Comparative approaches to escape

Tonically active GABAergic neurons in the dorsal periaqueductal gray control instinctive escape in mice

Escape behavior is a set of locomotor actions that move an animal away from threat. While these actions can be stereotyped, it is advantageous for survival that they are flexible.1,2,3 For example, escape probability depends on predation risk and competing motivations,4,5,6,7,8,9,10,11 and flight to safety requires continuous adjustments of trajectory and must terminate at the appropriate place and time.12,13,14,15,16 This degree of flexibility suggests that modulatory components, like inhibitory networks, act on the neural circuits controlling instinctive escape.17,18,19,20,21,22 In mice, the decision to escape from imminent threats is implemented by a feedforward circuit in the midbrain, where excitatory vesicular glutamate transporter 2-positive (VGluT2+) neurons in the dorsal periaqueductal gray (dPAG) compute escape initiation and escape vigor.23,24,25 Here we tested the hypothesis that local GABAergic neurons within the dPAG control escape behavior by setting the excitability of the dPAG escape network. Using in vitro patch-clamp and in vivo neural activity recordings, we found that vesicular GABA transporter-positive (VGAT+) dPAG neurons fire action potentials tonically in the absence of synaptic inputs and are a major source of inhibition to VGluT2+ dPAG neurons. Activity in VGAT+ dPAG cells transiently decreases at escape onset and increases during escape, peaking at escape termination. Optogenetically increasing or decreasing VGAT+ dPAG activity changes the probability of escape when the stimulation is delivered at threat onset and the duration of escape when delivered after escape initiation. We conclude that the activity of tonically firing VGAT+ dPAG neurons sets a threshold for escape initiation and controls the execution of the flight action.

Visual looming is a primitive for human emotion

The neural computations for looming detection are strikingly similar across species. In mammals, information about approaching threats is conveyed from the retina to the midbrain superior colliculus, where approach variables are computed to enable defensive behavior. Although neuroscientific theories posit that midbrain representations contribute to emotion through connectivity with distributed brain systems, it remains unknown whether a computational system for looming detection can predict both defensive behavior and phenomenal experience in humans. Here, we show that a shallow convolutional neural network based on the Drosophila visual system predicts defensive blinking to looming objects in infants and superior colliculus responses to optical expansion in adults. Further, the neural network's responses to naturalistic video clips predict self-reported emotion largely by way of subjective arousal. These findings illustrate how a simple neural network architecture optimized for a species-general task relevant for survival explains motor and experiential components of human emotion.

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.

Biological aging of two innate behaviors of Drosophila melanogaster: Escape climbing versus courtship learning and memory

Motor and cognitive aging can severely affect life quality of elderly people and burden health care systems. In search for diagnostic behavioral biomarkers, it has been suggested that walking speed can predict forms of cognitive decline, but in humans, it remains challenging to separate the effects of biological aging and lifestyle. We examined a possible association of motor and cognitive decline in Drosophila, a genetic model organism of healthy aging. Long term courtship memory is present in young male flies but absent already during mid life (4-8 weeks). By contrast, courtship learning index and short term memory (STM) are surprisingly robust and remain stable through mid (4-8 weeks) and healthy late life (>8 weeks), until courtship performance collapses suddenly at ~4.5 days prior to death. By contrast, climbing speed declines gradually during late life (>8 weeks). The collapse of courtship performance and short term memory close to the end of life occur later and progress with a different time course than the gradual late life decline in climbing speed. Thus, during healthy aging in male Drosophila, climbing and courtship motor behaviors decline differentially. Moreover, cognitive and motor performances decline at different time courses. Differential behavioral decline during aging may indicate different underlying causes, or alternatively, a common cause but different thresholds for defects in different behaviors.

Environmental impact on visual perception modulates behavioral responses of schooling fish to looming predators

Aggregation in social fishes has evolved to improve safety from predators. The individual interaction mechanisms that govern collective behavior are determined by the sensory systems that translate environmental information into behavior. In dynamic environments, shifts in conditions impede effective visual sensory perception in fish schools, and may induce changes in the collective response. Here, we consider whether environmental conditions that affect visual contrast modulate the collective response of schools to looming predators. By using a virtual environment to simulate four contrast levels, we tested whether the collective state of minnow fish schools was modified in response to a looming optical stimulus. Our results indicate that fish swam slower and were less polarized in lower contrast conditions. Additionally, schooling metrics known to be regulated by non-visual sensory systems tended to correlate better when contrast decreased. Over the course of the escape response, schools remained tightly formed and retained the capability of transferring social information. We propose that when visual perception is compromised, the interaction rules governing collective behavior are likely to be modified to prioritize ancillary sensory information crucial to maximizing chance of escape. Our results imply that multiple sensory systems can integrate to control collective behavior in environments with unreliable visual information.

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.

Threatening stimuli elicit a sequential cardiac pattern in arthropods

In order to cope with the challenges of living in dynamic environments, animals rapidly adjust their behaviors in coordination with different physiological responses. Here, we studied whether threatening visual stimuli evoke different heart rate patterns in arthropods and whether these patterns are related with defensive behaviors. We identified two sequential phases of crab's cardiac response that occur with a similar timescale to that of the motor arrest and later escape response. The first phase was modulated by low salience stimuli and persisted throughout spaced stimulus presentation. The second phase was modulated by high-contrast stimuli and reduced by repetitive stimulus presentation. The overall correspondence between cardiac and motor responses suggests that the first cardiac response phase might be related to motor arrest while the second to the escape response. We show that in the face of threat arthropods coordinate their behavior and cardiac activity in a rapid and flexible manner.

Visual looming is a primitive for human emotion

Looming objects afford threat of collision across the animal kingdom. Defensive responses to looming and neural computations for looming detection are strikingly conserved across species. In mammals, information about rapidly approaching threats is conveyed from the retina to the midbrain superior colliculus, where variables that indicate the position and velocity of approach are computed to enable defensive behavior. Although neuroscientific theories posit that midbrain representations contribute to emotion through connectivity with distributed brain systems, it remains unknown whether a computational system for looming detection can predict both defensive behavior and phenomenal experience in humans. Here, we show that a shallow convolutional neural network based on the Drosophila visual system predicts defensive blinking to looming objects in infants and superior colliculus responses to optical expansion in adults. Further, the responses of the convolutional network to a broad array of naturalistic video clips predict self-reported emotion largely on the basis of subjective arousal. Our findings illustrate how motor and experiential components of human emotion relate to species-general systems for survival in unpredictable environments.

How Flies See Motion

How neurons detect the direction of motion is a prime example of neural computation: Motion vision is found in the visual systems of virtually all sighted animals, it is important for survival, and it requires interesting computations with well-defined linear and nonlinear processing steps-yet the whole process is of moderate complexity. The genetic methods available in the fruit fly Drosophila and the charting of a connectome of its visual system have led to rapid progress and unprecedented detail in our understanding of how neurons compute the direction of motion in this organism. The picture that emerged incorporates not only the identity, morphology, and synaptic connectivity of each neuron involved but also its neurotransmitters, its receptors, and their subcellular localization. Together with the neurons' membrane potential responses to visual stimulation, this information provides the basis for a biophysically realistic model of the circuit that computes the direction of visual motion.

Integrating sensory ecology and predator-prey theory to understand animal responses to fire

Fire regimes are changing dramatically worldwide due to climate change, habitat conversion, and the suppression of Indigenous landscape management. Although there has been extensive work on plant responses to fire, including their adaptations to withstand fire and long-term effects of fire on plant communities, less is known about animal responses to fire. Ecologists lack a conceptual framework for understanding behavioural responses to fire, which can hinder wildlife conservation and management. Here, we integrate cue-response sensory ecology and predator-prey theory to predict and explain variation in if, when and how animals react to approaching fire. Inspired by the literature on prey responses to predation risk, this framework considers both fire-naïve and fire-adapted animals and follows three key steps: vigilance, cue detection and response. We draw from theory on vigilance tradeoffs, signal detection, speed-accuracy tradeoffs, fear generalization, neophobia and adaptive dispersal. We discuss how evolutionary history with fire, but also other selective pressures, such as predation risk, should influence animal behavioural responses to fire. We conclude by providing guidance for empiricists and outlining potential conservation applications.

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.

Recording central nervous system responses of freely-swimming marine and freshwater fishes with a customizable, implantable AC differential amplifier

BACKGROUND

Fish have adapted to a diversity of environments but the neural mechanisms underlying natural aquatic behaviors are not well known.

NEW METHOD

We have developed a small, customizable AC differential amplifier and surgical procedures for recording multi-unit extracellular signals in the CNS of marine and freshwater fishes.

RESULTS

Our minimally invasive amplifier allowed fish to orient to flow and respond to hydrodynamic and visual stimuli. We recorded activity in the cerebellum during these behaviors.

COMPARISON WITH EXISTING METHODS

Our system is very low-cost, hydrodynamically streamlined, and capable of high-gain in order to allow for recordings from freely behaving, fast fishes in complex fluid environments.

CONCLUSIONS

Our tethered approach allows access to record neural activity in a diversity of adult fishes in the lab, but can also be modified for data logging in the field.

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.

Animal behavior: Timing escape on angular size or angular velocity?

Animals avoid rapidly approaching objects. In many arthropods, angular size is a common visual cue used to decide the time of avoidance. A new study shows that fiddler crabs decide when to escape based on object angular expansion velocity.

Center-surround interactions underlie bipolar cell motion sensitivity in the mouse retina

Motion sensing is a critical aspect of vision. We studied the representation of motion in mouse retinal bipolar cells and found that some bipolar cells are radially direction selective, preferring the origin of small object motion trajectories. Using a glutamate sensor, we directly observed bipolar cells synaptic output and found that there are radial direction selective and non-selective bipolar cell types, the majority being selective, and that radial direction selectivity relies on properties of the center-surround receptive field. We used these bipolar cell receptive fields along with connectomics to design biophysical models of downstream cells. The models and additional experiments demonstrated that bipolar cells pass radial direction selective excitation to starburst amacrine cells, which contributes to their directional tuning. As bipolar cells provide excitation to most amacrine and ganglion cells, their radial direction selectivity may contribute to motion processing throughout the visual system.

Feature encoding: How back-to-front motion guides the polite fly

Motion of a visual image from back-to-front across a visual field can provide an early-stage cue for impending collisions. A new study reveals visual feature encoding neurons that drive behavioral responses to back-to-front motion in the fly Drosophila melanogaster.

Neural mechanisms to exploit positional geometry for collision avoidance

Visual motion provides rich geometrical cues about the three-dimensional configuration of the world. However, how brains decode the spatial information carried by motion signals remains poorly understood. Here, we study a collision-avoidance behavior in Drosophila as a simple model of motion-based spatial vision. With simulations and psychophysics, we demonstrate that walking Drosophila exhibit a pattern of slowing to avoid collisions by exploiting the geometry of positional changes of objects on near-collision courses. This behavior requires the visual neuron LPLC1, whose tuning mirrors the behavior and whose activity drives slowing. LPLC1 pools inputs from object and motion detectors, and spatially biased inhibition tunes it to the geometry of collisions. Connectomic analyses identified circuitry downstream of LPLC1 that faithfully inherits its response properties. Overall, our results reveal how a small neural circuit solves a specific spatial vision task by combining distinct visual features to exploit universal geometrical constraints of the visual world.

Feature Detection by Retinal Ganglion Cells

Retinal circuits transform the pixel representation of photoreceptors into the feature representations of ganglion cells, whose axons transmit these representations to the brain. Functional, morphological, and transcriptomic surveys have identified more than 40 retinal ganglion cell (RGC) types in mice. RGCs extract features of varying complexity; some simply signal local differences in brightness (i.e., luminance contrast), whereas others detect specific motion trajectories. To understand the retina, we need to know how retinal circuits give rise to the diverse RGC feature representations. A catalog of the RGC feature set, in turn, is fundamental to understanding visual processing in the brain. Anterograde tracing indicates that RGCs innervate more than 50 areas in the mouse brain. Current maps connecting RGC types to brain areas are rudimentary, as is our understanding of how retinal signals are transformed downstream to guide behavior. In this article, I review the feature selectivities of mouse RGCs, how they arise, and how they are utilized downstream. Not only is knowledge of the behavioral purpose of RGC signals critical for understanding the retinal contributions to vision; it can also guide us to the most relevant areas of visual feature space. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Avoiding obstacles while intercepting a moving target: a miniature fly's solution

The miniature robber fly Holcocephala fusca intercepts its targets with behaviour that is approximated by the proportional navigation guidance law. During predatory trials, we challenged the interception of H. fusca performance by placing a large object in its potential flight path. In response, H. fusca deviated from the path predicted by pure proportional navigation, but in many cases still eventually contacted the target. We show that such flight deviations can be explained as the output of two competing navigational systems: pure-proportional navigation and a simple obstacle avoidance algorithm. Obstacle avoidance by H. fusca is here described by a simple feedback loop that uses the visual expansion of the approaching obstacle to mediate the magnitude of the turning-away response. We name the integration of this steering law with proportional navigation 'combined guidance'. The results demonstrate that predatory intent does not operate a monopoly on the fly's steering when attacking a target, and that simple guidance combinations can explain obstacle avoidance during interceptive tasks.

Shallow neural networks trained to detect collisions recover features of visual loom-selective neurons

Animals have evolved sophisticated visual circuits to solve a vital inference problem: detecting whether or not a visual signal corresponds to an object on a collision course. Such events are detected by specific circuits sensitive to visual looming, or objects increasing in size. Various computational models have been developed for these circuits, but how the collision-detection inference problem itself shapes the computational structures of these circuits remains unknown. Here, inspired by the distinctive structures of LPLC2 neurons in the visual system of Drosophila, we build anatomically-constrained shallow neural network models and train them to identify visual signals that correspond to impending collisions. Surprisingly, the optimization arrives at two distinct, opposing solutions, only one of which matches the actual dendritic weighting of LPLC2 neurons. Both solutions can solve the inference problem with high accuracy when the population size is large enough. The LPLC2-like solutions reproduces experimentally observed LPLC2 neuron responses for many stimuli, and reproduces canonical tuning of loom sensitive neurons, even though the models are never trained on neural data. Thus, LPLC2 neuron properties and tuning are predicted by optimizing an anatomically-constrained neural network to detect impending collisions. More generally, these results illustrate how optimizing inference tasks that are important for an animal's perceptual goals can reveal and explain computational properties of specific sensory neurons.

Action selection based on multiple-stimulus aspects in wind-elicited escape behavior of crickets

Escape behavior is essential for animals to avoid attacks by predators. In some species, multiple escape responses could be employed. However, it remains unknown what aspects of threat stimuli affect the choice of an escape response. We focused on two distinct escape responses (running and jumping) to short airflow in crickets and examined the effects of multiple stimulus aspects including the angle, velocity, and duration on the choice between these responses. The faster and longer the airflow, the more frequently the crickets jumped. This meant that the choice of an escape response depends on both the velocity and duration of the stimulus and suggests that the neural basis for choosing an escape response includes the integration process of multiple stimulus parameters. In addition, the moving speed and distance changed depending on the stimulus velocity and duration for running but not for jumping. Running away would be more adaptive escape behavior.

Should I stay or should I go? A thalamic circuit for modulating behavioral responses to visual threat

In this issue of Neuron and in Cell Reports, Fratzl et al. (2021) and Salay and Huberman (2021) identify the ventral lateral geniculate nucleus (vLGN) of the thalamus as a key regulator for adjusting defensive behaviors according to the level of perceived visual threat.

Flexible inhibitory control of visually evoked defensive behavior by the ventral lateral geniculate nucleus

Animals can choose to act upon, or to ignore, sensory stimuli, depending on circumstance and prior knowledge. This flexibility is thought to depend on neural inhibition, through suppression of inappropriate and disinhibition of appropriate actions. Here, we identified the ventral lateral geniculate nucleus (vLGN), an inhibitory prethalamic area, as a critical node for control of visually evoked defensive responses in mice. The activity of vLGN projections to the medial superior colliculus (mSC) is modulated by previous experience of threatening stimuli, tracks the perceived threat level in the environment, and is low prior to escape from a visual threat. Optogenetic stimulation of the vLGN abolishes escape responses, and suppressing its activity lowers the threshold for escape and increases risk-avoidance behavior. The vLGN most strongly affects visual threat responses, potentially via modality-specific inhibition of mSC circuits. Thus, inhibitory vLGN circuits control defensive behavior, depending on an animal’s prior experience and its anticipation of danger in the environment.

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Activity of vLGN axons in the mSC reflects the previous experience of threat

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The vLGN bidirectionally controls escape from visual threat

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Activating the vLGN specifically reduces the activity of visual units in mSC

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Activating vLGN axons in the mSC specifically suppresses escape from visual threat

An Algorithmic Approach to Natural Behavior

Uncovering the mechanisms and implications of natural behavior is a goal that unites many fields of biology. Yet, the diversity, flexibility, and multi-scale nature of these behaviors often make understanding elusive. Here, we review studies of animal pursuit and evasion - two special classes of behavior where theory-driven experiments and new modeling techniques are beginning to uncover the general control principles underlying natural behavior. A key finding of these studies is that intricate sequences of pursuit and evasion behavior can often be constructed through simple, repeatable rules that link sensory input to motor output: we refer to these rules as behavioral algorithms. Identifying and mathematically characterizing these algorithms has led to important insights, including the discovery of guidance rules that attacking predators use to intercept mobile prey, and coordinated neural and biomechanical mechanisms that animals use to avoid impending collisions. Here, we argue that algorithms provide a good starting point for studies of natural behavior more generally. Rather than beginning at the neural or ecological levels of organization, we advocate starting in the middle, where the algorithms that link sensory input to behavioral output can provide a solid foundation from which to explore both the implementation and the ecological outcomes of behavior. We review insights that have been gained through such an algorithmic approach to pursuit and evasion behaviors. From these, we synthesize theoretical principles and lay out key modeling tools needed to apply an algorithmic approach to the study of other complex natural behaviors.

The complex synaptic pathways onto a looming-detector neuron revealed using serial block-face scanning electron microscopy

The ability of locusts to detect looming stimuli and avoid collisions or predators depends on a neuronal circuit in the locust's optic lobe. Although comprehensively studied for over three decades, there are still major questions about the computational steps of this circuit. We used fourth instar larvae of Locusta migratoria to describe the connection between the lobula giant movement detector 1 (LGMD1) neuron in the lobula complex and the upstream neuropil, the medulla. Serial block-face scanning electron microscopy (SBEM) was used to characterize the morphology of the connecting neurons termed trans-medullary afferent (TmA) neurons and their synaptic connectivity. This enabled us to trace neurons over several hundred micrometers between the medulla and the lobula complex while identifying their synapses. We traced two different TmA neurons, each from a different individual, from their synapses with the LGMD in the lobula complex up into the medulla and describe their synaptic relationships. There is not a simple downstream transmission of the signal from a lamina neuron onto these TmA neurons; there is also a feedback loop in place with TmA neurons making outputs as well as receiving inputs. More than one type of neuron shapes the signal of the TmA neurons in the medulla. We found both columnar and trans-columnar neurons connected with the traced TmA neurons in the medulla. These findings indicate that there are computational steps in the medulla that have not been included in models of the neuronal pathway for looming detection.

OFF-transient alpha RGCs mediate looming triggered innate defensive response

Animals respond to visual threats, such as a looming object, with innate defensive behaviors. Here, we report that a specific type of retinal ganglion cell (RGC), the OFF-transient alpha RGC, is critical for the detection of looming objects. We identified Kcnip2 as its molecular marker. The activity of the Kcnip2-expressing RGCs encodes the size of the looming object. Ablation or suppression of these RGCs abolished or severely impaired the escape and freezing behaviors of mice in response to a looming object, while activation of their somas in the retina, or their axon terminals in the superior colliculus, triggered immediate escape behavior. Our results link the activity of a single type of RGC to visually triggered innate defensive behaviors and underscore that ethologically significant visual information is encoded by a labeled line strategy as early as in the retina.

A Signaled Locomotor Avoidance Action Is Fully Represented in the Neural Activity of the Midbrain Tegmentum

Animals, including humans, readily learn to avoid harmful and threatening situations by moving in response to cues that predict the threat (e.g., fire alarm, traffic light). During a negatively reinforced sensory-guided locomotor action, known as signaled active avoidance, animals learn to avoid a harmful unconditioned stimulus (US) by moving away when signaled by a harmless conditioned stimulus (CS) that predicts the threat. CaMKII-expressing neurons in the pedunculopontine tegmentum area (PPT) of the midbrain locomotor region have been shown to play a critical role in the expression of this learned behavior, but the activity of these neurons during learned behavior is unknown. Using calcium imaging fiber photometry in freely behaving mice, we show that PPT neurons sharply activate during presentation of the auditory CS that predicts the threat before onset of avoidance movement. PPT neurons activate further during the succeeding CS-driven avoidance movement, or during the faster US-driven escape movement. PPT neuron activation was weak during slow spontaneous movements but correlated sharply with movement speed and, therefore, with the urgency of the behavior. Moreover, using optogenetics, we found that these neurons must discharge during the signaled avoidance interval for naive mice to effectively learn the active avoidance behavior. As an essential hub for signaled active avoidance, neurons in the midbrain tegmentum process the conditioned cue that predicts the threat and discharge sharply relative to the speed or apparent urgency of the avoidance (learned) and escape (innate) responses.SIGNIFICANCE STATEMENT During signaled active avoidance behavior, subjects move away to avoid a threat when directed by an innocuous sensory stimulus. Using imaging methods in freely behaving mice, we found that the activity of neurons in a part of the midbrain, known as the pedunculopontime tegmentum, increases during the presentation of the innocuous sensory stimulus that predicts the threat and also during the expression of the learned behavior as mice move away to avoid the threat. In addition, inhibiting these neurons abolishes the ability of mice to learn the behavior. Thus, neurons in this part of the midbrain code and are essential for signaled active avoidance behavior.

Dendritic and parallel processing of visual threats in the retina control defensive responses

Approaching predators cast expanding shadows (i.e., looming) that elicit innate defensive responses in most animals. Where looming is first detected and how critical parameters of predatory approaches are extracted are unclear. In mice, we identify a retinal interneuron (the VG3 amacrine cell) that responds robustly to looming, but not to related forms of motion. Looming-sensitive calcium transients are restricted to a specific layer of the VG3 dendrite arbor, which provides glutamatergic input to two ganglion cells (W3 and OFFα). These projection neurons combine shared excitation with dissimilar inhibition to signal approach onset and speed, respectively. Removal of VG3 amacrine cells reduces the excitation of W3 and OFFα ganglion cells and diminishes defensive responses of mice to looming without affecting other visual behaviors. Thus, the dendrites of a retinal interneuron detect visual threats, divergent circuits downstream extract critical threat parameters, and these retinal computations initiate an innate survival behavior.

Evolutionary and homeostatic changes in morphology of visual dendrites of Mauthner cells in Astyanax blind cavefish

Mauthner cells are the largest neurons in the hindbrain of teleost fish and most amphibians. Each cell has two major dendrites thought to receive segregated streams of sensory input: the lateral dendrite receives mechanosensory input while the ventral dendrite receives visual input. These inputs, which mediate escape responses to sudden stimuli, may be modulated by the availability of sensory information to the animal. To understand the impact of the absence of visual information on the morphologies of Mauthner cells during developmental and evolutionary time scales, we examined the teleost Astyanax mexicanus. This species of tetra is found in two morphs: a seeing surface fish and a blind cavefish. We compared the structure of Mauthner cells in surface fish raised under daily light conditions, in surface fish raised in constant darkness, and in two independent lineages of cave populations. The length of ventral dendrites of Mauthner cells in dark-raised surface fish larvae were longer and more branched, while in both cave morphs the ventral dendrites were smaller or absent. The absence of visual input in surface fish with normal eye development leads to a homeostatic increase in dendrite size, whereas over evolution, the absence of light led to the loss of eyes and a reduction in dendrite size.

Behavioral and neuronal underpinnings of safety in numbers in fruit flies

Living in a group allows individuals to decrease their defenses, enabling other beneficial behaviors such as foraging. The detection of a threat through social cues is widely reported, however, the safety cues that guide animals to break away from a defensive behavior and resume alternate activities remain elusive. Here we show that fruit flies display a graded decrease in freezing behavior, triggered by an inescapable threat, with increasing group sizes. Furthermore, flies use the cessation of movement of other flies as a cue of threat and its resumption as a cue of safety. Finally, we find that lobula columnar neurons, LC11, mediate the propensity for freezing flies to resume moving in response to the movement of others. By identifying visual motion cues, and the neurons involved in their processing, as the basis of a social safety cue this study brings new insights into the neuronal basis of safety in numbers.

The Neural Basis of Escape Behavior in Vertebrates

Escape is one of the most studied animal behaviors, and there is a rich normative theory that links threat properties to evasive actions and their timing. The behavioral principles of escape are evolutionarily conserved and rely on elementary computational steps such as classifying sensory stimuli and executing appropriate movements. These are common building blocks of general adaptive behaviors. Here we consider the computational challenges required for escape behaviors to be implemented, discuss possible algorithmic solutions, and review some of the underlying neural circuits and mechanisms. We outline shared neural principles that can be implemented by evolutionarily ancient neural systems to generate escape behavior, to which cortical encephalization has been added to allow for increased sophistication and flexibility in responding to threat.

Predator-induced stress responses in insects: A review

Predators can induce extreme stress and profound physiological responses in prey. Insects are the most dominant animal group on Earth and serve as prey for many different predators. Although insects have an extraordinary diversity of anti-predator behavioral and physiological responses, predator-induced stress has not been studied extensively in insects, especially at the molecular level. Here, we review the existing literature on physiological predator-induced stress responses in insects and compare what is known about insect stress to vertebrate stress systems. We conclude that many unrelated insects share a baseline pathway of predator-induced stress responses that we refer to as the octopamine-adipokinetic hormone (OAH) axis. We also present best practices for studying predator-induced stress responses in prey insects. We encourage investigators to compare neurophysiological responses to predator-related stress at the organismal, neurohormonal, tissue, and cellular levels within and across taxonomic groups. Studying stress-response variation between ecological contexts and across taxonomic levels will enable the field to build a holistic understanding of, and distinction between, taxon- and stimulus-specific responses relative to universal stress responses.

Visual determinants of prey chasing behavior in a mudflat crab

The crab Neohelice granulata inhabits mudflats where it is preyed upon by gulls and, conversely, preys on smaller crabs. Therefore, on seeing moving stimuli, this crab can behave as prey or predator. The crab escape response to visual stimuli has been extensively investigated from the behavioral to the neuronal level. The predatory response (PR), however, has not yet been explored. Here, we show that this response can be reliably elicited and investigated in a laboratory arena. By using dummies of three different sizes moved on the ground at three different velocities over multiple trials, we identified important stimulation conditions that boost the occurrence of PR and its chances of ending in successful prey capture. PR probability was sustained during the first 10 trials of our experiments but then declined. PR was elicited with high probability by the medium size dummy, less effectively by the small dummy, and hardly brought about by the large dummy, which mostly elicited avoidance responses. A GLMM analysis indicated that the dummy size and the tracking line distance were two strong determinants for eliciting PR. The rate of successful captures, however, mainly depended on the dummy velocity. Our results suggest that crabs are capable of assessing the distance to the dummy and its absolute size. The PR characterized here, in connection with the substantial knowledge of the visual processing associated with the escape response, provides excellent opportunities for comparative analyses of the organization of two distinct visually guided behaviors in a single animal.

Antagonistic Inhibitory Circuits Integrate Visual and Gravitactic Behaviors

Larvae of the tunicate Ciona intestinalis possess a central nervous system of 177 neurons. This simplicity has facilitated the generation of a complete synaptic connectome. As chordates and the closest relatives of vertebrates, tunicates promise insight into the organization and evolution of vertebrate nervous systems. Ciona larvae have several sensory systems, including the ocellus and otolith, which are sensitive to light and gravity, respectively. Here, we describe circuitry by which these two are integrated into a complex behavior: the rapid reorientation of the body followed by upward swimming in response to dimming. Significantly, the gravity response causes an orienting behavior consisting of curved swims in downward-facing larvae but only when triggered by dimming. In contrast, the majority of larvae facing upward do not respond to dimming with orientation swims-but instead swim directly upward. Under constant light conditions, the gravity circuit appears to be inoperable, and both upward and downward swims were observed. Using connectomic and neurotransmitter data, we propose a circuit model that can account for these behaviors. The otolith consists of a statocyst cell and projecting excitatory sensory neurons (antenna cells). Postsynaptic to the antenna cells are a group of inhibitory primary interneurons, the antenna relay neurons (antRNs), which then project asymmetrically to the right and left motor units, thereby mediating curved orientation swims. Also projecting to the antRNs are inhibitory photoreceptor relay interneurons. These interneurons appear to antagonize the otolith circuit until they themselves are inhibited by photoreceptors in response to dimming, thus providing a triggering circuit.

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.

Neural dynamics of emotion and cognition: From trajectories to underlying neural geometry

How can we study, characterize, and understand the neural underpinnings of cognitive-emotional behaviors as inherently dynamic processes? In the past 50 years, Stephen Grossberg has developed a research program that embraces the themes of dynamics, decentralized computation, emergence, selection and competition, and autonomy. The present paper discusses how these principles can be heeded by experimental scientists to advance the understanding of the brain basis of behavior. It is suggested that a profitable way forward is to focus on investigating the dynamic multivariate structure of brain data. Accordingly, central research problems involve characterizing "neural trajectories" and the associated geometry of the underlying "neural space." Finally, it is argued that, at a time when the development of neurotechniques has reached a fever pitch, neuroscience needs to redirect its focus and invest comparable energy in the conceptual and theoretical dimensions of its research endeavor. Otherwise we run the risk of being able to measure "every atom" in the brain in a theoretical vacuum.

Conserved behavioral circuits govern high-speed decision-making in wild fish shoals

To evade their predators, animals must quickly detect potential threats, gauge risk, and mount a response. Putative neural circuits responsible for these tasks have been isolated in laboratory studies. However, it is unclear whether and how these circuits combine to generate the flexible, dynamic sequences of evasion behavior exhibited by wild, freely moving animals. Here, we report that evasion behavior of wild fish on a coral reef is generated through a sequence of well-defined decision rules that convert visual sensory input into behavioral actions. Using an automated system to present visual threat stimuli to fish in situ, we show that individuals initiate escape maneuvers in response to the perceived size and expansion rate of an oncoming threat using a decision rule that matches dynamics of known loom-sensitive neural circuits. After initiating an evasion maneuver, fish adjust their trajectories using a control rule based on visual feedback to steer away from the threat and toward shelter. These decision rules accurately describe evasion behavior of fish from phylogenetically distant families, illustrating the conserved nature of escape decision-making. Our results reveal how the flexible behavioral responses required for survival can emerge from relatively simple, conserved decision-making mechanisms.

Luminance Changes Drive Directional Startle through a Thalamic Pathway

Looming visual stimuli result in escape responses that are conserved from insects to humans. Despite their importance for survival, the circuits mediating visual startle have only recently been explored in vertebrates. Here we show that the zebrafish thalamus is a luminance detector critical to visual escape. Thalamic projection neurons deliver dim-specific information to the optic tectum, and ablations of these projections disrupt normal tectal responses to looms. Without this information, larvae are less likely to escape from dark looming stimuli and lose the ability to escape away from the source of the loom. Remarkably, when paired with an isoluminant loom stimulus to the opposite eye, dimming is sufficient to increase startle probability and to reverse the direction of the escape so that it is toward the loom. We suggest that bilateral comparisons of luminance, relayed from the thalamus to the tectum, facilitate escape responses and are essential for their directionality.

Emotion and the Interactive Brain: Insights From Comparative Neuroanatomy and Complex Systems

Although emotion is closely associated with motivation, and interacts with perception, cognition, and action, many conceptualizations still treat emotion as separate from these domains. Here, a comparative/evolutionary anatomy framework is presented to motivate the idea that long-range, distributed circuits involving the midbrain, thalamus, and forebrain are central to emotional processing. It is proposed that emotion can be understood in terms of large-scale network interactions spanning the neuroaxis that form "functionally integrated systems." At the broadest level, the argument is made that we need to move beyond a Newtonian view of causation to one involving complex systems where bidirectional influences and nonlinearities abound. Therefore, understanding interactions between subsystems and signal integration becomes central to unraveling the organization of the emotional brain.

Photoreceptor specialization and the visuomotor repertoire of the primitive chordate Ciona

The swimming tadpole larva of Ciona has one of the simplest central nervous systems (CNSs) known, with only 177 neurons. Despite its simplicity, the Ciona CNS has a common structure with the CNS of its close chordate relatives, the vertebrates. The recent completion of a larval Ciona CNS connectome creates enormous potential for detailed understanding of chordate CNS function, yet our understanding of Ciona larval behavior is incomplete. We show here that Ciona larvae have a surprisingly rich and dynamic set of visual responses, including a looming-object escape behavior characterized by erratic circular swims, as well as negative phototaxis characterized by sustained directional swims. Making use of mutant lines, we show that these two behaviors are mediated by distinct groups of photoreceptors. The Ciona connectome predicts that these two behavioral responses should act through distinct, but overlapping, visuomotor pathways, and that the escape behavior is likely to be integrated into a broader startle behavior.

Divergent midbrain circuits orchestrate escape and freezing responses to looming stimuli in mice

Animals respond to environmental threats, e.g. looming visual stimuli, with innate defensive behaviors such as escape and freezing. The key neural circuits that participate in the generation of such dimorphic defensive behaviors remain unclear. Here we show that the dimorphic behavioral patterns triggered by looming visual stimuli are mediated by parvalbumin-positive (PV⁺) projection neurons in mouse superior colliculus (SC). Two distinct groups of SC PV⁺ neurons form divergent pathways to transmit threat-relevant visual signals to neurons in the parabigeminal nucleus (PBGN) and lateral posterior thalamic nucleus (LPTN). Activations of PV⁺ SC-PBGN and SC-LPTN pathways mimic the dimorphic defensive behaviors. The PBGN and LPTN neurons are co-activated by looming visual stimuli. Bilateral inactivation of either nucleus results in the defensive behavior dominated by the other nucleus. Together, these data suggest that the SC orchestrates dimorphic defensive behaviors through two separate tectofugal pathways that may have interactions.

In response to environmental threats, such as visual looming stimuli, mice either freeze or escape. Here the authors demonstrate that these two behaviors are mediated by separate tectofugal pathways formed by parvalbumin-positive neurons in the superior colliculus.

Ultra-selective looming detection from radial motion opponency

Nervous systems combine lower-level sensory signals to detect higher order stimulus features critical to survival^1–3, such as the visual looming motion created by an imminent collision or approaching predator⁴. Looming-sensitive neurons have been identified in diverse animal species^5–9. Different large-scale visual features such as looming often share local cues, which means loom-detecting neurons face the challenge of rejecting confounding stimuli. Here we report the discovery of an ultra-selective looming detecting neuron, LPLC2¹⁰ in Drosophila, and show how its selectivity is established by radial motion opponency. In the fly visual system, directionally-selective small-field neurons called T4 and T5 form a spatial map in the lobula plate, where they each terminate in one of four retinotopic layers, such that each layer responds to motion in a different cardinal direction^11–13. Single cell anatomical analysis reveals that each arm of LPLC2’s cross-shaped primary dendrites ramifies in one of these layers and extends along that layer’s preferred motion direction. In vivo calcium imaging demonstrates that, as their shape predicts, individual LPLC2 neurons respond strongly to outward motion emanating from the center of the neuron’s receptive field. Each dendritic arm also receives local inhibitory inputs directionally selective for inward motion opposing the excitation. This radial motion opponency generates a balance of excitation and inhibition that makes LPLC2 non-responsive to related patterns of motion such as contraction, wide-field translation, or luminance change. As a population, LPLC2 neurons densely cover visual space and terminate onto the giant fiber descending neurons, which drive the jump muscle motoneuron to trigger an escape takeoff. Our findings provide a mechanistic description of the selective feature detection that flies use to discern and escape looming threats.

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.

The predator and prey behaviors of crabs: from ecology to neural adaptations

Predator avoidance and prey capture are among the most vital of animal behaviors. They require fast reactions controlled by comparatively straightforward neural circuits often containing giant neurons, which facilitates their study with electrophysiological techniques. Naturally occurring avoidance behaviors, in particular, can be easily and reliably evoked in the laboratory, enabling their neurophysiological investigation. Studies in the laboratory alone, however, can lead to a biased interpretation of an animal's behavior in its natural environment. In this Review, we describe current knowledge – acquired through both laboratory and field studies – on the visually guided escape behavior of the crab Neohelice granulata. Analyses of the behavioral responses to visual stimuli in the laboratory have revealed the main characteristics of the crab's performance, such as the continuous regulation of the speed and direction of the escape run, or the enduring changes in the strength of escape induced by learning and memory. This work, in combination with neuroanatomical and electrophysiological studies, has allowed the identification of various giant neurons, the activity of which reflects most essential aspects of the crabs' avoidance performance. In addition, behavioral analyses performed in the natural environment reveal a more complex picture: crabs make use of much more information than is usually available in laboratory studies. Moreover, field studies have led to the discovery of a robust visually guided chasing behavior in Neohelice. Here, we describe similarities and differences in the results obtained between the field and the laboratory, discuss the sources of any differences and highlight the importance of combining the two approaches.

Spatial Memory: Mice Quickly Learn a Safe Haven

New work on innate escape behavior shows that mice spontaneously form a spatially precise memory of the location of shelter, which is laid down quickly and updated continuously.

A retinoraphe projection regulates serotonergic activity and looming-evoked defensive behaviour

Animals promote their survival by avoiding rapidly approaching objects that indicate threats. In mice, looming-evoked defensive responses are triggered by the superior colliculus (SC) which receives direct retinal inputs. However, the specific neural circuits that begin in the retina and mediate this important behaviour remain unclear. Here we identify a subset of retinal ganglion cells (RGCs) that controls mouse looming-evoked defensive responses through axonal collaterals to the dorsal raphe nucleus (DRN) and SC. Looming signals transmitted by DRN-projecting RGCs activate DRN GABAergic neurons that in turn inhibit serotoninergic neurons. Moreover, activation of DRN serotoninergic neurons reduces looming-evoked defensive behaviours. Thus, a dedicated population of RGCs signals rapidly approaching visual threats and their input to the DRN controls a serotonergic self-gating mechanism that regulates innate defensive responses. Our study provides new insights into how the DRN and SC work in concert to extract and translate visual threats into defensive behavioural responses.