Imaging Of Mouse Brain Research Articles

3D MR fingerprinting for dynamic contrast-enhanced imaging of whole mouse brain.

Quantitative MRI enables direct quantification of contrast agent concentrations in contrast-enhanced scans. However, the lengthy scan times required by conventional methods are inadequate for tracking contrast agent transport dynamically in mouse brain. We developed a 3D MR fingerprinting (MRF) method for simultaneous T1 and T2 mapping across the whole mouse brain with 4.3-min temporal resolution. We designed a 3D MRF sequence with variable acquisition segment lengths and magnetization preparations on a 9.4T preclinical MRI scanner. Model-based reconstruction approaches were employed to improve the accuracy and speed of MRF acquisition. The method's accuracy for T1 and T2 measurements was validated in vitro, while its repeatability of T1 and T2 measurements was evaluated in vivo (n = 3). The utility of the 3D MRF sequence for dynamic tracking of intracisternally infused gadolinium-diethylenetriamine pentaacetic acid (Gd-DTPA) in the whole mouse brain was demonstrated (n = 5). Phantom studies confirmed accurate T1 and T2 measurements by 3D MRF with an undersampling factor of up to 48. Dynamic contrast-enhancedMRF scans achieved a spatial resolution of 192 × 192 × 500 μm3 and a temporal resolution of 4.3 min, allowing for the analysis and comparison of dynamic changes in concentration and transport kinetics of intracisternally infused Gd-DTPA across brain regions. The sequence also enabled highly repeatable, high-resolution T1 and T2 mapping of the whole mouse brain (192 × 192 × 250 μm3) in 30 min. We present the first dynamic and multi-parametric approach for quantitatively tracking contrast agent transport in the mouse brain using 3D MRF.

ClearScope: a fully integrated light sheet theta microscope for sub-cellular resolution imaging without lateral size constraints.

Three-dimensional (3D) ex vivo imaging of cleared intact brains of animal models and large human and non-human primate postmortem brain specimens is important for understanding the physiological neural network connectivity patterns and the pathological alterations underlying neuropsychiatric and neurological disorders. Light-sheet microscopy has emerged as a highly effective imaging modality for rapid high-resolution imaging of large cleared samples. However, the orthogonal arrangements of illumination and detection optics in light sheet microscopy limits the size of specimen that can be imaged. Recently developed light sheet theta microscopy (LSTM) technology addressed this by utilizing a unique arrangement of two illumination light paths oblique to the detection light path, while allowing perpendicular arrangement of the detection light path relative to the specimen surface. Here, we report development of a next-generation, fully integrated, and user-friendly LSTM system for rapid sub-cellular resolution imaging uniformly throughout a large specimen without constraining the lateral (XY) size. In addition, we provide a seamlessly integrated workflow for image acquisition, data storage, pre- and post-processing, enhancement, and quantitative analysis. We demonstrate the system performance by high-resolution 3D imaging of intact mouse brains and human brain samples, and complete data analysis including digital neuron tracing, vessel reconstruction and design-based stereological analysis in 3D. This technically enhanced and user-friendly LSTM implementation will enable rapid quantitative mapping of molecular and cellular features of interests in diverse types of very large samples.

AnNoBrainer, An Automated Annotation of Mouse Brain Images using Deep Learning.

Annotation of multiple regions of interest across the whole mouse brain is an indispensable process for quantitative evaluation of a multitude of study endpointsin neuroscience digital pathology. Prior experience and domain expert knowledge are the key aspects for image annotation quality and consistency. At present, image annotation is often achieved manually by certified pathologists or trained technicians, limiting the total throughput of studies performed at neuroscience digital pathology labs. It may also mean that simpler and quicker methods of examining tissue samples are used by non-pathologists, especially in the early stages of research and preclinical studies. To address these limitations and to meet the growing demand for image analysis in a pharmaceutical setting, we developed AnNoBrainer, an open-source software tool that leverages deep learning, image registration, and standard cortical brain templates to automatically annotate individual brain regions on 2D pathology slides. Application of AnNoBrainer to a published set of pathology slides from transgenic mice models of synucleinopathy revealed comparable accuracy, increased reproducibility, and a significant reduction (~ 50%) in time spent on brain annotation, quality control and labelling compared to trained scientists in pathology. Taken together, AnNoBrainer offers a rapid, accurate, and reproducible automated annotation of mouse brain images that largely meets the experts' histopathological assessment standards (> 85% of cases) and enables high-throughput image analysis workflows in digital pathology labs.

Conjugate Polymer Anchor Enhancing Matrix Vacuum Stability and Improving MALDI MSI via Ion Bond.

Poor vacuum stability limits the application of many matrices in matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) that requires long-term measurement duration in high vacuum. In this study, a new approach using conjugate polymer anchor to protect unstable matrix from volatilizing in MALDI source based on ion bond is provided. Unlike strong covalent bonds which often introduce unnecessary groups, the weaker ion bonds are more conducive to breaking under laser radiation while effectively preventing matrix volatilization in a vacuum environment. The results confirm that conjugate polymer anchor will neither introduce additional ion peaks nor affect signal intensity, yet maintains comparable quantification properties. Vacuum stability of three kinds of typical matrices is enhanced using polymer anchors, and the in situ MALDI MS imaging of mouse brain and liver cancer is improved significantly.

Targeting soluble amyloid-beta oligomers with a novel nanobody

The classical amyloid cascade hypothesis postulates that the aggregation of amyloid plaques and the accumulation of intracellular hyperphosphorylated Tau tangles, together, lead to profound neuronal death. However, emerging research has demonstrated that soluble amyloid-β oligomers (SAβOs) accumulate early, prior to amyloid plaque formation. SAβOs induce memory impairment and disrupt cognitive function independent of amyloid-β plaques, and even in the absence of plaque formation. This work describes the development and characterization of a novel anti-SAβO (E3) nanobody generated from an alpaca immunized with SAβO. In-vitro assays and in-vivo studies using 5XFAD mice indicate that the fluorescein (FAM)-labeled E3 nanobody recognizes both SAβOs and amyloid-β plaques. The E3 nanobody traverses across the blood–brain barrier and binds to amyloid species in the brain of 5XFAD mice. Imaging of mouse brains reveals that SAβO and amyloid-β plaques are not only different in size, shape, and morphology, but also have a distinct spatial distribution in the brain. SAβOs are associated with neurons, while amyloid plaques reside in the extracellular matrix. The results of this study demonstrate that the SAβO nanobody can serve as a diagnostic agent with potential theragnostic applications in Alzheimer’s disease.

High-resolution hybrid micro-CT imaging pipeline for mouse brain region segmentation and volumetric morphometry.

Brain region segmentation and morphometry in humanized apolipoprotein E (APOE) mouse models with a human NOS2 background (HN) contribute to Alzheimer's disease (AD) research by demonstrating how various risk factors affect the brain. Photon-counting detector (PCD) micro-CT provides faster scan times than MRI, with superior contrast and spatial resolution to energy-integrating detector (EID) micro-CT. This paper presents a pipeline for mouse brain imaging, segmentation, and morphometry from PCD micro-CT. We used brains of 26 mice from 3 genotypes (APOE22HN, APOE33HN, APOE44HN). The pipeline included PCD and EID micro-CT scanning, hybrid (PCD and EID) iterative reconstruction, and brain region segmentation using the Small Animal Multivariate Brain Analysis (SAMBA) tool. We applied SAMBA to transfer brain region labels from our new PCD CT atlas to individual PCD brains via diffeomorphic registration. Region-based and voxel-based analyses were used for comparisons by genotype and sex. Together, PCD and EID scanning take ~5 hours to produce images with a voxel size of 22 μm, which is faster than MRI protocols for mouse brain morphometry with voxel size above 40 μm. Hybrid iterative reconstruction generates PCD images with minimal artifacts and higher spatial resolution and contrast than EID images. Our PCD atlas is qualitatively and quantitatively similar to the prior MRI atlas and successfully transfers labels to PCD brains in SAMBA. Male and female mice had significant volume differences in 26 regions, including parts of the entorhinal cortex and cingulate cortex. APOE22HN brains were larger than APOE44HN brains in clusters from the hippocampus, a region where atrophy is associated with AD. This work establishes a pipeline for mouse brain analysis using PCD CT, from staining to imaging and labeling brain images. Our results validate the effectiveness of the approach, setting a foundation for research on AD mouse models while reducing scanning durations.

The role of CCN1 in kidney-brain crosstalk

Cognitive impairment and dementia are major global health problems of the aging human population. It is estimated that about 55 million people were living with dementia in 2019 and this number is expected to triple by 2050. Dementia can result from abnormal structure and function of brain blood vessels that may develop in a variety of conditions including chronic kidney disease (CKD). Recent studies from our laboratory suggest that in addition to controlling blood volume and blood pressure (renin), and blood cell count (erythropoietin), the kidney produces novel systemic angiogenic hormones to maintain blood vessels, such as the matricellular protein Cellular Communication Network factor 1 (CCN1). These hormones are then released to the blood and may act as new molecular mechanisms of kidney-brain crosstalk. We hypothesized that kidney-derived CCN1 helps to preserve the normal structure and function of blood vessels throughout the body, including a healthy blood-brain barrier (BBB). We further hypothesized that reduced plasma CCN1 caused by diminished renal production of CCN1 due to kidney disease plays a major role in the development of brain vascular dysfunction, and therefore in the pathogenesis and progression of dementia and cognitive impairment. Intravital multiphoton (MPM) imaging of the intact mouse brain in control or after 5/6 nephrectomy (5/6 Nx), a well-established mouse model of chronic kidney disease (CKD) was used to measure changes in BBB permeability with or without chronic CCN1 treatment. Kidney and BBB structure/function phenotyping was performed using CCN1 ELISA assay, the Medibeacon transdermal GFR measurement system, tissue harvest, and immunohistochemistry. Compared to control, 5/6 Nx mice had reduced plasma CCN1 levels, reduced GFR, but no difference in systolic blood pressure. MPM imaging showed increased fluorescence intensity of mid-size plasma proteins (A680 conjugated Albumin 70 kDa) compared to high molecular weight markers (A488 conjugated Dextran 500 kDa) in brain interstitium in 5/6 Nx compared to control. In addition, the density of cell-to-cell junctions in brain endothelial cells were 20% reduced in CKD compared to control healthy mice. In brain endothelial cells cultured in vitro, CCN1 treatment had protective effects on cell proliferation, motility and angiogenesis as confirmed by scratch and tube formation assays. In summary, this study identified new mechanisms of kidney-brain crosstalk, and helped to improve our mechanistic understanding of cerebrovascular pathology in CKD. DK123564, DK064324, DK135290. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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.

An MR-based brain template and atlas for optical projection tomography and light sheet fluorescence microscopy in neuroscience.

Optical Projection Tomography (OPT) and light sheet fluorescence microscopy (LSFM) are high resolution optical imaging techniques, ideally suited for ex vivo 3D whole mouse brain imaging. Although they exhibit high specificity for their targets, the anatomical detail provided by tissue autofluorescence remains limited. T1-weighted images were acquired from 19 BABB or DBE cleared brains to create an MR template using serial longitudinal registration. Afterwards, fluorescent OPT and LSFM images were coregistered/normalized to the MR template to create fusion images. Volumetric calculations revealed a significant difference between BABB and DBE cleared brains, leading to develop two optimized templates, with associated tissue priors and brain atlas, for BABB (OCUM) and DBE (iOCUM). By creating fusion images, we identified virus infected brain regions, mapped dopamine transporter and translocator protein expression, and traced innervation from the eye along the optic tract to the thalamus and superior colliculus using cholera toxin B. Fusion images allowed for precise anatomical identification of fluorescent signal in the detailed anatomical context provided by MR. The possibility to anatomically map fluorescent signals on magnetic resonance (MR) images, widely used in clinical and preclinical neuroscience, would greatly benefit applications of optical imaging of mouse brain. These specific MR templates for cleared brains enable a broad range of neuroscientific applications integrating 3D optical brain imaging.

NIEND: neuronal image enhancement through noise disentanglement.

The full automation of digital neuronal reconstruction from light microscopic images has long been impeded by noisy neuronal images. Previous endeavors to improve image quality can hardly get a good compromise between robustness and computational efficiency. We present the image enhancement pipeline named Neuronal Image Enhancement through Noise Disentanglement (NIEND). Through extensive benchmarking on 863 mouse neuronal images with manually annotated gold standards, NIEND achieves remarkable improvements in image quality such as signal-background contrast (40-fold) and background uniformity (10-fold), compared to raw images. Furthermore, automatic reconstructions on NIEND-enhanced images have shown significant improvements compared to both raw images and images enhanced using other methods. Specifically, the average F1 score of NIEND-enhanced reconstructions is 0.88, surpassing the original 0.78 and the second-ranking method, which achieved 0.84. Up to 52% of reconstructions from NIEND-enhanced images outperform all other four methods in F1 scores. In addition, NIEND requires only 1.6 s on average for processing 256 × 256 × 256-sized images, and images after NIEND attain a substantial average compression rate of 1% by LZMA. NIEND improves image quality and neuron reconstruction, providing potential for significant advancements in automated neuron morphology reconstruction of petascale. The study is conducted based on Vaa3D and Python 3.10. Vaa3D is available on GitHub (https://github.com/Vaa3D). The proposed NIEND method is implemented in Python, and hosted on GitHub along with the testing code and data (https://github.com/zzhmark/NIEND). The raw neuronal images of mouse brains can be found at the BICCN's Brain Image Library (BIL) (https://www.brainimagelibrary.org). The detailed list and associated meta information are summarized in Supplementary Table S3.

In Vivo Intelligent Fluorescence Endo-Microscopy by Varifocal Meta-Device and Deep Learning.

Endo-microscopy is crucial for real-time 3D visualization of internal tissues and subcellular structures. Conventional methods rely on axial movement of optical components for precise focus adjustment, limiting miniaturization and complicating procedures. Meta-device, composed of artificial nanostructures, is an emerging optical flat device that can freely manipulate the phase and amplitude of light. Here, an intelligent fluorescence endo-microscope is developed based on varifocal meta-lens and deep learning (DL). The breakthrough enables in vivo 3D imaging of mouse brains, where varifocal meta-lens focal length adjusts through relative rotation angle. The system offers key advantages such as invariant magnification, a large field-of-view, and optical sectioning at a maximum focal length tuning range of ≈2mm with 3µm lateral resolution. Using a DL network, image acquisition time and system complexity are significantly reduced, and in vivo high-resolution brain images of detailed vessels and surrounding perivascular space are clearly observed within 0.1 s (≈50 times faster). The approach will benefit various surgical procedures, such as gastrointestinal biopsies, neural imaging, brain surgery, etc.

Large-scale cranial window for in vivo mouse brain imaging utilizing fluoropolymer nanosheet and light-curable resin

Two-photon microscopy enables in vivo imaging of neuronal activity in mammalian brains at high resolution. However, two-photon imaging tools for stable, long-term, and simultaneous study of multiple brain regions in same mice are lacking. Here, we propose a method to create large cranial windows covering such as the whole parietal cortex and cerebellum in mice using fluoropolymer nanosheets covered with light-curable resin (termed the ‘Nanosheet Incorporated into light-curable REsin’ or NIRE method). NIRE method can produce cranial windows conforming the curved cortical and cerebellar surfaces, without motion artifacts in awake mice, and maintain transparency for >5 months. In addition, we demonstrate that NIRE method can be used for in vivo two-photon imaging of neuronal ensembles, individual neurons and subcellular structures such as dendritic spines. The NIRE method can facilitate in vivo large-scale analysis of heretofore inaccessible neural processes, such as the neuroplastic changes associated with maturation, learning and neural pathogenesis.

Geometric transformation adaptive optics (GTAO) for volumetric deep brain imaging through gradient-index lenses

The advance of genetic function indicators has enabled the observation of neuronal activities at single-cell resolutions. A major challenge for the applications on mammalian brains is the limited optical access depth. Currently, the method of choice to access deep brain structures is to insert miniature optical components. Among these validated miniature optics, the gradient-index (GRIN) lens has been widely employed for its compactness and simplicity. However, due to strong fourth-order astigmatism, GRIN lenses suffer from a small imaging field of view, which severely limits the measurement throughput and success rate. To overcome these challenges, we developed geometric transformation adaptive optics (GTAO), which enables adaptable achromatic large-volume correction through GRIN lenses. We demonstrate its major advances through in vivo structural and functional imaging of mouse brains. The results suggest that GTAO can serve as a versatile solution to enable large-volume recording of deep brain structures and activities through GRIN lenses.

Open-source versatile 3D-print animal conditioning platform design for in vivo preclinical brain imaging in awake mice and anesthetized mice and rats.

Proper animal conditioning is a key factor in the quality and success of preclinical neuroimaging applications. Here, we introduce an open-source easy-to-modify multimodal 3D printable design for rodent conditioning for magnetic resonance imaging (MRI) or other imaging modalities. Our design can be used for brain imaging in anesthetized or awake mice, and in anesthetized rats. We show ease of use and reproducibility of subject conditioning with anatomical T2-weighted imaging for both mice and rats. We also demonstrate the application of our design for awake functional MRI in mice using both visual evoked potential and olfactory stimulation paradigms. In addition, using a combined MRI, positron emission tomography and X-ray computed tomography experiment, we demonstrate that our proposed cradle design can be utilized for multiple imaging modalities.

Multibeam continuous axial scanning two-photon microscopy for in vivo volumetric imaging in mouse brain.

This study presents an alternative approach for two-photon volumetric imaging that combines multibeam lateral scanning with continuous axial scanning using a confocal spinning-disk scanner and an electrically focus tunable lens. Using this proposed system, the brain of a living mouse could be imaged at a penetration depth of over 450 μm from the surface. In vivo volumetric Ca2+ imaging at a volume rate of 1.5 Hz within a depth range of 130-200 μm, was segmented with an axial pitch of approximately 5-µm and revealed spontaneous activity of neurons with their 3D positions. This study offers a practical microscope design equipped with compact scanners, a simple control system, and readily adjustable imaging parameters, which is crucial for the widespread adoption of two-photon volumetric imaging.

Data-driven coordinated attention deep learning for high-fidelity brain imaging denoising and inpainting.

Deep learning offers promise in enhancing low-quality images by addressing weak fluorescence signals, especially in deep in vivo mouse brain imaging. However, current methods struggle with photon scarcity and noise within in vivo deep mouse brains, and often neglecting tissue preservation. In this study, we propose an innovative in vivo cortical fluorescence image restoration approach, combining signal enhancement, denoising, and inpainting. We curated a deep brain cortical image dataset and developed a novel deep brain coordinate attention restoration network (DeepCAR), integrating coordinate attention with optimized residual networks. Our method swiftly and accurately restores deep cortex images exceeding 800 μm, preserving small-scale tissue structures. It boosts the peak signal-to-noise ratio (PSNR) by 6.94 dB for weak signals and 11.22 dB for large noisy images. Crucially, we validate the effectiveness on external datasets with diverse noise distributions, structural features compared to those in our training data, showcasing real-time high-performance image restoration capabilities.

A novel NIR fluorescent probe for copper(ii) imaging in Parkinson's disease mouse brain.

Abnormal copper ion (Cu2+) levels are considered to be one of the pathological factors of Parkinson's disease (PD), but the internal relationship between Cu2+ and PD progression remains elusive. Visualizing Cu2+ in the brain will be pivotal for comprehending the underlying pathophysiological processes of PD. In this work, a near-infrared (NIR) fluorescent probe, DDAO-Cu, capable of detecting Cu2+ with exceptional sensitivity (about 1.8 nM of detection limit) and selectivity, rapid response (<3 min), and deep tissue penetration, was designed for quantification and visualization of the Cu2+ level. It could detect not only Cu2+ in cells but also the changes in the Cu2+ level in the rotenone-induced cell and zebrafish PD models. Moreover, DDAO-Cu can cross the blood-brain barrier to image Cu2+ in the brain of PD model mice. The imaging result showed a significant increase in Cu2+ levels in brain regions of PD model mice, including the cerebral cortex, hippocampus, and striatum. Meanwhile, Cu2+ levels in the substantia nigra region were significantly reduced in PD model mice. It revealed the nuanced relationship of Cu2+ levels in different brain regions in the disease and indicated the pathological complexity of PD. Overall, DDAO-Cu represents a novel and practical tool for investigating Cu2+-related physiological and pathological processes underlying Parkinson's disease.

Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images.

Knowledge of protein expression in mammalian brains at regional and cellular levels can facilitate understanding of protein functions and associated diseases. As the mouse brain is a typical mammalian brain considering cell type and structure, several studies have been conducted to analyze protein expression in mouse brains. However, labeling protein expression using biotechnology is costly and time-consuming. Therefore, automated models that can accurately recognize protein expression are needed. Here, we constructed machine learning models to automatically annotate the protein expression intensity and cellular location in different mouse brain regions from immunofluorescence images. The brain regions and sub-regions were segmented through learning image features using an autoencoder and then performing K-means clustering and registration to align with the anatomical references. The protein expression intensities for those segmented structures were computed on the basis of the statistics of the image pixels, and patch-based weakly supervised methods and multi-instance learning were used to classify the cellular locations. Results demonstrated that the models achieved high accuracy in the expression intensity estimation, and the F1 score of the cellular location prediction was 74.5%. This work established an automated pipeline for analyzing mouse brain images and provided a foundation for further study of protein expression and functions.

Associations of neuro-glial network calcium activity with mice movements &lt;i&gt;in vivo&lt;/i&gt;

Calcium imaging of nerve activity in the mouse hippocampus provides insights into cell-to-cell interactions [1]. Over time, fluctuations in cellular calcium levels encode distinct brain states during mouse brain imaging. Although synapses connect cells and transmit information, it is challenging to detect the spatiotemporal transmission pathway via calcium imaging of multiple cells due to the complexity of the spatial structure and imaging in a separate focal plane [2]. Reconstruction of the dynamic graph of connections between cells was proposed to overcome this problem. A dynamic graph comprises of individual graphs for each time point. A graph linked to a particular time t is composed of vertices representing cells and edges that depict the transmission of signals between cells at that moment. This paper puts forth 3 approaches for creating networks. The first method considers the overlapping time intervals of calcium events in individual cells [3]. The link is established between the cell with the earlier event and the cell with the later start of the event during the moments when the events occurred simultaneously in separate cells. Alternatively, time intervals between the start of events were taken into account. Potentially connected events that began no later than 2 s were linked, with the edge drawn from the cell depicting the earlier starting event to the second cell. The third technique involved linking sequentially occurring events in distinct cells. The edge is drawn from all active cells at the previous time step to newly activated cells at the subsequent time step. Data analysis is based on an experiment in which a mouse moved along a circular track while the fluorescence of neuronal calcium activity and the mouse’s position were recorded at a frequency of 20 frames per second [4]. A red dot was marked on the mouse’s head to track its position. The reconstructed dynamic graph was compared to the angular coordinate of the mouse on the ring to look for repeating patterns of activity. The racetrack was divided into 20 overlapping sectors, each spanning 36 degrees. The reconstructed networks were then assigned to sectors that aligned with the mouse’s angular position on the track. Next, we estimated the frequency of individual edge repetitions within each network group. Only edges that occurred at least three times were chosen for further analysis. We found repeated activations of various cell pairs that corresponded to clockwise and counterclockwise movement within the same sector. Furthermore, we identified the presence of alternating activation, where activity occurred in the first cell, then the second cell, and then again in the first cell. In addition, we identified complex sequences of 5–6 non-sequential activations, represented as a digraph without cycles, which is typical for single sectors.

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.