Rapid whole brain imaging of neural activity in freely behaving larval zebrafish (Danio rerio)

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.

CRASH2p: Closed-loop Two Photon Imaging in Freely Moving Animals

Direct measurement of neural activity in freely moving animals is essential for understanding how the brain controls and represents behaviors. Genetically encoded calcium indicators report neural activity as changes in fluorescence intensity, but brain motion confounds quantitative measurement of fluorescence. Translation, rotation, and deformation of the brain and the movements of intervening scattering or auto-fluorescent tissue all alter the amount of fluorescent light captured by a microscope. Compared to single-photon approaches, two photon microscopy is less sensitive to scattering and off-target fluorescence, but more sensitive to motion, and two photon imaging has always required anchoring the microscope to the brain. We developed a closed-loop resonant axial-scanning high-speed two photon (CRASH2p) microscope for real-time 3D motion correction in unrestrained animals, without implantation of reference markers. We complemented CRASH2p with a novel scanning strategy and a multistage registration pipeline. We performed volumetric ratiometrically corrected functional imaging in the CNS of freely moving Drosophila larvae and discovered previously unknown neural correlates of behavior.

Vertebrates on a Chip: Noninvasive Electrical and Optical Mapping of Whole Brain Activity Associated with Pharmacological Treatments

Mapping brain activities is necessary for understanding brain physiology and discovering new treatments for neurological disorders. Such efforts have greatly benefited from the advancement in technologies for analyzing neural activity with improving temporal or spatial resolution. Here, we constructed a multielectrode array based brain activity mapping (BAM) system capable of stabilizing and orienting zebrafish larvae for recording electroencephalogram (EEG) like local field potential (LFP) signals and brain-wide calcium dynamics in awake zebrafish. Particularly, we designed a zebrafish trap chip that integrates with an eight-by-eight surface electrode array, so that brain electrophysiology can be noninvasively recorded in an agarose-free and anesthetic-free format with a high temporal resolution of 40 μs, matching the capability typically achieved by invasive LFP recording. Benefiting from the specially designed hybrid system, we can also conduct calcium imaging directly on immobilized awake larval zebrafish, which further supplies us with high spatial resolution brain-wide activity data. All of these innovations reconcile the limitations of sole LFP recording or calcium imaging, emphasizing a synergy of combining electrical and optical modalities within one unified device for activity mapping across a whole vertebrate brain with both improved spatial and temporal resolutions. The compatibility with in vivo drug treatment further makes it suitable for pharmacology studies based on multimodal measurement of brain-wide physiology.

Spatio-temporal brain invasion pattern of Streptococcus pneumoniae and dynamic changes in the cellular environment in bacteremia-derived meningitis

Streptococcus pneumoniae (the pneumococcus) is the major cause of bacterial meningitis globally, and pneumococcal meningitis is associated with increased risk of long-term neurological sequelae. These include several sensorimotor functions that are controlled by specific brain regions which, during bacterial meningitis, are damaged by a neuroinflammatory response and the deleterious action of bacterial toxins in the brain. However, little is known about the invasion pattern of the pneumococcus into the brain. Using a bacteremia-derived meningitis mouse model, we combined 3D whole brain imaging with brain microdissection to show that all brain regions were equally affected during disease progression, with the presence of pneumococci closely associated to the microvasculature. In the hippocampus, the invasion provoked microglial activation, while the neurogenic niche showed increased proliferation and migration of neuroblasts. Our results indicate that, even before the outbreak of symptoms, the bacterial load throughout the brain is high and causes neuroinflammation and cell death, a pathological scenario which ultimately leads to a failing regeneration of new neurons.

Long-term intravital subcellular imaging with confocal scanning light-field microscopy

Long-term observation of subcellular dynamics in living organisms is limited by background fluorescence originating from tissue scattering or dense labeling. Existing confocal approaches face an inevitable tradeoff among parallelization, resolution and phototoxicity. Here we present confocal scanning light-field microscopy (csLFM), which integrates axially elongated line-confocal illumination with the rolling shutter in scanning light-field microscopy (sLFM). csLFM enables high-fidelity, high-speed, three-dimensional (3D) imaging at near-diffraction-limit resolution with both optical sectioning and low phototoxicity. By simultaneous 3D excitation and detection, the excitation intensity can be reduced below 1 mW mm-2, with 15-fold higher signal-to-background ratio over sLFM. We imaged subcellular dynamics over 25,000 timeframes in optically challenging environments in different species, such as migrasome delivery in mouse spleen, retractosome generation in mouse liver and 3D voltage imaging in Drosophila. Moreover, csLFM facilitates high-fidelity, large-scale neural recording with reduced crosstalk, leading to high orientation selectivity to visual stimuli, similar to two-photon microscopy, which aids understanding of neural coding mechanisms.

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

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

Model-Based Explainable Deep Learning for Light-Field Microscopy Imaging

In modern neuroscience, observing the dynamics of large populations of neurons is a critical step of understanding how networks of neurons process information. Light-field microscopy (LFM) has emerged as a type of scanless, high-speed, three-dimensional (3D) imaging tool, particularly attractive for this purpose. Imaging neuronal activity using LFM calls for the development of novel computational approaches that fully exploit domain knowledge embedded in physics and optics models, as well as enabling high interpretability and transparency. To this end, we propose a model-based explainable deep learning approach for LFM. Different from purely data-driven methods, the proposed approach integrates wave-optics theory, sparse representation and non-linear optimization with the artificial neural network. In particular, the architecture of the proposed neural network is designed following precise signal and optimization models. Moreover, the network's parameters are learned from a training dataset using a novel training strategy that integrates layer-wise training with tailored knowledge distillation. Such design allows the network to take advantage of domain knowledge and learned new features. It combines the benefit of both model-based and learning-based methods, thereby contributing to superior interpretability, transparency and performance. By evaluating on both structural and functional LFM data obtained from scattering mammalian brain tissues, we demonstrate the capabilities of the proposed approach to achieve fast, robust 3D localization of neuron sources and accurate neural activity identification.

Connectome spectrum electromagnetic tomography: A method to reconstruct electrical brain source networks at high-spatial resolution

Connectome spectrum electromagnetic tomography (CSET) combines diffusion MRI-derived structural connectivity data with well-established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and two EEG datasets on visual-evoked potentials, we provide evidence supporting that (i) CSET captures realistic neurophysiological patterns with better accuracy than state-of-the-art methods, (ii) CSET can reconstruct brain responses more accurately and with more robustness to intrinsic noise in the EEG signal. These results demonstrate that CSET offers high spatio-temporal accuracy, enabling neuroscientists to extend their research beyond the current limitations of low sampling frequency in functional MRI and the poor spatial resolution of M/EEG.

Inhibitory control in teleost fish: a methodological and conceptual review

Inhibitory control (IC) plays a central role in behaviour control allowing an individual to resist external lures and internal predispositions. While IC has been consistently investigated in humans, other mammals, and birds, research has only recently begun to explore IC in other vertebrates. This review examines current literature on teleost fish, focusing on both methodological and conceptual aspects. I describe the main paradigms adopted to study IC in fish, identifying well-established tasks that fit various research applications and highlighting their advantages and limitations. In the conceptual analysis, I identify two well-developed lines of research with fish examining IC. The first line focuses on a comparative approach aimed to describe IC at the level of species and to understand the evolution of interspecific differences in relation to ecological specialisation, brain size, and factors affecting cognitive performance. Findings suggest several similarities between fish and previously studied vertebrates. The second line of research focuses on intraspecific variability of IC. Available results indicate substantial variation in fish IC related to sex, personality, genetic, age, and phenotypic plasticity, aligning with what is observed with other vertebrates. Overall, this review suggests that although data on teleosts are still scarce compared to mammals, the contribution of this group to IC research is already substantial and can further increase in various disciplines including comparative psychology, cognitive ecology, and neurosciences, and even in applied fields such as psychiatry research.

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

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

Light-field flow cytometry for high-resolution, volumetric and multiparametric 3D single-cell analysis

Imaging flow cytometry (IFC) combines flow cytometry and fluorescence microscopy to enable high-throughput, multiparametric single-cell analysis with rich spatial details. However, current IFC techniques remain limited in their ability to reveal subcellular information with a high 3D resolution, throughput, sensitivity, and instrumental simplicity. In this study, we introduce a light-field flow cytometer (LFC), an IFC system capable of high-content, single-shot, and multi-color acquisition of up to 5,750 cells per second with a near-diffraction-limited resolution of 400-600 nm in all three dimensions. The LFC system integrates optical, microfluidic, and computational strategies to facilitate the volumetric visualization of various 3D subcellular characteristics through convenient access to commonly used epi-fluorescence platforms. We demonstrate the effectiveness of LFC in assaying, analyzing, and enumerating intricate subcellular morphology, function, and heterogeneity using various phantoms and biological specimens. The advancement offered by the LFC system presents a promising methodological pathway for broad cell biological and translational discoveries, with the potential for widespread adoption in biomedical research.

Fast light-field 3D microscopy with out-of-distribution detection and adaptation through conditional normalizing flows

Real-time 3D fluorescence microscopy is crucial for the spatiotemporal analysis of live organisms, such as neural activity monitoring. The eXtended field-of-view light field microscope (XLFM), also known as Fourier light field microscope, is a straightforward, single snapshot solution to achieve this. The XLFM acquires spatial-angular information in a single camera exposure. In a subsequent step, a 3D volume can be algorithmically reconstructed, making it exceptionally well-suited for real-time 3D acquisition and potential analysis. Unfortunately, traditional reconstruction methods (like deconvolution) require lengthy processing times (0.0220 Hz), hampering the speed advantages of the XLFM. Neural network architectures can overcome the speed constraints but do not automatically provide a way to certify the realism of their reconstructions, which is essential in the biomedical realm. To address these shortcomings, this work proposes a novel architecture to perform fast 3D reconstructions of live immobilized zebrafish neural activity based on a conditional normalizing flow. It reconstructs volumes at 8 Hz spanning 512x512x96 voxels, and it can be trained in under two hours due to the small dataset requirements (50 image-volume pairs). Furthermore, normalizing flows provides a way to compute the exact likelihood of a sample. This allows us to certify whether the predicted output is in- or ood, and retrain the system when a novel sample is detected. We evaluate the proposed method on a cross-validation approach involving multiple in-distribution samples (genetically identical zebrafish) and various out-of-distribution ones.

High-resolution 3D imaging in light-field microscopy through Stokes matrices and data fusion

The trade-off between the lateral and vertical resolution has long posed challenges to the efficient and widespread application of Fourier light-field microscopy, a highly scalable 3D imaging tool. Although existing methods for resolution enhancement can improve the measurement result to a certain extent, they come with limitations in terms of accuracy and applicable specimen types. To address these problems, this paper proposed a resolution enhancement scheme utilizing data fusion of polarization Stokes vectors and light-field information for Fourier light-field microscopy system. By introducing the surface normal vector information obtained from polarization measurement and integrating it with the light-field 3D point cloud data, 3D reconstruction results accuracy is highly improved in axial direction. Experimental results with a Fourier light-field 3D imaging microscope demonstrated a substantial enhancement of vertical resolution with a depth resolution to depth of field ratio of 0.19%. This represented approximately 44 times the improvement compared to the theoretical ratio before data fusion, enabling the system to access more detailed information with finer measurement accuracy for test samples. This work not only provides a feasible solution for breaking the limitations imposed by traditional light-field microscope hardware configurations but also offers superior 3D measurement approach in a more cost-effective and practical manner.

All-optical interrogation of brain-wide activity in freely swimming larval zebrafish

We introduce an all-optical technique that enables volumetric imaging of brain-wide calcium activity and targeted optogenetic stimulation of specific brain regions in unrestrained larval zebrafish. The system consists of three main components: a 3D tracking module, a dual-color fluorescence imaging module, and a real-time activity manipulation module. Our approach uses a sensitive genetically encoded calcium indicator in combination with a long Stokes shift red fluorescence protein as a reference channel, allowing the extraction of Ca2+ activity from signals contaminated by motion artifacts. The method also incorporates rapid 3D image reconstruction and registration, facilitating real-time selective optogenetic stimulation of different regions of the brain. By demonstrating that selective light activation of the midbrain regions in larval zebrafish could reliably trigger biased turning behavior and changes of brain-wide neural activity, we present a valuable tool for investigating the causal relationship between distributed neural circuit dynamics and naturalistic behavior.

Simultaneous Behavioral and Neuronal Imaging by Tracking Microscopy

Tracking microscopy enables whole-brain cellular resolution imaging in freely swimming animals. This technique enables both structural and functional imaging without immobilizing the animal, and greatly expands the range of the behaviors accessible to neuroscientists. We use infrared imaging to track the target animal in a behavioral arena. Based on the predicted trajectory of the brain, we apply optimal control theory to a motorized stage system to cancel brain motion in three dimensions. We have combined this motion cancellation system with Differential Illumination Focal Filtering (DIFF), a form of structured illumination microscopy, which enables us to image the brain of a freely swimming larval zebrafish for over an hour. Here we describe the typical experimental procedure for data acquisition and processing using the tracking microscope.

Imaging the voltage of neurons distributed across entire brains of larval zebrafish

Neurons interact in networks distributed throughout the brain. Although much effort has focused on whole-brain calcium imaging, recent advances in genetically encoded voltage indicators (GEVIs) raise the possibility of imaging voltage of neurons distributed across brains. To achieve this, a microscope must image at high volumetric rate and signal-to-noise ratio. We present a remote scanning light-sheet microscope capable of imaging GEVI-expressing neurons distributed throughout entire brains of larval zebrafish at a volumetric rate of 200.8 Hz. We measured voltage of ∼1/3 of the neurons of the brain, distributed throughout. We observed that neurons firing at different times during a sequence were located at different brain locations, for sequences elicited by a visual stimulus, which mapped onto locations throughout the optic tectum, as well as during stimulus-independent bursts, which mapped onto locations in the cerebellum and medulla. Whole-brain voltage imaging may open up frontiers in the fundamental operation of neural systems.

A protocol for whole-brain Ca2+ imaging in Astyanax mexicanus, a model of comparative evolution

In this protocol, we describe a comparative approach to study the evolution of brain function in the Mexican tetra, Astyanax mexicanus. We developed surface fish and two independent populations of cavefish with pan-neuronal expression of the Ca2+ sensor GCaMP6s. We describe a methodology to prepare samples and image activity across the optic tectum and olfactory bulb.

Video-rate 3D imaging of living cells using Fourier view-channel-depth light field microscopy

Interrogation of subcellular biological dynamics occurring in a living cell often requires noninvasive imaging of the fragile cell with high spatiotemporal resolution across all three dimensions. It thereby poses big challenges to modern fluorescence microscopy implementations because the limited photon budget in a live-cell imaging task makes the achievable performance of conventional microscopy approaches compromise between their spatial resolution, volumetric imaging speed, and phototoxicity. Here, we incorporate a two-stage view-channel-depth (VCD) deep-learning reconstruction strategy with a Fourier light-field microscope based on diffractive optical element to realize fast 3D super-resolution reconstructions of intracellular dynamics from single diffraction-limited 2D light-filed measurements. This VCD-enabled Fourier light-filed imaging approach (F-VCD), achieves video-rate (50 volumes per second) 3D imaging of intracellular dynamics at a high spatiotemporal resolution of ~180 nm × 180 nm × 400 nm and strong noise-resistant capability, with which light field images with a signal-to-noise ratio (SNR) down to -1.62 dB could be well reconstructed. With this approach, we successfully demonstrate the 4D imaging of intracellular organelle dynamics, e.g., mitochondria fission and fusion, with ~5000 times of observation.

Utility of the Zebrafish Model for Studying Neuronal and Behavioral Disturbances Induced by Embryonic Exposure to Alcohol, Nicotine, and Cannabis

It is estimated that 5% of pregnant women consume drugs of abuse during pregnancy. Clinical research suggests that intake of drugs during pregnancy, such as alcohol, nicotine and cannabis, disturbs the development of neuronal systems in the offspring, in association with behavioral disturbances early in life and an increased risk of developing drug use disorders. After briefly summarizing evidence in rodents, this review focuses on the zebrafish model and its inherent advantages for studying the effects of embryonic exposure to drugs of abuse on behavioral and neuronal development, with an emphasis on neuropeptides known to promote drug-related behaviors. In addition to stimulating the expression and density of peptide neurons, as in rodents, zebrafish studies demonstrate that embryonic drug exposure has marked effects on the migration, morphology, projections, anatomical location, and peptide co-expression of these neurons. We also describe studies using advanced methodologies that can be applied in vivo in zebrafish: first, to demonstrate a causal relationship between the drug-induced neuronal and behavioral disturbances and second, to discover underlying molecular mechanisms that mediate these effects. The zebrafish model has great potential for providing important information regarding the development of novel and efficacious therapies for ameliorating the effects of early drug exposure.

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

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

Assessing Drug Administration Techniques in Zebrafish Models of Neurological Disease

Neurological diseases, including neurodegenerative and neurodevelopmental disorders, affect nearly one in six of the world's population. The burden of the resulting deaths and disability is set to rise during the next few decades as a consequence of an aging population. To address this, zebrafish have become increasingly prominent as a model for studying human neurological diseases and exploring potential therapies. Zebrafish offer numerous benefits, such as genetic homology and brain similarities, complementing traditional mammalian models and serving as a valuable tool for genetic screening and drug discovery. In this comprehensive review, we highlight various drug delivery techniques and systems employed for therapeutic interventions of neurological diseases in zebrafish, and evaluate their suitability. We also discuss the challenges encountered during this process and present potential advancements in innovative techniques.

Rapid automated 3-D pose estimation of larval zebrafish using a physical model-trained neural network

Quantitative ethology requires an accurate estimation of an organism's postural dynamics in three dimensions plus time. Technological progress over the last decade has made animal pose estimation in challenging scenarios possible with unprecedented detail. Here, we present (i) a fast automated method to record and track the pose of individual larval zebrafish in a 3-D environment, applicable when accurate human labeling is not possible; (ii) a rich annotated dataset of 3-D larval poses for ethologists and the general zebrafish and machine learning community; and (iii) a technique to generate realistic, annotated larval images in different behavioral contexts. Using a three-camera system calibrated with refraction correction, we record diverse larval swims under free swimming conditions and in response to acoustic and optical stimuli. We then employ a convolutional neural network to estimate 3-D larval poses from video images. The network is trained against a set of synthetic larval images rendered using a 3-D physical model of larvae. This 3-D model samples from a distribution of realistic larval poses that we estimate a priori using a template-based pose estimation of a small number of swim bouts. Our network model, trained without any human annotation, performs larval pose estimation three orders of magnitude faster and with accuracy comparable to the template-based approach, capturing detailed kinematics of 3-D larval swims. It also applies accurately to other datasets collected under different imaging conditions and containing behavioral contexts not included in our training.

Optimal sparsity allows reliable system-aware restoration of fluorescence microscopy images

Fluorescence microscopy is one of the most indispensable and informative driving forces for biological research, but the extent of observable biological phenomena is essentially determined by the content and quality of the acquired images. To address the different noise sources that can degrade these images, we introduce an algorithm for multiscale image restoration through optimally sparse representation (MIRO). MIRO is a deterministic framework that models the acquisition process and uses pixelwise noise correction to improve image quality. Our study demonstrates that this approach yields a remarkable restoration of the fluorescence signal for a wide range of microscopy systems, regardless of the detector used (e.g., electron-multiplying charge-coupled device, scientific complementary metal-oxide semiconductor, or photomultiplier tube). MIRO improves current imaging capabilities, enabling fast, low-light optical microscopy, accurate image analysis, and robust machine intelligence when integrated with deep neural networks. This expands the range of biological knowledge that can be obtained from fluorescence microscopy.

Network models to enhance the translational impact of cross-species studies

Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.

Volumetric live-cell autofluorescence imaging using Fourier light-field microscopy

This study introduces a rapid, volumetric live-cell imaging technique for visualizing autofluorescent sub-cellular structures and their dynamics by employing high-resolution Fourier light-field microscopy. We demonstrated this method by capturing lysosomal autofluorescence in fibroblasts and HeLa cells. Additionally, we conducted multicolor imaging to simultaneously observe lysosomal autofluorescence and fluorescently-labeled organelles such as lysosomes and mitochondria. We further analyzed the data to quantify the interactions between lysosomes and mitochondria. This research lays the foundation for future exploration of native cellular states and functions in three-dimensional environments, effectively reducing photodamage and eliminating the necessity for exogenous labels.

Multi-neuronal recording in unrestrained animals with all acousto-optic random-access line-scanning two-photon microscopy

To understand how neural activity encodes and coordinates behavior, it is desirable to record multi-neuronal activity in freely behaving animals. Imaging in unrestrained animals is challenging, especially for those, like larval Drosophila melanogaster, whose brains are deformed by body motion. A previously demonstrated two-photon tracking microscope recorded from individual neurons in freely crawling Drosophila larvae but faced limits in multi-neuronal recording. Here we demonstrate a new tracking microscope using acousto-optic deflectors (AODs) and an acoustic GRIN lens (TAG lens) to achieve axially resonant 2D random access scanning, sampling along arbitrarily located axial lines at a line rate of 70 kHz. With a tracking latency of 0.1 ms, this microscope recorded activities of various neurons in moving larval Drosophila CNS and VNC including premotor neurons, bilateral visual interneurons, and descending command neurons. This technique can be applied to the existing two-photon microscope to allow for fast 3D tracking and scanning.

Imaging Approaches to Investigate Pathophysiological Mechanisms of Brain Disease in Zebrafish

Zebrafish has become an essential model organism in modern biomedical research. Owing to its distinctive features and high grade of genomic homology with humans, it is increasingly employed to model diverse neurological disorders, both through genetic and pharmacological intervention. The use of this vertebrate model has recently enhanced research efforts, both in the optical technology and in the bioengineering fields, aiming at developing novel tools for high spatiotemporal resolution imaging. Indeed, the ever-increasing use of imaging methods, often combined with fluorescent reporters or tags, enable a unique chance for translational neuroscience research at different levels, ranging from behavior (whole-organism) to functional aspects (whole-brain) and down to structural features (cellular and subcellular). In this work, we present a review of the imaging approaches employed to investigate pathophysiological mechanisms underlying functional, structural, and behavioral alterations of human neurological diseases modeled in zebrafish.

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

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

Optical projection tomography of fluorescent microscopic specimens using lateral translation of tube lens

Optical projection tomography (OPT) is a three-dimensional (3D) fluorescence imaging technique, in which projection images are acquired for varying orientations of a sample using a large depth of field. OPT is typically applied to a millimeter-sized specimen, because the rotation of a microscopic specimen is challenging and not compatible with live cell imaging. In this Letter, we demonstrate fluorescence optical tomography of a microscopic specimen by laterally translating the tube lens of a wide-field optical microscope, which allows for high-resolution OPT without rotating the sample. The cost is the reduction of the field of view to about halfway along the direction of the tube lens translation. Using bovine pulmonary artery endothelial cells and 0.1 µm beads, we compare the 3D imaging performance of the proposed method with that of the conventional objective-focus scan method.

Virtual-scanning light-field microscopy for robust snapshot high-resolution volumetric imaging

High-speed three-dimensional (3D) intravital imaging in animals is useful for studying transient subcellular interactions and functions in health and disease. Light-field microscopy (LFM) provides a computational solution for snapshot 3D imaging with low phototoxicity but is restricted by low resolution and reconstruction artifacts induced by optical aberrations, motion and noise. Here, we propose virtual-scanning LFM (VsLFM), a physics-based deep learning framework to increase the resolution of LFM up to the diffraction limit within a snapshot. By constructing a 40 GB high-resolution scanning LFM dataset across different species, we exploit physical priors between phase-correlated angular views to address the frequency aliasing problem. This enables us to bypass hardware scanning and associated motion artifacts. Here, we show that VsLFM achieves ultrafast 3D imaging of diverse processes such as the beating heart in embryonic zebrafish, voltage activity in Drosophila brains and neutrophil migration in the mouse liver at up to 500 volumes per second.

Whole-brain imaging of freely-moving zebrafish

One of the holy grails of neuroscience is to record the activity of every neuron in the brain while an animal moves freely and performs complex behavioral tasks. While important steps forward have been taken recently in large-scale neural recording in rodent models, single neuron resolution across the entire mammalian brain remains elusive. In contrast the larval zebrafish offers great promise in this regard. Zebrafish are a vertebrate model with substantial homology to the mammalian brain, but their transparency allows whole-brain recordings of genetically-encoded fluorescent indicators at single-neuron resolution using optical microscopy techniques. Furthermore zebrafish begin to show a complex repertoire of natural behavior from an early age, including hunting small, fast-moving prey using visual cues. Until recently work to address the neural bases of these behaviors mostly relied on assays where the fish was immobilized under the microscope objective, and stimuli such as prey were presented virtually. However significant progress has recently been made in developing brain imaging techniques for zebrafish which are not immobilized. Here we discuss recent advances, focusing particularly on techniques based on light-field microscopy. We also draw attention to several important outstanding issues which remain to be addressed to increase the ecological validity of the results obtained.

Mesoscale volumetric light-field (MesoLF) imaging of neuroactivity across cortical areas at 18 Hz

Various implementations of mesoscopes provide optical access for calcium imaging across multi-millimeter fields of view in the mammalian brain; however, capturing the activity of the neuronal population within such fields of view near-simultaneously and in a volumetric fashion has remained challenging as approaches for imaging scattering brain tissues typically are based on sequential acquisition. Here we present a modular, mesoscale light-field (MesoLF) imaging hardware and software solution that allows recording from thousands of neurons within volumes of ⌀ 4 × 0.2 mm, located at up to 350 µm depth in the mouse cortex, at 18 volumes per second and an effective voxel rate of ~40 megavoxels per second. Using our optical design and computational approach we show recording of ~10,000 neurons across multiple cortical areas in mice using workstation-grade computing resources.

Mesoscale volumetric light field (MesoLF) imaging of neuroactivity across cortical areas at 18 Hz

Various implementations of mesoscopes provide optical access for calcium imaging across multi-millimeter fields-of-view (FOV) in the mammalian brain. However, capturing the activity of the neuronal population within such FOVs near-simultaneously and in a volumetric fashion has remained challenging since approaches for imaging scattering brain tissues typically are based on sequential acquisition. Here, we present a modular, mesoscale light field (MesoLF) imaging hardware and software solution that allows recording from thousands of neurons within volumes of 4000 × 200 μm, located at up to 400 μm depth in the mouse cortex, at 18 volumes per second. Our optical design and computational approach enable up to hour-long recording of ~10,000 neurons across multiple cortical areas in mice using workstation-grade computing resources.

Compact, Hybrid Light-Sheet and Fourier Light-Field Microscopy with a Single Objective for High-Speed Volumetric Imaging In Vivo

Volumetric imaging of biodynamics at high spatiotemporal resolutions in vivo is vital in biomedical studies, in which Fourier light field microscopy (FLFM) is a promising technique. However, the commonly used wide-field illumination strategy in FLFM introduces intense out of depth-of-field background, which not only degrades the image quality, but also introduces reconstruction artifacts. Employing light sheet illumination is an effective way to alleviate the background and reduce photobleaching in light-field microscopy. Unfortunately, the introduction of light-sheet illumination often requires an extra objective and precise alignment, which increases the system complexity. Here, we propose the compact, hybrid light-sheet and FLFM (CLS-FLFM), which uses only a single objective to achieve both light-sheet illumination and Fourier light-field imaging simultaneously. With a micromirror under the objective, we focus the light sheet, which ensures selective-volume-illumination, on the imaging plane of the FLFM to perform volumetric imaging. We demonstrate the superior performance of CLS-FLFM in inhibiting background in both structural and dynamical imaging of larval zebrafish in vivo. We envision that CLS-FLFM finds wide applications in high-speed, background-inhibited volumetric imaging of biodynamics in vivo.

A single-cell resolution gene expression atlas of the larval zebrafish brain

The advent of multimodal brain atlases promises to accelerate progress in neuroscience by allowing in silico queries of neuron morphology, connectivity, and gene expression. We used multiplexed fluorescent in situ RNA hybridization chain reaction (HCR) technology to generate expression maps across the larval zebrafish brain for a growing set of marker genes. The data were registered to the Max Planck Zebrafish Brain (mapzebrain) atlas, thus allowing covisualization of gene expression, single-neuron tracings, and expertly curated anatomical segmentations. Using post hoc HCR labeling of the immediate early gene cfos, we mapped responses to prey stimuli and food ingestion across the brain of freely swimming larvae. This unbiased approach revealed, in addition to previously described visual and motor areas, a cluster of neurons in the secondary gustatory nucleus, which express the marker calb2a, as well as a specific neuropeptide Y receptor, and project to the hypothalamus. This discovery exemplifies the power of this new atlas resource for zebrafish neurobiology.

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.

An optofluidic platform for interrogating chemosensory behavior and brainwide neural representation in larval zebrafish

Studying chemosensory processing desires precise chemical cue presentation, behavioral response monitoring, and large-scale neuronal activity recording. Here we present Fish-on-Chips, a set of optofluidic tools for highly-controlled chemical delivery while simultaneously imaging behavioral outputs and whole-brain neuronal activities at cellular resolution in larval zebrafish. These include a fluidics-based swimming arena and an integrated microfluidics-light sheet fluorescence microscopy (µfluidics-LSFM) system, both of which utilize laminar fluid flows to achieve spatiotemporally precise chemical cue presentation. To demonstrate the strengths of the platform, we used the navigation arena to reveal binasal input-dependent behavioral strategies that larval zebrafish adopt to evade cadaverine, a death-associated odor. The µfluidics-LSFM system enables sequential presentation of odor stimuli to individual or both nasal cavities separated by only ~100 µm. This allowed us to uncover brainwide neural representations of cadaverine sensing and binasal input summation in the vertebrate model. Fish-on-Chips is readily generalizable and will empower the investigation of neural coding in the chemical senses.

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.

Longitudinal in vivo imaging of adult Danionella cerebrum using standard confocal microscopy

Danionella cerebrum is a new vertebrate model that offers an exciting opportunity to visualize dynamic biological processes in intact adult animals. Key advantages of this model include its small size, life-long optical transparency, genetic amenability and short generation time. Establishing a reliable method for longitudinal in vivo imaging of adult D. cerebrum while maintaining viability will allow in-depth image-based studies of various processes involved in development, disease onset and progression, wound healing, and aging in an intact live animal. Here, a method for both prolonged and longitudinal confocal live imaging of adult D. cerebrum using custom-designed and 3D-printed imaging chambers is described. Two transgenic D. cerebrum lines were created to test the imaging system, i.e. Tg(mpeg1:dendra2) and Tg(kdrl:mCherry-caax). The first line was used to visualize macrophages and microglia, and the second for spatial registration. By using this approach, differences in immune cell morphology and behavior during homeostasis as well as in response to a stab wound or two-photon-induced brain injury were observed in intact adult fish over the course of several days.

Gigapixel imaging with a novel multi-camera array microscope

The dynamics of living organisms are organized across many spatial scales. However, current cost-effective imaging systems can measure only a subset of these scales at once. We have created a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution recording from multiple spatial scales simultaneously, ranging from structures that approach the cellular scale to large-group behavioral dynamics. By collecting data from up to 96 cameras, we computationally generate gigapixel-scale images and movies with a field of view over hundreds of square centimeters at an optical resolution of 18 µm. This allows us to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales, including larval zebrafish, fruit flies, nematodes, carpenter ants, and slime mold. Further, the MCAM architecture allows stereoscopic tracking of the z-position of organisms using the overlapping field of view from adjacent cameras. Overall, by removing the bottlenecks imposed by single-camera image acquisition systems, the MCAM provides a powerful platform for investigating detailed biological features and behavioral processes of small model organisms across a wide range of spatial scales.

Computational Analysis of Cardiac Contractile Function

PURPOSE OF REVIEW

Heart failure results in the high incidence and mortality all over the world. Mechanical properties of myocardium are critical determinants of cardiac function, with regional variations in myocardial contractility demonstrated within infarcted ventricles. Quantitative assessment of cardiac contractile function is therefore critical to identify myocardial infarction for the early diagnosis and therapeutic intervention.

RECENT FINDINGS

Current advancement of cardiac functional assessments is in pace with the development of imaging techniques. The methods tailored to advanced imaging have been widely used in cardiac magnetic resonance, echocardiography, and optical microscopy. In this review, we introduce fundamental concepts and applications of representative methods for each imaging modality used in both fundamental research and clinical investigations. All these methods have been designed or developed to quantify time-dependent 2-dimensional (2D) or 3D cardiac mechanics, holding great potential to unravel global or regional myocardial deformation and contractile function from end-systole to end-diastole. Computational methods to assess cardiac contractile function provide a quantitative insight into the analysis of myocardial mechanics during cardiac development, injury, and remodeling.

A review on the impacts of nanomaterials on neuromodulation and neurological dysfunction using a zebrafish animal model

Nanomaterials have been widely employed from industrial to medical fields due to their small sizes and versatile characteristics. However, nanomaterials can also induce unexpected adverse effects on health. In particular, exposure of the nervous system to nanomaterials can cause serious neurological dysfunctions and neurodegenerative diseases. A number of studies have adopted various animal models to evaluate the neurotoxic effects of nanomaterials. Among them, zebrafish has become an attractive animal model for neurotoxicological studies due to several advantages, including the well-characterized nervous system, efficient genome editing, convenient generation of transgenic lines, high-resolution in vivo imaging, and an array of behavioral assays. In this review, we summarize recent studies on the neurotoxicological effects of nanomaterials, particularly engineered nanomaterials and nanoplastics, using zebrafish and discuss key findings with advantages and limitations of the zebrafish model in neurotoxicological studies.

3D super-resolution live-cell imaging with radial symmetry and Fourier light-field microscopy

Live-cell imaging reveals the phenotypes and mechanisms of cellular function and their dysfunction that underscore cell physiology, development, and pathology. Here, we report a 3D super-resolution live-cell microscopy method by integrating radiality analysis and Fourier light-field microscopy (rad-FLFM). We demonstrated the method using various live-cell specimens, including actins in Hela cells, microtubules in mammary organoid cells, and peroxisomes in COS-7 cells. Compared with conventional wide-field microscopy, rad-FLFM realizes scanning-free, volumetric 3D live-cell imaging with sub-diffraction-limited resolution of ∼150 nm (x-y) and 300 nm (z), milliseconds volume acquisition time, six-fold extended depth of focus of ∼6 µm, and low photodamage. The method provides a promising avenue to explore spatiotemporal-challenging subcellular processes in a wide range of cell biological research.

Brain milieu induces early microglial maturation through the BAX-Notch axis

Microglia are derived from primitive myeloid cells and gain their early identity in the embryonic brains. However, the mechanism by which the brain milieu confers microglial maturation signature remains elusive. Here, we demonstrate that the bax^cq55 zebrafish and Bax^tm1Sjk mouse embryos exhibit similarly defective early microglial maturation. BAX, a typical pro-apoptotic factor, is highly enriched in neuronal cells and regulates microglial maturation through both pro-apoptotic and non-apoptotic mechanisms. BAX regulates dlb via the CaMKII-CREB axis calcium-dependently in living neurons while ensuring the efficient Notch activation in the immigrated pre-microglia by apoptotic neurons. Notch signaling is conserved in supporting embryonic microglia maturation. Compromised microglial development occurred in the Cx3cr1^Cre/+Rbpj^fl/fl embryonic mice; however, microglia acquire their appropriate signature when incubated with DLL3 in vitro. Thus, our findings elucidate a BAX-CaMKII-CREB-Notch network triggered by the neuronal milieu in microglial development, which may provide innovative insights for targeting microglia in neuronal disorder treatment.

Rapid detection and recognition of whole brain activity in a freely behaving Caenorhabditis elegans

Advanced volumetric imaging methods and genetically encoded activity indicators have permitted a comprehensive characterization of whole brain activity at single neuron resolution in Caenorhabditis elegans. The constant motion and deformation of the nematode nervous system, however, impose a great challenge for consistent identification of densely packed neurons in a behaving animal. Here, we propose a cascade solution for long-term and rapid recognition of head ganglion neurons in a freely moving C. elegans. First, potential neuronal regions from a stack of fluorescence images are detected by a deep learning algorithm. Second, 2-dimensional neuronal regions are fused into 3-dimensional neuron entities. Third, by exploiting the neuronal density distribution surrounding a neuron and relative positional information between neurons, a multi-class artificial neural network transforms engineered neuronal feature vectors into digital neuronal identities. With a small number of training samples, our bottom-up approach is able to process each volume—1024 × 1024 × 18 in voxels—in less than 1 second and achieves an accuracy of 91% in neuronal detection and above 80% in neuronal tracking over a long video recording. Our work represents a step towards rapid and fully automated algorithms for decoding whole brain activity underlying naturalistic behaviors.

An important question in neuroscience is to understand the relationship between brain dynamics and naturalistic behaviors when an animal is freely exploring its environment. In the last decade, it has become possible to genetically engineer animals whose neurons produce fluorescence reporters that change their brightness in response to brain activity. In small animals such as the nematode C. elegans, we can now record the fluorescence changes in and thereby infer neural activity from most neurons in the head of a worm, when the animal is freely moving. These neurons are densely packed in a small volume. Since the brain and body are moving and its shape undergoes significant deformation, a human expert, even after long hours of inspection, may still have difficulty to tell where the neurons are and who they are.

We sought to develop an automatic method for rapidly detecting and tracking most of these neurons in a moving animal. To do this, we asked a human expert to annotate all head neurons—their locations and digital identities—across a small number of volumes. Then, we trained a computer to learn the locations and digital identities of these neurons across different imaging volumes. Our machine inference method is fast and accurate. While it takes a human expert several hours to complete a sequence of volumes, a machine can finish the task in a few minutes. We hope our method provides a better and more efficient engine for extracting knowledge from whole brain imaging datasets and animal behaviors.

Comparing synthetic refocusing to deconvolution for the extraction of neuronal calcium transients from light fields

Significance: Light-field microscopy (LFM) enables fast, light-efficient, volumetric imaging of neuronal activity with calcium indicators. Calcium transients differ in temporal signal-to-noise ratio (tSNR) and spatial confinement when extracted from volumes reconstructed by different algorithms. Aim: We evaluated the capabilities and limitations of two light-field reconstruction algorithms for calcium fluorescence imaging. Approach: We acquired light-field image series from neurons either bulk-labeled or filled intracellularly with the red-emitting calcium dye CaSiR-1 in acute mouse brain slices. We compared the tSNR and spatial confinement of calcium signals extracted from volumes reconstructed with synthetic refocusing and Richardson-Lucy three-dimensional deconvolution with and without total variation regularization. Results: Both synthetic refocusing and Richardson-Lucy deconvolution resolved calcium signals from single cells and neuronal dendrites in three dimensions. Increasing deconvolution iteration number improved spatial confinement but reduced tSNR compared with synthetic refocusing. Volumetric light-field imaging did not decrease calcium signal tSNR compared with interleaved, widefield image series acquired in matched planes. Conclusions: LFM enables high-volume rate, volumetric imaging of calcium transients in single cell somata (bulk-labeled) and dendrites (intracellularly loaded). The trade-offs identified for tSNR, spatial confinement, and computational cost indicate which of synthetic refocusing or deconvolution can better realize the scientific requirements of future LFM calcium imaging applications.

Background inhibited and speed-loss-free volumetric imaging in vivo based on structured-illumination Fourier light field microscopy

Benefiting from its advantages in fast volumetric imaging for recording biodynamics, Fourier light field microscopy (FLFM) has a wide range of applications in biomedical research, especially in neuroscience. However, the imaging quality of the FLFM is always deteriorated by both the out-of-focus background and the strong scattering in biological samples. Here we propose a structured-illumination and interleaved-reconstruction based Fourier light field microscopy (SI-FLFM), in which we can filter out the background fluorescence in FLFM without sacrificing imaging speed. We demonstrate the superiority of our SI-FLFM in high-speed, background-inhibited volumetric imaging of various biodynamics in larval zebrafish and mice in vivo. The signal-to-background ratio (SBR) is improved by tens of times. And the volumetric imaging speed can be up to 40 Hz, avoiding artifacts caused by temporal under-sampling in conventional structured illumination microscopy. These suggest that our SI-FLFM is suitable for applications of weak fluorescence signals but high imaging speed requirements.

Volumetric optoacoustic neurobehavioral tracking of epileptic seizures in freely-swimming zebrafish larvae

Fast three-dimensional imaging of freely-swimming zebrafish is essential to understand the link between neuronal activity and behavioral changes during epileptic seizures. Studying the complex spatiotemporal patterns of neuronal activity at the whole-brain or -body level typically requires physical restraint, thus hindering the observation of unperturbed behavior. Here we report on real-time volumetric optoacoustic imaging of aberrant circular swimming activity and calcium transients in freely behaving zebrafish larvae, continuously covering their motion across an entire three-dimensional region. The high spatiotemporal resolution of the technique enables capturing ictal-like epileptic seizure events and quantifying their propagation speed, independently validated with simultaneous widefield fluorescence recordings. The work sets the stage for discerning functional interconnections between zebrafish behavior and neuronal activity for studying fundamental mechanisms of epilepsy and in vivo validation of treatment strategies.