High-Speed and Scalable Whole-Brain Imaging in Rodents and Primates

A multiwell plate approach to increase the sample throughput during tissue clearing

Tissue clearing, coupled with immunostaining, enables the transition from two-dimensional to three-dimensional pathology and has the potential to substantially improve data quality for biomedical diagnostics. Nevertheless, the workflows are limited by the complex sample processing protocols. Approaches for the parallel processing of samples, to include tissue clearing, immunostaining, imaging and analysis can increase three-dimensional pathology throughput. Here we detail a step-by-step approach that combines a tissue clearing device with a six-well multiwell plate to increase the throughput compared with methods using conventional clearing protocols. The six-well multiplate allows for parallel tissue clearing of multiple samples and is compatible with passive tissue clearing methods including Clear, Unobstructed Brain/Body Imaging Cocktails and Computational (CUBIC) analysis. In addition, gel embedding is performed without moving the samples from the wells, and a series of steps such as imaging with a high-speed light-sheet microscope and analysis in the cloud can be performed. Although this procedure slightly extends the overall time required for preparing and analyzing a single sample, it reduces the effort required at each step, such as reagent exchange and gel embedding, which results in an overall reduction in hands-on time due to the parallel sample processing. We describe a series of whole-organ analyses, including high-throughput tissue clearing, staining, gel embedding, imaging and data analysis in the cloud, as a useful platform for cellular biology and pathology. The total process varies depending on the presence or absence of immunostaining, but for some six-well plates, the tissue clearing process, imaging and data analysis can be completed within 10 d.

Brain-wide immunolabeling and tissue clearing applications for engram research

In recent years, there has been significant progress in memory research, driven by genetic and imaging technological advances that have given unprecedented access to individual memory traces or engrams. Although Karl Lashley argued since the 1930s that an engram is not confined to a particular area but rather distributed across the entire brain, most current studies have focused exclusively on a single or few brain regions. However, this compartmentalized approach overlooks the interactions between multiple brain regions, limiting our understanding of engram mechanisms. More recently, several studies have begun to investigate engrams across the brain, but research is still limited by a lack of standardized techniques capable of reconstructing multiple ensembles at single-cell resolution across the entire brain. In this review, we guide researchers through the latest technological advancements and discoveries in immediate early gene (IEG) techniques, tissue clearing methods, microscope modalities, and automated large-scale analysis. These innovations could propel the field forward in building brain-wide engram maps of normal and disease states, thus, providing unprecedented new insights. Ultimately, this review aims to bridge the gap between research focused on single brain regions and the need for a comprehensive understanding of whole-brain engrams, revealing new approaches for exploring the neuronal mechanisms underlying engrams.

Mesocorticolimbic circuit mechanisms of social dominance behavior

Social animals, including rodents, primates, and humans, partake in competition for finite resources, thereby establishing social hierarchies wherein an individual's social standing influences diverse behaviors. Understanding the neurobiological underpinnings of social dominance is imperative, given its ramifications for health, survival, and reproduction. Social dominance behavior comprises several facets, including social recognition, social decision-making, and actions, indicating the concerted involvement of multiple brain regions in orchestrating this behavior. While extensive research has been dedicated to elucidating the neurobiology of social interaction, recent studies have increasingly delved into adverse social behaviors such as social competition and hierarchy. This review focuses on the latest advancements in comprehending the mechanisms of the mesocorticolimbic circuit governing social dominance, with a specific focus on rodent studies, elucidating the intricate dynamics of social hierarchies and their implications for individual well-being and adaptation.

Brain image data processing using collaborative data workflows on Texera

In the realm of neuroscience, mapping the three-dimensional (3D) neural circuitry and architecture of the brain is important for advancing our understanding of neural circuit organization and function. This study presents a novel pipeline that transforms mouse brain samples into detailed 3D brain models using a collaborative data analytics platform called "Texera." The user-friendly Texera platform allows for effective interdisciplinary collaboration between team members in neuroscience, computer vision, and data processing. Our pipeline utilizes the tile images from a serial two-photon tomography/TissueCyte system, then stitches tile images into brain section images, and constructs 3D whole-brain image datasets. The resulting 3D data supports downstream analyses, including 3D whole-brain registration, atlas-based segmentation, cell counting, and high-resolution volumetric visualization. Using this platform, we implemented specialized optimization methods and obtained significant performance enhancement in workflow operations. We expect the neuroscience community can adopt our approach for large-scale image-based data processing and analysis.

EDTP enhances and protects the fluorescent signal of GFP in cleared and expanded tissues

Advanced 3D high-resolution imaging techniques are essential for investigating biological challenges, such as neural circuit analysis and tumor microenvironment in intact tissues. However, the fluorescence signal emitted by endogenous fluorescent proteins in cleared or expanded biological samples gradually diminishes with repeated irradiation and prolonged imaging, compromising its ability to accurately depict the underlying scientific problem. We have developed a strategy to preserve fluorescence in cleared and expanded tissue samples during prolonged high-resolution three-dimensional imaging. We evaluated various compounds at different concentrations to determine their ability to enhance fluorescence intensity and resistance to photobleaching while maintaining the structural integrity of the tissue. Specifically, we investigated the impact of EDTP utilization on GFP, as it has been observed to significantly improve fluorescence intensity, resistance to photobleaching, and maintain fluorescence during extended room temperature storage. This breakthrough will facilitate extended hydrophilic and hydrogel-based clearing and expansion methods for achieving long-term high-resolution 3D imaging of cleared biological tissues by effectively safeguarding fluorescent proteins within the tissue.

Optimization of AAV vectors for transactivator-regulated enhanced gene expression within targeted neuronal populations

Adeno-associated virus (AAV) vectors are potential tools for cell-type-selective gene delivery to the central nervous system. Although cell-type-specific enhancers and promoters have been identified for AAV systems, there is limited information regarding the effects of AAV genomic components on the selectivity and efficiency of gene expression. Here, we offer an alternative strategy to provide specific and efficient gene delivery to a targeted neuronal population by optimizing recombinant AAV genomic components, named TAREGET (TransActivator-Regulated Enhanced Gene Expression within Targeted neuronal populations). We established this strategy in oxytocinergic neurons and showed that the TAREGET enabled sufficient gene expression to label long-projecting axons in wild-type mice. Its application to other cell types, including serotonergic and dopaminergic neurons, was also demonstrated. These results demonstrate that optimization of AAV expression cassettes can improve the specificity and efficiency of cell-type-specific gene expression and that TAREGET can renew previously established cell-type-specific promoters with improved performance.

Connecto-informatics at the mesoscale: current advances in image processing and analysis for mapping the brain connectivity

Mapping neural connections within the brain has been a fundamental goal in neuroscience to understand better its functions and changes that follow aging and diseases. Developments in imaging technology, such as microscopy and labeling tools, have allowed researchers to visualize this connectivity through high-resolution brain-wide imaging. With this, image processing and analysis have become more crucial. However, despite the wealth of neural images generated, access to an integrated image processing and analysis pipeline to process these data is challenging due to scattered information on available tools and methods. To map the neural connections, registration to atlases and feature extraction through segmentation and signal detection are necessary. In this review, our goal is to provide an updated overview of recent advances in these image-processing methods, with a particular focus on fluorescent images of the mouse brain. Our goal is to outline a pathway toward an integrated image-processing pipeline tailored for connecto-informatics. An integrated workflow of these image processing will facilitate researchers' approach to mapping brain connectivity to better understand complex brain networks and their underlying brain functions. By highlighting the image-processing tools available for fluroscent imaging of the mouse brain, this review will contribute to a deeper grasp of connecto-informatics, paving the way for better comprehension of brain connectivity and its implications.

A complementary approach for neocortical cytoarchitecture inspection with cellular resolution imaging at whole brain scale

Cytoarchitecture, the organization of cells within organs and tissues, serves as a crucial anatomical foundation for the delineation of various regions. It enables the segmentation of the cortex into distinct areas with unique structural and functional characteristics. While traditional 2D atlases have focused on cytoarchitectonic mapping of cortical regions through individual sections, the intricate cortical gyri and sulci demands a 3D perspective for unambiguous interpretation. In this study, we employed fluorescent micro-optical sectioning tomography to acquire architectural datasets of the entire macaque brain at a resolution of 0.65 μm × 0.65 μm × 3 μm. With these volumetric data, the cortical laminar textures were remarkably presented in appropriate view planes. Additionally, we established a stereo coordinate system to represent the cytoarchitectonic information as surface-based tomograms. Utilizing these cytoarchitectonic features, we were able to three-dimensionally parcel the macaque cortex into multiple regions exhibiting contrasting architectural patterns. The whole-brain analysis was also conducted on mice that clearly revealed the presence of barrel cortex and reflected biological reasonability of this method. Leveraging these high-resolution continuous datasets, our method offers a robust tool for exploring the organizational logic and pathological mechanisms of the brain's 3D anatomical structure.

Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN) for cross-modal individual analysis of the whole brain

Cross-modal analysis of the same whole brain is an ideal strategy to uncover brain function and dysfunction. However, it remains challenging due to the slow speed and destructiveness of traditional whole-brain optical imaging techniques. Here we develop a new platform, termed Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN), for non-destructive, high-speed, 3D imaging of ex vivo rodent, ferret, and non-human primate brains. Using an optimally designed image acquisition scheme and an accompanying machine-learning algorithm, PATTERN extracts signals of genetically-encoded probes from photobleaching-based temporal modulation and enables reliable visualization of neural projection in the whole central nervous system with 3D isotropic resolution. Without structural and biological perturbation to the sample, PATTERN can be combined with other whole-brain imaging modalities to acquire the whole-brain image with both high resolution and morphological fidelity. Furthermore, cross-modal transcriptome analysis of an individual brain is achieved by PATTERN imaging. Together, PATTERN provides a compatible and versatile strategy for brain-wide cross-modal analysis at the individual level.

(R)-ketamine restores anterior insular cortex activity and cognitive deficits in social isolation-reared mice

Chronic social isolation increases the risk of mental health problems, including cognitive impairments and depression. While subanesthetic ketamine is considered effective for cognitive impairments in patients with depression, the neural mechanisms underlying its effects are not well understood. Here we identified unique activation of the anterior insular cortex (aIC) as a characteristic feature in brain-wide regions of mice reared in social isolation and treated with (R)-ketamine, a ketamine enantiomer. Using fiber photometry recording on freely moving mice, we found that social isolation attenuates aIC neuronal activation upon social contact and that (R)-ketamine, but not (S)-ketamine, is able to counteracts this reduction. (R)-ketamine facilitated social cognition in social isolation-reared mice during the social memory test. aIC inactivation offset the effect of (R)-ketamine on social memory. Our results suggest that (R)-ketamine has promising potential as an effective intervention for social cognitive deficits by restoring aIC function.

Immunolabeling-compatible PEGASOS tissue clearing for high-resolution whole mouse brain imaging

Novel brain clearing methods revolutionize imaging by increasing visualization throughout the brain at high resolution. However, combining the standard tool of immunostaining targets of interest with clearing methods has lagged behind. We integrate whole-mount immunostaining with PEGASOS tissue clearing, referred to as iPEGASOS (immunostaining-compatible PEGASOS), to address the challenge of signal quenching during clearing processes. iPEGASOS effectively enhances molecular-genetically targeted fluorescent signals that are otherwise compromised during conventional clearing procedures. Additionally, we demonstrate the utility of iPEGASOS for visualizing neurochemical markers or viral labels to augment visualization that transgenic mouse lines cannot provide. Our study encompasses three distinct applications, each showcasing the versatility and efficacy of this approach. We employ whole-mount immunostaining to enhance molecular signals in transgenic reporter mouse lines to visualize the whole-brain spatial distribution of specific cellular populations. We also significantly improve the visualization of neural circuit connections by enhancing signals from viral tracers injected into the brain. Last, we show immunostaining without genetic markers to selectively label beta-amyloid deposits in a mouse model of Alzheimer's disease, facilitating the comprehensive whole-brain study of pathological features.

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By changing the cross-entropy weights and using augmentation, we demonstrate a generally improved adjusted F1-score over using the originally trained TrailMap model within our test datasets.

Clozapine Induces Neuronal Activation in the Medial Prefrontal Cortex in a Projection Target-Biased Manner

The medial prefrontal cortex (mPFC) is associated with various behavioral controls via diverse projections to cortical and subcortical areas of the brain. Dysfunctions and modulations of this circuitry are related to the pathophysiology of schizophrenia and its pharmacotherapy, respectively. Clozapine is an atypical antipsychotic drug used for treatment-resistant schizophrenia and is known to modulate neuronal activity in the mPFC. However, it remains unclear which prefrontal cortical projections are activated by clozapine among the various projection targets. To identify the anatomical characteristics of neurons activated by clozapine at the mesoscale level, we investigated the brain-wide projection patterns of neurons with clozapine-induced c-Fos expression in the mPFC. Using a whole-brain imaging and virus-mediated genetic tagging of activated neurons, we found that clozapine-responsive neurons in the mPFC had a wide range of projections to the mesolimbic, amygdala and thalamic areas, especially the mediodorsal thalamus. These results may provide key insights into the neuronal basis of the therapeutic action of clozapine.

Deep learning in mesoscale brain image analysis: A review

Mesoscale microscopy images of the brain contain a wealth of information which can help us understand the working mechanisms of the brain. However, it is a challenging task to process and analyze these data because of the large size of the images, their high noise levels, the complex morphology of the brain from the cellular to the regional and anatomical levels, the inhomogeneous distribution of fluorescent labels in the cells and tissues, and imaging artifacts. Due to their impressive ability to extract relevant information from images, deep learning algorithms are widely applied to microscopy images of the brain to address these challenges and they perform superiorly in a wide range of microscopy image processing and analysis tasks. This article reviews the applications of deep learning algorithms in brain mesoscale microscopy image processing and analysis, including image synthesis, image segmentation, object detection, and neuron reconstruction and analysis. We also discuss the difficulties of each task and possible directions for further research.

Whole-brain Optical Imaging: A Powerful Tool for Precise Brain Mapping at the Mesoscopic Level

The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons. Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain. Optical approaches can achieve submicron lateral resolution and achieve "optical sectioning" by a variety of means, which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level. Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues. Combined with various fluorescent labeling techniques, whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells, circuits, and blood vessels. In this review, we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.

Comparison of Light-Sheet Fluorescence Microscopy and Fast-Confocal Microscopy for Three-Dimensional Imaging of Cleared Mouse Brain

Whole-brain imaging is important for understanding brain functions through deciphering tissue structures, neuronal circuits, and single-neuron tracing. Thus, many clearing methods have been developed to acquire whole-brain images or images of three-dimensional thick tissues. However, there are several limitations to imaging whole-brain volumes, including long image acquisition times, large volumes of data, and a long post-image process. Based on these limitations, many researchers are unsure about which light microscopy is most suitable for imaging thick tissues. Here, we compared fast-confocal microscopy with light-sheet fluorescence microscopy for whole-brain three-dimensional imaging, which can acquire images the fastest. To compare the two types of microscopies for large-volume imaging, we performed tissue clearing of a whole mouse brain, and changed the sample chamber and low- magnification objective lens and modified the sample holder of a light-sheet fluorescence microscope. We found out that light-sheet fluorescence microscopy using a 2.5× objective lens possesses several advantages, including saving time, large-volume image acquisitions, and high Z-resolution, over fast-confocal microscopy, which uses a 4× objective lens. Therefore, we suggest that light-sheet fluorescence microscopy is suitable for whole mouse brain imaging and for obtaining high-resolution three-dimensional images.

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By fine-tuning the final two layers of the neural network at a lower learning rate of the TrailMap model, we demonstrate an improved recall and an occasionally improved adjusted F1-score within our test dataset over using the originally trained TrailMap model.

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

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

On-line clearing and staining method for the efficient optical imaging of large volume samples at the cellular resolution

Optical microscopy is a powerful tool for exploring the structure and function of organisms. However, the three-dimensional (3D) imaging of large volume samples is time-consuming and difficult. In this manuscript, we described an on-line clearing and staining method for efficient imaging of large volume samples at the cellular resolution. The optimized cocktail can increase staining and imaging depth to reduce the sectioning and scanning time, more than doubling the operational efficiency of the system. Using this method, we demonstrated the rapid acquisition of Aβ plaques in whole mouse brain and obtained a complete set of cytoarchitecture images of an adult porcine hemisphere at 1.625 × 1.625 × 10 µm3 voxel resolution for about 49 hours.

Deep ultraviolet fluorescence microscopy of three-dimensional structures in the mouse brain

Three-dimensional (3D) imaging at cellular resolution improves our understanding of the brain architecture and is crucial for structural and functional integration as well as for the understanding of normal and pathological conditions in the brain. We developed a wide-field fluorescent microscope for 3D imaging of the brain structures using deep ultraviolet (DUV) light. This microscope allowed fluorescence imaging with optical sectioning due to the large absorption at the surface of the tissue and hence low tissue penetration of DUV light. Multiple channels of fluorophore signals were detected using single or a combination of dyes emitting fluorescence in the visible range of spectrum upon DUV excitation. Combination of this DUV microscope with microcontroller-based motorized stage enabled wide-field imaging of a coronal section of the cerebral hemisphere in mouse for deciphering cytoarchitecture of each substructure in detail. We extended this by integrating vibrating microtome which allowed serial block-face imaging of the brain structure such as the habenula in mouse. Acquired images were with resolution high enough for quantification of the cell numbers and density in the mouse habenula. Upon block-face imaging of the tissues covering entire extent of the cerebral hemisphere of the mouse brain, acquired data were registered and segmented for quantification of cell number in each brain regions. Results in the current analysis indicated that this novel microscope could be a convenient tool for large-scale 3D analysis of the brain in mice.

Connectome-based biophysics models of Alzheimer's disease diagnosis and prognosis

With the increasing prevalence of Alzheimer's disease (AD) among aging populations and the limited therapeutic options available to slow or reverse its progression, the need has never been greater for improved diagnostic tools for identifying patients in the preclinical and prodomal phases of AD. Biophysics models of the connectome-based spread of amyloid-beta (Aβ) and microtubule-associated protein tau (τ) have enjoyed recent success as tools for predicting the time course of AD-related pathological changes. However, given the complex etiology of AD, which involves not only connectome-based spread of protein pathology but also the interactions of many molecular and cellular players over multiple spatiotemporal scales, more robust, complete biophysics models are needed to better understand AD pathophysiology and ultimately provide accurate patient-specific diagnoses and prognoses. Here we discuss several areas of active research in AD whose insights can be used to enhance the mathematical modeling of AD pathology as well as recent attempts at developing improved connectome-based biophysics models. These efforts toward a comprehensive yet parsimonious mathematical description of AD hold great promise for improving both the diagnosis of patients at risk for AD and our mechanistic understanding of how AD progresses.

Three-dimensional mapping in multi-samples with large-scale imaging and multiplexed post staining

Dissection of the anatomical information at the single-cell level is crucial for understanding the organization rule and pathological mechanism of biological tissues. Mapping the whole organ in numerous groups with multiple conditions brings the challenges in imaging and analysis. Here, we describe an approach, named array fluorescent micro-optical sectioning tomography (array-fMOST), to identify the three-dimensional information at single-cell resolution from multi-samples. The pipeline contains array embedding, large-scale imaging, post-imaging staining and data analysis, which could image over 24 mouse brains simultaneously and collect the slices for further analysis. With transgenic mice, we acquired the distribution information of neuropeptide somatostatin neurons during natural aging and compared the changes in the microenvironments by multi-component labeling of serial sections with precise co-registration of serial datasets quantitatively. With viral labeling, we also analyzed the input circuits of the medial prefrontal cortex in the whole brain of Alzheimer's disease and autism model mice. This pipeline is highly scalable to be applied to anatomical alterations screening and identification. It provides new opportunities for combining multi-sample whole-organ imaging and molecular phenotypes identification analysis together. Such integrated high-dimensional information acquisition method may accelerate our understanding of pathogenesis and progression of disease in situ at multiple levels.

New imaging instrument in animal models: Two-photon miniature microscope and large field of view miniature microscope for freely behaving animals

Over the past decade, novel optical imaging tools have been developed for imaging neuronal activities along with the evolution of fluorescence indicators with brighter expression and higher sensitivity. Miniature microscopes, as revolutionary approaches, enable the imaging of large populations of neuron ensembles in freely behaving rodents and mammals, which allows exploring the neural basis of behaviors. Recent progress in two-photon miniature microscopes and mesoscale single-photon miniature microscopes further expand those affordable methods to navigate neural activities during naturalistic behaviors. In this review article, two-photon miniature microscopy techniques are summarized historically from the first documented attempt to the latest ones, and comparisons are made. The driving force behind and their potential for neuroscientific inquiries are also discussed. Current progress in terms of the mesoscale, i.e., the large field-of-view miniature microscopy technique, is addressed as well. Then, pipelines for registering single cells from the data of two-photon and large field-of-view miniature microscopes are discussed. Finally, we present the potential evolution of the techniques.

Pre-treatment of oncolytic reovirus improves tumor accumulation and intratumoral distribution of PEG-liposomes

PEGylated liposomes (PEG-liposomes) are a promising drug delivery vehicle for tumor targeting because of their efficient tumor disposition profiles via the enhanced permeability and retention (EPR) effect. However, tumor targeting of PEG-liposomes, particularly their delivery inside the tumors, is often disturbed by physical barriers in the tumor, including tumor cells themselves, extracellular matrices, and interstitial pressures. In this study, B16 melanoma tumor-bearing mice were injected intravenously with oncolytic reovirus before administration of PEG-liposomes to enhance PEG-liposomes' tumor disposition. Three days after reovirus administration, significant expression of reovirus sigma 3 protein, elevation of apoptosis-related gene expression, and activation of caspase 3 in the tumors were found. Apoptotic cells were found inside the tumors. These data indicated that reovirus efficiently replicated in the tumors and induced apoptosis of tumor cells. The tumor disposition levels of PEG-liposomes were approximately doubled by reovirus pre-administration, compared with a PBS-pretreated group. PEG-liposomes were widely distributed in the tumors of reovirus-pretreated mice, whereas in the PBS-pretreated group, PEG-liposomes were found mainly around or inside the blood vessels in the tumors. Pre-treatment with reovirus also improved the tumor accumulation of PEG-liposomes in human pancreatic BxPC-3 tumors. 3D imaging analysis of whole BxPC-3 tumors demonstrated that pretreatment with reovirus led to the enhancement of PEG-liposome accumulation inside the tumors. Combination treatment with reovirus and paclitaxel-loaded PEG-liposomes (PTX-PEG-liposomes) significantly suppressed B16 tumor growth. These results provide important information for clinical use of combination therapy of reovirus and nanoparticle-based drug delivery system (DDS).

Parabrachial-to-parasubthalamic nucleus pathway mediates fear-induced suppression of feeding in male mice

Feeding behavior is adaptively regulated by external and internal environment, such that feeding is suppressed when animals experience pain, sickness, or fear. While the lateral parabrachial nucleus (lPB) plays key roles in nociception and stress, neuronal pathways involved in feeding suppression induced by fear are not fully explored. Here, we investigate the parasubthalamic nucleus (PSTN), located in the lateral hypothalamus and critically involved in feeding behaviors, as a target of lPB projection neurons. Optogenetic activation of lPB-PSTN terminals in male mice promote avoidance behaviors, aversive learning, and suppressed feeding. Inactivation of the PSTN and lPB-PSTN pathway reduces fear-induced feeding suppression. Activation of PSTN neurons expressing pituitary adenylate cyclase-activating polypeptide (PACAP), a neuropeptide enriched in the PSTN, is sufficient for inducing avoidance behaviors and feeding suppression. Blockade of PACAP receptors impaires aversive learning induced by lPB-PSTN photomanipulation. These findings indicate that lPB-PSTN pathway plays a pivotal role in fear-induced feeding suppression.

Acute social defeat stress activated neurons project to the claustrum and basolateral amygdala

We recently reported that a neuronal population in the claustrum (CLA) identified under exposure to psychological stressors plays a key role in stress response processing. Upon stress exposure, the main inputs to the CLA come from the basolateral amygdala (BLA); however, the upstream brain regions that potentially regulate both the CLA and BLA during stressful experiences remain unclear. Here by combining activity-dependent viral retrograde labeling with whole brain imaging, we analyzed neurons projecting to the CLA and BLA activated by exposure to social defeat stress. The labeled CLA projecting neurons were mostly ipsilateral, excluding the prefrontal cortices, which had a distinctly labeled population in the contralateral hemisphere. Similarly, the labeled BLA projecting neurons were predominantly ipsilateral, aside from the BLA in the opposite hemisphere, which also had a notably labeled population. Moreover, we found co-labeled double-projecting single neurons in multiple brain regions such as the ipsilateral ectorhinal/perirhinal cortex, entorhinal cortex, and the contralateral BLA. These results suggest that CLA and BLA receive inputs from neuron collaterals in various brain regions during stress, which may regulate the CLA and BLA forming in a stress response circuitry.

Molecular basis of astrocyte diversity and morphology across the CNS in health and disease

Astrocytes, a type of glia, are abundant and morphologically complex cells. Here, we report astrocyte molecular profiles, diversity, and morphology across the mouse central nervous system (CNS). We identified shared and region-specific astrocytic genes and functions and explored the cellular origins of their regional diversity. We identified gene networks correlated with astrocyte morphology, several of which unexpectedly contained Alzheimer's disease (AD) risk genes. CRISPR/Cas9-mediated reduction of candidate genes reduced astrocyte morphological complexity and resulted in cognitive deficits. The same genes were down-regulated in human AD, in an AD mouse model that displayed reduced astrocyte morphology, and in other human brain disorders. We thus provide comprehensive molecular data on astrocyte diversity and mechanisms across the CNS and on the molecular basis of astrocyte morphology in health and disease.

Multicolor high-resolution whole-brain imaging for acquiring and comparing the brain-wide distributions of type-specific and projection-specific neurons with anatomical annotation in the same brain

Visualizing the relationships and interactions among different biological components in the whole brain is crucial to our understanding of brain structures and functions. However, an automatic multicolor whole-brain imaging technique is still lacking. Here, we developed a multicolor wide-field large-volume tomography (multicolor WVT) to simultaneously acquire fluorescent signals in blue, green, and red channels in the whole brain. To facilitate the segmentation of brain regions and anatomical annotation, we used 4′, 6-diamidino-2-phenylindole (DAPI) to provide cytoarchitecture through real-time counterstaining. We optimized the imaging planes and modes of three channels to overcome the axial chromatic aberration of the illumination path and avoid the crosstalk from DAPI to the green channel without the modification of system configuration. We also developed an automatic contour recognition algorithm based on DAPI-staining cytoarchitecture to shorten data acquisition time and reduce data redundancy. To demonstrate the potential of our system in deciphering the relationship of the multiple components of neural circuits, we acquired and quantified the brain-wide distributions of cholinergic neurons and input of ventral Caudoputamen (CP) with the anatomical annotation in the same brain. We further identified the cholinergic type of upstream neurons projecting to CP through the triple-color collocated analysis and quantified its proportions in the two brain-wide distributions. Both accounted for 0.22%, implying CP might be modulated by non-cholinergic neurons. Our method provides a new research tool for studying the different biological components in the same organ and potentially facilitates the understanding of the processing mechanism of neural circuits and other biological activities.

Fluorescent transgenic mouse models for whole-brain imaging in health and disease

A paradigm shift is occurring in neuroscience and in general in life sciences converting biomedical research from a descriptive discipline into a quantitative, predictive, actionable science. Living systems are becoming amenable to quantitative description, with profound consequences for our ability to predict biological phenomena. New experimental tools such as tissue clearing, whole-brain imaging, and genetic engineering technologies have opened the opportunity to embrace this new paradigm, allowing to extract anatomical features such as cell number, their full morphology, and even their structural connectivity. These tools will also allow the exploration of new features such as their geometrical arrangement, within and across brain regions. This would be especially important to better characterize brain function and pathological alterations in neurological, neurodevelopmental, and neurodegenerative disorders. New animal models for mapping fluorescent protein-expressing neurons and axon pathways in adult mice are key to this aim. As a result of both developments, relevant cell populations with endogenous fluorescence signals can be comprehensively and quantitatively mapped to whole-brain images acquired at submicron resolution. However, they present intrinsic limitations: weak fluorescent signals, unequal signal strength across the same cell type, lack of specificity of fluorescent labels, overlapping signals in cell types with dense labeling, or undetectable signal at distal parts of the neurons, among others. In this review, we discuss the recent advances in the development of fluorescent transgenic mouse models that overcome to some extent the technical and conceptual limitations and tradeoffs between different strategies. We also discuss the potential use of these strains for understanding disease.

Cryo-fluorescence micro-optical sectioning tomography for volumetric imaging of various whole organs with subcellular resolution

Optical visualization of complex microstructures in the entire organ is essential for biomedical research. However, the existing methods fail to accurately acquire the detailed microstructures of whole organs with good morphological and biochemical preservation. This study proposes a cryo-fluorescence micro-optical sectioning tomography (cryo-fMOST) to image whole organs in three dimensions (3D) with submicron resolution. The system comprises a line-illumination microscope module, cryo-microtome, three-stage refrigeration module, and heat insulation device. To demonstrate the imaging capacity and wide applicability of the system, we imaged and reconstructed various organs of mice in 3D, including the healthy tongue, kidney, and brain, as well as the infarcted heart. More importantly, imaged brain slices were performed sugar phosphates determination and fluorescence in situ hybridization imaging to verify the compatibility of multi-omics measurements. The results demonstrated that cryo-fMOST is capable of acquiring high-resolution morphological details of various whole organs and may be potentially useful for spatial multi-omics.

Advances in studying whole mouse brain vasculature using high-resolution 3D light microscopy imaging

Significance: The cerebrovasculature has become increasingly recognized as a major player in overall brain health and many brain disorders. Although there have been several landmark studies to understand details of these crucially important structures in an anatomically defined area, brain-wide examination of the whole cerebrovasculature, including microvessels, has been challenging. However, emerging techniques, including tissue processing and three-dimensional (3D) microscopy imaging, enable neuroscientists to examine the total vasculature in the entire mouse brain. Aim: Here, we aim to highlight advances in these high-resolution 3D mapping methods including block-face imaging and light sheet fluorescent microscopy. Approach: We summarize latest mapping tools to understand detailed anatomical arrangement of the cerebrovascular network and the organizing principles of the neurovascular unit (NVU) as a whole. Results: We discuss biological insights gained from studies using these imaging methods and how these tools can be used to advance our understanding of the cerebrovascular network and related cell types in the entire brain. Conclusions: This review article will help to understand recent advance in high-resolution NVU mapping in mice and provide perspective on future studies.

Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics

Small animal models play a fundamental role in brain research by deepening the understanding of the physiological functions and mechanisms underlying brain disorders and are thus essential in the development of therapeutic and diagnostic imaging tracers targeting the central nervous system. Advances in structural, functional, and molecular imaging using MRI, PET, fluorescence imaging, and optoacoustic imaging have enabled the interrogation of the rodent brain across a large temporal and spatial resolution scale in a non-invasively manner. However, there are still several major gaps in translating from preclinical brain imaging to the clinical setting. The hindering factors include the following: (1) intrinsic differences between biological species regarding brain size, cell type, protein expression level, and metabolism level and (2) imaging technical barriers regarding the interpretation of image contrast and limited spatiotemporal resolution. To mitigate these factors, single-cell transcriptomics and measures to identify the cellular source of PET tracers have been developed. Meanwhile, hybrid imaging techniques that provide highly complementary anatomical and molecular information are emerging. Furthermore, deep learning-based image analysis has been developed to enhance the quantification and optimization of the imaging protocol. In this mini-review, we summarize the recent developments in small animal neuroimaging toward improved translational power, with a focus on technical improvement including hybrid imaging, data processing, transcriptomics, awake animal imaging, and on-chip pharmacokinetics. We also discuss outstanding challenges in standardization and considerations toward increasing translational power and propose future outlooks.

Advanced high resolution three-dimensional imaging to visualize the cerebral neurovascular network in stroke

As an important method to accurately and timely diagnose stroke and study physiological characteristics and pathological mechanism in it, imaging technology has gone through more than a century of iteration. The interaction of cells densely packed in the brain is three-dimensional (3D), but the flat images brought by traditional visualization methods show only a few cells and ignore connections outside the slices. The increased resolution allows for a more microscopic and underlying view. Today's intuitive 3D imagings of micron or even nanometer scale are showing its essentiality in stroke. In recent years, 3D imaging technology has gained rapid development. With the overhaul of imaging mediums and the innovation of imaging mode, the resolution has been significantly improved, endowing researchers with the capability of holistic observation of a large volume, real-time monitoring of tiny voxels, and quantitative measurement of spatial parameters. In this review, we will summarize the current methods of high-resolution 3D imaging applied in stroke.

Claustrum mediates bidirectional and reversible control of stress-induced anxiety responses

The processing of stress responses involves brain-wide communication among cortical and subcortical regions; however, the underlying mechanisms remain elusive. Here, we show that the claustrum (CLA) is crucial for the control of stress-induced anxiety-related behaviors. A combined approach using brain activation mapping and machine learning showed that the CLA activation serves as a reliable marker of exposure to acute stressors. In TRAP2 mice, which allow activity-dependent genetic labeling, chemogenetic activation of the CLA neuronal ensemble tagged by acute social defeat stress (DS) elicited anxiety-related behaviors, whereas silencing of the CLA ensemble attenuated DS-induced anxiety-related behaviors. Moreover, the CLA received strong input from DS-activated basolateral amygdala neurons, and its circuit-selective optogenetic photostimulation temporarily elicited anxiety-related behaviors. Last, silencing of the CLA ensemble during stress exposure increased resistance to chronic DS. The CLA thus bidirectionally controls stress-induced emotional responses, and its inactivation can serve as a preventative strategy to increase stress resilience.

Three-dimensional label-free histological imaging of whole organs by microtomy-assisted autofluorescence tomography

Three-dimensional (3D) histology is vitally important to characterize disease-induced tissue heterogeneity at the individual cell level. However, it remains challenging for both high-throughput 3D imaging and volumetric reconstruction. Here we propose a label-free, cost-effective, and ready-to-use 3D histological imaging technique, termed microtomy-assisted autofluorescence tomography with ultraviolet excitation (MATE). With the combination of block-face imaging and serial microtome sectioning, MATE can achieve rapid and label-free imaging of paraffin-embedded whole organs at an acquisition speed of 1 cm3 per 4 h with a voxel resolution of 1.2 × 1.2 × 10 μm3. We demonstrate that MATE enables simultaneous visualization of cell nuclei, fiber tracts, and blood vessels in mouse/human brains without tissue staining or clearing. Moreover, diagnostic features, including nuclear size and packing density, can be quantitatively extracted with high accuracy. MATE is augmented to the current slide-based 2D histology, holding great promise to facilitate histopathological interpretation at the organelle level.

Towards a Comprehensive Optical Connectome at Single Synapse Resolution via Expansion Microscopy

Mapping and determining the molecular identity of individual synapses is a crucial step towards the comprehensive reconstruction of neuronal circuits. Throughout the history of neuroscience, microscopy has been a key technology for mapping brain circuits. However, subdiffraction size and high density of synapses in brain tissue make this process extremely challenging. Electron microscopy (EM), with its nanoscale resolution, offers one approach to this challenge yet comes with many practical limitations, and to date has only been used in very small samples such as C. elegans, tadpole larvae, fruit fly brain, or very small pieces of mammalian brain tissue. Moreover, EM datasets require tedious data tracing. Light microscopy in combination with tissue expansion via physical magnification-known as expansion microscopy (ExM)-offers an alternative approach to this problem. ExM enables nanoscale imaging of large biological samples, which in combination with multicolor neuronal and synaptic labeling offers the unprecedented capability to trace and map entire neuronal circuits in fully automated mode. Recent advances in new methods for synaptic staining as well as new types of optical molecular probes with superior stability, specificity, and brightness provide new modalities for studying brain circuits. Here we review advanced methods and molecular probes for fluorescence staining of the synapses in the brain that are compatible with currently available expansion microscopy techniques. In particular, we will describe genetically encoded probes for synaptic labeling in mice, zebrafish, Drosophila fruit flies, and C. elegans, which enable the visualization of post-synaptic scaffolds and receptors, presynaptic terminals and vesicles, and even a snapshot of the synaptic activity itself. We will address current methods for applying these probes in ExM experiments, as well as appropriate vectors for the delivery of these molecular constructs. In addition, we offer experimental considerations and limitations for using each of these tools as well as our perspective on emerging tools.

Continuous subcellular resolution three-dimensional imaging on intact macaque brain

To decipher the organizational logic of complex brain circuits, it is important to chart long-distance pathways while preserving micron-level accuracy of local network. However, mapping the neuronal projections with individual-axon resolution in the large and complex primate brain is still challenging. Herein, we describe a highly efficient pipeline for three-dimensional mapping of the entire macaque brain with subcellular resolution. The pipeline includes a novel poly-N-acryloyl glycinamide (PNAGA)-based embedding method for long-term structure and fluorescence preservation, high-resolution and rapid whole-brain optical imaging, and image post-processing. The cytoarchitectonic information of the entire macaque brain was acquired with a voxel size of 0.32 μm × 0.32 μm × 10 μm, showing its anatomical structure with cell distribution, density, and shape. Furthermore, thanks to viral labeling, individual long-distance projection axons from the frontal cortex were for the first time reconstructed across the entire brain hemisphere with a voxel size of 0.65 μm × 0.65 μm × 3 μm. Our results show that individual cortical axons originating from the prefrontal cortex simultaneously target multiple brain regions, including the visual cortex, striatum, thalamus, and midbrain. This pipeline provides an efficient method for cellular and circuitry investigation of the whole macaque brain with individual-axon resolution, and can shed light on brain function and disorders.

Trends in big data analyses by multicenter collaborative translational research in psychiatry

The underlying pathologies of psychiatric disorders, which cause substantial personal and social losses, remain unknown, and their elucidation is an urgent issue. To clarify the core pathological mechanisms underlying psychiatric disorders, in addition to laboratory-based research that incorporates the latest findings, it is necessary to conduct large-sample-size research and verify reproducibility. For this purpose, it is critical to conduct multicenter collaborative research across various fields, such as psychiatry, neuroscience, molecular biology, genomics, neuroimaging, cognitive science, neurophysiology, psychology, and pharmacology. Moreover, collaborative research plays an important role in the development of young researchers. In this respect, the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium and Cognitive Genetics Collaborative Research Organization (COCORO) have played important roles. In this review, we first overview the importance of multicenter collaborative research and our target psychiatric disorders. Then, we introduce research findings on the pathophysiology of psychiatric disorders from neurocognitive, neurophysiological, neuroimaging, genetic, and basic neuroscience perspectives, focusing mainly on the findings obtained by COCORO. It is our hope that multicenter collaborative research will contribute to the elucidation of the pathological basis of psychiatric disorders.

Mesoscale microscopy and image analysis tools for understanding the brain

Over the last ten years, developments in whole-brain microscopy now allow for high-resolution imaging of intact brains of small animals such as mice. These complex images contain a wealth of information, but many neuroscience laboratories do not have all of the computational knowledge and tools needed to process these data. We review recent open source tools for registration of images to atlases, and the segmentation, visualisation and analysis of brain regions and labelled structures such as neurons. Since the field lacks fully integrated analysis pipelines for all types of whole-brain microscopy analysis, we propose a pathway for tool developers to work together to meet this challenge.

High-throughput mapping of a whole rhesus monkey brain at micrometer resolution

Whole-brain mesoscale mapping in primates has been hindered by large brain sizes and the relatively low throughput of available microscopy methods. Here, we present an approach that combines primate-optimized tissue sectioning and clearing with ultrahigh-speed fluorescence microscopy implementing improved volumetric imaging with synchronized on-the-fly-scan and readout technique, and is capable of completing whole-brain imaging of a rhesus monkey at 1 × 1 × 2.5 µm³ voxel resolution within 100 h. We also developed a highly efficient method for long-range tracing of sparse axonal fibers in datasets numbering hundreds of terabytes. This pipeline, which we call serial sectioning and clearing, three-dimensional microscopy with semiautomated reconstruction and tracing (SMART), enables effective connectome-scale mapping of large primate brains. With SMART, we were able to construct a cortical projection map of the mediodorsal nucleus of the thalamus and identify distinct turning and routing patterns of individual axons in the cortical folds while approaching their arborization destinations.

Sparse imaging and reconstruction tomography for high-speed high-resolution whole-brain imaging

Understanding brain functions requires detailed knowledge of long-range connectivity through which different areas communicate. A key step toward illuminating the long-range structures is to image the whole brain at synaptic resolution to trace axonal arbors of individual neurons to their termini. However, high-resolution brain-wide imaging requires continuous imaging for many days to sample over 10 trillion voxels, even in the mouse brain. Here, we have developed a sparse imaging and reconstruction tomography (SMART) system that allows brain-wide imaging of cortical projection neurons at synaptic resolution in about 20 h, an order of magnitude faster than previous methods. Analyses of morphological features reveal that single cortical neurons show remarkable diversity in local and long-range projections, with prefrontal, premotor, and visual neurons having distinct distribution of dendritic and axonal features. The fast imaging system and diverse projection patterns of individual neurons highlight the importance of high-resolution brain-wide imaging in revealing full neuronal morphology.

Multi-Scale Light-Sheet Fluorescence Microscopy for Fast Whole Brain Imaging

Whole-brain imaging has become an increasingly important approach to investigate neural structures, such as somata distribution, dendritic morphology, and axonal projection patterns. Different structures require whole-brain imaging at different resolutions. Thus, it is highly desirable to perform whole-brain imaging at multiple scales. Imaging a complete mammalian brain at synaptic resolution is especially challenging, as it requires continuous imaging from days to weeks because of the large number of voxels to sample, and it is difficult to acquire a constant quality of imaging because of light scattering during in toto imaging. Here, we reveal that light-sheet microscopy has a unique advantage over wide-field microscopy in multi-scale imaging because of its decoupling of illumination and detection. Based on this observation, we have developed a multi-scale light-sheet microscope that combines tiling of light-sheet, automatic zooming, periodic sectioning, and tissue expansion to achieve a constant quality of brain-wide imaging from cellular (3 μm × 3 μm × 8 μm) to sub-micron (0.3 μm × 0.3 μm × 1 μm) spatial resolution rapidly (all within a few hours). We demonstrated the strength of the system by testing it using mouse brains prepared using different clearing approaches. We were able to track electrode tracks as well as axonal projections at sub-micron resolution to trace the full morphology of single medial prefrontal cortex (mPFC) neurons that have remarkable diversity in long-range projections.

Precision vibratome for high-speed ultrathin biotissue cutting and organ-wide imaging

Cutting tissues into ultrathin slices is highly desired in sectioning-based organ-wide imaging. However, it is difficult to perform tissue cutting at a high speed with excellent quality. Here, we design a precision vibratome based on a paired double parallelogram flexure, which enables a vibrating blade to move strictly along a straight line. Meanwhile, we develop a high-speed cutting method that does not compromise cutting quality, which the vibratome operated at a high frequency mode. The characterized parasitic motion errors of a 180-Hz vibratome were less than 300 nm. It achieved a cutting speed six times that of an 85-Hz vibratome with acceptable quality. The capacity of the vibratome was investigated by organ-wide imaging, and the results revealed that it can be adapted in different tissues, such as the mouse brain and liver. This new vibratome shows great potential in speeding up organ-wide imaging applications especially for large volume biotissues.

Large-scale, cell-resolution volumetric mapping allows layer-specific investigation of human brain cytoarchitecture

Although neuronal density analysis on human brain slices is available from stereological studies, data on the spatial distribution of neurons in 3D are still missing. Since the neuronal organization is very inhomogeneous in the cerebral cortex, it is critical to map all neurons in a given volume rather than relying on sparse sampling methods. To achieve this goal, we implement a new tissue transformation protocol to clear and label human brain tissues and we exploit the high-resolution optical sectioning of two-photon fluorescence microscopy to perform 3D mesoscopic reconstruction. We perform neuronal mapping of 100mm3 human brain samples and evaluate the volume and density distribution of neurons from various areas of the cortex originating from different subjects (young, adult, and elderly, both healthy and pathological). The quantitative evaluation of the density in combination with the mean volume of the thousands of neurons identified within the specimens, allow us to determine the layer-specific organization of the cerebral architecture.

A deep learning algorithm for 3D cell detection in whole mouse brain image datasets

Understanding the function of the nervous system necessitates mapping the spatial distributions of its constituent cells defined by function, anatomy or gene expression. Recently, developments in tissue preparation and microscopy allow cellular populations to be imaged throughout the entire rodent brain. However, mapping these neurons manually is prone to bias and is often impractically time consuming. Here we present an open-source algorithm for fully automated 3D detection of neuronal somata in mouse whole-brain microscopy images using standard desktop computer hardware. We demonstrate the applicability and power of our approach by mapping the brain-wide locations of large populations of cells labeled with cytoplasmic fluorescent proteins expressed via retrograde trans-synaptic viral infection.

A Versatile Tiling Light Sheet Microscope for Imaging of Cleared Tissues

We present a tiling light sheet microscope compatible with all tissue clearing methods for rapid multicolor 3D imaging of cleared tissues with micron-scale (4 × 4 × 10 μm³) to submicron-scale (0.3 × 0.3 × 1 μm³) spatial resolution. The resolving ability is improved to sub-100 nm (70 × 70 × 200 nm³) via tissue expansion. The microscope uses tiling light sheets to achieve higher spatial resolution and better optical sectioning ability than conventional light sheet microscopes. The illumination light is phase modulated to adjust the position and intensity profile of the light sheet based on the desired spatial resolution and imaging speed and to keep the microscope aligned. The ability of the microscope to align via phase modulation alone also ensures its accuracy for multicolor 3D imaging and makes the microscope reliable and easy to operate. Here we describe the working principle and design of the microscope. We demonstrate its utility by imaging various cleared tissues.