Automated identification of neurons and their locations

Individual locations of many neuronal cell bodies (>10⁴) are needed to enable statistically significant measurements of spatial organization within the brain such as nearest‐neighbour and microcolumnarity measurements. In this paper, we introduce an Automated Neuron Recognition Algorithm (ANRA) which obtains the (x, y) location of individual neurons within digitized images of Nissl‐stained, 30 μm thick, frozen sections of the cerebral cortex of the Rhesus monkey. Identification of neurons within such Nissl‐stained sections is inherently difficult due to the variability in neuron staining, the overlap of neurons, the presence of partial or damaged neurons at tissue surfaces, and the presence of non‐neuron objects, such as glial cells, blood vessels, and random artefacts. To overcome these challenges and identify neurons, ANRA applies a combination of image segmentation and machine learning. The steps involve active contour segmentation to find outlines of potential neuron cell bodies followed by artificial neural network training using the segmentation properties (size, optical density, gyration, etc.) to distinguish between neuron and non‐neuron segmentations. ANRA positively identifies 86 ± 5% neurons with 15 ± 8% error (mean ± SD) on a wide range of Nissl‐stained images, whereas semi‐automatic methods obtain 80 ± 7%/17 ± 12%. A further advantage of ANRA is that it affords an unlimited increase in speed from semi‐automatic methods, and is computationally efficient, with the ability to recognize ～100 neurons per minute using a standard personal computer. ANRA is amenable to analysis of huge photo‐montages of Nissl‐stained tissue, thereby opening the door to fast, efficient and quantitative analysis of vast stores of archival material that exist in laboratories and research collections around the world.     

Automated recognition and mapping of immunolabelled neurons in the developing brain

The cerebral cortex is distinguished by layers of neurons of different morphologies and densities. The layers are formed by the migration of newly generated neurons from the ventricular zone to the cortical plate near the outer (pial) boundary of the cortex, along radial paths approximately perpendicular to the cortical surface. Immunochemical labelling makes these cells' patterns visible in brightfield microscopy so that layer formation can be studied. We developed a suite of programs that automatically digitize the entire cortex, identify the labelled cells and compute cell densities along local radial paths. Cell identification used supervised classification on all the significantly stained objects corresponding to maxima in lowpass filtered versions of the digital micrographs. Classification of all the stained objects as cells or noncell objects was made by a decision rule based on morphometric and grey-level texture features, including features based on Gabor functions. Detection sensitivity and classification accuracy were jointly maximized on training data consisting of about 3000 expert-identified neurons in micrographs. Total program performance was tested on a separate (test) set of labelled neurons the same size as the training data set. The program detected 85% of the cells in the test set with a total error of 019. The identified cells' locations were used to compute population densities along normals to the cortical layers, and these densities served as a measure of neuronal migration. Transcortical density profiles obtained by computation and by manual cell counting were very similar. The cell identification program was built on well-established methods in statistical pattern recognition and image analysis and should generalize readily to other histological preparations.     

Five-colour in vivo imaging of neurons in Caenorhabditis elegans

In the last few years variants of the ‘green fluorescent protein’ (GFP) with different spectral properties have been generated. This has greatly increased the number of possible applications for these fluorochromes in cell biology. The significant overlap of the excitation and emission spectra of the different GFP variants imposes constraints on the number of variants that can be used simultaneously in a single sample. In particular, the two brightest variants, GFP and YFP, are difficult to separate spectrally. This study shows that GFP and YFP can be readily separated with little spectral overlap (cross‐talk) with the use of a confocal microscope equipped with an acusto‐optical beam splitter and freely adjustable emission windows. Under optimal recording conditions cross‐talk is less than 10%. Together with two other fluorescent proteins and the lipophilic dye DiD a total of five different colours can now be used simultaneously to label in vivo distinct anatomical structures such as neurons and their processes. Spatial resolution of the confocal microscope is sufficient to resolve the relative position of labelled axons within a single axon bundle. The use of five distinct marker dyes allows the in vivo analysis of the Caenorhabditis elegans nervous system at unprecedented resolution and richness in detail at the light microscopic level.     

Use of microwaves for rapid fixation of tissues in vivo

Accurate knowledge of the concentration in the central nervous system of neurochemicals undergoing rapid enzymatic destruction or synthesis is sparse because of the difficulty in stopping the rapid reactions while causing only minimal adverse changes in the neurochemistry and structure. Microwave heating can be effectively used to rapidly stop enzyme activity in the central nervous system with minimal adverse changes. This rapid inactivation of the enzymes increases the validity of the sample that is taken for analysis of the concentration of the enzyme's substrate.     

A simple method for processing individual oocytes and embryos for electron microscopy

A simple method for handling individual specimens that must be processed either for scanning or transmission electron microscopy studies is described. For scanning microscope processing, dehydration is carried out with samples enclosed in small cages made from TAAB capsules in which top and bottom are substituted by plankton nets, and for transmission electron microscopy, samples are pre-embedded in agarose. This procedure significantly reduces mouth pipetting, dissecting microscope observations, is less labour intensive and, most importantly, reduces sample loss.     

A method for the compound fault diagnosis of gearboxes based on morphological component analysis

An improved morphological component analysis (MCA) method is proposed for the compound fault diagnosis of gearboxes. When gear fault and bearing fault occur simultaneously, the compound fault signal of the gearbox contains meshing components (related to the gear fault) and periodic impulse components (related to the bearing fault). The corresponding fault characteristics can be separated by MCA according to the morphological differences of the components. In the proposed method, the optimal dictionary, which can represent the characteristics of bearing faults, is first selected based on the principle of minimum information entropy. Then, the compound fault signal is decomposed into the meshing component and the periodic impulse component using MCA. Finally, the separated components are subjected to the Hilbert envelope spectrum analysis. The faults of the gear and the bearing can be diagnosed according to the envelope spectra of the separated fault signal components. Simulation and experimental studies validate the effectiveness of the proposed method for the compound fault diagnosis of gearboxes.     

压力容器开孔补强简易计算判别法

在压力容器设计的过程中,为了使设备能够进行正常的工艺操作,满足容器制造、安装、检验及维修等要求,在壳体和端盖上往往需要有各种开孔并联结接管,例如:物料进、出口,测量和控制点,室镜、液面计孔,人孔和手孔等,所以,在压力容器上开孔是不可避免的。容器开孔以后,不仅整体强度受到削弱,而且还因开孔引起的应力集中造成开孔边缘局部的高应力,加上接管上有时还有其它的外载荷,而开孔结构在制造过程中又不可避免地会形成缺陷和残余应力,于是开孔附近就往往成为容器的破坏源-主要是疲劳破坏和脆性裂口,因此,在压力容器设计中必须充分考     

A fault identification method of rotating machinerybased on t-SNE

A fault identification method ofrotating machinery is proposed,which combines wavelet packet of time-frequency analysis and manifold learning.Firstly,the sampled vibration signal is decomposed to multilayer information with wavelet packet decomposition(WPD) method.Andevery level data of wavelet packet decomposition is processed bydemodulatingof Hilbert transform,eliminating the high frequency noiseof FIR filterand reducing the data length of the low frequency of resampling.Further,every level data vector is deal with normalization and calculated for the auto power spectrum.Finally,the manifold learning methods of t distributed stochastic neighbor embedding(t-SNE) is applied to do dimension reduction to generate 2D manifold figure data.Different fault forms of gearbox have different manifold features,which is used to identify failure status of equipment.With the experiment test,the feasibility and effectiveness of this identification method is verified.     

Tracing axons in the human brain: A method utilizing light and TEM techniques

The neuroanatomy of experimental animals has been investigated through a variety of histological and physiological techniques. Recently, more sophisticated methods have permitted a better understanding of the complex connections of animal brains. In contrast, the methods available for the direct examination of the human brain have remained relatively primitive. We have developed a staining method (paraphenylene-diamine method: PPD) which bridges the techniques of light and electron microscopy. The method permits the tracing of degenerated fibers in the human brain even after very long survival periods. With this method we have documented several visual pathways not previously described in man. We have also demonstrated, in several species, that products of axonal degeneration remain far longer than previously supposed. The PPD technique is relatively simple, reliable, provides high resolution, works in human brains, and can be used in conjunction with TEM.     

模糊辨识器的参数辨识

本文针对基于BP网络进行参数辨识的模糊辨识器,采用更为合理的学习步长--变步长,从而使在线辨识更加快速,为实时控制节约了宝贵的时间.     

A new method for comparative light and electron microscopic studies of individual cells,selected in the living state

A method is described which permits comparative light and electronmicroscopic studies of cell cultures, cell spreads or single selected cells which have been kept in the Plastic Film Dish (PFD). The PFD is a versatile large surface tissue culture chamber which, for electron microscopy, is mounted with a transparent FEP-Teflon film bottom. Cells are observed, selected and marked on the PFD-bottom with a high power inverted light microscope. The cells are fixed and dehydrated with a semi-automatic device while they are still in situ in the PFD. During the preparation steps for electron microscopy the topographical relationship between individual cells and between cells and cell support is accurately retained. After embedding and polymerization the Teflon film is easily peeled off the polymerized Epon, leaving a replica of the mark around the selected cell. This permits relocation of the selected cells for ultrathin sectioning in a plane plan-parallel to the original cell support. To enable orientated sectioning of selected cells in a plane perpendicular to the cell support, cells are tagged with Letraset-letters after original embedding and polymerization. Subsequently the re-embedded polymerized specimens are orientated in the microtome in a position which permits controlled thin sectioning of the tagged cells in the previously selected plane.     

A new velocity estimation method using spectral identification of noise

In all measurement techniques one seeks accuracy and precision. In ultrasonic Doppler velocimetry, those qualities strongly depend on signal to noise ratio of the Doppler signal and on the performance of the velocity estimator. The most widely used estimation method in ultrasonic coherent Doppler velocimetry is the pulse pair method. Its success is due to the computation efficiency of the algorithm combined to an unbiased estimator. Unfortunately, for a wide range of experimental fluid flows, the pulse pair estimation is less efficient, especially for clear water or concentrated mud where the signal to noise ratio can be very low, or for highly turbulent flows where the Doppler signal has a broad spectrum. Our approach is based on the treatment of the Doppler spectral information. It uses a simple parametric identification inspired by theoretical models and experimental observations. It acts through noise subtraction and subsequent cutting. Thus, we have developed a fast velocity estimation algorithm superior to the pulse pair one in terms of accuracy. The robustness of the method was evaluated by adding different levels of white Gaussian noise to an experimental Doppler signal. The results demonstrate an increase of noise immunity up to one decade compared to the pulse pair method.     

A novel method for three-dimensional observation of the vascular networks in the whole mouse brain

A novel method for acquiring serial images suitable for three-dimensional reconstruction of vascular networks in the whole brain of mouse was developed. The brain infused with a White India ink-gelatin solution was fixed and embedded in paraffin containing Sudan Black B through xylene also containing Sudan Black B. Each sliced surface of the paraffin block was coated with liquid paraffin and its image was serially acquired. Coating with liquid paraffin extremely improved the quality of the image. The series of serial images was free of distortion and a three-dimensional image was reconstructed without the problem of the alignment and registration of adjacent images. The volume-rendered image indicated three-dimensional distribution of blood vessels in a whole brain. No ghost or shadow was observed on a volume-rendered image of the White India ink-gelatin infused brain. The z-axial resolution examined on the orthogonal sections reconstituted from serial images obtained at an interval of 5 mum showed no cross talk, indicating that the z-axial resolution was no larger than 5 mum. A proper understanding of the vascular system in a whole brain is indispensable to reveal the development of the vascular system in the brain of normal and genetically manipulated mouse and vascular alterations in pathological situation, such as stroke and neurodegenerative disease. Although simple and inexpensive, this method will provide fundamental information on the vascular system in a whole brain.     

A method for the identification of hydraulic damper characteristics from steady velocity inputs

The research presented in this paper investigates the possibility of precise experimental identification of steady damper characteristics. The paper considers velocity sensitive and nominally symmetric hydraulic dampers. The proposed identification methodology is based on a piecewise constant velocity excitation. One goal of the paper is to analyze the transient nature of the damper response in the context of finite permissible piston displacements and first order transient effects due to elastic elements in the damper structure. The proposed methodology is formalized in a framework suitable for experimental design, allowing the detailed study of steady state damper performance. The second goal of the paper is to demonstrate the practical application of the proposed methodology. It is applied to the case of a safety critical hydraulic damper used for stability augmentation in production helicopters. The research work presented shows that this methodology can be used for identification in a finite but relatively wide range of piston velocities. The case study demonstrates a successful example of damper property identification where the resulting characteristics prove useful as a tool for model validation. Finally, the identification results are related to the results of a more traditional test with harmonic piston excitation.     

A joint adaptive wavelet filter and morphological signal processing method for weak mechanical impulse extraction

Periodical impulses are vital indicators of rotating machinery faults. Therefore, the extraction of weak periodical impulses from vibration signals is of great importance for incipient fault detection. However, measured signals are often severely tainted by various noises, which makes the detection of impulses rather difficult. As such, a proper signal processing technique is necessary. In this paper, a hybrid method comprised of wavelet filter and morphological signal processing (MSP) is proposed for this task. The wavelet filter is used to eliminate the noise and enhance the impulsive features. Then, the filtered signal is processed by the morphological closing operator and a local maximum algorithm to isolate periodical impulses. To select the proper parameters of the joint approach, i.e., the center frequency, the bandwidth of wavelet filter, and the length of flat structuring elements (SE), a novel optimization algorithm based on differential evolution (DE) is developed. The results of simulated experiments and bearing vibration signal analysis verify the effectiveness of the proposed method.     

Automated identification of neurons in 3D confocal datasets from zebrafish brainstem

Many kinds of neuroscience data are being acquired regarding the dynamic behaviour and phenotypic diversity of nerve cells. But as the size, complexity and numbers of 3D neuroanatomical datasets grow ever larger, the need for automated detection and analysis of individual neurons takes on greater importance. We describe here a method that detects and identifies neurons within confocal image stacks acquired from the zebrafish brainstem. The first step is to create a template that incorporates the location of all known neurons within a population – in this case the population of reticulospinal cells. Once created, the template is used in conjunction with a sequence of algorithms to determine the 3D location and identity of all fluorescent neurons in each confocal dataset. After an image registration step, neurons are segmented within the confocal image stack and subsequently localized to specific locations within the brainstem template – in many instances identifying neurons as specific, individual reticulospinal cells. This image-processing sequence is fully automated except for the initial selection of three registration points on a maximum projection image. In analysing confocal image stacks that ranged considerably in image quality, we found that this method correctly identified on average ∼80% of the neurons (if we assume that manual detection by experts constitutes 'ground truth'). Because this identification can be generated approximately 100 times faster than manual identification, it offers a considerable time savings for the investigation of zebrafish reticulospinal neurons. In addition to its cell identification function, this protocol might also be integrated with stereological techniques to enhance quantification of neurons in larger databases. Our focus has been on zebrafish brainstem systems, but the methods described should be applicable to diverse neural architectures including retina, hippocampus and cerebral cortex.     

Confocal microscopy and three-dimensional reconstruction of electrophysiologically identified neurons in thick brain slices

Three-dimensional morphology and electrophysiology were correlated from individual neurons in a thick brain slice preparation. The hippocampal formation from immature and adult rats was cut transverse to the longitudinal axis into 500 μ Um-thick slices which were maintained under physiologic conditions. Individual neurons were impaled and physiologically characterized using microelectrodes. Recordings were made from the soma and in some cases from a dendrite. The impaled neurons were filled through the microelectrode with the fluorescent dye lucifer yellow and imaged by confocal scanning laser microscopy using an analog preprocessor. As many as 180 optical sections were recorded as a function of depth through the slices. Images are presented as a series of optical sections, stereo pairs, or three-dimensional reconstructions. Both stereo contouring and volume rendering methods were employed, and the reconstructions were viewed from any arbitrary perspective. Dendritic and axonal fields were separated from each other and displayed separately or as different pseudocolors. The three-dimensional reconstructions provided perspectives that were difficult or impossible to appreciate by viewing the optical sections or conventionally formed stereo pairs.     

A new identification method of viscoelastic behavior: Application to the generalized Maxwell model

This paper focuses on the generalized Maxwell model (GMM) identification. The formulation of the transfer function of the GMM is defined, as well as its asymptotes. To compare identification methods of the parameters of the GMM, a test transfer function and two quality indicators are defined. Then, three graphical methods are described, the enclosing curve method, the CRONE method and an original one. But the results of graphical methods are not good enough. Thus, two optimization recursive processes are described to improve the results of graphical methods. The first one is based on an unconstrained non-linear optimization algorithm and the second one is original and allows constraining identified parameters. This new process uses the asymptotes of the modulus and the phase of the transfer function of the GMM. The result of the graphical method optimized with the new process is very accurate and fast.