Investigation of a complete squeeze-film damping model for MEMS devices.

Dynamic performance has long been critical for micro-electro-mechanical system (MEMS) devices and is significantly affected by damping. Different structural vibration conditions lead to different damping effects, including border and amplitude effects, which represent the effect of gas flowing around a complicated boundary of a moving plate and the effect of a large vibration amplitude, respectively. Conventional models still lack a complete understanding of damping and cannot offer a reasonably good estimate of the damping coefficient for a case with both effects.

SparseTracer: the Reconstruction of Discontinuous Neuronal Morphology in Noisy Images.

Digital reconstruction of a single neuron occupies an important position in computational neuroscience. Although many novel methods have been proposed, recent advances in molecular labeling and imaging systems allow for the production of large and complicated neuronal datasets, which pose many challenges for neuron reconstruction, especially when discontinuous neuronal morphology appears in a strong noise environment. Here, we develop a new pipeline to address this challenge.

Automated, highly reproducible, wide-field, light-based cortical mapping method using a commercial stereo microscope and its applications.

We introduce a more flexible optogenetics-based mapping system attached on a stereo microscope, which offers automatic light stimulation to individual regions of interest in the cortex that expresses light-activated channelrhodopsin-2 . Combining simultaneous recording of electromyography from specific forelimb muscles, we demonstrate that this system offers much better efficiency and precision in mapping distinct domains for controlling limb muscles in the mouse motor cortex. Furthermore, the compact and modular design of the system also yields a simple and flexible implementation to different commercial stereo microscopes, and thus could be widely used among laboratories.

Large-scale localization of touching somas from 3D images using density-peak clustering.

Background: Soma localization is an important step in computational neuroscience to map neuronal circuits. However, locating somas from large-scale and complicated datasets is challenging. The challenges primarily originate from the dense distribution of somas, the diversity of soma sizes and the inhomogeneity of image contrast.

Structural anisotropy quantification improves the final superresolution image of localization microscopy.

Superresolution localization microscopy initially produces a dataset of fluorophore coordinates instead of a conventional digital image. Therefore, superresolution localization microscopy requires additional data analysis to present a final superresolution image. However, methods of employing the structural information within the localization dataset to improve the data analysis performance remain poorly developed.

Visual Cue-Discriminative Dopaminergic Control of Visuomotor Transformation and Behavior Selection.

Animals behave differently in response to visual cues with distinct ethological meaning, a process usually thought to be achieved through differential visual processing. Using a defined zebrafish escape circuit as a model, we found that behavior selection can be implemented at the visuomotor transformation stage through a visually responsive dopaminergic-inhibitory circuit module. In response to non-threatening visual stimuli, hypothalamic dopaminergic neurons and their positively regulated hindbrain inhibitory interneurons increase activity, suppressing synaptic transmission from the visual center to the escape circuit.

Reconstruction of micron resolution mouse brain surface from large-scale imaging dataset using resampling-based variational model.

Brain surface profile is essential for brain studies, including registration, segmentation of brain structure and drawing neuronal circuits. Recent advances in high-throughput imaging techniques enable imaging whole mouse brain at micron spatial resolution and provide a basis for more fine quantitative studies in neuroscience. However, reconstructing micron resolution brain surface from newly produced neuronal dataset still faces challenges.

iCut: an Integrative Cut Algorithm Enables Accurate Segmentation of Touching Cells.

Individual cells play essential roles in the biological processes of the brain. The number of neurons changes during both normal development and disease progression. High-resolution imaging has made it possible to directly count cells.

Rapid imaging of large tissues using high-resolution stage-scanning microscopy.

Rapid and high-resolution imaging of large tissues is essential in biological research, like brain neuron connectivity research and cancer margins imaging. Here a novel stage-scanning confocal microscopy was developed for rapid imaging of large tissues. Line scanning methods and strip imaging strategy were used to increase the imaging speed.

Decoupled fluorescence Monte Carlo model for direct computation of fluorescence in turbid media.

We present a decoupled fluorescence Monte Carlo (dfMC) model for the direct computation of the fluorescence in turbid media. By decoupling the excitation-to-emission conversion and transport process of the fluorescence from the path probability density function and associating the corresponding parameters involving the fluorescence process with the weight function, the dfMC model employs the path histories of the excitation photons and the corresponding new weight function to directly calculate the fluorescence. We verify the model’s accuracy using phantom experiments and compare it with that of the perturbation fluorescence Monte Carlo model.

Fast and automatic imaging of immunoenzyme-stained neuronal circuits in the whole brain of Drosophila.

Knowledge of neuronal wiring and morphogenesis in Drosophila is essential to understand brain function and dysfunction. The immunoenzyme method based on horseradish peroxidase/diaminobenzidine (HRP/DAB) provides high-contrast images to resolve details underlying neuronal architecture. However, the poor staining penetration and a lack of corresponding three-dimensional imaging methodology limit its application.

An automated three-dimensional detection and segmentation method for touching cells by integrating concave points clustering and random walker algorithm.

Characterizing cytoarchitecture is crucial for understanding brain functions and neural diseases. In neuroanatomy, it is an important task to accurately extract cell populations' centroids and contours. Recent advances have permitted imaging at single cell resolution for an entire mouse brain using the Nissl staining method.

Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity.

ABSTRACT. Near-infrared spectroscopy (NIRS) is a developing and promising functional brain imaging technology. Developing data analysis methods to effectively extract meaningful information from collected data is the major bottleneck in popularizing this technology.

Digital reconstruction of the cell body in dense neural circuits using a spherical-coordinated variational model.

Mapping the neuronal circuits is essential to understand brain function. Recent technological advancements have made it possible to acquire the brain atlas at single cell resolution. Digital reconstruction of the neural circuits down to this level across the whole brain would significantly facilitate brain studies.

Indian-ink perfusion based method for reconstructing continuous vascular networks in whole mouse brain.

The topology of the cerebral vasculature, which is the energy transport corridor of the brain, can be used to study cerebral circulatory pathways. Limited by the restrictions of the vascular markers and imaging methods, studies on cerebral vascular structure now mainly focus on either observation of the macro vessels in a whole brain or imaging of the micro vessels in a small region. Simultaneous vascular studies of arteries, veins and capillaries have not been achieved in the whole brain of mammals.

Refractory period modulates the spatiotemporal evolution of cortical spreading depression: a computational study.

Cortical spreading depression (CSD) is a pathophysiological phenomenon, which underlies some neurological disorders, such as migraine and stroke, but its mechanisms are still not completely understood. One of the striking facts is that the spatiotemporal evolution of CSD wave is varying. Observations in experiments reveal that a CSD wave may propagate through the entire cortex, or just bypass some areas of the cortex.

Rapid reconstruction of 3D neuronal morphology from light microscopy images with augmented rayburst sampling.

Digital reconstruction of three-dimensional (3D) neuronal morphology from light microscopy images provides a powerful technique for analysis of neural circuits. It is time-consuming to manually perform this process. Thus, efficient computer-assisted approaches are preferable.

3D BrainCV: simultaneous visualization and analysis of cells and capillaries in a whole mouse brain with one-micron voxel resolution.

Systematic cellular and vascular configurations are essential for understanding fundamental brain anatomy and metabolism. We demonstrated a 3D brainwide cellular and vascular (called 3D BrainCV) visualization and quantitative protocol for a whole mouse brain. We developed a modified Nissl staining method that quickly labeled the cells and blood vessels simultaneously in an entire mouse brain.

Automatic macroscopic density artefact removal in a Nissl-stained microscopic atlas of whole mouse brain.

Acquiring a whole mouse brain at the micrometer scale is a complex, continuous and time-consuming process. Because of defects caused by sample preparation and microscopy, the acquired image data sets suffer from various macroscopic density artefacts that worsen the image quality. We have to develop the available preprocessing methods to improve image quality by removing the artefacts that effect cell segmentation, vascular tracing and visualization.

Automated and accurate detection of soma location and surface morphology in large-scale 3D neuron images.

Automated and accurate localization and morphometry of somas in 3D neuron images is essential for quantitative studies of neural networks in the brain. However, previous methods are limited in obtaining the location and surface morphology of somas with variable size and uneven staining in large-scale 3D neuron images. In this work, we proposed a method for automated soma locating in large-scale 3D neuron images that contain relatively sparse soma distributions.

Visualization of brain circuits using two-photon fluorescence micro-optical sectioning tomography.

Neural circuits are fundamental for brain functions. However, obtaining long range continuous projections of neurons in the entire brain is still challenging. Here a two-photon fluorescence micro-optical sectioning tomography (2p-fMOST) method is developed for high-throughput, high-resolution visualization of the brain circuits.

Development of a plastic embedding method for large-volume and fluorescent-protein-expressing tissues.

Fluorescent proteins serve as important biomarkers for visualizing both subcellular organelles in living cells and structural and functional details in large-volume tissues or organs. However, current techniques for plastic embedding are limited in their ability to preserve fluorescence while remaining suitable for micro-optical sectioning tomography of large-volume samples. In this study, we quantitatively evaluated the fluorescence preservation and penetration time of several commonly used resins in a Thy1-eYFP-H transgenic whole mouse brain, including glycol methacrylate (GMA), LR White, hydroxypropyl methacrylate (HPMA) and Unicryl.

NeuroGPS: automated localization of neurons for brain circuits using L1 minimization model.

Drawing the map of neuronal circuits at microscopic resolution is important to explain how brain works. Recent progresses in fluorescence labeling and imaging techniques have enabled measuring the whole brain of a rodent like a mouse at submicron-resolution. Considering the huge volume of such datasets, automatic tracing and reconstruct the neuronal connections from the image stacks is essential to form the large scale circuits.

Continuously tracing brain-wide long-distance axonal projections in mice at a one-micron voxel resolution.

Revealing neural circuit mechanisms is critical for understanding brain functions. Significant progress in dissecting neural connections has been made using optical imaging with fluorescence labels, especially in dissecting local connections. However, acquiring and tracing brain-wide, long-distance neural circuits at the neurite level remains a substantial challenge.