Neural Circuits Underlying Visually Evoked Escapes in Larval Zebrafish

Understanding collective behavior through neurobiology

A variety of organisms exhibit collective movement, including schooling fish and flocking birds, where coordinated behavior emerges from the interactions between group members. Despite the prevalence of collective movement in nature, little is known about the neural mechanisms producing each individual's behavior within the group. Here we discuss how a neurobiological approach can enrich our understanding of collective behavior by determining the mechanisms by which individuals interact. We provide examples of sensory systems for social communication during collective movement, highlight recent discoveries about neural systems for detecting the position and actions of social partners, and discuss opportunities for future research. Understanding the neurobiology of collective behavior can provide insight into how nervous systems function in a dynamic social world.

Brain Mechanisms Underlying Panic Attack and Panic Disorder

Panic disorder is a psychiatric disorder characterized by recurrent panic attacks, with a prevalence of ~ 4% in the general population, causing heavy personal and socioeconomic burdens. The similarities of animal defense responses to clinical panic attack symptoms in humans make it possible to translate neuroanatomical pathways identified in animal studies to panic disorder in humans. Therefore, in this review we first present a basic overview of panic disorder in humans including the main subtypes, models commonly used to trigger panic attacks, related hypotheses, the neurotransmitter systems that may be involved, and the current clinical treatments to give the reader a comprehensive understanding of panic disorder. The animal section introduces the models that trigger panic-like behavior in animals and the brain regions that may be involved, providing insights for future elucidation of the neural circuit mechanisms behind panic attacks.

Automated escape system: identifying prey's kinematic and behavioral features critical for predator evasion

Identifying the kinematic and behavioral variables of prey that influence evasion from predator attacks remains challenging. To address this challenge, we have developed an automated escape system that responds quickly to an approaching predator and pulls the prey away from the predator rapidly, similar to real prey. Reaction distance, response latency, escape speed and other variables can be adjusted in the system. By repeatedly measuring the response latency and escape speed of the system, we demonstrated the system's ability to exhibit fast and rapid responses while maintaining consistency across successive trials. Using the live predatory fish species Coreoperca kawamebari, we show that escape speed and reaction distance significantly affect the outcome of predator-prey interactions. These findings indicate that the developed escape system is useful for identifying kinematic and behavioral features of prey that are critical for predator evasion, as well as for measuring the performance of predators.

Real-time analysis of large-scale neuronal imaging enables closed-loop investigation of neural dynamics

Large-scale imaging of neuronal activities is crucial for understanding brain functions. However, it is challenging to analyze large-scale imaging data in real time, preventing closed-loop investigation of neural circuitry. Here we develop a real-time analysis system with a field programmable gate array-graphics processing unit design for an up to 500-megabyte-per-second image stream. Adapted to whole-brain imaging of awake larval zebrafish, the system timely extracts activity from up to 100,000 neurons and enables closed-loop perturbations of neural dynamics.

The Calmodulin-interacting peptide Pcp4a regulates feeding state-dependent behavioral choice in zebrafish

Animals constantly need to judge the valence of an object in their environment: is it potential food or a threat? The brain makes fundamental decisions on the appropriate behavioral strategy by integrating external information from sensory organs and internal signals related to physiological needs. For example, a hungry animal may take more risks than a satiated one when deciding to approach or avoid an object. Using a proteomic profiling approach, we identified the Calmodulin-interacting peptide Pcp4a as a key regulator of foraging-related decisions. Food intake reduced abundance of protein and mRNA of pcp4a via dopamine D2-like receptor-mediated repression of adenylate cyclase. Accordingly, deleting the pcp4a gene made zebrafish larvae more risk averse in a binary decision assay. Strikingly, neurons in the tectum became less responsive to prey-like visual stimuli in pcp4a mutants, thus biasing the behavior toward avoidance. This study pinpoints a molecular mechanism modulating behavioral choice according to internal state.

Key HPI axis receptors facilitate light adaptive behavior in larval zebrafish

The vertebrate stress response (SR) is mediated by the hypothalamic-pituitary-adrenal (HPA) axis and contributes to generating context appropriate physiological and behavioral changes. Although the HPA axis plays vital roles both in stressful and basal conditions, research has focused on the response under stress. To understand broader roles of the HPA axis in a changing environment, we characterized an adaptive behavior of larval zebrafish during ambient illumination changes. Genetic abrogation of glucocorticoid receptor (nr3c1) decreased basal locomotor activity in light and darkness. Some key HPI axis receptors (mc2r [ACTH receptor], nr3c1), but not nr3c2 (mineralocorticoid receptor), were required to adapt to light more efficiently but became dispensable when longer illumination was provided. Such light adaptation was more efficient in dimmer light. Our findings show that the HPI axis contributes to the SR, facilitating the phasic response and maintaining an adapted basal state, and that certain adaptations occur without HPI axis activity.

Doppler detection triggers instantaneous escape behavior in scanning bats

Animals must instantaneously escape from predators for survival, which requires quick detection of approaching threats. Although the neural mechanisms underlying the perception of looming objects have been extensively studied in the visual system, little is known about their auditory counterparts. Echolocating bats use their auditory senses to perceive not only the soundscape, but also the physical environment through active sensing. Although object movement induces both echo delay changes and Doppler shifts, the actual information required to perceive movement has been unclear. Herein, we addressed this question by playing back phantom echoes mimicking an approaching target to horseshoe bats and found that they relied only on Doppler shifts. This suggests that the bats do not perceive object motion in the spatiotemporal dimension (i.e., positional variation), as in vision, but rather take advantage of acoustic sensing by directly detecting velocity, thereby enabling them to respond instantaneously to approaching threats.

Whole-brain neural substrates of behavioral variability in the larval zebrafish

Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visual-encoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animal's internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brain's remarkable flexibility and robustness.

Effect of a looming visual cue on situation awareness and perceived urgency in response to a takeover request

This study aimed to investigate the effect of a looming visual cue on situation awareness and perceived urgency in response to a takeover request (TOR), and to explore the underlying mechanisms of this effect through three experiments. In Experiment 1, the optimal size and speed of a red disk were determined, which were effective in capturing looming motion and conveying the urgency of the situation. The results indicated that both looming speed and size ratio had significant effects on situation awareness and perceived urgency. In Experiment 2, the effects of looming stimuli were compared with dimming stimuli, and the results showed that the looming visual cue was more effective in promoting perceived urgency and situation awareness. The results also indicated that the looming visual cue attracted more visual attention than the dimming visual cue, in line with previous studies. Experiment 3 utilized a driving simulator to test the effectiveness of the looming visual cue in promoting fast and appropriate responses to TORs in complex driving scenarios. The results showed that the looming visual cue was more effective in promoting perceived urgency and enhancing situation awareness, especially in highly complex driving situations. Overall, the findings suggest that the looming visual cue is a powerful tool for promoting fast and appropriate responses to TORs and enhancing situation awareness, particularly in complex driving scenarios. These results have important implications for designing effective TOR systems and improving driver safety on the road.

Human subcortical pathways automatically detect collision trajectory without attention and awareness

Detecting imminent collisions is essential for survival. Here, we used high-resolution fMRI at 7 Tesla to investigate the role of attention and consciousness for detecting collision trajectory in human subcortical pathways. Healthy participants can precisely discriminate collision from near-miss trajectory of an approaching object, with pupil size change reflecting collision sensitivity. Subcortical pathways from the superior colliculus (SC) to the ventromedial pulvinar (vmPul) and ventral tegmental area (VTA) exhibited collision-sensitive responses even when participants were not paying attention to the looming stimuli. For hemianopic patients with unilateral lesions of the geniculostriate pathway, the ipsilesional SC and VTA showed significant activation to collision stimuli in their scotoma. Furthermore, stronger SC responses predicted better behavioral performance in collision detection even in the absence of awareness. Therefore, human tectofugal pathways could automatically detect collision trajectories without the observers' attention to and awareness of looming stimuli, supporting "blindsight" detection of impending visual threats.

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.

A synaptic corollary discharge signal suppresses midbrain visual processing during saccade-like locomotion

In motor control, the brain not only sends motor commands to the periphery, but also generates concurrent internal signals known as corollary discharge (CD) that influence sensory information processing around the time of movement. CD signals are important for identifying sensory input arising from self-motion and to compensate for it, but the underlying mechanisms remain unclear. Using whole-cell patch clamp recordings from neurons in the zebrafish optic tectum, we discovered an inhibitory synaptic signal, temporally locked to spontaneous and visually driven locomotion. This motor-related inhibition was appropriately timed to counteract visually driven excitatory input arising from the fish's own motion, and transiently suppressed tectal spiking activity. High-resolution calcium imaging revealed localized motor-related signals in the tectal neuropil and the upstream torus longitudinalis, suggesting that CD enters the tectum via this pathway. Together, our results show how visual processing is suppressed during self-motion by motor-related phasic inhibition. This may help explain perceptual saccadic suppression observed in many species.

Zebrafish Models of Rare Neurological Diseases like Spinocerebellar Ataxias (SCAs): Advantages and Limitations

Spinocerebellar ataxia (SCA) is a heterogeneous group of rare familial neurodegenerative disorders that share the key feature of cerebellar ataxia. Clinical heterogeneity, diverse gene mutations and complex neuropathology pose significant challenges for developing effective disease-modifying therapies in SCAs. Without a deep understanding of the molecular mechanisms involved for each SCA, we cannot succeed in developing targeted therapies. Animal models are our best tool to address these issues and several have been generated to study the pathological conditions of SCAs. Among them, zebrafish (Danio rerio) models are emerging as a powerful tool for in vivo study of SCAs, as well as rapid drug screens. In this review, we will summarize recent progress in using zebrafish to study the pathology of SCAs. We will discuss recent advancements on how zebrafish models can further clarify underlying genetic, neuroanatomical, and behavioral pathogenic mechanisms of disease. We highlight their usefulness in rapid drug discovery and large screens. Finally, we will discuss the advantages and limitations of this in vivo model to develop tailored therapeutic strategies for SCA.

Modular circuit organization for speed control of locomotor movements

Our movements and actions stem from complex processes in the central nervous system. Precise adaptation of locomotor movements is essential for effectively interacting with the environment. To understand the mechanisms underlying these movements, it is crucial to determine the organization of spinal circuits at the level of individual neurons and synapses. This review highlights the insights gained from studying spinal circuits in adult zebrafish and discusses their broader implications for our understanding of locomotor control across species.

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.

Context-dependent hyperactivity in syngap1a and syngap1b zebrafish autism models

Background and Aims

SYNGAP1 disorder is a prevalent genetic form of Autism Spectrum Disorder and Intellectual Disability (ASD/ID) and is caused by de novo or inherited mutations in one copy of the SYNGAP1 gene. In addition to ASD/ID, SYNGAP1 disorder is associated with comorbid symptoms including treatment-resistant-epilepsy, sleep disturbances, and gastrointestinal distress. Mechanistic links between these diverse symptoms and SYNGAP1 variants remain obscure, therefore, our goal was to generate a zebrafish model in which this range of symptoms can be studied.

Methods

We used CRISPR/Cas9 to introduce frameshift mutations in the syngap1a and syngap1b zebrafish duplicates (syngap1ab) and validated these stable models for Syngap1 loss-of-function. Because SYNGAP1 is extensively spliced, we mapped splice variants to the two zebrafish syngap1a and b genes and identified mammalian-like isoforms. We then quantified locomotory behaviors in zebrafish syngap1ab larvae under three conditions that normally evoke different arousal states in wild type larvae: aversive, high-arousal acoustic, medium-arousal dark, and low-arousal light stimuli.

Results

We show that CRISPR/Cas9 indels in zebrafish syngap1a and syngap1b produced loss-of-function alleles at RNA and protein levels. Our analyses of zebrafish Syngap1 isoforms showed that, as in mammals, zebrafish Syngap1 N- and C-termini are extensively spliced. We identified a zebrafish syngap1 α1-like variant that maps exclusively to the syngap1b gene. Quantifying locomotor behaviors showed that syngap1ab larvae are hyperactive compared to wild type but to differing degrees depending on the stimulus. Hyperactivity was most pronounced in low arousal settings, with overall movement increasing with the number of mutant syngap1 alleles.

Conclusions

Our data support mutations in zebrafish syngap1ab as causal for hyperactivity associated with elevated arousal that is especially pronounced in low-arousal environments.

The canonical HPA axis facilitates and maintains light adaptive behavior

The vertebrate stress response (SR) is mediated by the hypothalamic-pituitary-adrenal (HPA) axis and contributes to generating context appropriate physiological and behavioral changes. Although the HPA axis plays vital roles both in stressful and basal conditions, research has focused on the response under stress. To understand broader roles of the HPA axis in a changing environment, we characterized an adaptive behavior of larval zebrafish during ambient illumination changes. The glucocorticoid receptor (nr3c1) was necessary to maintain basal locomotor activity in light and darkness. The HPA axis was required to adapt to light more efficiently but became dispensable when longer illumination was provided. Light adaptation was more efficient in dimmer light and did not require the mineralocorticoid receptor (nr3c2). Our findings show that the HPA axis contributes to the SR at various stages, facilitating the phasic response and maintaining an adapted basal state, and that certain adaptations occur without HPA axis activity.

Optimizing assays of zebrafish larvae swimming performance for drug discovery

INTRODUCTION

Zebrafish larvae are one of the few vertebrates amenable to large-scale drug discovery screens. Larval swimming behavior is often used as an outcome variable and many fields of study have developed assays for evaluating swimming performance. An unintended consequence of this wide interest is that details related to assay methodology and interpretation become scattered across the literature. The aim of this review is to consolidate this information, particularly as it relates to high-throughput approaches.

AREAS COVERED

The authors describe larval swimming behaviors as this forms the basis for understanding their experimentally evoked swimming or spontaneous activity. Next, they detail how swimming activity can serve as an outcome variable, particularly in the multi-well formats used in large-scale screening studies. They also highlight biological and technical factors that can impact the sensitivity and variability of these measurements.

EXPERT OPINION

Careful attention to animal husbandry, experimental design, data acquisition, and interpretation of results can improve screen outcomes by maximizing swimming activity while minimizing intra- and inter-larval variability. The development of more sensitive, quantitative methods of assessing swimming performance that can be incorporated into high-throughput workflows will be important in order to take full advantage of the zebrafish model.

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.

Spinal Basis of Direction Control during Locomotion in Larval Zebrafish

Navigation requires steering and propulsion, but how spinal circuits contribute to direction control during ongoing locomotion is not well understood. Here, we use drifting vertical gratings to evoke directed "fictive" swimming in intact but immobilized larval zebrafish while performing electrophysiological recordings from spinal neurons. We find that directed swimming involves unilateral changes in the duration of motor output and increased recruitment of motor neurons, without impacting the timing of spiking across or along the body. Voltage-clamp recordings from motor neurons reveal increases in phasic excitation and inhibition on the side of the turn. Current-clamp recordings from premotor interneurons that provide phasic excitation or inhibition reveal two types of recruitment patterns. A direction-agnostic pattern with balanced recruitment on the turning and nonturning sides is primarily observed in excitatory V2a neurons with ipsilateral descending axons, while a direction-sensitive pattern with preferential recruitment on the turning side is dominated by V2a neurons with ipsilateral bifurcating axons. Inhibitory V1 neurons are also divided into direction-sensitive and direction-agnostic subsets, although there is no detectable morphologic distinction. Our findings support the modular control of steering and propulsion by spinal premotor circuits, where recruitment of distinct subsets of excitatory and inhibitory interneurons provide adjustments in direction while on the move.SIGNIFICANCE STATEMENT Spinal circuits play an essential role in coordinating movements during locomotion. However, it is unclear how they participate in adjustments in direction that do not interfere with coordination. Here we have developed a system using larval zebrafish that allows us to directly record electrical signals from spinal neurons during "fictive" swimming guided by visual cues. We find there are subsets of spinal interneurons for coordination and others that drive unilateral asymmetries in motor neuron recruitment for direction control. Our findings suggest a modular organization of spinal premotor circuits that enables uninterrupted adjustments in direction during ongoing locomotion.

Neural dynamics and architecture of the heading direction circuit in zebrafish

Animals generate neural representations of their heading direction. Notably, in insects, heading direction is topographically represented by the activity of neurons in the central complex. Although head direction cells have been found in vertebrates, the connectivity that endows them with their properties is unknown. Using volumetric lightsheet imaging, we find a topographical representation of heading direction in a neuronal network in the zebrafish anterior hindbrain, where a sinusoidal bump of activity rotates following directional swims of the fish and is otherwise stable over many seconds. Electron microscopy reconstructions show that, although the cell bodies are located in a dorsal region, these neurons arborize in the interpeduncular nucleus, where reciprocal inhibitory connectivity stabilizes the ring attractor network that encodes heading. These neurons resemble those found in the fly central complex, showing that similar circuit architecture principles may underlie the representation of heading direction across the animal kingdom and paving the way to an unprecedented mechanistic understanding of these networks in vertebrates.

Wild animals suppress the spread of socially transmitted misinformation

Understanding the mechanisms by which information and misinformation spread through groups of individual actors is essential to the prediction of phenomena ranging from coordinated group behaviors to misinformation epidemics. Transmission of information through groups depends on the rules that individuals use to transform the perceived actions of others into their own behaviors. Because it is often not possible to directly infer decision-making strategies in situ, most studies of behavioral spread assume that individuals make decisions by pooling or averaging the actions or behavioral states of neighbors. However, whether individuals may instead adopt more sophisticated strategies that exploit socially transmitted information, while remaining robust to misinformation, is unknown. Here, we study the relationship between individual decision-making and misinformation spread in groups of wild coral reef fish, where misinformation occurs in the form of false alarms that can spread contagiously through groups. Using automated visual field reconstruction of wild animals, we infer the precise sequences of socially transmitted visual stimuli perceived by individuals during decision-making. Our analysis reveals a feature of decision-making essential for controlling misinformation spread: dynamic adjustments in sensitivity to socially transmitted cues. This form of dynamic gain control can be achieved by a simple and biologically widespread decision-making circuit, and it renders individual behavior robust to natural fluctuations in misinformation exposure.

Recurrent network interactions explain tectal response variability and experience-dependent behavior

Response variability is an essential and universal feature of sensory processing and behavior. It arises from fluctuations in the internal state of the brain, which modulate how sensory information is represented and transformed to guide behavioral actions. In part, brain state is shaped by recent network activity, fed back through recurrent connections to modulate neuronal excitability. However, the degree to which these interactions influence response variability and the spatial and temporal scales across which they operate, are poorly understood. Here, we combined population recordings and modeling to gain insights into how neuronal activity modulates network state and thereby impacts visually evoked activity and behavior. First, we performed cellular-resolution calcium imaging of the optic tectum to monitor ongoing activity, the pattern of which is both a cause and consequence of changes in network state. We developed a minimal network model incorporating fast, short range, recurrent excitation and long-lasting, activity-dependent suppression that reproduced a hallmark property of tectal activity - intermittent bursting. We next used the model to estimate the excitability state of tectal neurons based on recent activity history and found that this explained a portion of the trial-to-trial variability in visually evoked responses, as well as spatially selective response adaptation. Moreover, these dynamics also predicted behavioral trends such as selective habituation of visually evoked prey-catching. Overall, we demonstrate that a simple recurrent interaction motif can be used to estimate the effect of activity upon the incidental state of a neural network and account for experience-dependent effects on sensory encoding and visually guided behavior.

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.

Evaluating evasion strategies in zebrafish larvae

An effective evasion strategy allows prey to survive encounters with predators. Prey are generally thought to escape in a direction that is either random or serves to maximize the minimum distance from the predator. Here, we introduce a comprehensive approach to determine the most likely evasion strategy among multiple hypotheses and the role of biomechanical constraints on the escape response of prey fish. Through a consideration of six strategies with sensorimotor noise and previous kinematic measurements, our analysis shows that zebrafish larvae generally escape in a direction orthogonal to the predator's heading. By sensing only the predator's heading, this orthogonal strategy maximizes the distance from fast-moving predators, and, when operating within the biomechanical constraints of the escape response, it provides the best predictions of prey behavior among all alternatives. This work demonstrates a framework for resolving the strategic basis of evasion in predator-prey interactions, which could be applied to a broad diversity of animals.

Evaluating Evasion Strategies in Zebrafish Larvae

An effective evasion strategy allows prey to survive encounters with predators. Prey are generally thought to escape in a direction that is either random or serves to maximize the minimum distance from the predator. Here we introduce a comprehensive approach to determine the most likely evasion strategy among multiple hypotheses and the role of biomechanical constraints on the escape response of prey fish. Through a consideration of six strategies with sensorimotor noise and previous kinematic measurements, our analysis shows that zebrafish larvae generally escape in a direction orthogonal to the predator's heading. By sensing only the predator's heading, this orthogonal strategy maximizes the distance from fast-moving predators, and, when operating within the biomechanical constraints of the escape response, it provides the best predictions of prey behavior among all alternatives. This work demonstrates a framework for resolving the strategic basis of evastion in predator-prey interactions, which could be applied to a broad diversity of animals.

Wolfram syndrome 1b mutation suppresses Mauthner-cell axon regeneration via ER stress signal pathway

Wolfram Syndrome (WS) is a fatal human inherited disease with symptoms of diabetes, vision decreasing, and neurodegeneration caused by mutations in the endoplasmic reticulum (ER)-resident protein WFS1. WFS1 has been reported to play an important role in glucose metabolism. However, the role of WFS1 in axonal regeneration in the central nervous system has so far remained elusive. Herein, we established a model of the wfs1b globally deficient zebrafish line. wfs1b deficiency severely impeded the Mauthner-cell (M-cell) axon regeneration, which was partly dependent on the ER stress response. The administration of ER stress inhibitor 4-Phenylbutyric acid (4-PBA) promoted M-cell axon regeneration in wfs1b^-/- zebrafish larvae, while the ER stress activator Tunicamycin (TM) inhibited M-cell axon regeneration in wfs1b^+/+ zebrafish larvae. Moreover, complementation of wfs1b at the single-cell level stimulated M-cell axon regeneration in the wfs1b^-/- zebrafish larvae. Altogether, our results revealed that wfs1b promotes M-cell axon regeneration through the ER stress signal pathway and provide new evidence for a therapeutic target for WS and axon degeneration.

Male and female mice display consistent lifelong ability to address potential life-threatening cues using different post-threat coping strategies

BACKGROUND

Sex differences ranging from physiological functions to pathological disorders are developmentally hard-wired in a broad range of animals, from invertebrates to humans. These differences ensure that animals can display appropriate behaviors under a variety of circumstances, such as aggression, hunting, sleep, mating, and parental care, which are often thought to be important in the acquisition of resources, including territory, food, and mates. Although there are reports of an absence of sexual dimorphism in the context of innate fear, the question of whether there is sexual dimorphism of innate defensive behavior is still an open question. Therefore, an in-depth investigation to determine whether there are sex differences in developmentally hard-wired innate defensive behaviors in life-threatening circumstances is warranted.

RESULTS

We found that innate defensive behavioral responses to potentially life-threatening stimuli between males and females were indistinguishable over their lifespan. However, by using 3 dimensional (3D)-motion learning framework analysis, we found that males and females showed different behavioral patterns after escaping to the refuge. Specifically, the defensive "freezing" occurred primarily in males, whereas females were more likely to return directly to exploration. Moreover, there were also no estrous phase differences in innate defensive behavioral responses after looming stimuli.

CONCLUSIONS

Our results demonstrate that visually-evoked innate fear behavior is highly conserved throughout the lifespan in both males and females, while specific post-threat coping strategies depend on sex. These findings indicate that innate fear behavior is essential to both sexes and as such, there are no evolutionary-driven sex differences in defensive ability.

Visual object detection biases escape trajectories following acoustic startle in larval zebrafish

In this study, we investigated whether the larval zebrafish is sensitive to the presence of obstacles in its environment. Zebrafish execute fast escape swims when in danger of predation. We posited that collisions with solid objects during escape would be maladaptive to the fish, and therefore, the direction of escape swims should be informed by the locations of barriers. To test this idea, we developed a closed-loop imaging rig outfitted with barriers of various qualities. We show that when larval zebrafish escape in response to a non-directional vibrational stimulus, they use visual scene information to avoid collisions with obstacles. Our study demonstrates that barrier avoidance rate corresponds to the absolute distance of obstacles, as distant barriers outside of collision range elicit less bias than nearby collidable barriers that occupy the same amount of visual field. The computation of barrier avoidance is covert: the fact that fish will avoid barriers during escape cannot be predicted by its routine swimming behavior in the barrier arena. Finally, two-photon laser ablation experiments suggest that excitatory bias is provided to the Mauthner cell ipsilateral to approached barriers, either via direct excitation or a multi-step modulation process. We ultimately propose that zebrafish detect collidable objects via an integrative visual computation that is more complex than retinal occupancy alone, laying a groundwork for understanding how cognitive physical models observed in humans are implemented in an archetypal vertebrate brain. VIDEO ABSTRACT.

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.

Lateral septum modulates cortical state to tune responsivity to threat stimuli

Sudden unexpected environmental changes capture attention and, when perceived as potentially dangerous, evoke defensive behavioral states. Perturbations of the lateral septum (LS) can produce extreme hyperdefensiveness even to innocuous stimuli, but how this structure influences stimulus-evoked defensive responses and threat perception remains unclear. Here, we show that Crhr2-expressing neurons in mouse LS exhibit phasic activation upon detection of threatening but not rewarding stimuli. Threat-stimulus-driven activity predicts the probability but not vigor or type of defensive behavior evoked. Although necessary for and sufficient to potentiate stimulus-triggered defensive responses, LSCrhr2 neurons do not promote specific behaviors. Rather, their stimulation elicits negative valence and physiological arousal. Moreover, LSCrhr2 activity tracks brain state fluctuations and drives cortical activation and rapid awakening in the absence of threat. Together, our findings suggest that LS directs bottom-up modulation of cortical function to evoke preparatory defensive internal states and selectively enhance responsivity to threat-related stimuli.

Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain

Dense reconstruction of synaptic connectivity requires high-resolution electron microscopy images of entire brains and tools to efficiently trace neuronal wires across the volume. To generate such a resource, we sectioned and imaged a larval zebrafish brain by serial block-face electron microscopy at a voxel size of 14 × 14 × 25 nm3. We segmented the resulting dataset with the flood-filling network algorithm, automated the detection of chemical synapses and validated the results by comparisons to transmission electron microscopic images and light-microscopic reconstructions. Neurons and their connections are stored in the form of a queryable and expandable digital address book. We reconstructed a network of 208 neurons involved in visual motion processing, most of them located in the pretectum, which had been functionally characterized in the same specimen by two-photon calcium imaging. Moreover, we mapped all 407 presynaptic and postsynaptic partners of two superficial interneurons in the tectum. The resource developed here serves as a foundation for synaptic-resolution circuit analyses in the zebrafish nervous system.

Larval Zebrafish as a Model for Mechanistic Discovery in Mental Health

Animal models are essential for the discovery of mechanisms and treatments for neuropsychiatric disorders. However, complex mental health disorders such as depression and anxiety are difficult to fully recapitulate in these models. Borrowing from the field of psychiatric genetics, we reiterate the framework of 'endophenotypes' - biological or behavioral markers with cellular, molecular or genetic underpinnings - to reduce complex disorders into measurable behaviors that can be compared across organisms. Zebrafish are popular disease models due to the conserved genetic, physiological and anatomical pathways between zebrafish and humans. Adult zebrafish, which display more sophisticated behaviors and cognition, have long been used to model psychiatric disorders. However, larvae (up to 1 month old) are more numerous and also optically transparent, and hence are particularly suited for high-throughput screening and brain-wide neural circuit imaging. A number of behavioral assays have been developed to quantify neuropsychiatric phenomena in larval zebrafish. Here, we will review these assays and the current knowledge regarding the underlying mechanisms of their behavioral readouts. We will also discuss the existing evidence linking larval zebrafish behavior to specific human behavioral traits and how the endophenotype framework can be applied. Importantly, many of the endophenotypes we review do not solely define a diseased state but could manifest as a spectrum across the general population. As such, we make the case for larval zebrafish as a promising model for extending our understanding of population mental health, and for identifying novel therapeutics and interventions with broad impact.

The “Primitive Brain Dysfunction” Theory of Autism: The Superior Colliculus Role

A better understanding of the pathogenesis of autism will help clarify our conception of the complexity of normal brain development. The crucial deficit may lie in the postnatal changes that vision produces in the brainstem nuclei during early life. The superior colliculus is the primary brainstem visual center. Although difficult to examine in humans with present techniques, it is known to support behaviors essential for every vertebrate to survive, such as the ability to pay attention to relevant stimuli and to produce automatic motor responses based on sensory input. From birth to death, it acts as a brain sentinel that influences basic aspects of our behavior. It is the main brainstem hub that lies between the environment and the rest of the higher neural system, making continuous, implicit decisions about where to direct our attention. The conserved cortex-like organization of the superior colliculus in all vertebrates allows the early appearance of primitive emotionally-related behaviors essential for survival. It contains first-line specialized neurons enabling the detection and tracking of faces and movements from birth. During development, it also sends the appropriate impulses to help shape brain areas necessary for social-communicative abilities. These abilities require the analysis of numerous variables, such as the simultaneous evaluation of incoming information sustained by separate brain networks (visual, auditory and sensory-motor, social, emotional, etc.), and predictive capabilities which compare present events to previous experiences and possible responses. These critical aspects of decision-making allow us to evaluate the impact that our response or behavior may provoke in others. The purpose of this review is to show that several enigmas about the complexity of autism might be explained by disruptions of collicular and brainstem functions. The results of two separate lines of investigation: 1. the cognitive, etiologic, and pathogenic aspects of autism on one hand, and two. the functional anatomy of the colliculus on the other, are considered in order to bridge the gap between basic brain science and clinical studies and to promote future research in this unexplored area.

PyZebrascope: An Open-Source Platform for Brain-Wide Neural Activity Imaging in Zebrafish

Understanding how neurons interact across the brain to control animal behaviors is one of the central goals in neuroscience. Recent developments in fluorescent microscopy and genetically-encoded calcium indicators led to the establishment of whole-brain imaging methods in zebrafish, which record neural activity across a brain-wide volume with single-cell resolution. Pioneering studies of whole-brain imaging used custom light-sheet microscopes, and their operation relied on commercially developed and maintained software not available globally. Hence it has been challenging to disseminate and develop the technology in the research community. Here, we present PyZebrascope, an open-source Python platform designed for neural activity imaging in zebrafish using light-sheet microscopy. PyZebrascope has intuitive user interfaces and supports essential features for whole-brain imaging, such as two orthogonal excitation beams and eye damage prevention. Its camera module can handle image data throughput of up to 800 MB/s from camera acquisition to file writing while maintaining stable CPU and memory usage. Its modular architecture allows the inclusion of advanced algorithms for microscope control and image processing. As a proof of concept, we implemented a novel automatic algorithm for maximizing the image resolution in the brain by precisely aligning the excitation beams to the image focal plane. PyZebrascope enables whole-brain neural activity imaging in fish behaving in a virtual reality environment. Thus, PyZebrascope will help disseminate and develop light-sheet microscopy techniques in the neuroscience community and advance our understanding of whole-brain neural dynamics during animal behaviors.

The Superior Colliculus: Cell Types, Connectivity, and Behavior

The superior colliculus (SC), one of the most well-characterized midbrain sensorimotor structures where visual, auditory, and somatosensory information are integrated to initiate motor commands, is highly conserved across vertebrate evolution. Moreover, cell-type-specific SC neurons integrate afferent signals within local networks to generate defined output related to innate and cognitive behaviors. This review focuses on the recent progress in understanding of phenotypic diversity amongst SC neurons and their intrinsic circuits and long-projection targets. We further describe relevant neural circuits and specific cell types in relation to behavioral outputs and cognitive functions. The systematic delineation of SC organization, cell types, and neural connections is further put into context across species as these depend upon laminar architecture. Moreover, we focus on SC neural circuitry involving saccadic eye movement, and cognitive and innate behaviors. Overall, the review provides insight into SC functioning and represents a basis for further understanding of the pathology associated with SC dysfunction.

Transformation of an early-established motor circuit during maturation in zebrafish

Locomotion is mediated by spinal circuits that generate movements with a precise coordination and vigor. The assembly of these circuits is defined early during development; however, whether their organization and function remain invariant throughout development is unclear. Here, we show that the first established fast circuit between two dorsally located V2a interneuron types and the four primary motoneurons undergoes major transformation in adult zebrafish compared with what was reported in larvae. There is a loss of existing connections and establishment of new connections combined with alterations in the mode, plasticity, and strength of synaptic transmission. In addition, we show that this circuit no longer serves as a swim rhythm generator, but instead its components become embedded within the spinal escape circuit and control propulsion following the initial escape turn. Our results thus reveal significant changes in the organization and function of a motor circuit as animals develop toward adulthood.

High activity and high functional connectivity are mutually exclusive in resting state zebrafish and human brains

Background

The structural connectivity of neurons in the brain allows active neurons to impact the physiology of target neuron types with which they are functionally connected. While the structural connectome is at the basis of functional connectome, it is the functional connectivity measured through correlations between time series of individual neurophysiological events that underlies behavioral and mental states. However, in light of the diverse neuronal cell types populating the brain and their unique connectivity properties, both neuronal activity and functional connectivity are heterogeneous across the brain, and the nature of their relationship is not clear. Here, we employ brain-wide calcium imaging at cellular resolution in larval zebrafish to understand the principles of resting state functional connectivity.

Results

We recorded the spontaneous activity of >12,000 neurons in the awake resting state forebrain. By classifying their activity (i.e., variances of ΔF/F across time) and functional connectivity into three levels (high, medium, low), we find that highly active neurons have low functional connections and highly connected neurons are of low activity. This finding holds true when neuronal activity and functional connectivity data are classified into five instead of three levels, and in whole brain spontaneous activity datasets. Moreover, such activity-connectivity relationship is not observed in randomly shuffled, noise-added, or simulated datasets, suggesting that it reflects an intrinsic brain network property. Intriguingly, deploying the same analytical tools on functional magnetic resonance imaging (fMRI) data from the resting state human brain, we uncover a similar relationship between activity (signal variance over time) and functional connectivity, that is, regions of high activity are non-overlapping with those of high connectivity.

Conclusions

We found a mutually exclusive relationship between high activity (signal variance over time) and high functional connectivity of neurons in zebrafish and human brains. These findings reveal a previously unknown and evolutionarily conserved brain organizational principle, which has implications for understanding disease states and designing artificial neuronal networks.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01286-3.

Power-effective scanning with AODs for 3D optogenetic applications

Two-photon (2P) excitation is a cornerstone approach widely employed in neuroscience microscopy for deep optical access and sub-micrometric-resolution light targeting into the brain. However, besides structural and functional imaging, 2P optogenetic stimulations are less routinary, especially in 3D. This is because of the adopted scanning systems, often feebly effective, slow and mechanically constricted. Faster illumination can be achieved through acousto-optic deflectors (AODs) although their applicability to large volumes excitation has been limited by large efficiency drop along the optical axis. Here, we present a new AOD-based scheme for 2P 3D scanning that improves the power delivery between different illumination planes. We applied this approach to photostimulate an optogenetic actuator in zebrafish larvae, demonstrating the method efficiency observing increased activity responses and uniform activation probabilities from neuronal clusters addressed in the volume. This novel driving scheme can open to new AOD applications in neuroscience, allowing more effective 3D interrogation in large neuronal networks.

The Role of Estrogen and Thyroid Hormones in Zebrafish Visual System Function

Visual system development is a highly complex process involving coordination of environmental cues, cell pathways, and integration of functional circuits. Consequently, a change to any step, due to a mutation or chemical exposure, can lead to deleterious consequences. One class of chemicals known to have both overt and subtle effects on the visual system is endocrine disrupting compounds (EDCs). EDCs are environmental contaminants which alter hormonal signaling by either preventing compound synthesis or binding to postsynaptic receptors. Interestingly, recent work has identified neuronal and sensory systems, particularly vision, as targets for EDCs. In particular, estrogenic and thyroidogenic signaling have been identified as critical modulators of proper visual system development and function. Here, we summarize and review this work, from our lab and others, focusing on behavioral, physiological, and molecular data collected in zebrafish. We also discuss different exposure regimes used, including long-lasting effects of developmental exposure. Overall, zebrafish are a model of choice to examine the impact of EDCs and other compounds targeting estrogen and thyroid signaling and the consequences of exposure in visual system development and function.

Laser capture microdissection-capillary zone electrophoresis-tandem mass spectrometry (LCM-CZE-MS/MS) for spatially resolved top-down proteomics: a pilot study of zebrafish brain

Mass spectrometry (MS)-based spatially resolved top-down proteomics (TDP) of tissues is crucial for understanding the roles played by microenvironmental heterogeneity in the biological functions of organs and for discovering new proteoform biomarkers of diseases. There are few published spatially resolved TDP studies. One of the challenges relates to the limited performance of TDP for the analysis of spatially isolated samples using, for example, laser capture microdissection (LCM) because those samples are usually mass-limited. We present the first pilot study of LCM-capillary zone electrophoresis (CZE)-MS/MS for spatially resolved TDP and used zebrafish brain as the sample. The LCM-CZE-MS/MS platform employed a non-ionic detergent and a freeze-thaw method for efficient proteoform extraction from LCM isolated brain sections followed by CZE-MS/MS without any sample cleanup step, ensuring high sensitivity. Over 400 proteoforms were identified in a CZE-MS/MS analysis of one LCM brain section via consuming the protein content of roughly 250 cells. We observed drastic differences in proteoform profiles between two LCM brain sections isolated from the optic tectum (Teo) and telencephalon (Tel) regions. Proteoforms of three proteins (npy, penkb, and pyya) having neuropeptide hormone activity were exclusively identified in the isolated Tel section. Proteoforms of reticulon, myosin, and troponin were almost exclusively identified in the isolated Teo section, and those proteins play essential roles in visual and motor activities. The proteoform profiles accurately reflected the main biological functions of the Teo and Tel regions of the brain. Additionally, hundreds of post-translationally modified proteoforms were identified.

Brain-wide visual habituation networks in wild type and fmr1 zebrafish

Habituation is a form of learning during which animals stop responding to repetitive stimuli, and deficits in habituation are characteristic of several psychiatric disorders. Due to technical challenges, the brain-wide networks mediating habituation are poorly understood. Here we report brain-wide calcium imaging during larval zebrafish habituation to repeated visual looming stimuli. We show that different functional categories of loom-sensitive neurons are located in characteristic locations throughout the brain, and that both the functional properties of their networks and the resulting behavior can be modulated by stimulus saliency and timing. Using graph theory, we identify a visual circuit that habituates minimally, a moderately habituating midbrain population proposed to mediate the sensorimotor transformation, and downstream circuit elements responsible for higher order representations and the delivery of behavior. Zebrafish larvae carrying a mutation in the fmr1 gene have a systematic shift toward sustained premotor activity in this network, and show slower behavioral habituation.

Evolution of behavioural control from chordates to primates

This article outlines a hypothetical sequence of evolutionary innovations, along the lineage that produced humans, which extended behavioural control from simple feedback loops to sophisticated control of diverse species-typical actions. I begin with basic feedback mechanisms of ancient mobile animals and follow the major niche transitions from aquatic to terrestrial life, the retreat into nocturnality in early mammals, the transition to arboreal life and the return to diurnality. Along the way, I propose a sequence of elaboration and diversification of the behavioural repertoire and associated neuroanatomical substrates. This includes midbrain control of approach versus escape actions, telencephalic control of local versus long-range foraging, detection of affordances by the dorsal pallium, diversified control of nocturnal foraging in the mammalian neocortex and expansion of primate frontal, temporal and parietal cortex to support a wide variety of primate-specific behavioural strategies. The result is a proposed functional architecture consisting of parallel control systems, each dedicated to specifying the affordances for guiding particular species-typical actions, which compete against each other through a hierarchy of selection mechanisms.

This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.

The neuroecology of the water-to-land transition and the evolution of the vertebrate brain

The water-to-land transition in vertebrate evolution offers an unusual opportunity to consider computational affordances of a new ecology for the brain. All sensory modalities are changed, particularly a greatly enlarged visual sensorium owing to air versus water as a medium, and expanded by mobile eyes and neck. The multiplication of limbs, as evolved to exploit aspects of life on land, is a comparable computational challenge. As the total mass of living organisms on land is a hundredfold larger than the mass underwater, computational improvements promise great rewards. In water, the midbrain tectum coordinates approach/avoid decisions, contextualized by water flow and by the animal's body state and learning. On land, the relative motions of sensory surfaces and effectors must be resolved, adding on computational architectures from the dorsal pallium, such as the parietal cortex. For the large-brained and long-living denizens of land, making the right decision when the wrong one means death may be the basis of planning, which allows animals to learn from hypothetical experience before enactment. Integration of value-weighted, memorized panoramas in basal ganglia/frontal cortex circuitry, with allocentric cognitive maps of the hippocampus and its associated cortices becomes a cognitive habit-to-plan transition as substantial as the change in ecology. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Escape steering by cholecystokinin peptidergic signaling

Escape is an evolutionarily conserved and essential avoidance response. Considered to be innate, most studies on escape responses focused on hard-wired circuits. We report here that a neuropeptide NLP-18 and its cholecystokinin receptor CKR-1 enable the escape circuit to execute a full omega (Ω) turn. We demonstrate in vivo NLP-18 is mainly secreted by the gustatory sensory neuron (ASI) to activate CKR-1 in the head motor neuron (SMD) and the turn-initiating interneuron (AIB). Removal of NLP-18 or CKR-1 or specific knockdown of CKR-1 in SMD or AIB neurons leads to shallower turns, hence less robust escape steering. Consistently, elevation of head motor neuron (SMD)'s Ca²⁺ transients during escape steering is attenuated upon the removal of NLP-18 or CKR-1. In vitro, synthetic NLP-18 directly evokes CKR-1-dependent currents in oocytes and CKR-1-dependent Ca²⁺ transients in SMD. Thus, cholecystokinin peptidergic signaling modulates an escape circuit to generate robust escape steering.

Input from torus longitudinalis drives binocularity and spatial summation in zebrafish optic tectum

Background

A continued effort in neuroscience aims to understand the way brain circuits consisting of diverse neuronal types generate complex behavior following sensory input. A common feature of vertebrate visual systems is that lower-order and higher-order visual areas are reciprocally connected. Feedforward projections confer visual responsiveness to higher-order visual neurons while feedback projections likely serve to modulate responses of lower-order visual neurons in a context-dependent manner. Optic tectum is the largest first-order visual brain area in zebrafish and is reciprocally connected with the torus longitudinalis (TL), a second-order visual brain area that does not receive retinal input. A functional role for feedback projections from TL to tectum has not been identified. Here we aim to understand how this feedback contributes to visual processing.

Results

In this study, we demonstrate that TL feedback projections to tectum drive binocular integration and spatial summation in a defined tectal circuit. We performed genetically targeted, cell type-specific functional imaging in tectal pyramidal neurons (PyrNs) and their two input neuron populations: retinal ganglion cells (RGCs) and neurons in TL. We find that PyrNs encode gradual changes in scene luminance using a complement of three distinct response classes that encode different light intensity ranges. Functional imaging of RGC inputs to tectum suggest that these response classes originate in the retina and RGC input specifies PyrN functional classes. In contrast, TL input serves to endow PyrNs with large, compound receptive fields that span both retinal hemifields.

Conclusions

These findings reveal a novel role for the zebrafish TL in driving binocular integration and spatial summation in tectal PyrNs. The neural circuit we describe generates a population of tectal neurons with large receptive fields tailored for detecting changes in the visual scene.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01222-x.

Audiovisual integration in the Mauthner cell enhances escape probability and reduces response latency

Fast and accurate threat detection is critical for animal survival. Reducing perceptual ambiguity by integrating multiple sources of sensory information can enhance perception and reduce response latency. However, studies addressing the link between behavioral correlates of multisensory integration and its underlying neural basis are rare. Fish that detect an urgent threat escape with an explosive behavior known as C-start. The C-start is driven by an identified neural circuit centered on the Mauthner cell, an identified neuron capable of triggering escapes in response to visual and auditory stimuli. Here we demonstrate that goldfish can integrate visual looms and brief auditory stimuli to increase C-start probability. This multisensory enhancement is inversely correlated to the salience of the stimuli, with weaker auditory cues producing a proportionally stronger multisensory effect. We also show that multisensory stimuli reduced C-start response latency, with most escapes locked to the presentation of the auditory cue. We make a direct link between behavioral data and its underlying neural mechanism by reproducing the behavioral data with an integrate-and-fire computational model of the Mauthner cell. This model of the Mauthner cell circuit suggests that excitatory inputs integrated at the soma are key elements in multisensory decision making during fast C-start escapes. This provides a simple but powerful mechanism to enhance threat detection and survival.

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.