studies on the neural substrate that can account for interpopulation behavioural adaptations are scarce. Predation is one of the strongest driving forces for behavioural evolvability and, consequently, for shaping structural and functional brain adaptations. We analysed the escape response of crabs Neohelice granulata from two isolated populations exposed to different risks of avian predation. Individuals from the high-risk area proved to be more reactive to visual danger stimuli (VDS) than those from an area where predators are rare. Control experiments indicate that the response difference was specific for impending visual threats. Subsequently, we analysed the response to VDS of a group of giant brain neurons that are thought to play a main role in the visually guided escape response of the crab. Neurons from animals of the population with the stronger escape response were more responsive to VDS than neurons from animals of the less reactive population. Our results suggest a robust linkage between the pressure imposed by the predation risk, the response of identified neurons and the behavioural outcome.

Neural Circuits Underlying Visually Evoked Escapes in Larval Zebrafish

Escape behaviors deliver organisms away from imminent catastrophe. Here, we characterize behavioral responses of freely swimming larval zebrafish to looming visual stimuli simulating predators. We report that the visual system alone can recruit lateralized, rapid escape motor programs, similar to those elicited by mechanosensory modalities. Two-photon calcium imaging of retino-recipient midbrain regions isolated the optic tectum as an important center processing looming stimuli, with ensemble activity encoding the critical image size determining escape latency. Furthermore, we describe activity in retinal ganglion cell terminals and superficial inhibitory interneurons in the tectum during looming and propose a model for how temporal dynamics in tectal periventricular neurons might arise from computations between these two fundamental constituents. Finally, laser ablations of hindbrain circuitry confirmed that visual and mechanosensory modalities share the same premotor output network. We establish a circuit for the processing of aversive stimuli in the context of an innate visual behavior.

Organization of descending neurons in Drosophila melanogaster

Neural processing in the brain controls behavior through descending neurons (DNs) - neurons which carry signals from the brain to the spinal cord (or thoracic ganglia in insects). Because DNs arise from multiple circuits in the brain, the numerical simplicity and availability of genetic tools make Drosophila a tractable model for understanding descending motor control. As a first step towards a comprehensive study of descending motor control, here we estimate the number and distribution of DNs in the Drosophila brain. We labeled DNs by backfilling them with dextran dye applied to the neck connective and estimated that there are ~1100 DNs distributed in 6 clusters in Drosophila. To assess the distribution of DNs by neurotransmitters, we labeled DNs in flies in which neurons expressing the major neurotransmitters were also labeled. We found DNs belonging to every neurotransmitter class we tested: acetylcholine, GABA, glutamate, serotonin, dopamine and octopamine. Both the major excitatory neurotransmitter (acetylcholine) and the major inhibitory neurotransmitter (GABA) are employed equally; this stands in contrast to vertebrate DNs which are predominantly excitatory. By comparing the distribution of DNs in Drosophila to those reported previously in other insects, we conclude that the organization of DNs in insects is highly conserved.

Object approach computation by a giant neuron and its relation with the speed of escape in the crab Neohelice

Upon detection of an approaching object the crab Neohelice granulata continuously regulates the direction and speed of escape according to ongoing visual information. These visuomotor transformations are thought to be largely accounted for by a small number of motion-sensitive giant neurons projecting from the lobula (third optic neuropil) towards the supraesophageal ganglion. One of these elements, the monostratified lobula giant neurons of type 2 (MLG2), proved to be highly sensitive to looming stimuli (a 2D representation of an object approach). By performing in vivo intracellular recordings we assessed the response of the MLG2 neuron to a variety of looming stimuli representing objects of different sizes and velocities of approach. This allowed us: a) to identify some of the physiological mechanisms involved in the regulation of the MLG2 activity and to test a simplified biophysical model of its response to looming stimuli; b) to identify the stimulus optical parameters encoded by the MLG2, and to formulate a phenomenological model able to predict the temporal course of the neural firing responses to all looming stimuli; c) to incorporate the MLG2 encoded information of the stimulus (in terms of firing rate) into a mathematical model able to fit the speed of the escape run of the animal. The agreement between the model predictions and the actual escape speed measured on a treadmill for all tested stimuli strengthens our interpretation of the computations performed by the MLG2 and of the involvement of this neuron in the regulation of the animal's speed of run while escaping from objects approaching with constant speed.

Burst Firing in a Motion-Sensitive Neural Pathway Correlates with Expansion Properties of Looming Objects that Evoke Avoidance Behaviors

The locust visual system contains a well-defined motion-sensitive pathway that transfers visual input to motor centers involved in predator evasion and collision avoidance. One interneuron in this pathway, the descending contralateral movement detector (DCMD), is typically described as using rate coding; edge expansion of approaching objects causes an increased rate of neuronal firing that peaks after a certain retinal threshold angle is exceeded. However, evidence of intrinsic DCMD bursting properties combined with observable oscillations in mean firing rates and tight clustering of spikes in raw traces, suggest that bursting may be important for motion detection. Sensory neuron bursting provides important timing information about dynamic stimuli in many model systems, yet no studies have rigorously investigated if bursting occurs in the locust DCMD during object approach. We presented repetitions of 30 looming stimuli known to generate behavioral responses to each of 20 locusts in order to identify and quantify putative bursting activity in the DCMD. Overall, we found a bimodal distribution of inter-spike intervals (ISI) with peaks of more frequent and shorter ISIs occurring from 1–8 ms and longer less frequent ISIs occurring from 40–50 ms. Subsequent analysis identified bursts and isolated single spikes from the responses. Bursting frequency increased in the latter phase of an approach and peaked at the time of collision, while isolated spiking was predominant during the beginning of stimulus approach. We also found that the majority of inter-burst intervals (IBIs) occurred at 40–50 ms (or 20–25 bursts/s). Bursting also occurred across varied stimulus parameters and suggests that burst timing may be a key component of looming detection. Our findings suggest that the DCMD uses two modes of coding to transmit information about looming stimuli and that these modes change dynamically with a changing stimulus at a behaviorally-relevant time.

Compass Cells in the Brain of an Insect Are Sensitive to Novel Events in the Visual World

The central complex of the insect brain comprises a group of neuropils involved in spatial orientation and memory. In fruit flies it mediates place learning based on visual landmarks and houses neurons that encode the orientation for goal-directed locomotion, based on landmarks and self-motion cues for angular path-integration. In desert locusts, the central complex holds a compass-like representation of head directions, based on the polarization pattern of skylight. Through intracellular recordings from immobilized locusts, we investigated whether sky compass neurons of the central complex also represent the position or any salient feature of possible landmarks, in analogy to the observations in flies. Neurons showed strongest responses to the novel appearance of a small moving square, but we found no evidence for a topographic representation of object positions. Responses to an individual square were independent of direction of motion and trajectory, but showed rapid adaptation to successive stimulation, unaffected by changing the direction of motion. Responses reappeared, however, if the moving object changed its trajectory or if it suddenly reversed moving direction against the movement of similar objects that make up a coherent background-flow as induced by ego-motion. Response amplitudes co-varied with the precedent state of dynamic background activity, a phenomenon that has been related to attention-dependent saliency coding in neurons of the mammalian primary visual cortex. The data show that neurons of the central complex of the locust brain are visually bimodal, signaling sky compass direction and the novelty character of moving objects. These response properties might serve to attune compass-aided locomotor control to unexpected events in the environment. The difference to data obtained in fruit flies might relate to differences in the lifestyle of landmark learners (fly) and compass navigators (locust), point to the existence of parallel networks for the two orientation strategies, or reflect differences in experimental conditions.

Dendritic Pooling of Noisy Threshold Processes Can Explain Many Properties of a Collision-Sensitive Visual Neuron

Power laws describe brain functions at many levels (from biophysics to psychophysics). It is therefore possible that they are generated by similar underlying mechanisms. Previously, the response properties of a collision-sensitive neuron were reproduced by a model which used a power law for scaling its inhibitory input. A common characteristic of such neurons is that they integrate information across a large part of the visual field. Here we present a biophysically plausible model of collision-sensitive neurons with η-like response properties, in which we assume that each information channel is noisy and has a response threshold. Then, an approximative power law is obtained as a result of pooling these channels. We show that with this mechanism one can successfully predict many response characteristics of the Lobula Giant Movement Detector Neuron (LGMD). Moreover, the results depend critically on noise in the inhibitory pathway, but they are fairly robust against noise in the excitatory pathway.

Many different animals (from insects to primates) try to escape from collision threats, because it is very possible that the approaching object is a predator. The corresponding neurons in the various nervous systems must therefore detect such threats and signal when it is time to escape. Surprisingly, the neurons of different animals which selectively respond to approaching objects have very similar properties. It is therefore worthwhile to understand their underlying computational principles. A common characteristic of such neurons is that they receive (or integrate) information from the whole visual field. The integration process is carried out by the dendritic tree of the neuron. Here we present a computational model in which we assume that each of the input signals is contaminated by noise, as well as having a response threshold (which has to be crossed in order to evoke a response). Then, dendritic integration approximates a mathematical function (a power law) which is essential in our model for explaining the response characteristics of collision-sensitive neurons. Thus, noise is used in a constructive way for computing collision-sensitive responses. Power laws are furthermore found in many different contexts, and may consequently hint at the presence of noise and thresholds.

A direct descending pathway informing locomotor networks about tactile sensor movement

Much like visually impaired humans use a white-cane, nocturnal insects and mammals use antennae or whiskers for near-range orientation. Stick insects, for example, rely heavily on antennal tactile cues to find footholds and detect obstacles. Antennal contacts can even induce aimed reaching movements. Because tactile sensors are essentially one-dimensional, they must be moved to probe the surrounding space. Sensor movement is thus an essential cue for tactile sensing, which needs to be integrated by thoracic networks for generating appropriate adaptive leg movements. Based on single and double recordings, we describe a descending neural pathway comprising three identified ON- and OFF-type neurons that convey complementary, unambiguous, and short-latency information about antennal movement to thoracic networks in the stick insect. The neurons are sensitive to the velocity of antennal movements across the entire range covered by natural movements, regardless of movement direction and joint angle. Intriguingly, none of them originates from the brain. Instead, they descend from the gnathal ganglion and receive input from antennal mechanoreceptors in this lower region of the CNS. From there, they convey information about antennal movement to the thorax. One of the descending neurons, which is additionally sensitive to substrate vibration, feeds this information back to the brain via an ascending branch. We conclude that descending interneurons with complementary tuning characteristics, gains, input and output regions convey detailed information about antennal movement to thoracic networks. This pathway bypasses higher processing centers in the brain and thus constitutes a shortcut between tactile sensors on the head and the thorax.

Activity in descending dopaminergic neurons represents but is not required for leg movements in the fruit fly Drosophila

Modulatory descending neurons (DNs) that link the brain to body motor circuits, including dopaminergic DNs (DA-DNs), are thought to contribute to the flexible control of behavior. Dopamine elicits locomotor-like outputs and influences neuronal excitability in isolated body motor circuits over tens of seconds to minutes, but it remains unknown how and over what time scale DA-DN activity relates to movement in behaving animals. To address this question, we identified DA-DNs in the Drosophila brain and developed an electrophysiological preparation to record and manipulate the activity of these cells during behavior. We find that DA-DN spike rates are rapidly modulated during a subset of leg movements and scale with the total speed of ongoing leg movements, whether occurring spontaneously or in response to stimuli. However, activating DA-DNs does not elicit leg movements in intact flies, nor do acute bidirectional manipulations of DA-DN activity affect the probability or speed of leg movements over a time scale of seconds to minutes. Our findings indicate that in the context of intact descending control, changes in DA-DN activity are not sufficient to influence ongoing leg movements and open the door to studies investigating how these cells interact with other descending and local neuromodulatory inputs to influence body motor output.

Extracting information in spike time patterns with wavelets and information theory

We present a new method to assess the information carried by temporal patterns in spike trains. The method first performs a wavelet decomposition of the spike trains, then uses Shannon information to select a subset of coefficients carrying information, and finally assesses timing information in terms of decoding performance: the ability to identify the presented stimuli from spike train patterns. We show that the method allows: 1) a robust assessment of the information carried by spike time patterns even when this is distributed across multiple time scales and time points; 2) an effective denoising of the raster plots that improves the estimate of stimulus tuning of spike trains; and 3) an assessment of the information carried by temporally coordinated spikes across neurons. Using simulated data, we demonstrate that the Wavelet-Information (WI) method performs better and is more robust to spike time-jitter, background noise, and sample size than well-established approaches, such as principal component analysis, direct estimates of information from digitized spike trains, or a metric-based method. Furthermore, when applied to real spike trains from monkey auditory cortex and from rat barrel cortex, the WI method allows extracting larger amounts of spike timing information. Importantly, the fact that the WI method incorporates multiple time scales makes it robust to the choice of partly arbitrary parameters such as temporal resolution, response window length, number of response features considered, and the number of available trials. These results highlight the potential of the proposed method for accurate and objective assessments of how spike timing encodes information.