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

Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience

Modern large-scale multineuronal recording methodologies, including multielectrode arrays, calcium imaging, and optogenetic techniques, produce single-neuron resolution data of a magnitude and precision that were the realm of science fiction twenty years ago. The major bottlenecks in systems and circuit neuroscience no longer lie in simply collecting data from large neural populations, but also in understanding this data: developing novel scientific questions, with corresponding analysis techniques and experimental designs to fully harness these new capabilities and meaningfully interrogate these questions. Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control-developed in lockstep with advances in experimental neurotechnology-promise major breakthroughs in multiple fundamental neuroscience problems. These trends are clear in a broad array of subfields of modern neuroscience; this review focuses on recent advances in methods for analyzing neural time-series data with single-neuronal precision.

Robust Depth Estimation for Light Field Microscopy

Light field technologies have seen a rise in recent years and microscopy is a field where such technology has had a deep impact. The possibility to provide spatial and angular information at the same time and in a single shot brings several advantages and allows for new applications. A common goal in these applications is the calculation of a depth map to reconstruct the three-dimensional geometry of the scene. Many approaches are applicable, but most of them cannot achieve high accuracy because of the nature of such images: biological samples are usually poor in features and do not exhibit sharp colors like natural scene. Due to such conditions, standard approaches result in noisy depth maps. In this work, a robust approach is proposed where accurate depth maps can be produced exploiting the information recorded in the light field, in particular, images produced with Fourier integral Microscope. The proposed approach can be divided into three main parts. Initially, it creates two cost volumes using different focal cues, namely correspondences and defocus. Secondly, it applies filtering methods that exploit multi-scale and super-pixels cost aggregation to reduce noise and enhance the accuracy. Finally, it merges the two cost volumes and extracts a depth map through multi-label optimization.

Visual Contrast Modulates Operant Learning Responses in Larval Zebrafish

The larval zebrafish is a promising vertebrate model organism to study neural mechanisms underlying learning and memory due to its small brain and rich behavioral repertoire. Here, we report on a high-throughput operant conditioning system for zebrafish larvae, which can simultaneously train 12 fish to associate a visual conditioned pattern with electroshocks. We find that the learning responses can be enhanced by the visual contrast, not the spatial features of the conditioned patterns, highlighted by several behavioral metrics. By further characterizing the learning curves as well as memory extinction, we demonstrate that the percentage of learners and the memory length increase as the conditioned pattern becomes darker. Finally, little difference in operant learning responses was found between AB wild-type fish and elavl3:H2B-GCaMP6f transgenic fish.

Scanless volumetric imaging by selective access multifocal multiphoton microscopy

Simultaneous, high-resolution imaging across a large number of synaptic and dendritic sites is critical for understanding how neurons receive and integrate signals. Yet, functional imaging that targets a large number of submicrometer-sized synaptic and dendritic locations poses significant technical challenges. We demonstrate a new parallelized approach to address such questions, increasing the signal-to-noise ratio by an order of magnitude compared to previous approaches. This selective access multifocal multiphoton microscopy uses a spatial light modulator to generate multifocal excitation in three dimensions (3D) and a Gaussian-Laguerre phase plate to simultaneously detect fluorescence from these spots throughout the volume. We test the performance of this system by simultaneously recording Ca2+ dynamics from cultured neurons at 98-118 locations distributed throughout a 3D volume. This is the first demonstration of 3D imaging in a "single shot" and permits synchronized monitoring of signal propagation across multiple different dendrites.

Detection and analysis of spatiotemporal patterns in brain activity

There is growing evidence that population-level brain activity is often organized into propagating waves that are structured in both space and time. Such spatiotemporal patterns have been linked to brain function and observed across multiple recording methodologies and scales. The ability to detect and analyze these patterns is thus essential for understanding the working mechanisms of neural circuits. Here we present a mathematical and computational framework for the identification and analysis of multiple classes of wave patterns in neural population-level recordings. By drawing a conceptual link between spatiotemporal patterns found in the brain and coherent structures such as vortices found in turbulent flows, we introduce velocity vector fields to characterize neural population activity. These vector fields are calculated for both phase and amplitude of oscillatory neural signals by adapting optical flow estimation methods from the field of computer vision. Based on these velocity vector fields, we then introduce order parameters and critical point analysis to detect and characterize a diverse range of propagating wave patterns, including planar waves, sources, sinks, spiral waves, and saddle patterns. We also introduce a novel vector field decomposition method that extracts the dominant spatiotemporal structures in a recording. This enables neural data to be represented by the activity of a small number of independent spatiotemporal modes, providing an alternative to existing dimensionality reduction techniques which separate space and time components. We demonstrate the capabilities of the framework and toolbox with simulated data, local field potentials from marmoset visual cortex and optical voltage recordings from whole mouse cortex, and we show that pattern dynamics are non-random and are modulated by the presence of visual stimuli. These methods are implemented in a MATLAB toolbox, which is freely available under an open-source licensing agreement.

Structured activity such as propagating wave patterns at the level of neural circuits can arise from highly variable firing activity of individual neurons. This property makes the brain, a quintessential example of a complex system, analogous to other complex physical systems such as turbulent fluids, in which structured patterns like vortices similarly emerge from molecules that behave irregularly. In this study, by uniquely adapting techniques for the identification of coherent structures in fluid turbulence, we develop new analytical and computational methods for the reliable detection of a diverse range of propagating wave patterns in large-scale neural recordings, for comprehensive analysis and visualization of these patterns, and for analysis of their dominant spatiotemporal modes. We demonstrate that these methods can be used to uncover the essential spatiotemporal properties of neural population activity recorded by different modalities, thus offering new insights into understanding the working mechanisms of neural systems.

All-optical imaging and manipulation of whole-brain neuronal activities in behaving larval zebrafish

All-optical interrogation of population neuron activity is a promising approach to deciphering the neural circuit mechanisms supporting brain functions. However, this interrogation is currently limited to local brain areas. Here, we incorporate patterned photo-stimulation into light-sheet microscopy, allowing simultaneous targeted optogenetic manipulation and brain-wide monitoring of the neuronal activities of head-restrained behaving larval zebrafish. Using this system, we photo-stimulate arbitrarily selected neurons (regions as small as ~10-20 neurons in 3D) in zebrafish larvae with pan-neuronal expression of a spectrally separated calcium indicator, GCaMP6f, and an activity actuator, ChrimsonR, and observe downstream neural circuit activation and behavior generation. This approach allows us to dissect the causal role of neural circuits in brain functions and behavior generation.

Prenatal Neuropathologies in Autism Spectrum Disorder and Intellectual Disability: The Gestation of a Comprehensive Zebrafish Model

Autism spectrum disorder (ASD) and intellectual disability (ID) are neurodevelopmental disorders with overlapping diagnostic behaviors and risk factors. These include embryonic exposure to teratogens and mutations in genes that have important functions prenatally. Animal models, including rodents and zebrafish, have been essential in delineating mechanisms of neuropathology and identifying developmental critical periods, when those mechanisms are most sensitive to disruption. This review focuses on how the developmentally accessible zebrafish is contributing to our understanding of prenatal pathologies that set the stage for later ASD-ID behavioral deficits. We discuss the known factors that contribute prenatally to ASD-ID and the recent use of zebrafish to model deficits in brain morphogenesis and circuit development. We conclude by suggesting that a future challenge in zebrafish ASD-ID modeling will be to bridge prenatal anatomical and physiological pathologies to behavioral deficits later in life.

Whole-Brain Calcium Imaging during Physiological Vestibular Stimulation in Larval Zebrafish

The vestibular apparatus provides animals with postural and movement-related information that is essential to adequately execute numerous sensorimotor tasks. In order to activate this sensory system in a physiological manner, one needs to macroscopically rotate or translate the animal's head, which in turn renders simultaneous neural recordings highly challenging. Here we report on a novel miniaturized, light-sheet microscope that can be dynamically co-rotated with a head-restrained zebrafish larva, enabling controlled vestibular stimulation. The mechanical rigidity of the microscope allows one to perform whole-brain functional imaging with state-of-the-art resolution and signal-to-noise ratio while imposing up to 25° in angular position and 6,000°/s² in rotational acceleration. We illustrate the potential of this novel setup by producing the first whole-brain response maps to sinusoidal and stepwise vestibular stimulation. The responsive population spans multiple brain areas and displays bilateral symmetry, and its organization is highly stereotypic across individuals. Using Fourier and regression analysis, we identified three major functional clusters that exhibit well-defined phasic and tonic response patterns to vestibular stimulation. Our rotatable light-sheet microscope provides a unique tool for systematically studying vestibular processing in the vertebrate brain and extends the potential of virtual-reality systems to explore complex multisensory and motor integration during simulated 3D navigation.

Recording Neural Activity in Unrestrained Animals with Three-Dimensional Tracking Two-Photon Microscopy

Optical recordings of neural activity in behaving animals can reveal the neural correlates of decision making, but brain motion, which often accompanies behavior, compromises these measurements. Two-photon point-scanning microscopy is especially sensitive to motion artifacts, and two-photon recording of activity has required rigid coupling between the brain and microscope. We developed a two-photon tracking microscope with extremely low-latency (360 μs) feedback implemented in hardware. This microscope can maintain continuous focus on neurons moving with velocities of 3 mm/s and accelerations of 1 m/s2 both in-plane and axially. We recorded calcium dynamics of motor neurons and inter-neurons in unrestrained freely behaving fruit fly larvae, correlating neural activity with stimulus presentations and behavioral outputs, and we measured light-induced depolarization of a visual interneuron in a moving animal using a genetically encoded voltage indicator. Our technique can be extended to stabilize recordings in a variety of moving substrates.

Brain-wide Organization of Neuronal Activity and Convergent Sensorimotor Transformations in Larval Zebrafish

Simultaneous recordings of large populations of neurons in behaving animals allow detailed observation of high-dimensional, complex brain activity. However, experimental approaches often focus on singular behavioral paradigms or brain areas. Here, we recorded whole-brain neuronal activity of larval zebrafish presented with a battery of visual stimuli while recording fictive motor output. We identified neurons tuned to each stimulus type and motor output and discovered groups of neurons in the anterior hindbrain that respond to different stimuli eliciting similar behavioral responses. These convergent sensorimotor representations were only weakly correlated to instantaneous motor activity, suggesting that they critically inform, but do not directly generate, behavioral choices. To catalog brain-wide activity beyond explicit sensorimotor processing, we developed an unsupervised clustering technique that organizes neurons into functional groups. These analyses enabled a broad overview of the functional organization of the brain and revealed numerous brain nuclei whose neurons exhibit concerted activity patterns.

Neuroplasticity in the acoustic startle reflex in larval zebrafish

Learning is essential for animal survival under changing environments. Even in its simplest form, learning involves interactions between a handful of neuronal circuits, hundreds of neurons and many thousand synapses. In this review I will focus on habituation - a form of non-associative learning during which organisms decrease their response to repetitions of identical sensory stimuli. I will discuss how recent studies of the acoustic startle reflex mediated by the Mauthner cell in the zebrafish larva are helping to understand the neuroplastic processes that underlie habituation. In addition to being a fascinating biological process, habituation is clinically relevant because it is affected in various neuropsychiatric disorders in humans, including autism, schizophrenia, Fragile-X and Tourette's syndromes.

Principles Governing Locomotion in Vertebrates: Lessons From Zebrafish

Locomotor behaviors are critical for survival and enable animals to navigate their environment, find food and evade predators. The circuits in the brain and spinal cord that initiate and maintain such different modes of locomotion in vertebrates have been studied in numerous species for over a century. In recent decades, the zebrafish has emerged as one of the main model systems for the study of locomotion, owing to its experimental amenability, and work in zebrafish has revealed numerous new insights into locomotor circuit function. Here, we review the literature that has led to our current understanding of the neural circuits controlling swimming and escape in zebrafish. We highlight recent studies that have enriched our comprehension of key topics, such as the interactions between premotor excitatory interneurons (INs) and motoneurons (MNs), supraspinal and spinal circuits that coordinate escape maneuvers, and developmental changes in overall circuit composition. We also discuss roles for neuromodulators and sensory inputs in modifying the relative strengths of constituent circuit components to provide flexibility in zebrafish behavior, allowing the animal to accommodate changes in the environment. We aim to provide a coherent framework for understanding the circuitry in the brain and spinal cord of zebrafish that allows the animal to flexibly transition between different speeds, and modes, of locomotion.

Multiscale light-sheet for rapid imaging of cardiopulmonary system

The ability to image tissue morphogenesis in real-time and in 3-dimensions (3-D) remains an optical challenge. The advent of light-sheet fluorescence microscopy (LSFM) has advanced developmental biology and tissue regeneration research. In this review, we introduce a LSFM system in which the illumination lens reshapes a thin light-sheet to rapidly scan across a sample of interest while the detection lens orthogonally collects the imaging data. This multiscale strategy provides deep-tissue penetration, high-spatiotemporal resolution, and minimal photobleaching and phototoxicity, allowing in vivo visualization of a variety of tissues and processes, ranging from developing hearts in live zebrafish embryos to ex vivo interrogation of the microarchitecture of optically cleared neonatal hearts. Here, we highlight multiple applications of LSFM and discuss several studies that have allowed better characterization of developmental and pathological processes in multiple models and tissues. These findings demonstrate the capacity of multiscale light-sheet imaging to uncover cardiovascular developmental and regenerative phenomena.

Three-dimensional behavioural phenotyping of freely moving C. elegans using quantitative light field microscopy

Behavioural phenotyping of model organisms is widely used to investigate fundamental aspects of organism biology, from the functioning of the nervous system to the effects of genetic mutations, as well as for screening new drug compounds. However, our capacity to observe and quantify the full range and complexity of behavioural responses is limited by the inability of conventional microscopy techniques to capture volumetric image information at sufficient speed. In this article we describe how combining light field microscopy with computational depth estimation provides a new method for fast, quantitative assessment of 3D posture and movement of the model organism Caenorhabditis elegans (C. elegans). We apply this technique to compare the behaviour of cuticle collagen mutants, finding significant differences in 3D posture and locomotion. We demonstrate the ability of quantitative light field microscopy to provide new fundamental insights into C. elegans locomotion by analysing the 3D postural modes of a freely swimming worm. Finally, we consider relative merits of the method and its broader application for phenotypic imaging of other organisms and for other volumetric bioimaging applications.

A Guide to Emerging Technologies for Large-Scale and Whole-Brain Optical Imaging of Neuronal Activity

The mammalian brain is a densely interconnected network that consists of millions to billions of neurons. Decoding how information is represented and processed by this neural circuitry requires the ability to capture and manipulate the dynamics of large populations at high speed and high resolution over a large area of the brain. Although the use of optical approaches by the neuroscience community has rapidly increased over the past two decades, most microscopy approaches are unable to record the activity of all neurons comprising a functional network across the mammalian brain at relevant temporal and spatial resolutions. In this review, we survey the recent development in optical technologies for Ca2+ imaging in this regard and provide an overview of the strengths and limitations of each modality and its potential for scalability. We provide guidance from the perspective of a biological user driven by the typical biological applications and sample conditions. We also discuss the potential for future advances and synergies that could be obtained through hybrid approaches or other modalities.

Opportunities and challenges for using the zebrafish to study neuronal connectivity as an endpoint of developmental neurotoxicity

Chemical exposures have been implicated as environmental risk factors that interact with genetic susceptibilities to influence individual risk for complex neurodevelopmental disorders, including autism spectrum disorder, schizophrenia, attention deficit hyperactivity disorder and intellectual disabilities. Altered patterns of neuronal connectivity represent a convergent mechanism of pathogenesis for these and other neurodevelopmental disorders, and growing evidence suggests that chemicals can interfere with specific signaling pathways that regulate the development of neuronal connections. There is, therefore, a growing interest in developing screening platforms to identify chemicals that alter neuronal connectivity. Cell-cell, cell-matrix interactions and systemic influences are known to be important in defining neuronal connectivity in the developing brain, thus, a systems-based model offers significant advantages over cell-based models for screening chemicals for effects on neuronal connectivity. The embryonic zebrafish represents a vertebrate model amenable to higher throughput chemical screening that has proven useful in characterizing conserved mechanisms of neurodevelopment. Moreover, the zebrafish is readily amenable to gene editing to integrate genetic susceptibilities. Although use of the zebrafish model in toxicity testing has increased in recent years, the diverse tools available for imaging structural differences in the developing zebrafish brain have not been widely applied to studies of the influence of gene by environment interactions on neuronal connectivity in the developing zebrafish brain. Here, we discuss tools available for imaging of neuronal connectivity in the developing zebrafish, review what has been published in this regard, and suggest a path forward for applying this information to developmental neurotoxicity testing.

High-speed 3D imaging of cellular activity in the brain using axially-extended beams and light sheets

As optical reporters and modulators of cellular activity have become increasingly sophisticated, the amount that can be learned about the brain via high-speed cellular imaging has increased dramatically. However, despite fervent innovation, point-scanning microscopy is facing a fundamental limit in achievable 3D imaging speeds and fields of view. A range of alternative approaches are emerging, some of which are moving away from point-scanning to use axially-extended beams or sheets of light, for example swept confocally aligned planar excitation (SCAPE) microscopy. These methods are proving effective for high-speed volumetric imaging of the nervous system of small organisms such as Drosophila (fruit fly) and D. Rerio (Zebrafish), and are showing promise for imaging activity in the living mammalian brain using both single and two-photon excitation. This article describes these approaches and presents a simple model that demonstrates key advantages of axially-extended illumination over point-scanning strategies for high-speed volumetric imaging, including longer integration times per voxel, improved photon efficiency and reduced photodamage.

Integrative whole-brain neuroscience in larval zebrafish

Due to their small size and transparency, zebrafish larvae are amenable to a range of fluorescence microscopy techniques. With the development of sensitive genetically encoded calcium indicators, this has extended to the whole-brain imaging of neural activity with cellular resolution. This technique has been used to study brain-wide population dynamics accompanying sensory processing and sensorimotor transformations, and has spurred the development of innovative closed-loop behavioral paradigms in which stimulus-response relationships can be studied. More recently, microscopes have been developed that allow whole-brain calcium imaging in freely swimming and behaving larvae. In this review, we highlight the technologies underlying whole-brain functional imaging in zebrafish, provide examples of the sensory and motor processes that have been studied with this technique, and discuss the need to merge data from whole-brain functional imaging studies with neurochemical and anatomical information to develop holistic models of functional neural circuits.

FIMic: design for ultimate 3D-integral microscopy of in-vivo biological samples

In this work, Fourier integral microscope (FIMic), an ultimate design of 3D-integral microscopy, is presented. By placing a multiplexing microlens array at the aperture stop of the microscope objective of the host microscope, FIMic shows extended depth of field and enhanced lateral resolution in comparison with regular integral microscopy. As FIMic directly produces a set of orthographic views of the 3D-micrometer-sized sample, it is suitable for real-time imaging. Following regular integral-imaging reconstruction algorithms, a 2.75-fold enhanced depth of field and [Formula: see text]-time better spatial resolution in comparison with conventional integral microscopy is reported. Our claims are supported by theoretical analysis and experimental images of a resolution test target, cotton fibers, and in-vivo 3D-imaging of biological specimens.

Quantifying behavior to solve sensorimotor transformations: advances from worms and flies

The development of new computational tools has recently opened up the study of natural behaviors at a precision that was previously unachievable. These tools permit a highly quantitative analysis of behavioral dynamics at timescales that are well matched to the timescales of neural activity. Here we examine how combining these methods with established techniques for estimating an animal's sensory experience presents exciting new opportunities for dissecting the sensorimotor transformations performed by the nervous system. We focus this review primarily on examples from Caenorhabditis elegans and Drosophila melanogaster-for these model systems, computational approaches to characterize behavior, in combination with unparalleled genetic tools for neural activation, silencing, and recording, have already proven instrumental for illuminating underlying neural mechanisms.