Rivulet: 3D Neuron Morphology Tracing with Iterative Back-Tracking

The digital reconstruction of single neurons from 3D confocal microscopic images is an important tool for understanding the neuron morphology and function. However the accurate automatic neuron reconstruction remains a challenging task due to the varying image quality and the complexity in the neuronal arborisation. Targeting the common challenges of neuron tracing, we propose a novel automatic 3D neuron reconstruction algorithm, named Rivulet, which is based on the multi-stencils fast-marching and iterative back-tracking. The proposed Rivulet algorithm is capable of tracing discontinuous areas without being interrupted by densely distributed noises. By evaluating the proposed pipeline with the data provided by the Diadem challenge and the recent BigNeuron project, Rivulet is shown to be robust to challenging microscopic imagestacks. We discussed the algorithm design in technical details regarding the relationships between the proposed algorithm and the other state-of-the-art neuron tracing algorithms.     

The Filament Editor: An Interactive Software Environment for Visualization,Proof-Editing and Analysis of 3D Neuron Morphology

Neuroanatomical analysis, such as classification of cell types, depends on reliable reconstruction of large numbers of complete 3D dendrite and axon morphologies. At present, the majority of neuron reconstructions are obtained from preparations in a single tissue slice in vitro, thus suffering from cut off dendrites and, more dramatically, cut off axons. In general, axons can innervate volumes of several cubic millimeters and may reach path lengths of tens of centimeters. Thus, their complete reconstruction requires in vivo labeling, histological sectioning and imaging of large fields of view. Unfortunately, anisotropic background conditions across such large tissue volumes, as well as faintly labeled thin neurites, result in incomplete or erroneous automated tracings and even lead experts to make annotation errors during manual reconstructions. Consequently, tracing reliability renders the major bottleneck for reconstructing complete 3D neuron morphologies. Here, we present a novel set of tools, integrated into a software environment named ‘Filament Editor’, for creating reliable neuron tracings from sparsely labeled in vivo datasets. The Filament Editor allows for simultaneous visualization of complex neuronal tracings and image data in a 3D viewer, proof-editing of neuronal tracings, alignment and interconnection across sections, and morphometric analysis in relation to 3D anatomical reference structures. We illustrate the functionality of the Filament Editor on the example of in vivo labeled axons and demonstrate that for the exemplary dataset the final tracing results after proof-editing are independent of the expertise of the human operator.     

A Broadly Applicable 3-D Neuron Tracing Method Based on Open-Curve Snake

This paper presents a broadly applicable algorithm and a comprehensive open-source software implementation for automated tracing of neuronal structures in 3-D microscopy images. The core 3-D neuron tracing algorithm is based on three-dimensional (3-D) open-curve active Contour (Snake). It is initiated from a set of automatically detected seed points. Its evolution is driven by a combination of deforming forces based on the Gradient Vector Flow (GVF), stretching forces based on estimation of the fiber orientations, and a set of control rules. In this tracing model, bifurcation points are detected implicitly as points where multiple snakes collide. A boundariness measure is employed to allow local radius estimation. A suite of pre-processing algorithms enable the system to accommodate diverse neuronal image datasets by reducing them to a common image format. The above algorithms form the basis for a comprehensive, scalable, and efficient software system developed for confocal or brightfield images. It provides multiple automated tracing modes. The user can optionally interact with the tracing system using multiple view visualization, and exercise full control to ensure a high quality reconstruction. We illustrate the utility of this tracing system by presenting results from a synthetic dataset, a brightfield dataset and two confocal datasets from the DIADEM challenge.     

Computerized image analysis for quantitative neuronal phenotyping in zebrafish

An integrated microscope image analysis pipeline is developed for automatic analysis and quantification of phenotypes in zebrafish with altered expression of Alzheimer's disease (AD)-linked genes. We hypothesize that a slight impairment of neuronal integrity in a large number of zebrafish carrying the mutant genotype can be detected through the computerized image analysis method. Key functionalities of our zebrafish image processing pipeline include quantification of neuron loss in zebrafish embryos due to knockdown of AD-linked genes, automatic detection of defective somites, and quantitative measurement of gene expression levels in zebrafish with altered expression of AD-linked genes or treatment with a chemical compound. These quantitative measurements enable the archival of analyzed results and relevant meta-data. The structured database is organized for statistical analysis and data modeling to better understand neuronal integrity and phenotypic changes of zebrafish under different perturbations. Our results show that the computerized analysis is comparable to manual counting with equivalent accuracy and improved efficacy and consistency. Development of such an automated data analysis pipeline represents a significant step forward to achieve accurate and reproducible quantification of neuronal phenotypes in large scale or high-throughput zebrafish imaging studies.     

Historical review of development of neuro-historogical techniques and three-dimensional reconstruction of individual neurons]

The image of neuron proposed by Barker in 1899 is until now useful. However this image could be said to be only a schema based on the data obtained by various histological techniques developed in the latter half of the nineteenth century. Although thereafter many careful observations on neuronal architecture have been made, much still remains to be done for revealing their true geometry. In our histological analysis with Golgi-stained materials in the cat, it was found that the reflecting illumination showed the somal surface and its relationship with the dendrites in clear relief. With this method it was possible to develop a new approach for photogrammetric representation of the neuronal soma as well as for following the total course of dendrites in successive serial sections that had been cut off by the microtome knife. This has provided a means for estimating precisely the dimensions of the neuron. In addition, by means of the intra-axonally injection of HRP in cats, the intramedullary course of physiologically identified afferent fibers originating from various muscles in lumbosacral region was also reconstructed three-dimensionally from serial sections. The results thus obtained revealed that the collaterals belonging to groups Ia, Ib and II fibers of the muscles examined showed some typical differences in their courses and in their terminations in the gray matter. The results of extra-cellular injection of BDA (Sato F. et al., 2000) into the Nucl. subthalamicus in monkeys also cited as this sort of work. It should be emphasized that, whether classic manual method or more effective modern techniques are used, three-dimensional reconstruction is the most important factor for studying the comlete axonal geometry of individual neurons, of which effects may be said, at least at present, to be still methodologically incomplete.     

Effect of chondroitin sulfate proteoglycans on neuronal cell adhesion,spreading and neurite growth in culture

As one major component of extracellular matrix(ECM) in the central nervous system, chondroitin sulfate proteoglycans(CSPGs) have long been known as inhibitors enriched in the glial scar that prevent axon regeneration after injury. Although many studies have shown that CSPGs inhibited neurite outgrowth in vitro using different types of neurons, the mechanism by which CSPGs inhibit axonal growth remains poorly understood. Using cerebellar granule neuron(CGN) culture, in this study, we evaluated the effects of different concentrations of both immobilized and soluble CSPGs on neuronal growth, including cell adhesion, spreading and neurite growth. Neurite length decreased while CSPGs concentration arised, meanwhile, a decrease in cell density accompanied by an increase in cell aggregates formation was observed. Soluble CSPGs also showed an inhibition on neurite outgrowth, but it required a higher concentration to induce cell aggregates formation than coated CSPGs. We also found that growth cone size was significantly reduced on CSPGs and neuronal cell spreading was restrained by CSPGs, attributing to an inhibition on lamellipodial extension. The effect of CSPGs on neuron adhesion was further evidenced by interference reflection microscopy(IRM) which directly demonstrated that both CGNs and cerebral cortical neurons were more loosely adherent to a CSPG substrate. These data demonstrate that CSPGs have an effect on cell adhesion and spreading in addition to neurite outgrowth.     

A novel tracing algorithm for high throughput imaging Screening of neuron-based assays

High throughput neuron image processing is an important method for drug screening and quantitative neurobiological studies. The method usually includes detection of neurite structures, feature extraction, quantification, and statistical analysis. In this paper, we present a new algorithm for fast and automatic extraction of neurite structures in microscopy neuron images. The algorithm is based on novel methods for soma segmentation, seed point detection, recursive center-line detection, and 2D curve smoothing. The algorithm is fully automatic without any human interaction, and robust enough for usage on images with poor quality, such as those with low contrast or low signal-to-noise ratio. It is able to completely and accurately extract neurite segments in neuron images with highly complicated neurite structures. Robustness comes from the use of 2D smoothening techniques and the idea of center-line extraction by estimating the surrounding edges. Efficiency is achieved by processing only pixels that are close enough to the line structures, and by carefully chosen stopping conditions. These make the proposed approach suitable for demanding image processing tasks in high throughput screening of neuron-based assays. Detailed results on experimental validation of the proposed method and on its comparative performance with other proposed schemes are included.     

Effects of selective inhibition of protein kinase C, cyclic AMP-dependent protein kinase, and Ca-calmodulin-dependent protein kinase on neurite development in cultured rat hippocampal neurons

A variety of experimental evidence suggests that calmodulin and protein kinases, especially protein kinase C, may participate in regulating neurite development in cultured neurons, particularly neurite initiation. However, the results are somewhat contradictory. Further, the roles of calmodulin and protein kinases on many aspects of neurite development, such as branching or elongation of axons vs dendrites, have not been extensively studied. Cultured embryonic rat hippocampal pyramidal neurons develop readily identifiable axons and dendrites. We used this culture system and the new generation of highly specific protein kinase inhibitors to investigate the roles of protein kinases and calmodulin in neurite development. Neurons were cultured for 2 days in the continuous presence of calphostin C (a specific inhibitor of protein kinase C), KT5720 (inhibitor of cyclic AMP-dependent protein kinase), KN62 (inhibitor of Ca²⁺-calmodulin-dependent protein kinase II), or calmidazolium (inhibitor of calmodulin), each at concentrations from approximately 1 to 10 times the concentration reported in the literature to inhibit each kinase by 50%. The effects of phorbol 12-myristate 13-acetate (an activator of protein kinase C) and 4α-phorbol 12,13-didecanoate (an inactive phorbol ester) were also tested.At concentrations that had no effect on neuronal viability, calphostin C reduced neurite initiation and axon branching without significantly affecting the number of dendrites per neuron, dendrite branching, dendrite length, or axon length. Phorbol 12-myristate 13-acetate increased axon branching and the number of dendrites per cell, compared to the inactive 4α-phorbol 12,13-didecanoate. KT5720 inhibited only axon branching. KN62 reduced axon length, the number of dendrites per neuron and both axon and dendrite branching. At low concentrations, calmidazolium had no effect on any aspect of neurite development, but at high concentrations, calmidazolium inhibited every parameter that was measured (including viability).These results suggest that these three protein kinases selectively modulate different aspects of neurite development. The universality of effects caused by calmodulin inhibition make it impossible to determine if there are specific targets of calmodulin action involved in neurite development. Finally, our data indicate that some superficially similar characteristics of neuronal differentiation, such as neurite initiation and branching, may be controlled by quite different molecular mechanisms.     

An Automated Pipeline for Dendrite Spine Detection and Tracking of 3D Optical Microscopy Neuron Images of In Vivo Mouse Models

The variations in dendritic branch morphology and spine density provide insightful information about the brain function and possible treatment to neurodegenerative disease, for example investigating structural plasticity during the course of Alzheimer’s disease. Most automated image processing methods aiming at analyzing these problems are developed for in vitro data. However, in vivo neuron images provide real time information and direct observation of the dynamics of a disease process in a live animal model. This paper presents an automated approach for detecting spines and tracking spine evolution over time with in vivo image data in an animal model of Alzheimer’s disease. We propose an automated pipeline starting with curvilinear structure detection to determine the medial axis of the dendritic backbone and spines connected to the backbone. We, then, propose the adaptive local binary fitting (aLBF) energy level set model to accurately locate the boundary of dendritic structures using the central line of curvilinear structure as initialization. To track the growth or loss of spines, we present a maximum likelihood based technique to find the graph homomorphism between two image graph structures at different time points. We employ dynamic programming to search for the optimum solution. The pipeline enables us to extract dynamically changing information from real time in vivo data. We validate our proposed approach by comparing with manual results generated by neurologists. In addition, we discuss the performance of 3D based segmentation and conclude that our method is more accurate in identifying weak spines. Experiments show that our approach can quickly and accurately detect and quantify spines of in vivo neuron images and is able to identify spine elimination and formation.     

GAP43 overexpression and enhanced neurite outgrowth in mucopolysaccharidosis type IIIB cortical neuron cultures

Behavioral manifestations mark the onset of disease expression in children with mucopolysaccharidosis type III (MPSIII, Sanfilippo syndrome), a genetic disorder resulting from interruption of the lysosomal degradation of heparan sulfate. In the mouse model of MPSIII type B (MPSIIIB), cortical neuron pathology and dysfunction occur several months before neuronal loss and are primarily cell autonomous. The gene coding for GAP43, a neurite growth potentiator, is overexpressed in the MPSIIIB mouse cortex, and neurite dystrophy was reported in other types of lysosomal storage diseases. We therefore examined the development of the neuritic trees in pure populations of MPSIIIB mouse embryo cortical neurons grown for up to 12 days in primary culture. Dynamic observation of living neurons and quantification of neurite growth parameters indicated more frequent neurite elongation and branching and less frequent neurite retraction, resulting in a relative overgrowth of MPSIIIB neuron neuritic trees, involving both dendrites and axons, compared with normal controls. Neurite overgrowth was concomitant with more than twofold increased expression of GAP43 mRNAs and proteins. Correction of the genetic defect leads to expression of the missing lysosomal enzyme, normal GAP43 mRNA expression, and reduced neurite outgrowth. These results indicate that heparan sulfate oligosaccharide storage modifies GAP43 expression in MPSIIIB cortical neurons with potential consequences for neurite development and neuronal functions that may be relevant to clinical manifestations. © 2009 Wiley‐Liss, Inc.     

Automated Neuron Tracing Methods: An Updated Account

The reconstruction of neuron morphology allows to investigate how the brain works, which is one of the foremost challenges in neuroscience. This process aims at extracting the neuronal structures from microscopic imaging data. The great advances in microscopic technologies have made a huge amount of data available at the micro-, or even lower, resolution where manual inspection is time consuming, prone to error and utterly impractical. This has motivated the development of methods to automatically trace the neuronal structures, a task also known as neuron tracing. This paper surveys the latest neuron tracing methods available in the scientific literature as well as a selection of significant older papers to better place these proposals into context. They are categorized into global processing, local processing and meta-algorithm approaches. Furthermore, we point out the algorithmic components used to design each method and we report information on the datasets and the performance metrics used.     

Co-culture of neurons and glia in a novel microfluidic platform

We have prepared the poly-d-lysine (PDL) bound surfaces for neuron cell culture by covalent binding between the poly-d-Lysine and substrates and investigated neuronal cell adhesion properties and cell growth morphology. The number of neuronal cell and the number of neurite per neuronal cell on PDL bound surfaces was much more than those on PDL coated surfaces and also the neuronal cells on PDL bounded surfaces survived a longer time. On the pattern of covalently bound PDL, neuronal cells and their neurites are confined within the grid line leading to patterned neuronal networks with the long-term survival.     

The DIADEM Data Sets: Representative Light Microscopy Images of Neuronal Morphology to Advance Automation of Digital Reconstructions

The comprehensive characterization of neuronal morphology requires tracing extensive axonal and dendritic arbors imaged with light microscopy into digital reconstructions. Considerable effort is ongoing to automate this greatly labor-intensive and currently rate-determining process. Experimental data in the form of manually traced digital reconstructions and corresponding image stacks play a vital role in developing increasingly more powerful reconstruction algorithms. The DIADEM challenge (short for DIgital reconstruction of Axonal and DEndritic Morphology) successfully stimulated progress in this area by utilizing six data set collections from different animal species, brain regions, neuron types, and visualization methods. The original research projects that provided these data are representative of the diverse scientific questions addressed in this field. At the same time, these data provide a benchmark for the types of demands automated software must meet to achieve the quality of manual reconstructions while minimizing human involvement. The DIADEM data underwent extensive curation, including quality control, metadata annotation, and format standardization, to focus the challenge on the most substantial technical obstacles. This data set package is now freely released ( http://diademchallenge.org ) to train, test, and aid development of automated reconstruction algorithms.     

Sprouting and retraction of neurites by undamaged adult molluscan neurons

The present study examined the morphology of an identified molluscan neuron subsequent to exposure of animals to a variety of forms of stress. The neuron exhibited the sprouting and retraction of a single neurite in response to specific forms of animal stress. This new form of neuronal plasticity may provide an insight into the factors regulating adult neuronal morphology.     

Three-dimensional neuron tracing by voxel scooping

Tracing the centerline of the dendritic arbor of neurons is a powerful technique for analyzing neuronal morphology. In the various neuron tracing algorithms in use nowadays, the competing goals of computational efficiency and robustness are generally traded off against each other. We present a novel method for tracing the centerline of a neuron from confocal image stacks, which provides an optimal balance between these objectives. Using only local information, thin cross-sectional layers of voxels (‘scoops’) are iteratively carved out of the structure, and clustered based on connectivity. Each cluster contributes a node along the centerline, which is created by connecting successive nodes until all object voxels are exhausted. While data segmentation is independent of this algorithm, we illustrate the use of the ISODATA method to achieve dynamic (local) segmentation. Diameter estimation at each node is calculated using the Rayburst Sampling algorithm, and spurious end nodes caused by surface irregularities are then removed. On standard computing hardware the algorithm can process hundreds of thousands of voxels per second, easily handling the multi-gigabyte datasets resulting from high-resolution confocal microscopy imaging of neurons. This method provides an accurate and efficient means for centerline extraction that is suitable for interactive neuron tracing applications.     

Neuro-2a细胞替代神经元原代培养进行神经轴突测量实验研究

目的 建立使用小鼠神经母细胞瘤Neuro-2a细胞替代原代培养神经元进行神经轴突测量的方法,用于神经损伤研究.方法 使用浓度200 μmol/L、500 μmol/L、1 000μmol/L过氧化氢处理Neuro-2a细胞12h,戊二醛固定,生物染色,在光学显微镜下手动测量突起长度.结果 过氧化氢可剂量依赖性引起神经突起逐渐回缩变短,1 000 μmol/L过氧化氢处理组光镜下见不到明显突起,突起测量数据显示,过氧化氢处理后突起长度与未经处理细胞有显著差异.结论 Neuro-2a细胞在一定程度上可替代原代培养神经元进行轴突测量研究,该测量方法可用于神经轴突再生研究.     

Stimulus-dependent modifications in astrocyte-derived extracellular vesicle cargo regulate neuronal excitability

Extracellular vesicles have now emerged as key players in cell-to-cell communication. This is particularly important in the central nervous system, where glia–neuron cross-talk helps maintain normal neuronal function. Astrocyte-derived extracellular vesicles (ADEVs) secreted constitutively promote neurite outgrowth and neuronal survival. However, extracellular stimuli can alter the cargo and downstream functions of ADEVs. For example, ADEVs secreted in response to inflammation contain cargo microRNAs and proteins that reduce neurite outgrowth, neuronal firing, and promote neuronal apoptosis. We performed a comprehensive quantitative proteomic analysis to enumerate the proteomic cargo of ADEVs secreted in response to multiple stimuli. Rat primary astrocytes were stimulated with a trophic stimulus (adenosine triphosphate, ATP), an inflammatory stimulus (IL-1β) or an anti-inflammatory stimulus (IL10) and extracellular vesicles secreted within a 2 hr time frame were collected using sequential ultracentrifugation method. ADEVs secreted constitutively without exposure to any stimulus were used a control. A tandem mass tag-based proteomic platform was used to identify and quantify proteins in the ADEVs. Ingenuity pathway analysis was performed to predict the downstream signaling events regulated by ADEVs. We found that in response to ATP or IL10, ADEVs contain a set of proteins that are involved in increasing neurite outgrowth, dendritic branching, regulation of synaptic transmission, and promoting neuronal survival. In contrast, ADEVs secreted in response to IL-1β contain proteins that regulate peripheral immune response and immune cell trafficking to the central nervous system.     

Automated Reconstruction of Dendritic and Axonal Trees by Global Optimization with Geometric Priors

We present a novel probabilistic approach to fully automated delineation of tree structures in noisy 2D images and 3D image stacks. Unlike earlier methods that rely mostly on local evidence, ours builds a set of candidate trees over many different subsets of points likely to belong to the optimal tree and then chooses the best one according to a global objective function that combines image evidence with geometric priors. Since the best tree does not necessarily span all the points, the algorithm is able to eliminate false detections while retaining the correct tree topology. Manually annotated brightfield micrographs, retinal scans and the DIADEM challenge datasets are used to evaluate the performance of our method. We used the DIADEM metric to quantitatively evaluate the topological accuracy of the reconstructions and showed that the use of the geometric regularization yields a substantial improvement.     

The DIADEM Metric: Comparing Multiple Reconstructions of the Same Neuron

Digital reconstructions of neuronal morphology are used to study neuron function, development, and responses to various conditions. Although many measures exist to analyze differences between neurons, none is particularly suitable to compare the same arborizing structure over time (morphological change) or reconstructed by different people and/or software (morphological error). The metric introduced for the DIADEM (DIgital reconstruction of Axonal and DEndritic Morphology) Challenge quantifies the similarity between two reconstructions of the same neuron by matching the locations of bifurcations and terminations as well as their topology between the two reconstructed arbors. The DIADEM metric was specifically designed to capture the most critical aspects in automating neuronal reconstructions, and can function in feedback loops during algorithm development. During the Challenge, the metric scored the automated reconstructions of best-performing algorithms against manually traced gold standards over a representative data set collection. The metric was compared with direct quality assessments by neuronal reconstruction experts and with clocked human tracing time saved by automation. The results indicate that relevant morphological features were properly quantified in spite of subjectivity in the underlying image data and varying research goals. The DIADEM metric is freely released open source ( http://diademchallenge.org ) as a flexible instrument to measure morphological error or change in high-throughput reconstruction projects.