Experience, circuit dynamics, and forebrain recruitment in larval zebrafish prey capture

Development of sensorimotor responses in larval zebrafish: A comparison between wild-type and GCaMP6s transgenic line

During early development, zebrafish larvae exhibit stereotypical behaviors, which rapidly become more complex. Thus, generating mutant transgenic lines that maintain transparency throughout their larval stage and that can be used to record brain activity has offered strategic opportunities to investigate the underlying neural correlates of behavior establishment. However, few studies have documented the sensorimotor profile of these lines during larval development. Here, we set up a behavioral characterization using diverse stimuli (light and vibration) throughout larval development to compare the responses of a transgenic strain expressing a pan-neuronal calcium indicator (GCaMP6s) with that of a wild-type strain. Interestingly, we report a drastic switch in behavioral responses to light transitions at 11 days post-fertilization (dpf) and to vibration stimuli at 14 dpf in both lines. These data highlight a specific time window representing an increase in behavioral complexity. Meanwhile, we found some differences in the maturation of sensorimotor responses between GCaMP6s and wild-type strains. Although some of these differences are minor, they highlight the need for careful attention when using mutant/transgenic lines for behavioral studies. Overall, our results support using GCaMP6s strain in investigating the neural mechanisms underlying the developmental maturation of sensorimotor responses.

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 nearly 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.

Days-old zebrafish rapidly learn to recognize threatening agents through noradrenergic and forebrain circuits

Animals need to rapidly learn to recognize and avoid predators. This ability may be especially important for young animals due to their increased vulnerability. It is unknown whether, and how, nascent vertebrates are capable of such rapid learning. Here, we used a robotic predator-prey interaction assay to show that 1 week after fertilization-a developmental stage where they have approximately 1% the number of neurons of adults-zebrafish larvae rapidly and robustly learn to recognize a stationary object as a threat after the object pursues the fish for ∼1 min. Larvae continue to avoid the threatening object after it stops moving and can learn to distinguish threatening from non-threatening objects of a different color. Whole-brain functional imaging revealed the multi-timescale activity of noradrenergic neurons and forebrain circuits that encoded the threat. Chemogenetic ablation of those populations prevented the learning. Thus, a noradrenergic and forebrain multiregional network underlies the ability of young vertebrates to rapidly learn to recognize potential predators within their first week of life.

Counterillumination reduces bites by Great White sharks

In the open ocean, achieving camouflage is complicated by the fact that the downwelling light is generally much brighter than the upwelling light, which means that any object, even if its ventral surface is white due to countershading, will appear as a dark silhouette when viewed from below.1,2,3 To overcome this, many marine species employ counterillumination, whereby light is emitted from photophores on their ventral surface to replace the downwelling light blocked by their body.4,5,6 However, only a single behavioral study has tested the efficacy of counterillumination as an anti-predation strategy.7 Counterillumination is predicted to be particularly useful against predators that have poor visual acuity and lack color vision,8 like the Great White shark (Carcharodon carcharias), the species responsible for most human shark-bite fatalities globally.9 Here, we take inspiration from nature to show that counterillumination can prevent Great White sharks from attacking artificial seal decoys. Using seal decoys fitted with LED lights and towed behind a boat, we explored the efficiency of different light configurations on the deterrence effect, showing that visual shape and motion cues are critical for prey recognition by Great White sharks. Counterillumination that is brighter than the background is most effective in deterring sharks, implying that, in this context, counterillumination works through disruptive camouflage rather than background matching. Our results reveal the importance of a dark silhouette against a lighter background in predatory behavior in Great White sharks and that altering the silhouette may form the basis of new non-invasive shark deterrent technology to protect human life. VIDEO ABSTRACT.

Uncovering multiscale structure in the variability of larval zebrafish navigation

Animals chain movements into long-lived motor strategies, exhibiting variability across scales that reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build Markov models of movement sequences that bridge across timescales and enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish responding to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising versus wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive stimuli, or in search for appetitive prey. As our method encodes the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies, we use it to uncover a hierarchical structure in the phenotypic variability that reflects exploration-exploitation trade-offs. Across a wide range of sensory cues, a major source of variation among fish is driven by prior and/or immediate exposure to prey that induces exploitation phenotypes. A large degree of variability that is not explained by environmental cues unravels hidden states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, by extracting the timescales of motor strategies deployed during navigation, our approach exposes structure among individuals and reveals internal states tuned by prior experience.

Experience-dependent modulation of collective behavior in larval zebrafish

Complex group behavior can emerge from simple inter-individual interactions. Commonly, these interactions are considered static and hardwired and little is known about how experience and learning affect collective group behavior. Young larvae use well described visuomotor transformations to guide interindividual interactions and collective group structure. Here, we use naturalistic and virtual-reality (VR) experiments to impose persistent changes in population density and measure their effects on future visually evoked turning behavior and the resulting changes in group structure. We find that neighbor distances decrease after exposure to higher population densities, and increase after the experience of lower densities. These adaptations develop slowly and gradually, over tens of minutes and remain stable over many hours. Mechanistically, we find that larvae estimate their current group density by tracking the frequency of neighbor-evoked looming events on the retina and couple the strength of their future interactions to that estimate. A time-varying state-space model that modulates agents' social interactions based on their previous visual-social experiences, accurately describes our behavioral observations and predicts novel aspects of behavior. These findings provide concrete evidence that inter-individual interactions are not static, but rather continuously evolve based on past experience and current environmental demands. The underlying neurobiological mechanisms of experience dependent modulation can now be explored in this small and transparent model organism.

The Visual Systems of Zebrafish

The zebrafish visual system has become a paradigmatic preparation for behavioral and systems neuroscience. Around 40 types of retinal ganglion cells (RGCs) serve as matched filters for stimulus features, including light, optic flow, prey, and objects on a collision course. RGCs distribute their signals via axon collaterals to 12 retinorecipient areas in forebrain and midbrain. The major visuomotor hub, the optic tectum, harbors nine RGC input layers that combine information on multiple features. The retinotopic map in the tectum is locally adapted to visual scene statistics and visual subfield-specific behavioral demands. Tectal projections to premotor centers are topographically organized according to behavioral commands. The known connectivity in more than 20 processing streams allows us to dissect the cellular basis of elementary perceptual and cognitive functions. Visually evoked responses, such as prey capture or loom avoidance, are controlled by dedicated multistation pathways that-at least in the larva-resemble labeled lines. This architecture serves the neuronal code's purpose of driving adaptive behavior.

Activity-dependent synthesis of Emerin gates neuronal plasticity by regulating proteostasis

Neurons dynamically regulate their proteome in response to sensory input, a key process underlying experience-dependent plasticity. We characterized the visual experience-dependent nascent proteome within a brief, defined time window after stimulation using an optimized metabolic labeling approach. Visual experience induced cell type-specific and age-dependent alterations in the nascent proteome, including proteostasis-related processes. We identified Emerin as the top activity-induced candidate plasticity protein and demonstrated that its rapid activity-induced synthesis is transcription-independent. In contrast to its nuclear localization and function in myocytes, activity-induced neuronal Emerin is abundant in the endoplasmic reticulum and broadly inhibits protein synthesis, including translation regulators and synaptic proteins. Downregulating Emerin shifted the dendritic spine population from predominantly mushroom morphology to filopodia and decreased network connectivity. In mice, decreased Emerin reduced visual response magnitude and impaired visual information processing. Our findings support an experience-dependent feed-forward role for Emerin in temporally gating neuronal plasticity by negatively regulating translation.

Uncovering multiscale structure in the variability of larval zebrafish navigation

Animals chain movements into long-lived motor strategies, exhibiting variability across scales that reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build Markov models of movement sequences that bridges across time scales and enables a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish responding to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising versus wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive stimuli, or in search for appetitive prey. As our method encodes the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies, we use it to uncover a hierarchical structure in the phenotypic variability that reflects exploration-exploitation trade-offs. Across a wide range of sensory cues, a major source of variation among fish is driven by prior and/or immediate exposure to prey that induces exploitation phenotypes. A large degree of variability that is not explained by environmental cues unravels motivational states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, by extracting the timescales of motor strategies deployed during navigation, our approach exposes structure among individuals and reveals internal states tuned by prior experience.

Uncovering multiscale structure in the variability of larval zebrafish navigation

Animals chain movements into long-lived motor strategies, resulting in variability that ultimately reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build models that bridges across time scales that enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish exposed to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising and wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive (dark) stimuli or in search for prey. Our method enables us to encode the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies. By doing so, we uncover a hierarchical structure to the phenotypic variability that corresponds to exploration-exploitation trade-offs. Within a wide range of sensory cues, a major source of variation among fish is driven by prior and immediate exposure to prey that induces exploitation phenotypes. However, a large degree of variability is unexplained by environmental cues, pointing to hidden states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, our approach extracts the timescales of motor strategies deployed during navigation, exposing undiscovered structure among individuals and pointing to internal states tuned by prior experience.

Corticosterone Contributes to Diet-Induced Reprogramming of Post-Metamorphic Behavior in Spadefoot Toads

Stressful experiences in early life can have phenotypic effects that persist into, or manifest during, adulthood. In vertebrates, such carryover effects can be driven by stress-induced secretion of glucocorticoid hormones, such as corticosterone, which can lead to developmental reprogramming of hypothalamic-pituitary-adrenal/interrenal axis activity and behavior. Nutritional stress in the form of early life nutrient restriction is well known to modify later life behaviors and stress activity through corticosterone-related mechanisms. However, it is not known whether corticosterone is also mechanistically involved in carryover effects induced by a different form of nutritional variation: the use of alternate or entirely novel types of dietary resources. The plains spadefoot (Spea bombifrons) presents an excellent system for testing this question, since larvae of this species have evolved to use 2 alternate diet types: an ancestral detritus-based diet and a more novel diet of live shrimp. While previous work has shown that feeding on the novel shrimp diet influences juvenile (i.e., post-metamorphic) behavior and corticosterone levels, it is unclear whether these diet-induced carryover effects are mediated by diet-induced corticosterone itself. To test for the mechanistic role of corticosterone in diet-induced carryover effects, we experimentally treated S. bombifrons larvae with exogenous corticosterone and measured subsequent effects on juvenile behavior and corticosterone levels. We found that while shrimp-fed larvae had elevated corticosterone levels, treatment of larvae with corticosterone itself had effects on juvenile behavior that partially resembled those carryover effects induced by the shrimp diet, such as altered food seeking and higher locomotor activity. However, unlike carryover effects caused by the shrimp diet, larval corticosterone exposure did not affect juvenile corticosterone levels. Overall, our study shows that corticosterone-related mechanisms are likely involved in carryover effects induced by a novel diet, yet such diet-induced carryover effects are not driven by corticosterone alone.

Functional neuronal circuits emerge in the absence of developmental activity

The complex neuronal circuitry of the brain develops from limited information contained in the genome. After the genetic code instructs the birth of neurons, the emergence of brain regions, and the formation of axon tracts, it is believed that temporally structured spiking activity shapes circuits for behavior. Here, we challenge the learning-dominated assumption that spiking activity is required for circuit formation by quantifying its contribution to the development of visually-guided swimming in the larval zebrafish. We found that visual experience had no effect on the emergence of the optomotor response (OMR) in dark-reared zebrafish. We then raised animals while pharmacologically silencing action potentials with the sodium channel blocker tricaine. After washout of the anesthetic, fish could swim and performed with 75-90% accuracy in the OMR paradigm. Brain-wide imaging confirmed that neuronal circuits came 'online' fully tuned, without requiring activity-dependent plasticity. Thus, complex sensory-guided behaviors can emerge through activity-independent developmental mechanisms.

Behavioral Assays Dissecting NMDA Receptor Function in Zebrafish

Zebrafish are a powerful system to study brain development and to dissect the activity of complex circuits. One advantage is that they display complex behaviors, including prey capture, learning, responses to photic and acoustic stimuli, and social interaction (Dreosti et al., Front Neural Circuits 9:39, 2015; Bruckner et al., PLoS Biol 20:e3001838, 2022; Zoodsma et al., Mol Autism 13:38, 2022) that can be probed to assess brain function. Many of these behaviors are easily assayed at early larval stages, offering a noninvasive and high-throughput readout of nervous system function. Additionally, larval zebrafish readily uptake small molecules dissolved in water making them ideal for behavioral-based drug screens. Together, larval zebrafish and their behavioral repertoire offer a means to rapidly dissect brain circuitry and can serve as a template for high-throughput small molecule screens.NMDA receptor subunits are highly conserved in zebrafish compared to mammals (Zoodsma et al., Mol Autism 13:38, 2022; Cox et al., Dev Dyn 234:756-766, 2005; Zoodsma et al., J Neurosci 40:3631-3645, 2020). High amino acid and domain structure homology between humans and zebrafish underlie conserved functional similarities. Here we describe a set of behavioral assays that are useful to study the NMDA receptor activity in brain function.

Perfluorooctane Sulfonate (PFOS) Negatively Impacts Prey Capture Capabilities in Larval Zebrafish

Per- and polyfluoroalkyl substances (PFAS) are widely used in many industrial and domestic applications, which has resulted in unintentional human exposures and bioaccumulation in blood and other organs. Perfluorooctane sulfonate (PFOS) is among the most prevalent PFAS in the environment and has been postulated to affect brain functions in exposed organisms. However, the impacts of PFOS in early neural development have not been well described. We used zebrafish larvae to assess the effects of PFOS on two fundamental complex behaviors, prey capture and learning. Zebrafish exposed to PFOS concentrations ranging from 2 to 20 µM for differing 48-h periods were viable through early larval stages. In addition, PFOS uptake was unaffected by the presence of a chorion. We employed two different experimental paradigms; first we assessed the impacts of increasing organismal PFOS bioaccumulation on prey capture and learning, and second, we probed stage-specific sensitivity to PFOS by exposing zebrafish at different developmental stages (0-2 vs. 3-5 days post fertilization). Following both assays we measured the amount of PFOS present in each larva and found that PFOS levels varied in larvae from different groups within each experimental paradigm. Significant negative correlations were observed between larval PFOS accumulation and percentage of captured prey, whereas nonsignificant negative correlations were observed between PFOS accumulation and experienced-induced prey capture learning. These findings suggest that PFOS accumulation negatively affects larval zebrafish's ability to perform complicated multisensory behaviors and highlights the potential risks of PFOS exposure to animals in the wild, with implications for human health. Environ Toxicol Chem 2024;00:1-9. © 2023 SETAC.

Retina-derived signals control pace of neurogenesis in visual brain areas but not circuit assembly

Brain development is orchestrated by both innate and experience-dependent mechanisms, but their relative contributions are difficult to disentangle. Here we asked if and how central visual areas are altered in a vertebrate brain depleted of any and all signals from retinal ganglion cells throughout development. We transcriptionally profiled neurons in pretectum, thalamus and other retinorecipient areas of larval zebrafish and searched for changes in lakritz mutants that lack all retinal connections. Although individual genes are dysregulated, the complete set of 77 neuronal types develops in apparently normal proportions, at normal locations, and along normal differentiation trajectories. Strikingly, the cell-cycle exits of proliferating progenitors in these areas are delayed, and a greater fraction of early postmitotic precursors remain uncommitted or are diverted to a pre-glial fate. Optogenetic stimulation targeting groups of neurons normally involved in processing visual information evokes behaviors indistinguishable from wildtype. In conclusion, we show that signals emitted by retinal axons influence the pace of neurogenesis in visual brain areas, but do not detectably affect the specification or wiring of downstream neurons.

Larval zebrafish as a model for studying individual variability in translational neuroscience research

The larval zebrafish is a popular model for translational research into neurological and psychiatric disorders due to its conserved vertebrate brain structures, ease of genetic and experimental manipulation and small size and scalability to large numbers. The possibility of obtaining in vivo whole-brain cellular resolution neural data is contributing important advances into our understanding of neural circuit function and their relation to behavior. Here we argue that the larval zebrafish is ideally poised to push our understanding of how neural circuit function relates to behavior to the next level by including considerations of individual differences. Understanding variability across individuals is particularly relevant for tackling the variable presentations that neuropsychiatric conditions frequently show, and it is equally elemental if we are to achieve personalized medicine in the future. We provide a blueprint for investigating variability by covering examples from humans and other model organisms as well as existing examples from larval zebrafish. We highlight recent studies where variability may be hiding in plain sight and suggest how future studies can take advantage of existing paradigms for further exploring individual variability. We conclude with an outlook on how the field can harness the unique strengths of the zebrafish model to advance this important impending translational question.

Connecting the Pipes: Agricultural Tile Drains and Elevated Imidacloprid Brain Concentrations in Juvenile Northern Leopard Frogs (Rana pipiens)

Neonicotinoids are neurotoxic insecticides and are often released into nearby wetlands via subsurface tile drains and can negatively impact nontarget organisms, such as amphibians. Previous studies have indicated that imidacloprid, a commonly used neonicotinoid, can cross the amphibian blood-brain barrier under laboratory conditions; however, little is known about the impact of low concentrations in a field-based setting. Here, we report aqueous pesticide concentrations at wetland production areas that were either connected or not connected to agricultural tile drains, quantified imidacloprid and its break down products in juvenile amphibian brains and livers, and investigated the relationship between imidacloprid brain concentration and brain size. Imidacloprid concentrations in brain and water samples were nearly 2.5 and 5 times higher at tile wetlands (brain = 4.12 ± 1.92 pg/mg protein; water = 0.032 ± 0.045 μg/L) compared to reference wetlands, respectively. Tile wetland amphibians also had shorter cerebellums (0.013 ± 0.001 mm), depicting a negative relationship between imidacloprid brain concentration and cerebellum length. The metabolite, desnitro-imidacloprid, had liver concentrations that were 2 times higher at tile wetlands (2 ± 0.3 μg/g). Our results demonstrate that imidacloprid can cross the amphibian blood-brain barrier under ecological conditions and may alter brain dimensions and provide insight into the metabolism of imidacloprid in amphibians.

Granger causality analysis for calcium transients in neuronal networks, challenges and improvements

One challenge in neuroscience is to understand how information flows between neurons in vivo to trigger specific behaviors. Granger causality (GC) has been proposed as a simple and effective measure for identifying dynamical interactions. At single-cell resolution however, GC analysis is rarely used compared to directionless correlation analysis. Here, we study the applicability of GC analysis for calcium imaging data in diverse contexts. We first show that despite underlying linearity assumptions, GC analysis successfully retrieves non-linear interactions in a synthetic network simulating intracellular calcium fluctuations of spiking neurons. We highlight the potential pitfalls of applying GC analysis on real in vivo calcium signals, and offer solutions regarding the choice of GC analysis parameters. We took advantage of calcium imaging datasets from motoneurons in embryonic zebrafish to show how the improved GC can retrieve true underlying information flow. Applied to the network of brainstem neurons of larval zebrafish, our pipeline reveals strong driver neurons in the locus of the mesencephalic locomotor region (MLR), driving target neurons matching expectations from anatomical and physiological studies. Altogether, this practical toolbox can be applied on in vivo population calcium signals to increase the selectivity of GC to infer flow of information across neurons.

From perception to behavior: The neural circuits underlying prey hunting in larval zebrafish

A key challenge for neural systems is to extract relevant information from the environment and make appropriate behavioral responses. The larval zebrafish offers an exciting opportunity for studying these sensing processes and sensory-motor transformations. Prey hunting is an instinctual behavior of zebrafish that requires the brain to extract and combine different attributes of the sensory input and form appropriate motor outputs. Due to its small size and transparency the larval zebrafish brain allows optical recording of whole-brain activity to reveal the neural mechanisms involved in prey hunting and capture. In this review we discuss how the larval zebrafish brain processes visual information to identify and locate prey, the neural circuits governing the generation of motor commands in response to prey, how hunting behavior can be modulated by internal states and experience, and some outstanding questions for the field.

Feature-space selection with banded ridge regression

Encoding models provide a powerful framework to identify the information represented in brain recordings. In this framework, a stimulus representation is expressed within a feature space and is used in a regularized linear regression to predict brain activity. To account for a potential complementarity of different feature spaces, a joint model is fit on multiple feature spaces simultaneously. To adapt regularization strength to each feature space, ridge regression is extended to banded ridge regression, which optimizes a different regularization hyperparameter per feature space. The present paper proposes a method to decompose over feature spaces the variance explained by a banded ridge regression model. It also describes how banded ridge regression performs a feature-space selection, effectively ignoring non-predictive and redundant feature spaces. This feature-space selection leads to better prediction accuracy and to better interpretability. Banded ridge regression is then mathematically linked to a number of other regression methods with similar feature-space selection mechanisms. Finally, several methods are proposed to address the computational challenge of fitting banded ridge regressions on large numbers of voxels and feature spaces. All implementations are released in an open-source Python package called Himalaya.

A binocular perception deficit characterizes prey pursuit in developing mice

Integration of binocular information at the cellular level has long been studied in the mouse model to uncover the fundamental developmental mechanisms underlying mammalian vision. However, we lack an understanding of the corresponding ontogeny of visual behavior in mice that relies on binocular integration. To address this major outstanding question, we quantified the natural visually guided behavior of postnatal day 21 (P21) and adult mice using a live prey capture assay and a computerized-spontaneous perception of objects task (C-SPOT). We found a robust and specific binocular visual field processing deficit in P21 mice as compared to adults that corresponded to a selective increase in c-Fos expression in the anterior superior colliculus (SC) of the juveniles after C-SPOT. These data link a specific binocular perception deficit in developing mice to activity changes in the SC.

From calcium imaging to graph topology

Systems neuroscience is facing an ever-growing mountain of data. Recent advances in protein engineering and microscopy have together led to a paradigm shift in neuroscience; using fluorescence, we can now image the activity of every neuron through the whole brain of behaving animals. Even in larger organisms, the number of neurons that we can record simultaneously is increasing exponentially with time. This increase in the dimensionality of the data is being met with an explosion of computational and mathematical methods, each using disparate terminology, distinct approaches, and diverse mathematical concepts. Here we collect, organize, and explain multiple data analysis techniques that have been, or could be, applied to whole-brain imaging, using larval zebrafish as an example model. We begin with methods such as linear regression that are designed to detect relations between two variables. Next, we progress through network science and applied topological methods, which focus on the patterns of relations among many variables. Finally, we highlight the potential of generative models that could provide testable hypotheses on wiring rules and network progression through time, or disease progression. While we use examples of imaging from larval zebrafish, these approaches are suitable for any population-scale neural network modeling, and indeed, to applications beyond systems neuroscience. Computational approaches from network science and applied topology are not limited to larval zebrafish, or even to systems neuroscience, and we therefore conclude with a discussion of how such methods can be applied to diverse problems across the biological sciences.

Disruption of grin2B, an ASD-associated gene, produces social deficits in zebrafish

BACKGROUND

Autism spectrum disorder (ASD), like many neurodevelopmental disorders, has complex and varied etiologies. Advances in genome sequencing have identified multiple candidate genes associated with ASD, including dozens of missense and nonsense mutations in the NMDAR subunit GluN2B, encoded by GRIN2B. NMDARs are glutamate-gated ion channels with key synaptic functions in excitatory neurotransmission. How alterations in these proteins impact neurodevelopment is poorly understood, in part because knockouts of GluN2B in rodents are lethal.

METHODS

Here, we use CRISPR-Cas9 to generate zebrafish lacking GluN2B (grin2B-/-). Using these fish, we run an array of behavioral tests and perform whole-brain larval imaging to assay developmental roles and functions of GluN2B.

RESULTS

We demonstrate that zebrafish GluN2B displays similar structural and functional properties to human GluN2B. Zebrafish lacking GluN2B (grin2B-/-) surprisingly survive into adulthood. Given the prevalence of social deficits in ASD, we assayed social preference in the grin2B-/- fish. Wild-type fish develop a strong social preference by 3 weeks post fertilization. In contrast, grin2B-/- fish at this age exhibit significantly reduced social preference. Notably, the lack of GluN2B does not result in a broad disruption of neurodevelopment, as grin2B-/- larvae do not show alterations in spontaneous or photic-evoked movements, are capable of prey capture, and exhibit learning. Whole-brain imaging of grin2B-/- larvae revealed reduction of an inhibitory neuron marker in the subpallium, a region linked to ASD in humans, but showed that overall brain size and E/I balance in grin2B-/- is comparable to wild type.

LIMITATIONS

Zebrafish lacking GluN2B, while useful in studying developmental roles of GluN2B, are unlikely to model nuanced functional alterations of human missense mutations that are not complete loss of function. Additionally, detailed mammalian homologies for larval zebrafish brain subdivisions at the age of whole-brain imaging are not fully resolved.

CONCLUSIONS

We demonstrate that zebrafish completely lacking the GluN2B subunit of the NMDAR, unlike rodent models, are viable into adulthood. Notably, they exhibit a highly specific deficit in social behavior. As such, this zebrafish model affords a unique opportunity to study the roles of GluN2B in ASD etiologies and establish a disease-relevant in vivo model for future studies.

Zebrafish behavior as a gateway to nervous system assembly and plasticity

Nervous system assembly relies on a diversity of cellular processes ranging from dramatic tissue reorganization to local, subcellular changes all driven by precise molecular programs. Combined, these processes culminate in an animal's ability to plan and execute behaviors. Animal behavior can, therefore, serve as a functional readout of nervous system development. Benefitting from an expansive and growing set of molecular and imaging tools paired with an ever-growing number of assays of diverse behaviors, the zebrafish system has emerged as an outstanding platform at the intersection of nervous system assembly, plasticity and behavior. Here, we summarize recent advancements in the field, including how developing neural circuits are refined to shape complex behaviors and plasticity.

Transduction of Brain Neurons in Juvenile Chum Salmon (Oncorhynchus keta) with Recombinant Adeno-Associated Hippocampal Virus Injected into the Cerebellum during Long-Term Monitoring

Corpus cerebelli in juvenile chum salmon is a multiprojective region of the brain connected via afferent and efferent projections with the higher regions of the brainstem and synencephalon, as well as with multiprojection regions of the medulla oblongata and spinal cord. During the postembryonic development of the cerebellum in chum salmon, Oncorhynchus keta, the lateral part of the juvenile cerebellum gives rise to the caudomedial part of the definitive cerebellum, which is consistent with the data reported for zebrafish and mouse cerebellum. Thus, the topographic organization of the cerebellum and its efferents are similar between fish (chum salmon and zebrafish) and mammals, including mice and humans. The distributions of recombinant adeno-associated viral vectors (rAAVs) after an injection of the base vector into the cerebellum have shown highly specific patterns of transgene expression in bipolar neurons in the latero-caudal lobe of the juvenile chum tectum opticum. The distribution of rAAVs in the dorsal thalamus, epithalamus, nucleus rotundus, and pretectal complex indicates the targeted distribution of the transgene via the thalamo-cerebellar projections. The detection of GFP expression in the cells of the epiphysis and posterior tubercle of juvenile chum salmon is associated with the transgene’s distribution and with the cerebrospinal fluid flow, the brain ventricles and its outer surface. The direct delivery of the rAAV into the central nervous system by intracerebroventricular administration allows it to spread widely in the brain. Thus, the presence of special projection areas in the juvenile chum salmon cerebellum, as well as outside it, and the identification of the transgene’s expression in them confirm the potential ability of rAAVs to distribute in both intracerebellar and afferent and efferent extracerebellar projections of the cerebellum.

Neuromodulation and Behavioral Flexibility in Larval Zebrafish: From Neurotransmitters to Circuits

Animals adapt their behaviors to their ever-changing needs. Internal states, such as hunger, fear, stress, and arousal are important behavioral modulators controlling the way an organism perceives sensory stimuli and reacts to them. The translucent zebrafish larva is an ideal model organism for studying neuronal circuits regulating brain states, owning to the possibility of easy imaging and manipulating activity of genetically identified neurons while the animal performs stereotyped and well-characterized behaviors. The main neuromodulatory circuits present in mammals can also be found in the larval zebrafish brain, with the advantage that they contain small numbers of neurons. Importantly, imaging and behavioral techniques can be combined with methods for generating targeted genetic modifications to reveal the molecular underpinnings mediating the functions of such circuits. In this review we discuss how studying the larval zebrafish brain has contributed to advance our understanding of circuits and molecular mechanisms regulating neuromodulation and behavioral flexibility.

In vivo calcium imaging reveals disordered interictal network dynamics in epileptic stxbp1b zebrafish

STXBP1 mutations are associated with encephalopathy, developmental delay, intellectual disability, and epilepsy. While neural networks are known to operate at a critical state in the healthy brain, network behavior during pathological epileptic states remains unclear. Examining activity during periods between well-characterized ictal-like events (i.e., interictal period) could provide a valuable step toward understanding epileptic networks. To study these networks in the context of STXBP1 mutations, we combine a larval zebrafish model with in vivo fast confocal calcium imaging and extracellular local field potential recordings. Stxbp1b mutants display transient periods of elevated activity among local clusters of interacting neurons. These network "cascade" events were significantly larger in size and duration in mutants. At mesoscale resolution, cascades exhibit neurodevelopmental abnormalities. At single-cell scale, we describe spontaneous hyper-synchronized neuronal ensembles. That calcium imaging reveals uniquely disordered brain states during periods between pathological ictal-like seizure events is striking and represents a potential interictal biomarker.

Learning steers the ontogeny of an efficient hunting sequence in zebrafish larvae

Goal-directed behaviors may be poorly coordinated in young animals but, with age and experience, behavior progressively adapts to efficiently exploit the animal’s ecological niche. How experience impinges on the developing neural circuits of behavior is an open question. We have conducted a detailed study of the effects of experience on the ontogeny of hunting behavior in larval zebrafish. We report that larvae with prior experience of live prey consume considerably more prey than naive larvae. This is mainly due to increased capture success and a modest increase in hunt rate. We demonstrate that the initial turn to prey and the final capture manoeuvre of the hunting sequence were jointly modified by experience and that modification of these components predicted capture success. Our findings establish an ethologically relevant paradigm in zebrafish for studying how the brain is shaped by experience to drive the ontogeny of efficient behavior.