Brain-wide mapping of neural activity controlling zebrafish exploratory locomotion

Neural circuits underlying divergent visuomotor strategies of zebrafish and Danionella cerebrum

Many animals respond to sensory cues with species-specific coordinated movements.1,2 A universal visually guided behavior is the optomotor response (OMR),3,4,5,6 which stabilizes the body by following optic flow induced by displacements in currents.7 While the brain-wide OMR circuits in zebrafish (Danio rerio) have been characterized,8,9,10,11,12 the homologous neural functions across teleost species with different ecological niches, such as Danionella cerebrum,13,14,15 remain largely unexplored. Here, we directly compare larval zebrafish and D. cerebrum to uncover the neural mechanisms underlying the natural variation of visuomotor coordination. Closed-loop behavioral tracking during visual stimulation revealed that D. cerebrum follow optic flow by swimming continuously, punctuated with sharp directional turns, in contrast to the burst-and-glide locomotion of zebrafish.16 Although D. cerebrum swim at higher average speeds, they lack the direction-dependent velocity modulation observed in zebrafish. Two-photon calcium imaging and tail tracking showed that both species exhibit direction-selective encoding in putative homologous regions, with D. cerebrum containing more monocular neurons. D. cerebrum sustain significantly longer directed swims across all stimuli than zebrafish, with zebrafish reducing tail movement duration in response to oblique, turn-inducing stimuli. While locomotion-associated neurons in D. cerebrum display more prolonged activity than zebrafish, lateralized turn-associated neural activity in the hindbrain suggests a shared neural circuit architecture that independently controls movement vigor and direction. These findings highlight the diversity in visuomotor strategies among teleost species with shared circuit motifs, establishing a framework for unraveling the neural mechanisms driving continuous and discrete locomotion.

Cerebellar Purkinje cells control posture in larval zebrafish (Danio rerio)

Cerebellar dysfunction leads to postural instability. Recent work in freely moving rodents has transformed investigations of cerebellar contributions to posture. However, the combined complexity of terrestrial locomotion and the rodent cerebellum motivate new approaches to perturb cerebellar function in simpler vertebrates. Here, we adapted a validated chemogenetic tool (TRPV1/capsaicin) to describe the role of Purkinje cells - the output neurons of the cerebellar cortex - as larval zebrafish swam freely in depth. We achieved both bidirectional control (activation and ablation) of Purkinje cells while performing quantitative high-throughput assessment of posture and locomotion. Activation modified postural control in the pitch (nose-up/nose-down) axis. Similarly, ablations disrupted pitch-axis posture and fin-body coordination responsible for climbs. Postural disruption was more widespread in older larvae, offering a window into emergent roles for the developing cerebellum in the control of posture. Finally, we found that activity in Purkinje cells could individually and collectively encode tilt direction, a key feature of postural control neurons. Our findings delineate an expected role for the cerebellum in postural control and vestibular sensation in larval zebrafish, establishing the validity of TRPV1/capsaicin-mediated perturbations in a simple, genetically tractable vertebrate. Moreover, by comparing the contributions of Purkinje cell ablations to posture in time, we uncover signatures of emerging cerebellar control of posture across early development. This work takes a major step towards understanding an ancestral role of the cerebellum in regulating postural maturation.

Separate brainstem circuits for fast steering and slow exploratory turns

Locomotion requires precise tuning of descending commands to scale turning movements, such as rapid steering during prey pursuit or shallow turns during exploration. We show that these two turn types are governed by distinct brainstem circuits. The rapid steering circuit involves excitatory V2a and inhibitory commissural V0d neurons, distributed across different brainstem nuclei. These neurons are coupled via gap junctions and activated simultaneously, ensuring rapid steering through asymmetrical activation of spinal motor neurons. The recruitment of this circuit correlates more with the degree of direction change than with locomotor frequency. Steering neurons are, in turn, controlled by a subset of V2a neurons in the pretectum, activated by salient visual input. In contrast, slow exploratory turns are governed by a separate set of V2a neurons confined to fewer brainstem nuclei. These findings reveal a modular organization of brainstem circuits that selectively control rapid steering and slow exploratory turning during locomotion.

Oxygen chemoreceptor inhibition by dopamine D2 receptors in isolated zebrafish gills

Dopamine is an essential modulator of oxygen sensing and control of ventilation and is the most well described and abundant neurotransmitter in the mammalian carotid body. Little is known of the evolutionary significance of dopamine in oxygen sensing, or whether it plays a similar role in anamniotes. In the model vertebrate, zebrafish (Danio rerio), presynaptic dopamine D2 receptor (D2R) expression was demonstrated in gill neuroepithelial cells (NECs), analogues of mammalian oxygen chemoreceptors; however, a mechanism for dopamine and D2R in the gills had not been defined. The present study tested the hypothesis that presynaptic D2Rs provide a feedback mechanism attenuating the chemoreceptor response to hypoxia. Using an isolated gill preparation from Tg(elavl3:GCaMP6s) zebrafish, we measured hypoxia-induced changes in intracellular Ca2+ concentration ([Ca2+]i) in NECs and postsynaptic neurons. Activation of D2R with dopamine or specific D2R agonist, quinpirole, decreased hypoxic responses in NECs; whereas D2R antagonist, domperidone, had the opposite effect. Addition of SQ22536, an adenylyl cyclase (AC) inhibitor, decreased the effect of hypoxia on [Ca2+]i, similar to dopamine. Activation of AC by forskolin partially recovered the suppressive effect of dopamine on the Ca2+ response to hypoxia. Furthermore, we demonstrate that the response to hypoxia in postsynaptic neurons was dependent upon innervation with NECs, and was subject to modulation by activation of presynaptic D2R. Our results provide the first evidence of neurotransmission of the hypoxic signal at the NEC-nerve synapse in the gill and suggest that a presynaptic, modulatory role for dopamine in oxygen sensing arose early in vertebrate evolution. KEY POINTS: For the first time, we present an experimental model that permits imaging of intracellular Ca2+ in identified oxygen chemoreceptors in zebrafish using GCaMP in a whole/intact sensing organ. The hypoxic response of zebrafish chemoreceptors is attenuated by dopamine through a mechanism involving D2 receptors and adenylyl cyclase. Zebrafish oxygen chemoreceptors send a hypoxic signal to postsynaptic (sensory) neurons. Postsynaptic neuronal responses to hypoxia are modulated by presynaptic D2 receptors, suggesting a link between chemoreceptor inhibition by dopamine and modulation of the hypoxic ventilatory response. Our results suggests that a modulatory role for dopamine in oxygen sensing arose early in vertebrate evolution.

Markov models bridge behavioral strategies and circuit principles facilitating thermoregulation

Behavioral thermoregulation is critical for survival across animals, including endothermic mammals. However, we do not understand how neural circuits control navigation towards preferred temperatures. Zebrafish exclusively regulate body temperature via behavior, making them ideal for studying thermal navigation. Here, we combine behavioral analysis, machine learning and calcium imaging to understand how larval zebrafish seek out preferred temperatures within thermal gradients. By developing a stimulus-controlled Markov model of thermal navigation we find that hot avoidance largely relies on the modulation of individual swim decisions. The avoidance of cold temperatures, a particular challenge in ectotherms, however relies on a deliberate strategy combining gradient alignment and directed reversals. Calcium imaging identified neurons within the medulla encoding thermal stimuli that form a place-code like representation of the gradient. Our findings establish a key link between neural activity and thermoregulatory behavior, elucidating the neural basis of how animals seek out preferred temperatures.

Whole-brain mapping in adult zebrafish and identification of the functional brain network underlying the novel tank test

Zebrafish have gained prominence as a model organism in neuroscience over the past several decades, generating key insight into the development and functioning of the vertebrate brain. However, techniques for whole brain mapping in adult stage zebrafish are lacking. Here, we describe a pipeline built using open-source tools for whole-brain activity mapping in adult zebrafish. Our pipeline combines advances in histology, microscopy, and machine learning to capture cfos activity across the entirety of the brain. Following tissue clearing, whole brain images are captured using light-sheet microscopy and registered to the recently created adult zebrafish brain atlas (AZBA) for automated segmentation. By way of example, we used our pipeline to measure brain activity after zebrafish were subject to the novel tank test, one of the most widely used behaviors in adult zebrafish. Cfos levels peaked 15 minutes following behavior and several regions, including those containing serotoninergic and dopaminergic neurons, were active during exploration. Finally, we generated a novel tank test functional brain network. This revealed that several regions of the subpallium form a cohesive sub-network during exploration. Functional interconnections between the subpallium and other regions appear to be mediated primarily by ventral nucleus of the ventral telencephalon (Vv), the olfactory bulb, and the anterior part of the parvocellular preoptic nucleus (PPa). Taken together, our pipeline enables whole-brain activity mapping in adult zebrafish while providing insight into neural basis for the novel tank test.Significance statement Zebrafish have grown in popularity as a model organism over the past several decades due to their low cost, ease of genetic manipulation, and similarity to other vertebrates like humans and rodents. However, to date, tools for whole-brain mapping in adult stage animals has been lacking. Here, we present an open-source pipeline for whole-brain mapping in adult zebrafish. We demonstrate the use of our pipeline by generating a functional brain network for one of the most widely used behavioral assays in adult zebrafish, the novel tank test. We found that exploration of a novel tank engages the olfactory bulb and a network of subpallial regions that correspond to the mammalian subpallial amygdala and basal ganglia.

Optogenetic interrogation of the lateral-line sensory system reveals mechanisms of pattern separation in the zebrafish brain

The ability of animals to interact with their environment hinges on the brain's capacity to distinguish between patterns of sensory information and accurately attribute them to specific sensory organs. The mechanisms by which neuronal circuits discriminate and encode the source of sensory signals remain elusive. To address this, we utilized as a model the posterior lateral line system of larval zebrafish, which is used to detect water currents. This system comprises a series of mechanosensory organs called neuromasts, which are innervated by neurons from the posterior lateral line ganglion. By combining single-neuromast optogenetic stimulation with whole-brain calcium imaging, we developed a novel approach to investigate how inputs from neuromasts are processed. Upon stimulating individual neuromasts, we observed that neurons in the brain of the zebrafish show diverse selectivity properties despite a lack of topographic organization in second-order circuits. We further demonstrated that complex combinations of neuromast stimulation are represented by sparse ensembles of neurons within the medial octavolateralis nucleus (MON) and found that neuromast input can be integrated nonlinearly. Our approach offers an innovative method for spatiotemporally interrogating the zebrafish lateral line system and presents a valuable model for studying whole-brain sensory encoding.

Ketamine induces plasticity in a norepinephrine-astroglial circuit to promote behavioral perseverance

Transient exposure to ketamine can trigger lasting changes in behavior and mood. We found that brief ketamine exposure causes long-term suppression of futility-induced passivity in larval zebrafish, reversing the "giving-up" response that normally occurs when swimming fails to cause forward movement. Whole-brain imaging revealed that ketamine hyperactivates the norepinephrine-astroglia circuit responsible for passivity. After ketamine washout, this circuit exhibits hyposensitivity to futility, leading to long-term increased perseverance. Pharmacological, chemogenetic, and optogenetic manipulations show that norepinephrine and astrocytes are necessary and sufficient for ketamine's long-term perseverance-enhancing aftereffects. In vivo calcium imaging revealed that astrocytes in adult mouse cortex are similarly activated during futility in the tail suspension test and that acute ketamine exposure also induces astrocyte hyperactivation. The cross-species conservation of ketamine's modulation of noradrenergic-astroglial circuits and evidence that plasticity in this pathway can alter the behavioral response to futility hold promise for identifying new strategies to treat affective disorders.

Subsets of extraocular motoneurons produce kinematically distinct saccades during hunting and exploration

Animals construct diverse behavioral repertoires by moving a limited number of body parts with varied kinematics and patterns of coordination. There is evidence that distinct movements can be generated by changes in activity dynamics within a common pool of motoneurons or by selectively engaging specific subsets of motoneurons in a task-dependent manner. However, in most cases, we have an incomplete understanding of the patterns of motoneuron activity that generate distinct actions and of how upstream premotor circuits select and assemble such motor programs. In this study, we used two closely related but kinematically distinct types of saccadic eye movement in larval zebrafish as a model to examine circuit control of movement diversity. In contrast to the prevailing view of a final common pathway, we found that in the oculomotor nucleus, distinct subsets of motoneurons were engaged for each saccade type. This type-specific recruitment was topographically organized and aligned with ultrastructural differences in motoneuron morphology and afferent synaptic innervation. Medially located motoneurons were active for both saccade types, and circuit tracing revealed a type-agnostic premotor pathway that appears to control their recruitment. By contrast, a laterally located subset of motoneurons was specifically active for hunting-associated saccades and received premotor input from pretectal hunting command neurons. Our data support a model in which generalist and action-specific premotor pathways engage distinct subsets of motoneurons to elicit varied movements of the same body part that subserve distinct behavioral functions.

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.

High resolution kinematic approach for quantifying impaired mobility of dystrophic zebrafish larvae

Dystrophin-deficient zebrafish larvae are a small, genetically tractable vertebrate model of Duchenne muscular dystrophy well suited for early stage therapeutic development. However, current approaches for evaluating their impaired mobility, a physiologically relevant therapeutic target, are characterized by low resolution and high variability. To address this, we used high speed videography and deep learning-based markerless motion capture to develop linked-segment models of larval escape response (ER) swimming. Kinematic models provided repeatable, high precision estimates of larval ER performance. Effect sizes for ER peak instantaneous acceleration and speed, final displacement, and ER distance were 2 to 3.5 standard deviations less for dystrophin-deficient mutants vs. wild-types. Further analysis revealed that mutants swam slower because of a reduction in their tail stroke frequency with little change in tail stroke amplitude. Kinematic variables were highly predictive of the dystrophic phenotype with ≤ 3% of larvae misclassified by random forest and support vector machine models. Tail kinematics also performed as well as in vitro assessments of tail muscle contractility in classifying larvae as mutants or wild-type, suggesting that ER kinematics could serve as a non-lethal proxy for direct measurements of muscle function. In summary, ER kinematics can be used as precise, physiologically relevant, non-lethal biomarkers of the dystrophic phenotype. The open-source approach described here may have applications not only for studies of skeletal muscle disease but for other disciplines that use larval mobility as an experimental outcome.

Divergent Visuomotor Strategies in Teleosts: Neural Circuit Mechanisms in Zebrafish and Danionella cerebrum

Many animals respond to sensory cues with species-specific coordinated movements to successfully navigate their environment. However, the neural mechanisms that support diverse sensorimotor transformations across species with distinct navigational strategies remain largely unexplored. By comparing related teleost species, zebrafish ( Danio rerio, ZF ) and Danionella cerebrum ( DC ), we investigated behavioral patterns and neural architectures during the visually guided optomotor response (OMR). Closed-loop behavioral tracking during visual stimulation revealed that larval ZF employ burst-and-glide locomotion, while larval DC display continuous, smooth swimming punctuated with sharp directional turns. Although DC achieve higher average speeds, they lack the direction-dependent velocity modulation observed in ZF . Whole-brain two-photon calcium imaging and tail tracking in head-fixed fish reveals that both species exhibit direction-selective motion encoding in homologous regions, including the retinorecipient pretectum, with DC exhibiting fewer binocular, direction-selective neurons overall. Kinematic analysis of head-fixed behavior reveals that DC sustain significantly longer directed swim events across all stimuli than ZF , highlighting the divergent visuomotor strategies, with ZF reducing tail movement duration in response to oblique, turn-inducing stimuli. Lateralized motor-associated neural activity in the medial and anterior hindbrain of both species suggests a shared circuit motif, with distinct neural circuits that independently control movement vigor and direction. These findings highlight the diversity in visuomotor strategies among teleost species, underscored by shared sensorimotor neural circuit motifs, and establish a robust framework for unraveling the neural mechanisms driving continuous and discrete visually guided locomotion, paving the way for deeper insights into vertebrate sensorimotor functions.

Research Highlights

Larval DC exhibit faster swimming than ZF , matching the direction of visual motion. DC execute OMR in smooth, curved swimming patterns, interspersed with sharp directional turns. ZF and DC share similar visuomotor neural architecture, recruiting pretectal and hindbrain regions. ZF and DC demonstrate lateralized encoding of turns, particularly in medial hindbrain neurons.

In Brief

Larval Danionella cerebrum respond to global visual motion cues in smooth, low-angle swimming patterns, interspersed with sharp directional turns, swimming consistently faster than zebrafish. Fouke et al. use behavioral tracking of freely moving and head fixed fish to reveal an evolutionarily conserved visuomotor neural architecture transforming visual motion cues into species-specific locomotor behaviors.

BIFROST: A method for registering diverse imaging datasets of the Drosophila brain

Imaging methods that span both functional measures in living tissue and anatomical measures in fixed tissue have played critical roles in advancing our understanding of the brain. However, making direct comparisons between different imaging modalities, particularly spanning living and fixed tissue, has remained challenging. For example, comparing brain-wide neural dynamics across experiments and aligning such data to anatomical resources, such as gene expression patterns or connectomes, requires precise alignment to a common set of anatomical coordinates. However, reaching this goal is difficult because registering in vivo functional imaging data to ex vivo reference atlases requires accommodating differences in imaging modality, microscope specification, and sample preparation. We overcome these challenges in Drosophila by building an in vivo reference atlas from multiphoton-imaged brains, called the Functional Drosophila Atlas. We then develop a registration pipeline, BrIdge For Registering Over Statistical Templates (BIFROST), for transforming neural imaging data into this common space and for importing ex vivo resources such as connectomes. Using genetically labeled cell types as ground truth, we demonstrate registration with a precision of less than 10 microns. Overall, BIFROST provides a pipeline for registering functional imaging datasets in the fly, both within and across experiments.

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.

Cerebellar Purkinje Cells Control Posture in Larval Zebrafish (Danio rerio)

Cerebellar dysfunction leads to postural instability. Recent work in freely moving rodents has transformed investigations of cerebellar contributions to posture. However, the combined complexity of terrestrial locomotion and the rodent cerebellum motivate new approaches to perturb cerebellar function in simpler vertebrates. Here, we adapted a validated chemogenetic tool (TRPV1/capsaicin) to describe the role of Purkinje cells - the output neurons of the cerebellar cortex - as larval zebrafish swam freely in depth. We achieved both bidirectional control (activation and ablation) of Purkinje cells while performing quantitative high-throughput assessment of posture and locomotion. Activation modified postural control in the pitch (nose-up/nose-down) axis. Similarly, ablations disrupted pitch-axis posture and fin-body coordination responsible for climbs. Postural disruption was more widespread in older larvae, offering a window into emergent roles for the developing cerebellum in the control of posture. Finally, we found that activity in Purkinje cells could individually and collectively encode tilt direction, a key feature of postural control neurons. Our findings delineate an expected role for the cerebellum in postural control and vestibular sensation in larval zebrafish, establishing the validity of TRPV1/capsaicin-mediated perturbations in a simple, genetically-tractable vertebrate. Moreover, by comparing the contributions of Purkinje cell ablations to posture in time, we uncover signatures of emerging cerebellar control of posture across early development. This work takes a major step towards understanding an ancestral role of the cerebellum in regulating postural maturation.

The recurrent temporal restricted Boltzmann machine captures neural assembly dynamics in whole-brain activity

Animal behaviour alternates between stochastic exploration and goal-directed actions, which are generated by the underlying neural dynamics. Previously, we demonstrated that the compositional Restricted Boltzmann Machine (cRBM) can decompose whole-brain activity of larval zebrafish data at the neural level into a small number (∼100-200) of assemblies that can account for the stochasticity of the neural activity (van der Plas et al., eLife, 2023). Here, we advance this representation by extending to a combined stochastic-dynamical representation to account for both aspects using the recurrent temporal RBM (RTRBM) and transfer-learning based on the cRBM estimate. We demonstrate that the functional advantage of the RTRBM is captured in the temporal weights on the hidden units, representing neural assemblies, for both simulated and experimental data. Our results show that the temporal expansion outperforms the stochastic-only cRBM in terms of generalization error and achieves a more accurate representation of the moments in time. Lastly, we demonstrate that we can identify the original time-scale of assembly dynamics by estimating multiple RTRBMs at different temporal resolutions. Together, we propose that RTRBMs are a valuable tool for capturing the combined stochastic and time-predictive dynamics of large-scale data sets.

Kinematically distinct saccades are used in a context-dependent manner by larval zebrafish

Saccades are rapid eye movements that are used by all species with good vision. In this study, we set out to characterize the complete repertoire of larval zebrafish horizontal saccades to gain insight into their contributions to visually guided behavior and underlying neural control. We identified five saccade types, defined by systematic differences in kinematics and binocular coordination, which were differentially expressed across a variety of behavioral contexts. Conjugate saccades formed a large group that serves at least four functions. These include fast phases of the optokinetic nystagmus, visual scanning in stationary animals, and shifting gaze in coordination with body turns. In addition, we discovered a previously undescribed pattern of eye-body coordination in which small conjugate saccades partially oppose head rotation to maintain gaze during forward locomotion. Convergent saccades were coordinated with body movements to foveate prey targets during hunting. Detailed kinematic analysis showed that conjugate and convergent saccades differed in the millisecond coordination of the eyes and body and followed distinct velocity main sequence relationships. This challenges the prevailing view that all horizontal saccades are controlled by a common brainstem circuit and instead indicates saccade-type-specific neural control.

Two-photon all-optical neurophysiology for the dissection of larval zebrafish brain functional and effective connectivity

One of the most audacious goals of modern neuroscience is unraveling the complex web of causal relations underlying the activity of neuronal populations on a whole-brain scale. This endeavor, which was prohibitive only a couple of decades ago, has recently become within reach owing to the advancements in optical methods and the advent of genetically encoded indicators/actuators. These techniques, applied to the translucent larval zebrafish have enabled recording and manipulation of the activity of extensive neuronal populations spanning the entire vertebrate brain. Here, we present a custom two-photon optical system that couples light-sheet imaging and 3D excitation with acousto-optic deflectors for simultaneous high-speed volumetric recording and optogenetic stimulation. By employing a zebrafish line with pan-neuronal expression of both the calcium reporter GCaMP6s and the red-shifted opsin ReaChR, we implemented a crosstalk-free, noninvasive all-optical approach and applied it to reconstruct the functional and effective connectivity of the left habenula.

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.

Norepinephrine changes behavioral state via astroglial purinergic signaling

Both neurons and glia communicate via diffusible neuromodulatory substances, but the substrates of computation in such neuromodulatory networks are unclear. During behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine drives fast excitation and delayed inhibition of behavior and circuit activity. We find that the inhibitory arm of this feedforward motif is implemented by astroglial purinergic signaling. Neuromodulator imaging, behavioral pharmacology, and perturbations of neurons and astroglia reveal that norepinephrine triggers astroglial release of adenosine triphosphate, extracellular conversion into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. This work, along with a companion piece by Lefton and colleagues demonstrating an analogous pathway mediating the effect of norepinephrine on synaptic connectivity in mice, identifies a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in norepinephrine-mediated behavioral and brain state transitions.

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.

BIFROST: a method for registering diverse imaging datasets of the Drosophila brain

The heterogeneity of brain imaging methods in neuroscience provides rich data that cannot be captured by a single technique, and our interpretations benefit from approaches that enable easy comparison both within and across different data types. For example, comparing brain-wide neural dynamics across experiments and aligning such data to anatomical resources, such as gene expression patterns or connectomes, requires precise alignment to a common set of anatomical coordinates. However, this is challenging because registering in vivo functional imaging data to ex vivo reference atlases requires accommodating differences in imaging modality, microscope specification, and sample preparation. We overcome these challenges in Drosophila by building an in vivo reference atlas from multiphoton-imaged brains, called the Functional Drosophila Atlas (FDA). We then develop a two-step pipeline, BrIdge For Registering Over Statistical Templates (BIFROST), for transforming neural imaging data into this common space and for importing ex vivo resources such as connectomes. Using genetically labeled cell types as ground truth, we demonstrate registration with a precision of less than 10 microns. Overall, BIFROST provides a pipeline for registering functional imaging datasets in the fly, both within and across experiments.

Significance

Large-scale functional imaging experiments in Drosophila have given us new insights into neural activity in various sensory and behavioral contexts. However, precisely registering volumetric images from different studies has proven challenging, limiting quantitative comparisons of data across experiments. Here, we address this limitation by developing BIFROST, a registration pipeline robust to differences across experimental setups and datasets. We benchmark this pipeline by genetically labeling cell types in the fly brain and demonstrate sub-10 micron registration precision, both across specimens and across laboratories. We further demonstrate accurate registration between in-vivo brain volumes and ultrastructural connectomes, enabling direct structure-function comparisons in future experiments.

Simultaneous, cortex-wide dynamics of up to 1 million neurons reveal unbounded scaling of dimensionality with neuron number

The brain's remarkable properties arise from the collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, can such low-dimensional representations truly explain the vast range of brain activity, and if not, what is the appropriate resolution and scale of recording to capture them? Imaging neural activity at cellular resolution and near-simultaneously across the mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number in populations up to 1 million neurons. Although half of the neural variance is contained within sixteen dimensions correlated with behavior, our discovered scaling of dimensionality corresponds to an ever-increasing number of neuronal ensembles without immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine grained and cortex wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.

Fast and sensitive GCaMP calcium indicators for neuronal imaging

We review the principles of development and deployment of genetically encoded calcium indicators (GECIs) for the detection of neural activity. Our focus is on the popular GCaMP family of green GECIs, culminating in the recent release of the jGCaMP8 sensors, with dramatically improved kinetics relative to previous generations. We summarize the properties of GECIs in multiple colour channels (blue, cyan, green, yellow, red, far-red) and highlight areas for further improvement. With their low-millisecond rise-times, the jGCaMP8 indicators allow new classes of experiments following neural activity in time frames approaching the underlying computations.

Network Statistics of the Whole-Brain Connectome of Drosophila

Brains comprise complex networks of neurons and connections. Network analysis applied to the wiring diagrams of brains can offer insights into how brains support computations and regulate information flow. The completion of the first whole-brain connectome of an adult Drosophila, the largest connectome to date, containing 130,000 neurons and millions of connections, offers an unprecedented opportunity to analyze its network properties and topological features. To gain insights into local connectivity, we computed the prevalence of two- and three-node network motifs, examined their strengths and neurotransmitter compositions, and compared these topological metrics with wiring diagrams of other animals. We discovered that the network of the fly brain displays rich club organization, with a large population (30% percent of the connectome) of highly connected neurons. We identified subsets of rich club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex and will serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

Mapping the neural dynamics of locomotion across the Drosophila brain

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

The preoptic area and dorsal habenula jointly support homeostatic navigation in larval zebrafish

Animals must maintain physiological processes within an optimal temperature range despite changes in their environment. Through behavioral assays, whole-brain functional imaging, and neural ablations, we show that larval zebrafish, an ectothermic vertebrate, achieves thermoregulation through homeostatic navigation-non-directional and directional movements toward the temperature closest to its physiological setpoint. A brain-wide circuit encompassing several brain regions enables this behavior. We identified the preoptic area of the hypothalamus (PoA) as a key brain structure in triggering non-directional reorientation when thermal conditions are worsening. This result shows an evolutionary conserved role of the PoA as principal thermoregulator of the brain also in ectotherms. We further show that the habenula (Hb)-interpeduncular nucleus (IPN) circuit retains a short-term memory of the sensory history to support the generation of coherent directed movements even in the absence of continuous sensory cues. We finally provide evidence that this circuit may not be exclusive for temperature but may convey a more abstract representation of relative valence of physiologically meaningful stimuli regardless of their specific identity to enable homeostatic navigation.

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number

The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.

Radial astrocyte synchronization modulates the visual system during behavioral-state transitions

Glial cells support the function of neurons. Recent evidence shows that astrocytes are also involved in brain computations. To explore whether and how their excitable nature affects brain computations and motor behaviors, we used two-photon Ca2+ imaging of zebrafish larvae expressing GCaMP in both neurons and radial astrocytes (RAs). We found that in the optic tectum, RAs synchronize their Ca2+ transients immediately after the end of an escape behavior. Using optogenetics, ablations, and a genetically encoded norepinephrine sensor, we observed that RA synchronous Ca2+ events are mediated by the locus coeruleus (LC)-norepinephrine circuit. RA synchronization did not induce direct excitation or inhibition of tectal neurons. Nevertheless, it modulated the direction selectivity and the long-distance functional correlations among neurons. This mechanism supports freezing behavior following a switch to an alerted state. These results show that LC-mediated neuro-glial interactions modulate the visual system during transitions between behavioral states.

Functional and pharmacological analyses of visual habituation learning in larval zebrafish

Habituation allows animals to learn to ignore persistent but inconsequential stimuli. Despite being the most basic form of learning, a consensus model on the underlying mechanisms has yet to emerge. To probe relevant mechanisms, we took advantage of a visual habituation paradigm in larval zebrafish, where larvae reduce their reactions to abrupt global dimming (a dark flash). We used Ca2+ imaging during repeated dark flashes and identified 12 functional classes of neurons that differ based on their rate of adaptation, stimulus response shape, and anatomical location. While most classes of neurons depressed their responses to repeated stimuli, we identified populations that did not adapt or that potentiated their response. These neurons were distributed across brain areas, consistent with a distributed learning process. Using a small-molecule screening approach, we confirmed that habituation manifests from multiple distinct molecular mechanisms, and we have implicated molecular pathways in habituation, including melatonin, oestrogen, and GABA signalling. However, by combining anatomical analyses and pharmacological manipulations with Ca2+ imaging, we failed to identify a simple relationship between pharmacology, altered activity patterns, and habituation behaviour. Collectively, our work indicates that habituation occurs via a complex and distributed plasticity processes that cannot be captured by a simple model. Therefore, untangling the mechanisms of habituation will likely require dedicated approaches aimed at sub-component mechanisms underlying this multidimensional learning process.

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.

Multisensory navigational strategies of hatchling fish for dispersal

Animals influence how they disperse in the environment by sensing local cues and adapting how they move. However, controlling dispersal can present a particular challenge early in life when animals tend to be more limited in their capacities to sense and move. To what extent and by what mechanisms can newly hatched fish control how they disperse? Here, we reveal hatchling sensorimotor mechanisms for controlling dispersal by combining swim tracking and precise sensory manipulations of a model species, zebrafish. In controlled laboratory experiments, if we physically constrained hatchlings or blocked sensations of motion through vision and the lateral line, hatchlings responded by elevating their buoyancy and passively moving with faster surface currents. Complementarily, in stagnant water, hatchlings covered more ground using hyperstable swimming, strongly orienting based on graviception. Using experimentally calibrated hydrodynamic simulations, we show that these hatchling behaviors nearly tripled diffusivity and made dispersal robust to local conditions, suggesting this multisensory strategy may provide important advantages for early life in a variable environment.

pi_tailtrack: A compact, inexpensive and open-source behaviour-tracking system for head-restrained zebrafish

Quantifying animal behaviour during microscopy is crucial to associate optically recorded neural activity with behavioural outputs and states. Here, I describe an imaging and tracking system for head-restrained larval zebrafish compatible with functional microscopy. This system is based on the Raspberry Pi computer, Pi NoIR camera and open-source software for the real-time tail segmentation and skeletonization of the zebrafish tail at over 100 Hz. This allows for precise and long-term analyses of swimming behaviour, which can be related to functional signals recorded in individual neurons. This system offers a simple but performant solution for quantifying the behaviour of head-restrained larval zebrafish, which can be built for 340€.

Optogenetic control of neural activity: The biophysics of microbial rhodopsins in neuroscience

Optogenetics, the use of microbial rhodopsins to make the electrical activity of targeted neurons controllable by light, has swept through neuroscience, enabling thousands of scientists to study how specific neuron types contribute to behaviors and pathologies, and how they might serve as novel therapeutic targets. By activating a set of neurons, one can probe what functions they can initiate or sustain, and by silencing a set of neurons, one can probe the functions they are necessary for. We here review the biophysics of these molecules, asking why they became so useful in neuroscience for the study of brain circuitry. We review the history of the field, including early thinking, early experiments, applications of optogenetics, pre-optogenetics targeted neural control tools, and the history of discovering and characterizing microbial rhodopsins. We then review the biophysical attributes of rhodopsins that make them so useful to neuroscience - their classes and structure, their photocycles, their photocurrent magnitudes and kinetics, their action spectra, and their ion selectivity. Our hope is to convey to the reader how specific biophysical properties of these molecules made them especially useful to neuroscientists for a difficult problem - the control of high-speed electrical activity, with great precision and ease, in the brain.

Compressive sensing of functional connectivity maps from patterned optogenetic stimulation of neuronal ensembles

Mapping functional connectivity between neurons is an essential step toward probing the neural computations mediating behavior. Accurately determining synaptic connectivity maps in populations of neurons is challenging in terms of yield, accuracy, and experimental time. Here, we developed a compressive sensing approach to reconstruct synaptic connectivity maps based on random two-photon cell-targeted optogenetic stimulation and membrane voltage readout of many putative postsynaptic neurons. Using a biophysical network model of interconnected populations of excitatory and inhibitory neurons, we characterized mapping recall and precision as a function of network observability, sparsity, number of neurons stimulated, off-target stimulation, synaptic reliability, propagation latency, and network topology. We found that mapping can be achieved with far fewer measurements than the standard pairwise sequential approach, with network sparsity and synaptic reliability serving as primary determinants of the performance. Our results suggest a rapid and efficient method to reconstruct functional connectivity of sparsely connected neuronal networks.

The mesencephalic locomotor region recruits V2a reticulospinal neurons to drive forward locomotion in larval zebrafish

The mesencephalic locomotor region (MLR) is a brain stem area whose stimulation triggers graded forward locomotion. How MLR neurons recruit downstream vsx2+ (V2a) reticulospinal neurons (RSNs) is poorly understood. Here, to overcome this challenge, we uncovered the locus of MLR in transparent larval zebrafish and show that the MLR locus is distinct from the nucleus of the medial longitudinal fasciculus. MLR stimulations reliably elicit forward locomotion of controlled duration and frequency. MLR neurons recruit V2a RSNs via projections onto somata in pontine and retropontine areas, and onto dendrites in the medulla. High-speed volumetric imaging of neuronal activity reveals that strongly MLR-coupled RSNs are active for steering or forward swimming, whereas weakly MLR-coupled medullary RSNs encode the duration and frequency of the forward component. Our study demonstrates how MLR neurons recruit specific V2a RSNs to control the kinematics of forward locomotion and suggests conservation of the motor functions of V2a RSNs across vertebrates.

Dimensionality reduction reveals separate translation and rotation populations in the zebrafish hindbrain

In many brain areas, neuronal activity is associated with a variety of behavioral and environmental variables. In particular, neuronal responses in the zebrafish hindbrain relate to oculomotor and swimming variables as well as sensory information. However, the precise functional organization of the neurons has been difficult to unravel because neuronal responses are heterogeneous. Here, we used dimensionality reduction methods on neuronal population data to reveal the role of the hindbrain in visually driven oculomotor behavior and swimming. We imaged neuronal activity in zebrafish expressing GCaMP6s in the nucleus of almost all neurons while monitoring the behavioral response to gratings that rotated with different speeds. We then used reduced-rank regression, a method that condenses the sensory and motor variables into a smaller number of "features," to predict the fluorescence traces of all ROIs (regions of interest). Despite the potential complexity of the visuo-motor transformation, our analysis revealed that a large fraction of the population activity can be explained by only two features. Based on the contribution of these features to each ROI's activity, ROIs formed three clusters. One cluster was related to vergent movements and swimming, whereas the other two clusters related to leftward and rightward rotation. Voxels corresponding to these clusters were segregated anatomically, with leftward and rightward rotation clusters located selectively to the left and right hemispheres, respectively. Just as described in many cortical areas, our analysis revealed that single-neuron complexity co-exists with a simpler population-level description, thereby providing insights into the organization of visuo-motor transformations in the hindbrain.

In situ assembly of bioresorbable organic bioelectronics in the brain

Bioelectronics can potentially complement classical therapies in nonchronic treatments, such as immunotherapy and cancer. In addition to functionality, minimally invasive implantation methods and bioresorbable materials are central to nonchronic treatments. The latter avoids the need for surgical removal after disease relief. Self-organizing substrate-free organic electrodes meet these criteria and integrate seamlessly into dynamic biological systems in ways difficult for classical rigid solid-state electronics. Here we place bioresorbable electrodes with a brain-matched shear modulus-made from water-dispersed nanoparticles in the brain-in the targeted area using a capillary thinner than a human hair. Thereafter, we show that an optional auxiliary module grows dendrites from the installed conductive structure to seamlessly embed neurons and modify the electrode's volume properties. We demonstrate that these soft electrodes set off a controlled cellular response in the brain when relaying external stimuli and that the biocompatible materials show no tissue damage after bioresorption. These findings encourage further investigation of temporary organic bioelectronics for nonchronic treatments assembled in vivo.

Using neuronal models to capture burst-and-glide motion and leadership in fish

While mathematical models, in particular self-propelled particle models, capture many properties of large fish schools, they do not always capture the interactions of smaller shoals. Nor do these models tend to account for the use of intermittent locomotion, often referred to as burst-and-glide, by many species. In this paper, we propose a model of social burst-and-glide motion by combining a well-studied model of neuronal dynamics, the FitzHugh-Nagumo model, with a model of fish motion. We first show that our model can capture the motion of a single fish swimming down a channel. Extending to a two-fish model, where visual stimulus of a neighbour affects the internal burst or glide state of the fish, we observe a rich set of dynamics found in many species. These include: leader-follower behaviour; periodic changes in leadership; apparently random (i.e. chaotic) leadership change; and tit-for-tat turn taking. Moreover, unlike previous studies where a randomness is required for leadership switching to occur, we show that this can instead be the result of deterministic interactions. We give several empirically testable predictions for how bursting fish interact and discuss our results in light of recently established correlations between fish locomotion and brain 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.

Early development of respiratory motor circuits in larval zebrafish (Danio rerio)

Rhythm-generating circuits in the vertebrate hindbrain form synaptic connections with cranial and spinal motor neurons, to generate coordinated, patterned respiratory behaviors. Zebrafish provide a uniquely tractable model system to investigate the earliest stages in respiratory motor circuit development in vivo. In larval zebrafish, respiratory behaviors are carried out by muscles innervated by cranial motor neurons-including the facial branchiomotor neurons (FBMNs), which innervate muscles that move the jaw, buccal cavity, and operculum. However, it is unclear when FBMNs first receive functional synaptic input from respiratory pattern-generating neurons, and how the functional output of the respiratory motor circuit changes across larval development. In the current study, we used behavior and calcium imaging to determine how early FBMNs receive functional synaptic inputs from respiratory pattern-generating networks in larval zebrafish. Zebrafish exhibited patterned operculum movements by 3 days postfertilization (dpf), though this behavior became more consistent at 4 and 5 dpf. Also by 3dpf, FBMNs fell into two distinct categories ("rhythmic" and "nonrhythmic"), based on patterns of neural activity. These two neuron categories were arranged differently along the dorsoventral axis, demonstrating that FBMNs have already established dorsoventral topography by 3 dpf. Finally, operculum movements were coordinated with pectoral fin movements at 3 dpf, indicating that the operculum behavioral pattern was driven by synaptic input. Taken together, this evidence suggests that FBMNs begin to receive initial synaptic input from a functional respiratory central pattern generator at or prior to 3 dpf. Future studies will use this model to study mechanisms of normal and abnormal respiratory circuit development.

Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second

Wide field of view microscopy that can resolve 3D information at high speed and spatial resolution is highly desirable for studying the behaviour of freely moving model organisms. However, it is challenging to design an optical instrument that optimises all these properties simultaneously. Existing techniques typically require the acquisition of sequential image snapshots to observe large areas or measure 3D information, thus compromising on speed and throughput. Here, we present 3D-RAPID, a computational microscope based on a synchronized array of 54 cameras that can capture high-speed 3D topographic videos over an area of 135 cm2, achieving up to 230 frames per second at spatiotemporal throughputs exceeding 5 gigapixels per second. 3D-RAPID employs a 3D reconstruction algorithm that, for each synchronized snapshot, fuses all 54 images into a composite that includes a co-registered 3D height map. The self-supervised 3D reconstruction algorithm trains a neural network to map raw photometric images to 3D topography using stereo overlap redundancy and ray-propagation physics as the only supervision mechanism. The resulting reconstruction process is thus robust to generalization errors and scales to arbitrarily long videos from arbitrarily sized camera arrays. We demonstrate the broad applicability of 3D-RAPID with collections of several freely behaving organisms, including ants, fruit flies, and zebrafish larvae.

Thalamic regulation of a visual critical period and motor behavior

During the visual critical period (CP), sensory experience refines the structure and function of visual circuits. The basis of this plasticity was long thought to be limited to cortical circuits, but recently described thalamic plasticity challenges this dogma and demonstrates greater complexity underlying visual plasticity. Yet how visual experience modulates thalamic neurons or how the thalamus modulates CP timing is incompletely understood. Using a larval zebrafish, thalamus-centric ocular dominance model, we show functional changes in the thalamus and a role of inhibitory signaling to establish CP timing using a combination of functional imaging, optogenetics, and pharmacology. Hemisphere-specific changes in genetically defined thalamic neurons correlate with changes in visuomotor behavior, establishing a role of thalamic plasticity in modulating motor performance. Our work demonstrates that visual plasticity is broadly conserved and that visual experience leads to neuron-level functional changes in the thalamus that require inhibitory signaling to establish critical period timing.

Thalamic neurons drive distinct forms of motor asymmetry that are conserved in teleost and dependent on visual evolution

Brain laterality is a prominent feature in Bilateria, where neural functions are favored in a single brain hemisphere. These hemispheric specializations are thought to improve behavioral performance and are commonly observed as sensory or motor asymmetries, such as handedness in humans. Despite its prevalence, our understanding of the neural and molecular substrates instructing functional lateralization is limited. Moreover, how functional lateralization is selected for or modulated throughout evolution is poorly understood. While comparative approaches offer a powerful tool for addressing this question, a major obstacle has been the lack of a conserved asymmetric behavior in genetically tractable organisms. Previously, we described a robust motor asymmetry in larval zebrafish. Following the loss of illumination, individuals show a persistent turning bias that is associated with search pattern behavior with underlying functional lateralization in the thalamus. This behavior permits a simple yet robust assay that can be used to address fundamental principles underlying lateralization in the brain across taxa. Here, we take a comparative approach and show that motor asymmetry is conserved across diverse larval teleost species, which have diverged over the past 200 million years. Using a combination of transgenic tools, ablation, and enucleation, we show that teleosts exhibit two distinct forms of motor asymmetry, vision-dependent and - independent. These asymmetries are directionally uncorrelated, yet dependent on the same subset of thalamic neurons. Lastly, we leverage Astyanax sighted and blind morphs, which show that fish with evolutionarily derived blindness lack both retinal-dependent and -independent motor asymmetries, while their sighted surface conspecifics retained both forms. Our data implicate that overlapping sensory systems and neuronal substrates drive functional lateralization in a vertebrate brain that are likely targets for selective modulation during evolution.

Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development

Mapping the eco-evolutionary factors shaping the development of animals' behavioural phenotypes remains a great challenge. Recent advances in 'big behavioural data' research-the high-resolution tracking of individuals and the harnessing of that data with powerful analytical tools-have vastly improved our ability to measure and model developing behavioural phenotypes. Applied to the study of behavioural ontogeny, the unfolding of whole behavioural repertoires can be mapped in unprecedented detail with relative ease. This overcomes long-standing experimental bottlenecks and heralds a surge of studies that more finely define and explore behavioural-experiential trajectories across development. In this review, we first provide a brief guide to state-of-the-art approaches that allow the collection and analysis of high-resolution behavioural data across development. We then outline how such approaches can be used to address key issues regarding the ecological and evolutionary factors shaping behavioural development: developmental feedbacks between behaviour and underlying states, early life effects and behavioural transitions, and information integration across development.

Brainstem circuits encoding start, speed, and duration of swimming in adult zebrafish

The flexibility of locomotor movements requires an accurate control of their start, duration, and speed. How brainstem circuits encode and convey these locomotor parameters remains unclear. Here, we have combined in vivo calcium imaging, electrophysiology, anatomy, and behavior in adult zebrafish to address these questions. We reveal that the detailed parameters of locomotor movements are encoded by two molecularly, topographically, and functionally segregated glutamatergic neuron subpopulations within the nucleus of the medial longitudinal fasciculus. The start, duration, and changes of locomotion speed are encoded by vGlut2⁺ neurons, whereas vGlut1⁺ neurons encode sudden changes to high speed/high amplitude movements. Ablation of vGlut2⁺ neurons compromised slow-explorative swimming, whereas vGlut1⁺ neuron ablation impaired fast swimming. Our results provide mechanistic insights into how separate brainstem subpopulations implement flexible locomotor commands. These two brainstem command subpopulations are suitably organized to integrate environmental cues and hence generate flexible swimming movements to match the animal's behavioral needs.

Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity

Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet, it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here, we recorded the activity from ∼40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven generative model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine (cRBM), unveils ∼200 neural assemblies, which compose neurophysiological circuits and whose various combinations form successive brain states. We then performed in silico perturbation experiments to determine the interregional functional connectivity, which is conserved across individual animals and correlates well with structural connectivity. Our results showcase how cRBMs can capture the coarse-grained organization of the zebrafish brain. Notably, this generative model can readily be deployed to parse neural data obtained by other large-scale recording techniques.

A brainstem integrator for self-location memory and positional homeostasis in zebrafish

To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation, but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation, we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through corrective swimming ("positional homeostasis"). Whole-brain functional imaging revealed a network in the medulla that stores a memory of location and induces an error signal in the inferior olive to drive future corrective swimming. Optogenetically manipulating medullary integrator cells evoked displacement-memory behavior. Ablating them, or downstream olivary neurons, abolished displacement corrections. These results reveal a multiregional hindbrain circuit in vertebrates that integrates self-motion and stores self-location to control locomotor behavior.

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.

Optokinetic set-point adaptation functions as an internal dynamic calibration mechanism for oculomotor disequilibrium

Experience-dependent brain circuit plasticity underlies various sensorimotor learning and memory processes. Recently, a novel set-point adaptation mechanism was identified that accounts for the pronounced negative optokinetic afternystagmus (OKAN) following a sustained period of unidirectional optokinetic nystagmus (OKN) in larval zebrafish. To investigate the physiological significance of optokinetic set-point adaptation, animals in the current study were exposed to a direction-alternating optokinetic stimulation paradigm that better resembles their visual experience in nature. Our results reveal that not only was asymmetric alternating stimulation sufficient to induce the set-point adaptation and the resulting negative OKAN, but most strikingly, under symmetric alternating stimulation some animals displayed an inherent bias of the OKN gain in one direction, and that was compensated by the similar set-point adaptation. This finding, supported by mathematical modeling, suggests that set-point adaptation allows animals to cope with asymmetric optokinetic behaviors evoked by either external stimuli or innate oculomotor biases.

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Optokinetic set-point adaptation reflects the temporal integration of visual input

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Wild-type zebrafish larvae may display innate optokinetic left-right asymmetries

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The degree of the optokinetic asymmetry among larvae is normally distributed

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The innate optokinetic asymmetry can be compensated by the set-point adaptation