High-definition imaging using line-illumination modulation microscopy.

The microscopic visualization of large-scale three-dimensional (3D) samples by optical microscopy requires overcoming challenges in imaging quality and speed and in big data acquisition and management. We report a line-illumination modulation (LiMo) technique for imaging thick tissues with high throughput and low background. Combining LiMo with thin tissue sectioning, we further develop a high-definition fluorescent micro-optical sectioning tomography (HD-fMOST) method that features an average signal-to-noise ratio of 110, leading to substantial improvement in neuronal morphology reconstruction. We achieve a >30-fold lossless data compression at a voxel resolution of 0.32 × 0.32 × 1.00 µm3, enabling online data storage to a USB drive or in the cloud, and high-precision (95% accuracy) brain-wide 3D cell counting in real time. These results highlight the potential of HD-fMOST to facilitate large-scale acquisition and analysis of whole-brain high-resolution datasets.

Pixel-reassigned line-scanning microscopy for fast volumetric super-resolution imaging.

Super-resolution microscopy has revolutionized the field of biophotonics by revealing detailed 3D biological structures. Nonetheless, the technique is still largely limited by the low throughput and hampered by increased background signals for dense or thick biological specimens. In this paper, we present a pixel-reassigned continuous line-scanning microscope for large-scale high-speed 3D super-resolution imaging, which achieves an imaging resolution of 0.41 µm in the lateral direction, i.e., a 2× resolution enhancement from the raw images. Specifically, the recorded line images are first reassigned to the line-excitation center at each scanning position to enhance the resolution. Next, a modified HiLo algorithm is applied to reduce the background signals. Parametric models have been developed to simulate the imaging results of randomly distributed fluorescent beads. Imaging experiments were designed and performed to verify the predicted performance on various biological samples, which demonstrated an imaging speed of 3400 pixels/ms on millimeter-scale specimens. These results confirm the pixel-reassigned line-scanning microscopy is a facile and powerful method to realize large-area super-resolution imaging on thick or dense biological samples.

Compressive sensing-based multi-focus line-scanning two-photon microscopy for fast 3D imaging.

Fast 3D volume imaging methods have been playing increasingly important roles in biological studies. In this article, we present the design and characterization of a multi-focus line-scanning two-photon microscope. Specifically, a digital micromirror device (DMD) is employed to generate a randomly distributed focus array on a plane (i.e., x-z) via binary holography. Next, a galvanometric mirror scans the focus array in a direction normal to the plane (i.e., y-axis) over the imaging volume. For sparse samples, e.g., neural networks in a brain, 1-3 foci are used together with compressive sensing algorithm to achieve a volume imaging rate of 15.5 volumes/sec over 77 × 120 × 40 µm3. High-resolution optical cross-sectional images on selected planes and regions can be generated by sequentially scanning the laser focus generated on the x-z plane with good imaging speeds (e.g., 107 frames/sec over 80 × 120 × 40 µm3). In the experiments, microbeads, pollens, and mouse brain slices have been imaged to characterize the point spread function and volume image rate and quality at different sampling ratios. The results show that the multi-focus line-scanning microscope presents a fast and versatile 3D imaging platform for deep tissue imaging and dynamic live animal studies.

High-throughput optical sectioning via line-scanning imaging with digital structured modulation.

Optical sectioning with high-throughput, a high signal-to-noise ratio (SNR), and submicrometer resolution is crucial, but challenging, to three-dimensional visualization of large biological tissue samples. Here we propose line-scanning imaging with digital structured modulation for optical sectioning. Our method generates images with a significantly improved SNR, compared to wide-field structured illumination microscopy (WF-SIM), without residual modulation artifacts. We image a 14.5mm×11.5mm horizontal view of mouse brain tissue at a pixel resolution of 0.32µm×0.32µm in 101 s, which, compared to WF-SIM, represents a significant improvement on imaging throughput. These results provide development opportunities for high-throughput, high-resolution large-area optical imaging methods.

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.

DeepMapi: a Fully Automatic Registration Method for Mesoscopic Optical Brain Images Using Convolutional Neural Networks.

The extreme complexity of mammalian brains requires a comprehensive deconstruction of neuroanatomical structures. Scientists normally use a brain stereotactic atlas to determine the locations of neurons and neuronal circuits. However, different brain images are normally not naturally aligned even when they are imaged with the same setup, let alone under the differing resolutions and dataset sizes used in mesoscopic imaging. As a result, it is difficult to achieve high-throughput automatic registration without manual intervention. Here, we propose a deep learning-based registration method called DeepMapi to predict a deformation field used to register mesoscopic optical images to an atlas. We use a self-feedback strategy to address the problem of imbalanced training sets (sampling at a fixed step size in nonuniform brains of structures and deformations) and use a dual-hierarchical network to capture the large and small deformations. By comparing DeepMapi with other registration methods, we demonstrate its superiority over a set of ground truth images, including both optical and MRI images. DeepMapi achieves fully automatic registration of mesoscopic micro-optical images, even macroscopic MRI datasets, in minutes, with an accuracy comparable to those of manual annotations by anatomists.

A whole-brain map of long-range inputs to GABAergic interneurons in the mouse medial prefrontal cortex.

The medial prefrontal cortex (mPFC) contains populations of GABAergic interneurons that play different roles in cognition and emotion. Their local and long-range inputs are incompletely understood. We used monosynaptic rabies viral tracers in combination with fluorescence micro-optical sectioning tomography to generate a whole-brain atlas of direct long-range inputs to GABAergic interneurons in the mPFC of male mice. We discovered that three subtypes of GABAergic interneurons in two areas of the mPFC are innervated by same upstream areas. Input from subcortical upstream areas includes cholinergic neurons from the basal forebrain and serotonergic neurons (which co-release glutamate) from the raphe nuclei. Reconstruction of single-neuron morphology revealed novel substantia innominata-anteromedial thalamic nucleus-mPFC and striatum-anteromedial thalamic nucleus-mPFC circuits. Based on the projection logic of individual neurons, we classified cortical and hippocampal input neurons into several types. This atlas provides the anatomical foundation for understanding the functional organization of the mPFC.

Simultaneous acquisition of neuronal morphology and cytoarchitecture in the same Golgi-stained brain.

Acquiring an accurate orientation reference is a prerequisite for precisely analysing the morphological features of Golgi-stained neurons in the whole brain. However, the same reflective imaging contrast of Golgi staining for morphology and Nissl staining for cytoarchitecture leads to the failure of distinguishing soma morphology and simultaneously co-locate cytoarchitecture. Here, we developed the dual-mode micro-optical sectioning tomography (dMOST) method to simultaneously image the reflective and fluorescent signals in three dimensions. We evaluated the feasibility of real-time fluorescent counterstaining on Golgi-stained brain tissue. With our system, we acquired whole-brain data sets of physiological and pathological Golgi-stained mouse model brains with fluorescence-labelled anatomical annotation at single-neuron resolution. We also obtained the neuronal morphology of macaque monkey brain tissue using this method. The results show that real-time acquisition of the co-located cytoarchitecture reference in the same brain greatly facilitates the precise morphological analysis of Golgi-stained neurons.

A platform for efficient identification of molecular phenotypes of brain-wide neural circuits.

A neural circuit is a structural-functional unit of achieving particular information transmission and processing, and have various inputs, outputs and molecular phenotypes. Systematic acquisition and comparative analysis of the molecular features of neural circuits are crucial to elucidating the operating mechanisms of brain function. However, no efficient, systematic approach is available for describing the molecular phenotypes of specific neural circuits at the whole brain scale. In this study, we developed a rapid whole-brain optical tomography method and devised an efficient approach to map brain-wide structural and molecular information in the same brain: rapidly imaging and sectioning the whole brain as well as automatically collecting all slices; conveniently selecting slices of interest through quick data browsing and then performing post hoc immunostaining of selected slices. Using this platform, we mapped the brain-wide distribution of inputs to motor, sensory and visual cortices and determined their molecular phenotypes in several subcortical regions. Our platform significantly enhances the efficiency of molecular phenotyping of neural circuits and provides access to automation and industrialization of cell type analyses for specific circuits.

High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level.

The precise annotation and accurate identification of neural structures are prerequisites for studying mammalian brain function. The orientation of neurons and neural circuits is usually determined by mapping brain images to coarse axial-sampling planar reference atlases. However, individual differences at the cellular level likely lead to position errors and an inability to orient neural projections at single-cell resolution. Here, we present a high-throughput precision imaging method that can acquire a co-localized brain-wide data set of both fluorescent-labelled neurons and counterstained cell bodies at a voxel size of 0.32 × 0.32 × 2.0 µm in 3 days for a single mouse brain. We acquire mouse whole-brain imaging data sets of multiple types of neurons and projections with anatomical annotation at single-neuron resolution. The results show that the simultaneous acquisition of labelled neural structures and cytoarchitecture reference in the same brain greatly facilitates precise tracing of long-range projections and accurate locating of nuclei.