Light-Sheet Microscopy in Neuroscience.

Light-sheet microscopy is an imaging approach that offers unique advantages for a diverse range of neuroscience applications. Unlike point-scanning techniques such as confocal and two-photon microscopy, light-sheet microscopes illuminate an entire plane of tissue, while imaging this plane onto a camera. Although early implementations of light sheet were optimized for longitudinal imaging of embryonic development in small specimens, emerging implementations are capable of capturing light-sheet images in freely moving, unconstrained specimens and even the intact in vivo mammalian brain. Meanwhile, the unique photobleaching and signal-to-noise benefits afforded by light-sheet microscopy's parallelized detection deliver the ability to perform volumetric imaging at much higher speeds than can be achieved using point scanning. This review describes the basic principles and evolution of light-sheet microscopy, followed by perspectives on emerging applications and opportunities for both imaging large, cleared, and expanded neural tissues and high-speed, functional imaging in vivo.

Real-time volumetric microscopy of in vivo dynamics and large-scale samples with SCAPE 2.0.

The limited per-pixel bandwidth of most microscopy methods requires compromises between field of view, sampling density and imaging speed. This limitation constrains studies involving complex motion or fast cellular signaling, and presents a major bottleneck for high-throughput structural imaging. Here, we combine high-speed intensified camera technology with a versatile, reconfigurable and dramatically improved Swept, Confocally Aligned Planar Excitation (SCAPE) microscope design that can achieve high-resolution volumetric imaging at over 300 volumes per second and over 1.2 GHz pixel rates. We demonstrate near-isotropic sampling in freely moving Caenorhabditis elegans, and analyze real-time blood flow and calcium dynamics in the beating zebrafish heart. The same system also permits high-throughput structural imaging of mounted, intact, cleared and expanded samples. SCAPE 2.0's significantly lower photodamage compared to point-scanning techniques is also confirmed. Our results demonstrate that SCAPE 2.0 is a powerful, yet accessible imaging platform for myriad emerging high-speed dynamic and high-throughput volumetric microscopy applications.

Audiovisualization of real-time neuroimaging data.

Advancements in brain imaging techniques have significantly expanded the size and complexity of real-time neuroimaging and behavioral data. However, identifying patterns, trends and synchronies within these datasets presents a significant computational challenge. Here, we demonstrate an approach that can translate time-varying neuroimaging data into unique audiovisualizations consisting of audible representations of dynamic data merged with simplified, color-coded movies of spatial components and behavioral recordings. Multiple variables can be encoded as different musical instruments, letting the observer differentiate and track multiple dynamic parameters in parallel. This representation enables intuitive assimilation of these datasets for behavioral correlates and spatiotemporal features such as patterns, rhythms and motifs that could be difficult to detect through conventional data interrogation methods. These audiovisual representations provide a novel perception of the organization and patterns of real-time activity in the brain, and offer an intuitive and compelling method for complex data visualization for a wider range of applications.

The spatial and temporal structure of neural activity across the fly brain.

What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate.

Neuronal birthdate reveals topography in a vestibular brainstem circuit for gaze stabilization.

Across the nervous system, neurons with similar attributes are topographically organized. This topography reflects developmental pressures. Oddly, vestibular (balance) nuclei are thought to be disorganized. By measuring activity in birthdated neurons, we revealed a functional map within the central vestibular projection nucleus that stabilizes gaze in the larval zebrafish. We first discovered that both somatic position and stimulus selectivity follow projection neuron birthdate. Next, with electron microscopy and loss-of-function assays, we found that patterns of peripheral innervation to projection neurons were similarly organized by birthdate. Finally, birthdate revealed spatial patterns of axonal arborization and synapse formation to projection neuron outputs. Collectively, we find that development reveals previously hidden organization to the input, processing, and output layers of a highly conserved vertebrate sensorimotor circuit. The spatial and temporal attributes we uncover constrain the developmental mechanisms that may specify the fate, function, and organization of vestibulo-ocular reflex neurons. More broadly, our data suggest that, like invertebrates, temporal mechanisms may assemble vertebrate sensorimotor architecture.

High-speed light-sheet microscopy for the in-situ acquisition of volumetric histological images of living tissue.

Histological examinations typically require the excision of tissue, followed by its fixation, slicing, staining, mounting and imaging, with timeframes ranging from minutes to days. This process may remove functional tissue, may miss abnormalities through under-sampling, prevents rapid decision-making, and increases costs. Here, we report the feasibility of microscopes based on swept confocally aligned planar excitation technology for the volumetric histological imaging of intact living tissue in real time. The systems' single-objective, light-sheet geometry and 3D imaging speeds enable roving image acquisition, which combined with 3D stitching permits the contiguous analysis of large tissue areas, as well as the dynamic assessment of tissue perfusion and function. Implemented in benchtop and miniaturized form factors, the microscopes also have high sensitivity, even for weak intrinsic fluorescence, allowing for the label-free imaging of diagnostically relevant histoarchitectural structures, as we show for pancreatic disease in living mice, for chronic kidney disease in fresh human kidney tissues, and for oral mucosa in a healthy volunteer. Miniaturized high-speed light-sheet microscopes for in-situ volumetric histological imaging may facilitate the point-of-care detection of diverse cellular-level biomarkers.

3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.

Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCellTracker successfully segmented and tracked ~100 cells in both semi-immobilized and 'straightened' freely moving worm's brain, in a naturally beating zebrafish heart, and ~1000 cells in a 3D cultured tumor spheroid. While these datasets were imaged with highly divergent optical systems, our method tracked 90-100% of the cells in most cases, which is comparable or superior to previous results. These results suggest that 3DeeCellTracker could pave the way for revealing dynamic cell activities in image datasets that have been difficult to analyze.

Microscopes have been used to decrypt the tiny details of life since the 17th century. Now, the advent of 3D microscopy allows scientists to build up detailed pictures of living cells and tissues. In that effort, automation is becoming increasingly important so that scientists can analyze the resulting images and understand how bodies grow, heal and respond to changes such as drug therapies. In particular, algorithms can help to spot cells in the picture (called cell segmentation), and then to follow these cells over time across multiple images (known as cell tracking). However, performing these analyses on 3D images over a given period has been quite challenging. In addition, the algorithms that have already been created are often not user-friendly, and they can only be applied to a specific dataset gathered through a particular scientific method. As a response, Wen et al. developed a new program called 3DeeCellTracker, which runs on a desktop computer and uses a type of artificial intelligence known as deep learning to produce consistent results. Crucially, 3DeeCellTracker can be used to analyze various types of images taken using different types of cutting-edge microscope systems. And indeed, the algorithm was then harnessed to track the activity of nerve cells in moving microscopic worms, of beating heart cells in a young small fish, and of cancer cells grown in the lab. This versatile tool can now be used across biology, medical research and drug development to help monitor cell activities.

Widespread receptor-driven modulation in peripheral olfactory coding.

Olfactory responses to single odors have been well characterized but in reality we are continually presented with complex mixtures of odors. We performed high-throughput analysis of single-cell responses to odor blends using Swept Confocally Aligned Planar Excitation (SCAPE) microscopy of intact mouse olfactory epithelium, imaging ~10,000 olfactory sensory neurons in parallel. In large numbers of responding cells, mixtures of odors did not elicit a simple sum of the responses to individual components of the blend. Instead, many neurons exhibited either antagonism or enhancement of their response in the presence of another odor. All eight odors tested acted as both agonists and antagonists at different receptors. We propose that this peripheral modulation of responses increases the capacity of the olfactory system to distinguish complex odor mixtures.

Characterization of Proprioceptive System Dynamics in Behaving Drosophila Larvae Using High-Speed Volumetric Microscopy.

Proprioceptors provide feedback about body position that is essential for coordinated movement. Proprioceptive sensing of the position of rigid joints has been described in detail in several systems; however, it is not known how animals with a flexible skeleton encode their body positions. Understanding how diverse larval body positions are dynamically encoded requires knowledge of proprioceptor activity patterns in vivo during natural movement. Here we used high-speed volumetric swept confocally aligned planar excitation (SCAPE) microscopy in crawling Drosophila larvae to simultaneously track the position, deformation, and intracellular calcium activity of their multidendritic proprioceptors. Most proprioceptive neurons were found to activate during segment contraction, although one subtype was activated by extension. During cycles of segment contraction and extension, different proprioceptor types exhibited sequential activity, providing a continuum of position encoding during all phases of crawling. This sequential activity was related to the dynamics of each neuron's terminal processes, and could endow each proprioceptor with a specific role in monitoring different aspects of body-wall deformation. We demonstrate this deformation encoding both during progression of contraction waves during locomotion as well as during less stereotyped, asymmetric exploration behavior. Our results provide powerful new insights into the body-wide neuronal dynamics of the proprioceptive system in crawling Drosophila, and demonstrate the utility of our SCAPE microscopy approach for characterization of neural encoding throughout the nervous system of a freely behaving animal.

Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

Calcium is a ubiquitous messenger in neural signaling events. An increasing number of techniques are enabling visualization of neurological activity in animal models via luminescent proteins that bind to calcium ions. These techniques generate large volumes of spatially correlated time series. A model-based functional data analysis methodology via Gaussian mixtures is suggested for the clustering of data from such visualizations is proposed. The methodology is theoretically justified and a computationally efficient approach to estimation is suggested. An example analysis of a zebrafish imaging experiment is presented.

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.

Swept confocally-aligned planar excitation (SCAPE) microscopy for high speed volumetric imaging of behaving organisms.

We report a new 3D microscopy technique that allows volumetric imaging of living samples at ultra-high speeds: Swept, confocally-aligned planar excitation (SCAPE) microscopy. While confocal and two-photon microscopy have revolutionized biomedical research, current implementations are costly, complex and limited in their ability to image 3D volumes at high speeds. Light-sheet microscopy techniques using two-objective, orthogonal illumination and detection require a highly constrained sample geometry, and either physical sample translation or complex synchronization of illumination and detection planes. In contrast, SCAPE microscopy acquires images using an angled, swept light-sheet in a single-objective, en-face geometry. Unique confocal descanning and image rotation optics map this moving plane onto a stationary high-speed camera, permitting completely translationless 3D imaging of intact samples at rates exceeding 20 volumes per second. We demonstrate SCAPE microscopy by imaging spontaneous neuronal firing in the intact brain of awake behaving mice, as well as freely moving transgenic Drosophila larvae.