Whole-brain functional imaging with two-photon light-sheet microscopy

High-resolution tracking of unconfined zebrafish behavior reveals stimulatory and anxiolytic effects of psilocybin

Serotonergic psychedelics are emerging therapeutics for psychiatric disorders, yet their underlying mechanisms of action in the brain remain largely elusive. Here, we developed a wide-field behavioral tracking system for larval zebrafish and investigated the effects of psilocybin, a psychedelic serotonin receptor agonist. Machine learning analyses of precise body kinematics identified latent behavioral states reflecting spontaneous exploration, visually-driven rapid swimming, and irregular swim patterns following stress exposure. Using this method, we found that acute psilocybin treatment has two behavioral effects: [i] facilitation of spontaneous exploration ("stimulatory") and [ii] prevention of irregular swim patterns following stress exposure ("anxiolytic"). These effects differed from the effect of acute SSRI treatment and were rather similar to the effect of ketamine treatment. Neural activity imaging in the dorsal raphe nucleus suggested that psilocybin inhibits serotonergic neurons by activating local GABAergic neurons, consistent with psychedelic-induced suppression of serotonergic neurons in mammals. These findings pave the way for using larval zebrafish to elucidate neural mechanisms underlying the behavioral effects of serotonergic psychedelics.

More than double the fun with two-photon excitation microscopy

For generations researchers have been observing the dynamic processes of life through the lens of a microscope. This has offered tremendous insights into biological phenomena that span multiple orders of time- and length-scales ranging from the pure magic of molecular reorganization at the membrane of immune cells, to cell migration and differentiation during development or wound healing. Standard fluorescence microscopy techniques offer glimpses at such processes in vitro, however, when applied in intact systems, they are challenged by reduced signal strengths and signal-to-noise ratios that result from deeper imaging. As a remedy, two-photon excitation (TPE) microscopy takes a special place, because it allows us to investigate processes in vivo, in their natural environment, even in a living animal. Here, we review the fundamental principles underlying TPE aimed at basic and advanced microscopy users interested in adopting TPE for intravital imaging. We focus on applications in neurobiology, present current trends towards faster, wider and deeper imaging, discuss the combination with photon counting technologies for metabolic imaging and spectroscopy, as well as highlight outstanding issues and drawbacks in development and application of these methodologies.

Open-top Bessel beam two-photon light sheet microscopy for three-dimensional pathology

Nondestructive pathology based on three-dimensional (3D) optical microscopy holds promise as a complement to traditional destructive hematoxylin and eosin (H&E) stained slide-based pathology by providing cellular information in high throughput manner. However, conventional techniques provided superficial information only due to shallow imaging depths. Herein, we developed open-top two-photon light sheet microscopy (OT-TP-LSM) for intraoperative 3D pathology. An extended depth of field two-photon excitation light sheet was generated by scanning a nondiffractive Bessel beam, and selective planar imaging was conducted with cameras at 400 frames/s max during the lateral translation of tissue specimens. Intrinsic second harmonic generation was collected for additional extracellular matrix (ECM) visualization. OT-TP-LSM was tested in various human cancer specimens including skin, pancreas, and prostate. High imaging depths were achieved owing to long excitation wavelengths and long wavelength fluorophores. 3D visualization of both cells and ECM enhanced the ability of cancer detection. Furthermore, an unsupervised deep learning network was employed for the style transfer of OT-TP-LSM images to virtual H&E images. The virtual H&E images exhibited comparable histological characteristics to real ones. OT-TP-LSM may have the potential for histopathological examination in surgical and biopsy applications by rapidly providing 3D information.

Unraveling the Neural Circuits: Techniques, Opportunities and Challenges in Epilepsy Research

Epilepsy, a prevalent neurological disorder characterized by high morbidity, frequent recurrence, and potential drug resistance, profoundly affects millions of people globally. Understanding the microscopic mechanisms underlying seizures is crucial for effective epilepsy treatment, and a thorough understanding of the intricate neural circuits underlying epilepsy is vital for the development of targeted therapies and the enhancement of clinical outcomes. This review begins with an exploration of the historical evolution of techniques used in studying neural circuits related to epilepsy. It then provides an extensive overview of diverse techniques employed in this domain, discussing their fundamental principles, strengths, limitations, as well as their application. Additionally, the synthesis of multiple techniques to unveil the complexity of neural circuits is summarized. Finally, this review also presents targeted drug therapies associated with epileptic neural circuits. By providing a critical assessment of methodologies used in the study of epileptic neural circuits, this review seeks to enhance the understanding of these techniques, stimulate innovative approaches for unraveling epilepsy's complexities, and ultimately facilitate improved treatment and clinical translation for epilepsy.

Temporal focusing multiphoton microscopy with cross-modality multi-stage 3D U-Net for fast and clear bioimaging

Temporal focusing multiphoton excitation microscopy (TFMPEM) enables fast widefield biotissue imaging with optical sectioning. However, under widefield illumination, the imaging performance is severely degraded by scattering effects, which induce signal crosstalk and a low signal-to-noise ratio in the detection process, particularly when imaging deep layers. Accordingly, the present study proposes a cross-modality learning-based neural network method for performing image registration and restoration. In the proposed method, the point-scanning multiphoton excitation microscopy images are registered to the TFMPEM images by an unsupervised U-Net model based on a global linear affine transformation process and local VoxelMorph registration network. A multi-stage 3D U-Net model with a cross-stage feature fusion mechanism and self-supervised attention module is then used to infer in-vitro fixed TFMPEM volumetric images. The experimental results obtained for in-vitro drosophila mushroom body (MB) images show that the proposed method improves the structure similarity index measures (SSIMs) of the TFMPEM images acquired with a 10-ms exposure time from 0.38 to 0.93 and 0.80 for shallow- and deep-layer images, respectively. A 3D U-Net model, pretrained on in-vitro images, is further trained using a small in-vivo MB image dataset. The transfer learning network improves the SSIMs of in-vivo drosophila MB images captured with a 1-ms exposure time to 0.97 and 0.94 for shallow and deep layers, respectively.

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.

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.

Structural and functional imaging of brains

Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.

Practical considerations for quantitative light sheet fluorescence microscopy

Fluorescence microscopy has evolved from a purely observational tool to a platform for quantitative, hypothesis-driven research. As such, the demand for faster and less phototoxic imaging modalities has spurred a rapid growth in light sheet fluorescence microscopy (LSFM). By restricting the excitation to a thin plane, LSFM reduces the overall light dose to a specimen while simultaneously improving image contrast. However, the defining characteristics of light sheet microscopes subsequently warrant unique considerations in their use for quantitative experiments. In this Perspective, we outline many of the pitfalls in LSFM that can compromise analysis and confound interpretation. Moreover, we offer guidance in addressing these caveats when possible. In doing so, we hope to provide a useful resource for life scientists seeking to adopt LSFM to quantitatively address complex biological hypotheses.

Extended depth-of-field light-sheet microscopy improves imaging of large volumes at high numerical aperture

Light-sheet microscopes must compromise among field of view, optical sectioning, resolution, and detection efficiency. High-numerical-aperture (NA) detection objective lenses provide higher resolution, but their narrow depth of field inefficiently captures the fluorescence signal generated throughout the thickness of the illumination light sheet when imaging large volumes. Here, we present ExD-SPIM (extended depth-of-field selective-plane illumination microscopy), an improved light-sheet microscopy strategy that solves this limitation by extending the depth of field (DOF) of high-NA detection objectives to match the thickness of the illumination light sheet. This extension of the DOF uses a phase mask to axially stretch the point-spread function of the objective lens while largely preserving lateral resolution. This matching of the detection DOF to the illumination-sheet thickness increases the total fluorescence collection, reduces the background, and improves the overall signal-to-noise ratio (SNR), as shown by numerical simulations, imaging of bead phantoms, and imaging living animals. In comparison to conventional light sheet imaging with low-NA detection that yields equivalent DOF, the results show that ExD-SPIM increases the SNR by more than threefold and dramatically reduces the rate of photobleaching. Compared to conventional high-NA detection, ExD-SPIM improves the signal sensitivity and volumetric coverage of whole-brain activity imaging, increasing the number of detected neurons by over a third.

Single-shot Mueller-matrix imaging of zebrafish tissues: In vivo analysis of developmental and pathological features

Zebrafish is a well-established animal model for developmental and disease studies. Its optical transparency at early developmental stages allows in vivo tissues visualization. Interaction of polarized light with these tissues provides information on their structure and properties. This approach is effective for muscle tissue analysis due to its birefringence. To enable real-time Mueller-matrix characterization of unanesthetized fish, we assembled a microscope for single-shot Mueller-matrix imaging. First, we performed a continuous observation of 48 species within the period of 2 to 96 hpf and measured temporal dependencies of the polarization features in different tissues. These measurements show that hatching was accompanied by a sharp change in the angle and degree of linearly polarized light after interaction with muscles. Second, we analyzed nine species with skeletal disorders and demonstrated that the spatial distribution of light depolarization features clearly indicated them. Obtained results demonstrated that real-time Mueller-matrix imaging is a powerful tool for label-free monitoring zebrafish embryos.

Quantity as a Fish Views It: Behavior and Neurobiology

An ability to estimate quantities, such as the number of conspecifics or the size of a predator, has been reported in vertebrates. Fish, in particular zebrafish, may be instrumental in advancing the understanding of magnitude cognition. We review here the behavioral studies that have described the ecological relevance of quantity estimation in fish and the current status of the research aimed at investigating the neurobiological bases of these abilities. By combining behavioral methods with molecular genetics and calcium imaging, the involvement of the retina and the optic tectum has been documented for the estimation of continuous quantities in the larval and adult zebrafish brain, and the contributions of the thalamus and the dorsal-central pallium for discrete magnitude estimation in the adult zebrafish brain. Evidence for basic circuitry can now be complemented and extended to research that make use of transgenic lines to deepen our understanding of quantity cognition at genetic and molecular levels.

Single-shot quantitative aberration and scattering length measurements in mouse brain tissues using an extended-source Shack-Hartmann wavefront sensor

Deep fluorescence imaging in mammalian brain tissues remains challenging due to scattering and optical aberration-induced loss in signal and resolution. Correction of aberrations using adaptive optics (AO) requires their reliable measurement in the tissues. Here, we show that an extended-source Shack-Hartmann wavefront sensor (ESSH) allows quantitative aberration measurements through fixed brain slices with a thickness up to four times their scattering length. We demonstrate in particular that this wavefront measurement method based on image correlation is more robust to scattering compared to the standard centroid-based approach. Finally, we obtain a measurement of the tissue scattering length taking advantage of the geometry of a Shack-Hartmann sensor.

Fast whole-brain imaging of seizures in zebrafish larvae by two-photon light-sheet microscopy

Light-sheet fluorescence microscopy (LSFM) enables real-time whole-brain functional imaging in zebrafish larvae. Conventional one-photon LSFM can however induce undesirable visual stimulation due to the use of visible excitation light. The use of two-photon (2P) excitation, employing near-infrared invisible light, provides unbiased investigation of neuronal circuit dynamics. However, due to the low efficiency of the 2P absorption process, the imaging speed of this technique is typically limited by the signal-to-noise-ratio. Here, we describe a 2P LSFM setup designed for non-invasive imaging that enables quintuplicating state-of-the-art volumetric acquisition rate of the larval zebrafish brain (5 Hz) while keeping low the laser intensity on the specimen. We applied our system to the study of pharmacologically-induced acute seizures, characterizing the spatial-temporal dynamics of pathological activity and describing for the first time the appearance of caudo-rostral ictal waves (CRIWs).

Designs, applications, and limitations of genetically encoded fluorescent sensors to explore plant biology

The understanding of signaling and metabolic processes in multicellular organisms requires knowledge of the spatial dynamics of small molecules and the activities of enzymes, transporters, and other proteins in vivo, as well as biophysical parameters inside cells and across tissues. The cellular distribution of receptors, ligands, and activation state must be integrated with information about the cellular distribution of metabolites in relation to metabolic fluxes and signaling dynamics in order to achieve the promise of in vivo biochemistry. Genetically encoded sensors are engineered fluorescent proteins that have been developed for a wide range of small molecules, such as ions and metabolites, or to report biophysical processes, such as transmembrane voltage or tension. First steps have been taken to monitor the activity of transporters in vivo. Advancements in imaging technologies and specimen handling and stimulation have enabled researchers in plant sciences to implement sensor technologies in intact plants. Here, we provide a brief history of the development of genetically encoded sensors and an overview of the types of sensors available for quantifying and visualizing ion and metabolite distribution and dynamics. We further discuss the pros and cons of specific sensor designs, imaging systems, and sample manipulations, provide advice on the choice of technology, and give an outlook into future developments.

Visualizing the Invisible: Advanced Optical Microscopy as a Tool to Measure Biomechanical Forces

The importance of mechanical force in biology is evident across diverse length scales, ranging from tissue morphogenesis during embryo development to mechanotransduction across single adhesion proteins at the cell surface. Consequently, many force measurement techniques rely on optical microscopy to measure forces being applied by cells on their environment, to visualize specimen deformations due to external forces, or even to directly apply a physical perturbation to the sample via photoablation or optogenetic tools. Recent developments in advanced microscopy offer improved approaches to enhance spatiotemporal resolution, imaging depth, and sample viability. These advances can be coupled with already existing force measurement methods to improve sensitivity, duration and speed, amongst other parameters. However, gaining access to advanced microscopy instrumentation and the expertise necessary to extract meaningful insights from these techniques is an unavoidable hurdle. In this Live Cell Imaging special issue Review, we survey common microscopy-based force measurement techniques and examine how they can be bolstered by emerging microscopy methods. We further explore challenges related to the accompanying data analysis in biomechanical studies and discuss the various resources available to tackle the global issue of technology dissemination, an important avenue for biologists to gain access to pre-commercial instruments that can be leveraged for biomechanical studies.

Removing striping artifacts in light-sheet fluorescence microscopy: a review

In recent years, light-sheet fluorescence microscopy (LSFM) has found a broad application for imaging of diverse biological samples, ranging from sub-cellular structures to whole animals, both in-vivo and ex-vivo, owing to its many advantages relative to point-scanning methods. By providing the selective illumination of sample single planes, LSFM achieves an intrinsic optical sectioning and direct 2D image acquisition, with low out-of-focus fluorescence background, sample photo-damage and photo-bleaching. On the other hand, such an illumination scheme is prone to light absorption or scattering effects, which lead to uneven illumination and striping artifacts in the images, oriented along the light sheet propagation direction. Several methods have been developed to address this issue, ranging from fully optical solutions to entirely digital post-processing approaches. In this work, we present them, outlining their advantages, performance and limitations.

In vivo Functional Genomics for Undiagnosed Patients: The Impact of Small GTPases Signaling Dysregulation at Pan-Embryo Developmental Scale

While individually rare, disorders affecting development collectively represent a substantial clinical, psychological, and socioeconomic burden to patients, families, and society. Insights into the molecular mechanisms underlying these disorders are required to speed up diagnosis, improve counseling, and optimize management toward targeted therapies. Genome sequencing is now unveiling previously unexplored genetic variations in undiagnosed patients, which require functional validation and mechanistic understanding, particularly when dealing with novel nosologic entities. Functional perturbations of key regulators acting on signals' intersections of evolutionarily conserved pathways in these pathological conditions hinder the fine balance between various developmental inputs governing morphogenesis and homeostasis. However, the distinct mechanisms by which these hubs orchestrate pathways to ensure the developmental coordinates are poorly understood. Integrative functional genomics implementing quantitative in vivo models of embryogenesis with subcellular precision in whole organisms contribute to answering these questions. Here, we review the current knowledge on genes and mechanisms critically involved in developmental syndromes and pediatric cancers, revealed by genomic sequencing and in vivo models such as insects, worms and fish. We focus on the monomeric GTPases of the RAS superfamily and their influence on crucial developmental signals and processes. We next discuss the effectiveness of exponentially growing functional assays employing tractable models to identify regulatory crossroads. Unprecedented sophistications are now possible in zebrafish, i.e., genome editing with single-nucleotide precision, nanoimaging, highly resolved recording of multiple small molecules activity, and simultaneous monitoring of brain circuits and complex behavioral response. These assets permit accurate real-time reporting of dynamic small GTPases-controlled processes in entire organisms, owning the potential to tackle rare disease mechanisms.

Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging

An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas.

Real Time Generation of Three Dimensional Patterns for Multiphoton Stimulation

The advent of optogenetics has revolutionized experimental research in the field of Neuroscience and the possibility to selectively stimulate neurons in 3D volumes has opened new routes in the understanding of brain dynamics and functions. The combination of multiphoton excitation and optogenetic methods allows to identify and excite specific neuronal targets by means of the generation of cloud of excitation points. The most widely employed approach to produce the points cloud is through a spatial light modulation (SLM) which works with a refresh rate of tens of Hz. However, the computational time requested to calculate 3D patterns ranges between a few seconds and a few minutes, strongly limiting the overall performance of the system. The maximum speed of SLM can in fact be employed either with high quality patterns embedded into pre-calculated sequences or with low quality patterns for real time update. Here, we propose the implementation of a recently developed compressed sensing Gerchberg-Saxton algorithm on a consumer graphical processor unit allowing the generation of high quality patterns at video rate. This, would in turn dramatically reduce dead times in the experimental sessions, and could enable applications previously impossible, such as the control of neuronal network activity driven by the feedback from single neurons functional signals detected through calcium or voltage imaging or the real time compensation of motion artifacts.

Spatio-temporal parameters for optical probing of neuronal activity

The challenge to understand the complex neuronal circuit functions in the mammalian brain has brought about a revolution in light-based neurotechnologies and optogenetic tools. However, while recent seminal works have shown excellent insights on the processing of basic functions such as sensory perception, memory, and navigation, understanding more complex brain functions is still unattainable with current technologies. We are just scratching the surface, both literally and figuratively. Yet, the path towards fully understanding the brain is not totally uncertain. Recent rapid technological advancements have allowed us to analyze the processing of signals within dendritic arborizations of single neurons and within neuronal circuits. Understanding the circuit dynamics in the brain requires a good appreciation of the spatial and temporal properties of neuronal activity. Here, we assess the spatio-temporal parameters of neuronal responses and match them with suitable light-based neurotechnologies as well as photochemical and optogenetic tools. We focus on the spatial range that includes dendrites and certain brain regions (e.g., cortex and hippocampus) that constitute neuronal circuits. We also review some temporal characteristics of some proteins and ion channels responsible for certain neuronal functions. With the aid of the photochemical and optogenetic markers, we can use light to visualize the circuit dynamics of a functioning brain. The challenge to understand how the brain works continue to excite scientists as research questions begin to link macroscopic and microscopic units of brain circuits.

Fast in vivo multiphoton light-sheet microscopy with optimal pulse frequency

Improving the imaging speed of multiphoton microscopy is an active research field. Among recent strategies, light-sheet illumination holds distinctive advantages for achieving fast imaging in vivo. However, photoperturbation in multiphoton light-sheet microscopy remains poorly investigated. We show here that the heart beat rate of zebrafish embryos is a sensitive probe of linear and nonlinear photoperturbations. By analyzing its behavior with respect to laser power, pulse frequency and wavelength, we derive guidelines to find the best balance between signal and photoperturbation. We then demonstrate one order-of-magnitude signal enhancement over previous implementations by optimizing the laser pulse frequency. These results open new opportunities for fast live tissue imaging.

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

Experience influences behavior, but little is known about how experience is encoded in the brain, and how changes in neural activity are implemented at a network level to improve performance. Here we investigate how differences in experience impact brain circuitry and behavior in larval zebrafish prey capture. We find that experience of live prey compared to inert food increases capture success by boosting capture initiation. In response to live prey, animals with and without prior experience of live prey show activity in visual areas (pretectum and optic tectum) and motor areas (cerebellum and hindbrain), with similar visual area retinotopic maps of prey position. However, prey-experienced animals more readily initiate capture in response to visual area activity and have greater visually-evoked activity in two forebrain areas: the telencephalon and habenula. Consequently, disruption of habenular neurons reduces capture performance in prey-experienced fish. Together, our results suggest that experience of prey strengthens prey-associated visual drive to the forebrain, and that this lowers the threshold for prey-associated visual activity to trigger activity in motor areas, thereby improving capture performance.

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

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

Effects of excitation light polarization on fluorescence emission in two-photon light-sheet microscopy

Light-sheet microscopy (LSM) is a powerful imaging technique that uses a planar illumination oriented orthogonally to the detection axis. Two-photon (2P) LSM is a variant of LSM that exploits the 2P absorption effect for sample excitation. The light polarization state plays a significant, and often overlooked, role in 2P absorption processes. The scope of this work is to test whether using different polarization states for excitation light can affect the detected signal levels in 2P LSM imaging of typical biological samples with a spatially unordered dye population. Supported by a theoretical model, we compared the fluorescence signals obtained using different polarization states with various fluorophores (fluorescein, EGFP and GCaMP6s) and different samples (liquid solution and fixed or living zebrafish larvae). In all conditions, in agreement with our theoretical expectations, linear polarization oriented parallel to the detection plane provided the largest signal levels, while perpendicularly-oriented polarization gave low fluorescence signal with the biological samples, but a large signal for the fluorescein solution. Finally, circular polarization generally provided lower signal levels. These results highlight the importance of controlling the light polarization state in 2P LSM of biological samples. Furthermore, this characterization represents a useful guide to choose the best light polarization state when maximization of signal levels is needed, e.g. in high-speed 2P LSM.

Blind deconvolution for spike inference from fluorescence recordings

The parallel developments of genetically-encoded calcium indicators and fast fluorescence imaging techniques allows one to simultaneously record neural activity of extended neuronal populations in vivo. To fully harness the potential of functional imaging, one needs to infer the sequence of action potentials from fluorescence traces. Here we build on recently proposed computational approaches to develop a blind sparse deconvolution (BSD) algorithm based on a generative model for inferring spike trains from fluorescence traces. BSD features, (1) automatic (fully unsupervised) estimation of the hyperparameters, such as spike amplitude, noise level and rise and decay time constants, (2) a novel analytical estimate of the sparsity prior, which yields enhanced robustness and computational speed with respect to existing methods, (3) automatic thresholding for binarizing spikes that maximizes the precision-recall performance, (4) super-resolution capabilities increasing the temporal resolution beyond the fluorescence signal acquisition rate. BSD also uniquely provides theoretically-grounded estimates of the expected performance of the spike reconstruction in terms of precision-recall and temporal accuracy for each recording. The performance of the algorithm is established using synthetic data and through the SpikeFinder challenge, a community-based initiative for spike-rate inference benchmarking based on a collection of joint electrophysiological and fluorescence recordings. Our method outperforms classical sparse deconvolution algorithms in terms of robustness, speed and/or accuracy and performs competitively in the SpikeFinder challenge. This algorithm is modular, easy-to-use and made freely available. Its novel features can thus be incorporated in a straightforward way into existing calcium imaging packages.

Planar Airy beam light-sheet for two-photon microscopy

We demonstrate the first planar Airy light-sheet microscope. Fluorescence light-sheet microscopy has become the method of choice to study large biological samples with cellular or sub-cellular resolution. The propagation-invariant Airy beam enables a ten-fold increase in field-of-view with single-photon excitation; however, the characteristic asymmetry of the light-sheet limits its potential for multi-photon excitation. Here we show how a planar light-sheet can be formed from the curved propagation-invariant Airy beam. The resulting symmetric light sheet excites two-photon fluorescence uniformly across an extended field-of-view without the need for deconvolution. We demonstrate the method for rapid two-photon imaging of large volumes of neuronal tissue.

In vivo microstimulation with cathodic and anodic asymmetric waveforms modulates spatiotemporal calcium dynamics in cortical neuropil and pyramidal neurons of male mice

Electrical stimulation has been critical in the development of an understanding of brain function and disease. Despite its widespread use and obvious clinical potential, the mechanisms governing stimulation in the cortex remain largely unexplored in the context of pulse parameters. Modeling studies have suggested that modulation of stimulation pulse waveform may be able to control the probability of neuronal activation to selectively stimulate either cell bodies or passing fibers depending on the leading polarity. Thus, asymmetric waveforms with equal charge per phase (i.e., increasing the leading phase duration and proportionately decreasing the amplitude) may be able to activate a more spatially localized or distributed population of neurons if the leading phase is cathodic or anodic, respectively. Here, we use two-photon and mesoscale calcium imaging of GCaMP6s expressed in excitatory pyramidal neurons of male mice to investigate the role of pulse polarity and waveform asymmetry on the spatiotemporal properties of direct neuronal activation with 10-Hz electrical stimulation. We demonstrate that increasing cathodic asymmetry effectively reduces neuronal activation and results in a more spatially localized subpopulation of activated neurons without sacrificing the density of activated neurons around the electrode. Conversely, increasing anodic asymmetry increases the spatial spread of activation and highly resembles spatiotemporal calcium activity induced by conventional symmetric cathodic stimulation. These results suggest that stimulation polarity and asymmetry can be used to modulate the spatiotemporal dynamics of neuronal activity thus increasing the effective parameter space of electrical stimulation to restore sensation and study circuit dynamics.

Mapping astrocyte activity domains by light sheet imaging and spatio-temporal correlation screening

Astrocytes are a major type of glial cell in the mammalian brain, essentially regulating neuronal development and function. Quantitative imaging represents an important approach to study astrocytic signaling in neural circuits. Focusing on astrocytic Ca²⁺ activity, a key pathway implicated in astrocye-neuron interaction, we here report a strategy combining fast light sheet fluorescence microscopy (LSFM) and correlative screening-based time series analysis, to map activity domains in astrocytes in living mammalian nerve tissue. Light sheet of micron-scale thickness enables wide-field optical sectioning to image astrocytes in acute mouse brain slices. Using both chemical and genetically encoded Ca²⁺ indicators, we demonstrate the complementary advantages of LSFM in mapping Ca²⁺ domains in astrocyte populations as compared to epifluorescence and two-photon microscopy. Our approach then revealed distinct kinetics of Ca²⁺ signals between cortical and hypothalamic astrocytes in resting conditions and following the activation of adrenergic G protein coupled receptor (GPCR). This observation highlights the activity heterogeneity across regionally distinct astrocyte populations, and indicates the potential of our method for investigating dynamic signals in astrocytes.

A minimal constraint device for imaging nuclei in live Drosophila contractile larval muscles reveals novel nuclear mechanical dynamics

Muscle contractions produce reiterated cytoplasmic mechanical variations, which potentially influence nuclear mechanotransduction, however information regarding the dynamics of muscle nuclei (myonuclei) in the course of muscle contraction is still missing. Towards that end, a minimal constraint device was designed in which intact live Drosophila larva is imaged, while its muscles still contract. The device is placed under spinning disc confocal microscope enabling imaging of fluorescently labeled sarcomeres and nuclei during muscle contraction, without any external stimulation. As a proof of principle we studied myonuclei dynamics in wild-type, as well as in Nesprin/klar mutant larvae lacking proper nuclear-cytoskeletal connections. Myonuclei in control larvae exhibited comparable dynamics in the course of multiple contractile events, independent of their position along the muscle fiber. In contrast, myonuclei of mutant larvae displayed differential dynamics at distinct positions along individual myofibers. Moreover, we identified a linear link between myonuclear volume and its acceleration values during muscle contraction which, in Nesprin/klar mutants exhibited an opposite tendency relative to control. Estimation of the drag force applied on individual myonuclei revealed that force fluctuations in time, but not the average force, differed significantly between control and Nesprin/klar mutant, and were considerably higher in the mutant myonuclei. Taken together these results imply significant alterations in the mechanical dynamics of individual myonuclei in the Nesprin/klar myonuclei relative to control. Such differences provide novel mechanical insight into Nesprin function in contractile muscles, and might reveal the mechanical basis underlying Nesprin-related human diseases.

Genetically Encoded Tools for Research of Cell Signaling and Metabolism under Brain Hypoxia

Hypoxia is characterized by low oxygen content in the tissues. The central nervous system (CNS) is highly vulnerable to a lack of oxygen. Prolonged hypoxia leads to the death of brain cells, which underlies the development of many pathological conditions. Despite the relevance of the topic, different approaches used to study the molecular mechanisms of hypoxia have many limitations. One promising lead is the use of various genetically encoded tools that allow for the observation of intracellular parameters in living systems. In the first part of this review, we provide the classification of oxygen/hypoxia reporters as well as describe other genetically encoded reporters for various metabolic and redox parameters that could be implemented in hypoxia studies. In the second part, we discuss the advantages and disadvantages of the primary hypoxia model systems and highlight inspiring examples of research in which these experimental settings were combined with genetically encoded reporters.

Sleep Circuits and Physiology in Non-Mammalian Systems

Research over the last 20 years has firmly established the existence of sleep states across the animal kingdom. Work in non-mammalian animal models such as nematodes, fruit flies, and zebrafish has now uncovered many evolutionarily conserved aspects of sleep physiology and regulation, including shared circuit architecture, homeostatic and circadian control elements, and principles linking sleep physiology to function. Non-mammalian sleep research is now shedding light on fundamental aspects of the genetic and neuronal circuit regulation of sleep, with direct implications for the understanding of how sleep is regulated in mammals.

Whole-Brain Profiling of Cells and Circuits in Mammals by Tissue Clearing and Light-Sheet Microscopy

Tissue clearing and light-sheet microscopy have a 100-year-plus history, yet these fields have been combined only recently to facilitate novel experiments and measurements in neuroscience. Since tissue-clearing methods were first combined with modernized light-sheet microscopy a decade ago, the performance of both technologies has rapidly improved, broadening their applications. Here, we review the state of the art of tissue-clearing methods and light-sheet microscopy and discuss applications of these techniques in profiling cells and circuits in mice. We examine outstanding challenges and future opportunities for expanding these techniques to achieve brain-wide profiling of cells and circuits in primates and humans. Such integration will help provide a systems-level understanding of the physiology and pathology of our central nervous system.

A versatile, multi-laser twin-microscope system for light-sheet imaging

Light-sheet microscopy offers faster imaging and reduced phototoxicity in comparison to conventional point-scanning microscopy, making it a preferred technique for imaging biological dynamics for durations of hours or days. Such extended imaging sessions pose a challenge, as it reduces the number of specimens that can be imaged in a given day. Here, we present a versatile light-sheet imaging instrument that combines two independently controlled microscope-twins, built so that they can share an ultrafast near-infrared laser and a bank of continuous-wave visible lasers, increasing the throughput and decreasing the cost. To permit a wide variety of specimens to be imaged, each microscope-twin provides flexible imaging parameters, including (i) operation in one-photon and/or two-photon excitation modes, (ii) delivery of one to three light-sheets via a trio of orthogonal excitation arms, (iii) sub-micron to micron imaging resolution, (iv) multicolor compatibility, and (v) upright (with provision for inverted) detection geometry. We offer a detailed description of the twin-microscope design to aid instrument builders who wish to construct and use similar systems. We demonstrate the instrument's versatility for biological investigation by performing fast imaging of the beating heart in an intact zebrafish embryo, deep imaging of thick patient-derived tumor organoids, and gentle whole-brain imaging of neural activity in behaving larval zebrafish.

High-contrast, synchronous volumetric imaging with selective volume illumination microscopy

Light-field fluorescence microscopy uniquely provides fast, synchronous volumetric imaging by capturing an extended volume in one snapshot, but often suffers from low contrast due to the background signal generated by its wide-field illumination strategy. We implemented light-field-based selective volume illumination microscopy (SVIM), where illumination is confined to only the volume of interest, removing the background generated from the extraneous sample volume, and dramatically enhancing the image contrast. We demonstrate the capabilities of SVIM by capturing cellular-resolution 3D movies of flowing bacteria in seawater as they colonize their squid symbiotic partner, as well as of the beating heart and brain-wide neural activity in larval zebrafish. These applications demonstrate the breadth of imaging applications that we envision SVIM will enable, in capturing tissue-scale 3D dynamic biological systems at single-cell resolution, fast volumetric rates, and high contrast to reveal the underlying biology.

Thai Truong et al. present light-field-based selective volume illumination microscopy (SVIM), a method for enhancing image contrast and resolution by combining light-field microscopy and selective plane illumination microscopy. They generate cellular-resolution 3D movies by applying SVIM to flowing bacteria in seawater and to the beating heart and whole brain of larval zebrafish.

Cerebellar Neurodynamics Predict Decision Timing and Outcome on the Single-Trial Level

Goal-directed behavior requires the interaction of multiple brain regions. How these regions and their interactions with brain-wide activity drive action selection is less understood. We have investigated this question by combining whole-brain volumetric calcium imaging using light-field microscopy and an operant-conditioning task in larval zebrafish. We find global, recurring dynamics of brain states to exhibit pre-motor bifurcations toward mutually exclusive decision outcomes. These dynamics arise from a distributed network displaying trial-by-trial functional connectivity changes, especially between cerebellum and habenula, which correlate with decision outcome. Within this network the cerebellum shows particularly strong and predictive pre-motor activity (>10 s before movement initiation), mainly within the granule cells. Turn directions are determined by the difference neuroactivity between the ipsilateral and contralateral hemispheres, while the rate of bi-hemispheric population ramping quantitatively predicts decision time on the trial-by-trial level. Our results highlight a cognitive role of the cerebellum and its importance in motor planning.

In vivo imaging of calcium and glutamate responses to intracortical microstimulation reveals distinct temporal responses of the neuropil and somatic compartments in layer II/III neurons

OBJECTIVE

Intracortical microelectrode implants can generate a tissue response hallmarked by glial scarring and neuron cell death within 100-150 μm of the biomaterial device. Many have proposed that any performance decline in intracortical microstimulation (ICMS) due to this foreign body tissue response could be offset by increasing the stimulation amplitude. The mechanisms of this approach are unclear, however, as there has not been consensus on how increasing amplitude affects the spatial and temporal recruitment patterns of ICMS.

APPROACH

We clarify these unknowns using in vivo two-photon imaging of mice transgenically expressing the calcium sensor GCaMP6s in Thy1 neurons or virally expressing the glutamate sensor iGluSnFr in neurons. Calcium and neurotransmitter activity are tracked in the neuronal somas and neuropil during long-train stimulation in Layer II/III of somatosensory cortex.

MAIN RESULTS

Neural calcium activity and glutamate release are dense and strongest within 20-40 μm around the electrode, falling off with distance from the electrode. Neuronal calcium increases with higher amplitude stimulations. During prolonged stimulation trains, a sub-population of somas fail to maintain calcium activity. Interestingly, neuropil calcium activity is 3-fold less correlated to somatic calcium activity for cells that drop-out during the long stimulation train compared to cells that sustain activity throughout the train. Glutamate release is apparent only within 20 μm of the electrode and is sustained for at least 10s after cessation of the 15 and 20 μA stimulation train, but not lower amplitudes.

SIGNIFICANCE

These results demonstrate that increasing amplitude can increase the radius and intensity of neural recruitment, but it also alters the temporal response of some neurons. Further, dense glutamate release is highest within the first 20 μm of the electrode site even at high amplitudes, suggesting that there may be spatial limitations to the amplitude parameter space. The glutamate elevation outlasts stimulation, suggesting that high-amplitude stimulation may affect neurotransmitter re-uptake. This ultimately suggests that increasing the amplitude of ICMS device stimulation may fundamentally alter the temporal neural response, which could have implications for using amplitude to improve the ICMS effect or "offset" the effects of glial scarring.

All-Optical Volumetric Physiology for Connectomics in Dense Neuronal Structures

All-optical physiology (AOP) manipulates and reports neuronal activities with light, allowing for interrogation of neuronal functional connections with high spatiotemporal resolution. However, contemporary high-speed AOP platforms are limited to single-depth or discrete multi-plane recordings that are not suitable for studying functional connections among densely packed small neurons, such as neurons in Drosophila brains. Here, we constructed a 3D AOP platform by incorporating single-photon point stimulation and two-photon high-speed volumetric recordings with a tunable acoustic gradient-index (TAG) lens. We demonstrated the platform effectiveness by studying the anterior visual pathway (AVP) of Drosophila. We achieved functional observation of spatiotemporal coding and the strengths of calcium-sensitive connections between anterior optic tubercle (AOTU) sub-compartments and >70 tightly assembled 2-μm bulb (BU) microglomeruli in 3D coordinates with a single trial. Our work aids the establishment of in vivo 3D functional connectomes in neuron-dense brain areas.

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All-optical volumetric physiology = precise stimulation + fast volumetric recording

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Precise single-photon point stimulation among genetically defined neurons

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3D two-photon imaging by an acoustic gradient-index lens for dense neural structures

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Observation of 3D functional connectivity in Drosophila anterior visual pathway

Propagating-path uniformly scanned light sheet excitation microscopy for isotropic volumetric imaging of large specimens

We demonstrate a propagating-path uniformly scanned light sheet excitation (PULSE) microscopy based on the oscillation of voice coil motor that can rapidly drive a thin light sheet along its propagation direction. By synchronizing the rolling shutter of a camera with the motion of laser sheet, we can obtain a uniform plane-illuminated image far beyond the confocal range of Gaussian beam. A stable 1.7-μm optical sectioning under a 3.3  mm  ×  3.3  mm wide field of view (FOV) has been achieved for up to 20 Hz volumetric imaging of large biological specimens. PULSE method transforms the extent of plane illumination from one intrinsically limited by the short confocal range (μm scale) to one defined by the motor oscillation range (mm scale). Compared to the conventional Gaussian light sheet imaging, our method greatly mitigates the compromise of axial resolution and successfully extends the FOV over 100 times. We demonstrate the applications of PULSE method by rapidly imaging cleared mouse spinal cord and live zebrafish larva at isotropic subcellular resolution.

Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins

A restricted Boltzmann machine (RBM) is an unsupervised machine learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relevant statistical features. RBMs were recently proposed for characterizing the patterns of coevolution between amino acids in protein sequences and for designing new sequences. Here, we study how the nature of the features learned by RBM changes with its defining parameters, such as the dimensionality of the representations (size of the hidden layer) and the sparsity of the features. We show that for adequate values of these parameters, RBMs operate in a so-called compositional phase in which visible configurations sampled from the RBM are obtained by recombining these features. We then compare the performance of RBM with other standard representation learning algorithms, including principal or independent component analysis (PCA, ICA), autoencoders (AE), variational autoencoders (VAE), and their sparse variants. We show that RBMs, due to the stochastic mapping between data configurations and representations, better capture the underlying interactions in the system and are significantly more robust with respect to sample size than deterministic methods such as PCA or ICA. In addition, this stochastic mapping is not prescribed a priori as in VAE, but learned from data, which allows RBMs to show good performance even with shallow architectures. All numerical results are illustrated on synthetic lattice protein data that share similar statistical features with real protein sequences and for which ground-truth interactions are known.

Evaluation of the Returned Electromagnetic Signal from Retro-reflectors in Turbid Media

We provide first-principle theoretical and numerical simulations using the coherent Transfer Matrix Approach (TMA) to describe the behavior of the three main class of the optical beacons namely phase conjugators, reflectors, and retroreflectors within a turbid medium. Our theory describes the extraordinary enhancement (about 5 dB) offered by retroreflectors compared to reflectors in our detailed experiments and shows that they effectively act as local optical phase conjugators. Moreover, the performance of retroreflectors shows little degradation for increased light incident angles in turbid media, while the performance of reflectors degrades drastically. These results may find applications for detection of the echoes of electromagnetic radiation in turbid media.

A practical guide to adaptive light-sheet microscopy

We describe the implementation and use of an adaptive imaging framework for optimizing spatial resolution and signal strength in a light-sheet microscope. The framework, termed AutoPilot, comprises hardware and software modules for automatically measuring and compensating for mismatches between light-sheet and detection focal planes in living specimens. Our protocol enables researchers to introduce adaptive imaging capabilities in an existing light-sheet microscope or use our SiMView microscope blueprint to set up a new adaptive multiview light-sheet microscope. The protocol describes (i) the mechano-optical implementation of the adaptive imaging hardware, including technical drawings for all custom microscope components; (ii) the algorithms and software library for automated adaptive imaging, including the pseudocode and annotated source code for all software modules; and (iii) the execution of adaptive imaging experiments, as well as the configuration and practical use of the AutoPilot framework. Setup of the adaptive imaging hardware and software takes 1-2 weeks each. Previous experience with light-sheet microscopy and some familiarity with software engineering and building of optical instruments are recommended. Successful implementation of the protocol recovers near diffraction-limited performance in many parts of typical multicellular organisms studied with light-sheet microscopy, such as fruit fly and zebrafish embryos, for which resolution and signal strength are improved two- to fivefold.

Modeling the Correlated Activity of Neural Populations: A Review

The principles of neural encoding and computations are inherently collective and usually involve large populations of interacting neurons with highly correlated activities. While theories of neural function have long recognized the importance of collective effects in populations of neurons, only in the past two decades has it become possible to record from many cells simultaneously using advanced experimental techniques with single-spike resolution and to relate these correlations to function and behavior. This review focuses on the modeling and inference approaches that have been recently developed to describe the correlated spiking activity of populations of neurons. We cover a variety of models describing correlations between pairs of neurons, as well as between larger groups, synchronous or delayed in time, with or without the explicit influence of the stimulus, and including or not latent variables. We discuss the advantages and drawbacks or each method, as well as the computational challenges related to their application to recordings of ever larger populations.

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.

Advances in Nanomaterials for Brain Microscopy

Microscopic imaging of the brain continues to reveal details of its structure, connectivity, and function. To further improve our understanding of the emergent properties and functions of neural circuits, new methods are necessary to directly visualize the relationship between brain structure, neuron activity, and neurochemistry. Advances in engineering the chemical and optical properties of nanomaterials concurrent with developments in deep-tissue microscopy hold tremendous promise for overcoming the current challenges associated with in vivo brain imaging, particularly for imaging the brain through optically-dense brain tissue, skull, and scalp. To this end, developments in nanomaterials offer much promise toward implementing tunable chemical functionality for neurochemical targeting and sensing, and fluorescence stability for long-term imaging. In this review, we summarize current brain microscopy methods and describe the diverse classes of nanomaterials recently leveraged as contrast agents and functional probes for microscopic optical imaging of the brain.

Bessel Beam Illumination Reduces Random and Systematic Errors in Quantitative Functional Studies Using Light-Sheet Microscopy

Light-sheet microscopy (LSM), in combination with intrinsically transparent zebrafish larvae, is a method of choice to observe brain function with high frame rates at cellular resolution. Inherently to LSM, however, residual opaque objects cause stripe artifacts, which obscure features of interest and, during functional imaging, modulate fluorescence variations related to neuronal activity. Here, we report how Bessel beams reduce streaking artifacts and produce high-fidelity quantitative data demonstrating a fivefold increase in sensitivity to calcium transients and a 20-fold increase in accuracy in the detection of activity correlations in functional imaging. Furthermore, using principal component analysis, we show that measurements obtained with Bessel beams are clean enough to reveal in one-shot experiments correlations that can not be averaged over trials after stimuli as is the case when studying spontaneous activity. Our results not only demonstrate the contamination of data by systematic and random errors through conventional Gaussian illumination and but,furthermore, quantify the increase in fidelity of such data when using Bessel beams.

Investigation of hindbrain activity during active locomotion reveals inhibitory neurons involved in sensorimotor processing

Locomotion in vertebrates relies on motor circuits in the spinal cord receiving inputs from the hindbrain to execute motor commands while dynamically integrating proprioceptive sensory feedback. The spatial organization of the neuronal networks driving locomotion in the hindbrain and role of inhibition has not been extensively investigated. Here, we mapped neuronal activity with single-cell resolution in the hindbrain of restrained transgenic Tg(HuC:GCaMP5G) zebrafish larvae swimming in response to whole-field visual motion. We combined large-scale population calcium imaging in the hindbrain with simultaneous high-speed recording of the moving tail in animals where specific markers label glycinergic inhibitory neurons. We identified cells whose activity preferentially correlates with the visual stimulus or motor activity and used brain registration to compare data across individual larvae. We then morphed calcium imaging data onto the zebrafish brain atlas to compare with known transgenic markers. We report cells localized in the cerebellum whose activity is shut off by the onset of the visual stimulus, suggesting these cells may be constitutively active and silenced during sensorimotor processing. Finally, we discover that the activity of a medial stripe of glycinergic neurons in the domain of expression of the transcription factor engrailed1b is highly correlated with the onset of locomotion. Our efforts provide a high-resolution, open-access dataset for the community by comparing our functional map of the hindbrain to existing open-access atlases and enabling further investigation of this population's role in locomotion.

Calcium imaging and dynamic causal modelling reveal brain-wide changes in effective connectivity and synaptic dynamics during epileptic seizures

Pathophysiological explanations of epilepsy typically focus on either the micro/mesoscale (e.g. excitation-inhibition imbalance), or on the macroscale (e.g. network architecture). Linking abnormalities across spatial scales remains difficult, partly because of technical limitations in measuring neuronal signatures concurrently at the scales involved. Here we use light sheet imaging of the larval zebrafish brain during acute epileptic seizure induced with pentylenetetrazole. Spectral changes of spontaneous neuronal activity during the seizure are then modelled using neural mass models, allowing Bayesian inference on changes in effective network connectivity and their underlying synaptic dynamics. This dynamic causal modelling of seizures in the zebrafish brain reveals concurrent changes in synaptic coupling at macro- and mesoscale. Fluctuations of both synaptic connection strength and their temporal dynamics are required to explain observed seizure patterns. These findings highlight distinct changes in local (intrinsic) and long-range (extrinsic) synaptic transmission dynamics as a possible seizure pathomechanism and illustrate how our Bayesian model inversion approach can be used to link existing neural mass models of seizure activity and novel experimental methods.