New techniques for imaging, digitization and analysis of three-dimensional neural morphology on multiple scales

A cell surface biotinylation assay to reveal membrane-associated neuronal cues: Negr1 regulates dendritic arborization

A complex and still not comprehensively resolved panel of transmembrane proteins regulates the outgrowth and the subsequent morphological and functional development of neuronal processes. In order to gain a more detailed description of these events at the molecular level, we have developed a cell surface biotinylation assay to isolate, detect, and quantify neuronal membrane proteins. When we applied our assay to investigate neuron maturation in vitro, we identified 439 differentially expressed proteins, including 20 members of the immunoglobulin superfamily. Among these candidates, we focused on Negr1, a poorly described cell adhesion molecule. We demonstrated that Negr1 controls the development of neurite arborization in vitro and in vivo. Given the tight correlation existing among synaptic cell adhesion molecules, neuron maturation, and a number of neurological disorders, our assay results are a useful tool that can be used to support the understanding of the molecular bases of physiological and pathological brain function.

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. In this paper, we present an innovative method for the tracing and reconstruction of 3D neuronal morphology from light microscopy images. The method uses a prediction and refinement strategy that is based on exploration of local neuron structural features. We extended the rayburst sampling algorithm to a marching fashion, which starts from a single or a few seed points and marches recursively forward along neurite branches to trace and reconstruct the whole tree-like structure. A local radius-related but size-independent hemispherical sampling was used to predict the neurite centerline and detect branches. Iterative rayburst sampling was performed in the orthogonal plane, to refine the centerline location and to estimate the local radius. We implemented the method in a cooperative 3D interactive visualization-assisted system named flNeuronTool. The source code in C++ and the binaries are freely available at http://sourceforge.net/projects/flneurontool/. We validated and evaluated the proposed method using synthetic data and real datasets from the Digital Reconstruction of Axonal and Dendritic Morphology (DIADEM) challenge. Then, flNeuronTool was applied to mouse brain images acquired with the Micro-Optical Sectioning Tomography (MOST) system, to reconstruct single neurons and local neural circuits. The results showed that the system achieves a reasonable balance between fast speed and acceptable accuracy, which is promising for interactive applications in neuronal image analysis.

Age-related changes to layer 3 pyramidal cells in the rhesus monkey visual cortex

The effects of normal aging on morphologic and electrophysiologic properties of layer 3 pyramidal neurons in rhesus monkey primary visual cortex (V1) were assessed with whole-cell, patch-clamp recordings in in vitro slices. In another cohort of monkeys, the ultrastructure of synapses in the layers 2-3 neuropil of V1 was assessed using electron microscopy. Distal apical dendritic branching complexity was reduced in aged neurons, as was the total spine density, due to specific loss of mushroom spines from the apical tree and of thin spines from the basal tree. There was also an age-related decrease in the numerical density of symmetric and asymmetric synapses. In contrast to these structural changes, intrinsic membrane, action potential (AP), and excitatory and inhibitory synaptic current properties were the same in aged and young neurons. Computational modeling using morphologic reconstructions predicts that reduced dendritic complexity leads to lower attenuation of voltage outward from the soma (e.g., backpropagating APs) in aged neurons. Importantly, none of the variables that changed with age differed in neurons from cognitively impaired versus unimpaired aged monkeys. In summary, there are age-related alterations to the structural properties of V1 neurons, but these are not associated with significant electrophysiologic changes or with cognitive decline.

The pattern of cortical dysfunction in a mouse model of a schizophrenia-related microdeletion

We used a mouse model of the schizophrenia-predisposing 22q11.2 microdeletion to evaluate how this genetic lesion affects cortical neural circuits at the synaptic, cellular, and molecular levels. Guided by cognitive deficits, we demonstrated that mutant mice display robust deficits in high-frequency synaptic transmission and short-term plasticity (synaptic depression and potentiation), as well as alterations in long-term plasticity and dendritic spine stability. Apart from previously reported reduction in dendritic complexity of layer 5 pyramidal neurons, altered synaptic plasticity occurs in the context of relatively circumscribed and often subtle cytoarchitectural changes in neuronal density and inhibitory neuron numbers. We confirmed the pronounced DiGeorge critical region 8 (Dgcr8)-dependent deficits in primary micro-RNA processing and identified additional changes in gene expression and RNA splicing that may underlie the effects of this mutation. Reduction in Dgcr8 levels appears to be a major driver of altered short-term synaptic plasticity in prefrontal cortex and working memory but not of long-term plasticity and cytoarchitecture. Our findings inform the cortical synaptic and neuronal mechanisms of working memory impairment in the context of psychiatric disorders. They also provide insight into the link between micro-RNA dysregulation and genetic liability to schizophrenia and cognitive dysfunction.

Dendrite complexity of sympathetic neurons is controlled during postnatal development by BMP signaling

Dendrite development is controlled by the interplay of intrinsic and extrinsic signals affecting initiation, growth, and maintenance of complex dendrites. Bone morphogenetic proteins (BMPs) stimulate dendrite growth in cultures of sympathetic, cortical, and hippocampal neurons but it was unclear whether BMPs control dendrite morphology in vivo. Using a conditional knock-out strategy to eliminate Bmpr1a and Smad4 in immature noradrenergic sympathetic neurons we now show that dendrite length, complexity, and neuron cell body size are reduced in adult mice deficient of Bmpr1a. The combined deletion of Bmpr1a and Bmpr1b causes no further decrease in dendritic features. Sympathetic neurons devoid of Bmpr1a/1b display normal Smad1/5/8 phosphorylation, which suggests that Smad-independent signaling paths are involved in dendritic growth control downstream of BMPR1A/B. Indeed, in the Smad4 conditional knock-out dendrite and cell body size are not affected and dendrite complexity and number are increased. Together, these results demonstrate an in vivo function for BMPs in the generation of mature sympathetic neuron dendrites. BMPR1 signaling controls dendrite complexity postnatally during the major dendritic growth period of sympathetic neurons.

Chronic stress-induced alterations of dendritic spine subtypes predict functional decrements in an hypothalamo-pituitary-adrenal-inhibitory prefrontal circuit

Activation of the hypothalamo-pituitary-adrenal (HPA) axis plays a vital role in promoting adaptation during acute stress, but adverse effects of chronic stress may result from overactivity of this system. Recent evidence highlights a subdivision of GABAergic neurons within anterior bed nuclei of the stria terminalis (aBST) that integrates and relays inhibitory influences to HPA-effector neurons in paraventricular hypothalamus during acute stress, notably from medial prefrontal [prelimbic (PL)] and hippocampal [ventral subiculum (vSUB)] cortical fields. Here we localize the site and candidate mechanism of neuroplasticity within upstream regions of this inhibitory network after chronic variable stress (CVS). Rats bearing retrograde tracer injections in aBST underwent CVS for 14 d. Retrogradely labeled and unlabeled neurons in vSUB and PL were selected for intracellular dye filling, followed by three-dimensional imaging and analysis of dendritic arborization and spine morphometry. Whereas PL neurons displayed decreases in dendritic branching and spine density after CVS, aBST-projecting cells showed a selective loss of mature mushroom-shaped spines. In a follow-up experiment, CVS-treated and control rats were exposed to a novel restraint challenge for assay of HPA activation and engagement of aBST-projecting cortical regions. CVS animals showed enhanced HPA output and decreased Fos activation in aBST-projecting PL neurons compared with acutely stressed controls. In contrast, vSUB failed to show any significant differences in structural plasticity or functional activation patterns after CVS. These findings define a mechanism whereby synaptic destabilization in the PL → aBST pathway may dampen its ability to impart inhibitory control over the HPA axis after chronic stress exposure.

In vivo characterization of a bigenic fluorescent mouse model of Alzheimer's disease with neurodegeneration

The loss of cognitive function in Alzheimer's disease (AD) patients is strongly correlated with the loss of neurons in various regions of the brain. We have created a new fluorescent bigenic mouse model of AD by crossing "H-line" yellow fluorescent protein (YFP) mice with the 5xFAD mouse model, which we call the 5XY mouse model. The 5xFAD mouse has been shown to have significant loss of L5 pyramidal neurons by 12 months of age. These neurons are transgenically labeled with YFP in the 5XY mouse, which enable longitudinal imaging of structural changes. In the 5XY mice, we observed an appearance of axonal dystrophies, with two distinct morphologies in the early stages of the disease progression. Simple swelling dystrophies are transient in nature and are not directly associated with amyloid plaques. Rosette dystrophies are more complex structures that remained stable throughout all imaging sessions, and always surrounded an amyloid plaque. Plaque growth was followed over 4 weeks, and significant growth was seen between weekly imaging sessions. In addition to axonal dystrophy appearance and plaque growth, we were able to follow spine stability in 4-month old 5XY mice, which revealed no significant loss of spines. 5XY mice also showed a striking shrinkage of the neocortex at older ages (12-14 months). The 5XY mouse model may be a valuable tool for studying specific events in the degeneration of the neocortex, and may suggest new avenues for therapeutic intervention.

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. Terabytes 3D datasets of the whole mouse brains, with unprecedented details of both individual cells and blood vessels, including capillaries, were simultaneously imaged at 1-μm voxel resolution using micro-optical sectioning tomography (MOST). For quantitative analysis, we proposed an automatic image-processing pipeline to perform brainwide vectorization and analysis of cells and blood vessels. Six representative brain regions from the cortex to the deep, including FrA, M1, PMBSF, V1, striatum, and amygdala, and six parameters, including cell number density, vascular length density, fractional vascular volume, distance from the cells to the nearest microvessel, microvascular length density, and fractional microvascular volume, had been quantitatively analyzed. The results showed that the proximity of cells to blood vessels was linearly correlated with vascular length density, rather than the cell number density. The 3D BrainCV made overall snapshots of the detailed picture of the whole brain architecture, which could be beneficial for the state comparison of the developing and diseased brain.

Statistical analysis of dendritic spine distributions in rat hippocampal cultures

BACKGROUND

Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley's K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites.

RESULTS

Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type.

CONCLUSIONS

Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons.

Novel objective classification of reactive microglia following hypoglossal axotomy using hierarchical cluster analysis

A total of 136 microglia were intracellularly labeled and their morphological features were evaluated by 3D morphometric measurement. According to hierarchical cluster analysis, microglia were objectively categorized into four groups termed types I-IV. The validity of this classification was confirmed by principal component analysis and linear discriminant analysis. Type I microglia were found in sham-operated mice and in mice sacrificed 28 days (D28) after axotomy. The appearance of type I cells was similar to so-called ramified microglia in a resting state. Type II microglia were mainly seen in D14 mice, which exhibited small cell bodies with thin and short processes. Interestingly, none of the already-known morphological types of microglia seemed to be comparable to type II cells. We thus named type II microglia "small ramified" cells. Types III and IV microglia were mainly seen in D3 and D7 mice and their appearances were similar to hypertrophied and bushy cells, respectively. Proliferating cell nuclear antigen (PCNA), a mitosis marker, was almost exclusively expressed in D3 mice. On the other hand, voltage-dependent potassium channels (Kv1.3/1.5), neurotoxicity-related molecules, were most highly expressed in D14 mice. Increased expression of Kv1.3/1.5 in D14 mice was suppressed by minocycline treatment. These findings indicate that type II and III microglia may be involved in neurotoxicity and mitosis, respectively. Type IV microglial cells are assumed to be in the process of losing mitotic activity and gaining neurotoxicity. Our data also suggest that type II microglia can be a potential therapeutic target against neurodegenerative diseases.

Chronic stress-induced disruption of the astrocyte network is driven by structural atrophy and not loss of astrocytes

Chronic stress is well recognized to decrease the number of GFAP⁺ astrocytes within the prefrontal cortex (PFC). Recent research, however, has suggested that our understanding of how stress alters astrocytes may be incomplete. Specifically, chronic stress has been shown to induce a unique form of microglial remodelling, but it is not yet clear whether astrocytes also undergo similar structural modifications. Such alterations may be significant given the role of astrocytes in modulating synaptic function. Accordingly, in the current study we have examined changes in astrocyte morphology following exposure to chronic stress in adult rats, using three-dimensional digital reconstructions of astrocytes. Our analysis indicated that chronic stress produced profound atrophy of astrocyte process length, branching and volume. We additionally examined changes in astrocyte-specific S100β, which are both a putative astrocyte marker and a protein whose expression is associated with astrocyte distress. While we found that S100β levels were increased by stress, this increase was not correlated with atrophy. We further established that while chronic stress was associated with a decrease in astrocyte numbers when GFAP labelling was used as a marker, we could find no evidence of a decrease in the total number of cells, based on Nissl staining, or in the number of S100β⁺ cells. This finding suggests that chronic stress may not actually reduce astrocyte numbers and may instead selectively decrease GFAP expression. The results of the current study are significant as they indicate stress-induced astrocyte-mediated disturbances may not be due to a loss of cells but rather due to significant remodeling of the astrocyte network.

Astroglial cells regulate the developmental timeline of human neurons differentiated from induced pluripotent stem cells

Neurons derived from human induced-pluripotent stem cells (hiPSCs) have been used to model a variety of neurological disorders. Different protocols have been used to differentiate hiPSCs into neurons, but their functional maturation process has varied greatly among different studies. Here, we demonstrate that laminin, a commonly used substrate for iPSC cultures, was inefficient to promote fully functional maturation of hiPSC-derived neurons. In contrast, astroglial substrate greatly accelerated neurodevelopmental processes of hiPSC-derived neurons. We have monitored the neural differentiation and maturation process for up to two months after plating hiPSC-derived neuroprogenitor cells (hNPCs) on laminin or astrocytes. We found that one week after plating hNPCs, there were 21-fold more newly differentiated neurons on astrocytes than on laminin. Two weeks after plating hNPCs, there were 12-fold more dendritic branches in neurons cultured on astrocytes than on laminin. Six weeks after plating hNPCs, the Na(+) and K(+) currents, as well as glutamate and GABA receptor currents, were 3-fold larger in neurons cultured on astrocytes than on laminin. And two months after plating hNPCs, the spontaneous synaptic events were 8-fold more in neurons cultured on astrocytes than on laminin. These results highlight a critical role of astrocytes in promoting neural differentiation and functional maturation of human neurons derived from hiPSCs. Moreover, our data presents a thorough developmental timeline of hiPSC-derived neurons in culture, providing important benchmarks for future studies on disease modeling and drug screening.

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. This method involves three steps: (i) deblocking the image with overlap between adjacent sub-stacks; (ii) locating the somas in each small sub-stack using multi-scale morphological close and adaptive thresholds; and (iii) fusion of the repeatedly located somas in all sub-stacks. We also describe a new method for the accurate detection of the surface morphology of somas containing hollowness; this was achieved by improving the classical Rayburst Sampling with a new gradient-based criteria. Three 3D neuron image stacks of different sizes were used to quantitatively validate our methods. For the soma localization algorithm, the average recall and precision were greater than 93% and 96%, respectively. For the soma surface detection algorithm, the overlap of the volumes created by automatic detection of soma surfaces and manually segmenting soma volumes was more than 84% for 89% of all correctly detected somas. Our method for locating somas can reveal the soma distributions in large-scale neural networks more efficiently. The method for soma surface detection will serve as a valuable tool for systematic studies of neuron types based on neuron structure.

RipleyGUI: software for analyzing spatial patterns in 3D cell distributions

The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. To facilitate the quantification of neuronal cell patterns we have developed RipleyGUI, a MATLAB-based software that can be used to detect patterns in the 3D distribution of cells. RipleyGUI uses Ripley's K-function to analyze spatial distributions. In addition the software contains statistical tools to determine quantitative statistical differences, and tools for spatial transformations that are useful for analyzing non-stationary point patterns. The software has a graphical user interface making it easy to use without programming experience, and an extensive user manual explaining the basic concepts underlying the different statistical tools used to analyze spatial point patterns. The described analysis tool can be used for determining the spatial organization of neurons that is important for a detailed study of structure-function relationships. For example, neocortex that can be subdivided into six layers based on cell density and cell types can also be analyzed in terms of organizational principles distinguishing the layers.

Localizing and extracting filament distributions from microscopy images

Detailed quantitative measurements of biological filament networks represent a crucial step in understanding architecture and structure of cells and tissues, which in turn explain important biological events such as wound healing and cancer metastases. Confocal microscope images of biological specimens marked for different structural proteins constitute an important source for observing and measuring meaningful parameters of biological networks. Unfortunately, current efforts at quantitative estimation of architecture and orientation of biological filament networks from microscopy images are predominantly limited to visual estimation and indirect experimental inference. Here we describe a new method for localizing and extracting filament distributions from 2D confocal microscopy images. The method combines a filter-based detection of pixels likely to contain a filament with a constrained reverse diffusion-based approach for localizing the filaments centrelines. We show with qualitative and quantitative experiments, using both simulated and real data, that the new method can provide more accurate centreline estimates of filament in comparison to other approaches currently available. In addition, we show the algorithm is more robust with respect to variations in the initial filter-based filament detection step often used. We demonstrate the application of the method in extracting quantitative parameters from an experiment that seeks to quantify the effects of carbon nanotubes on actin cytoskeleton in live HeLa cells. We show that their presence can disrupt the overall actin cytoskeletal organization in such cells.

Chapter 17: bioimage informatics for systems pharmacology

Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from conventional microscopy studies on a few cells, and could provide stronger statistical power for drawing experimental observations and conclusions. However, it is challenging to manually extract and quantify phenotypic changes from the large amounts of complex image data generated. Thus, bioimage informatics approaches are needed to rapidly and objectively quantify and analyze the image data. This paper provides an overview of the bioimage informatics challenges and approaches in image-based studies for drug and target discovery. The concepts and capabilities of image-based screening are first illustrated by a few practical examples investigating different kinds of phenotypic changes caEditorsused by drugs, compounds, or RNAi. The bioimage analysis approaches, including object detection, segmentation, and tracking, are then described. Subsequently, the quantitative features, phenotype identification, and multidimensional profile analysis for profiling the effects of drugs and targets are summarized. Moreover, a number of publicly available software packages for bioimage informatics are listed for further reference. It is expected that this review will help readers, including those without bioimage informatics expertise, understand the capabilities, approaches, and tools of bioimage informatics and apply them to advance their own studies.

Neuronal morphology goes digital: a research hub for cellular and system neuroscience

The importance of neuronal morphology in brain function has been recognized for over a century. The broad applicability of "digital reconstructions" of neuron morphology across neuroscience subdisciplines has stimulated the rapid development of numerous synergistic tools for data acquisition, anatomical analysis, three-dimensional rendering, electrophysiological simulation, growth models, and data sharing. Here we discuss the processes of histological labeling, microscopic imaging, and semiautomated tracing. Moreover, we provide an annotated compilation of currently available resources in this rich research "ecosystem" as a central reference for experimental and computational neuroscience.

A distance-field based automatic neuron tracing method

Background

Automatic 3D digital reconstruction (tracing) of neurons embedded in noisy microscopic images is challenging, especially when the cell morphology is complex.

Results

We have developed a novel approach, named DF-Tracing, to tackle this challenge. This method first extracts the neurite signal (foreground) from a noisy image by using anisotropic filtering and automated thresholding. Then, DF-Tracing executes a coupled distance-field (DF) algorithm on the extracted foreground neurite signal and reconstructs the neuron morphology automatically. Two distance-transform based “force” fields are used: one for “pressure”, which is the distance transform field of foreground pixels (voxels) to the background, and another for “thrust”, which is the distance transform field of the foreground pixels to an automatically determined seed point. The coupling of these two force fields can “push” a “rolling ball” quickly along the skeleton of a neuron, reconstructing the 3D cell morphology.

Conclusion

We have used DF-Tracing to reconstruct the intricate neuron structures found in noisy image stacks, obtained with 3D laser microscopy, of dragonfly thoracic ganglia. Compared to several previous methods, DF-Tracing produces better reconstructions.

Regulation of spine density and morphology by IQGAP1 protein domains

IQGAP1 is a scaffolding protein that regulates spine number. We now show a differential role for IQGAP1 domains in spine morphogenesis, in which a region of the N-terminus that promotes Arp2/3-mediated actin polymerization and branching stimulates spine head formation while a region that binds to Cdc42 and Rac is required for stalk extension. Conversely, IQGAP1 rescues spine deficiency induced by expression of dominant negative Cdc42 by stimulating formation of stubby spines. Together, our observations place IQGAP1 as a crucial regulator of spine number and shape acting through the N-Wasp Arp2/3 complex, as well as upstream and downstream of Cdc42.

Spine pruning in 5xFAD mice starts on basal dendrites of layer 5 pyramidal neurons

Transgenic mice with Alzheimer's disease (AD) mutations have been widely used to model changes in neuronal structure and function. While there are clear gross structural changes in post-mortem brains of AD patients, most mouse models of AD do not recapitulate the considerable loss of neurons. Furthermore, possible connections between early subtle structural changes and the loss of neurons are difficult to study. In an attempt to start unraveling how neurons are affected during the early stages of what becomes full neurodegeneration, we crossed a mouse model of familial AD, which displays massive neocortical neurodegeneration (the 5xFAD mouse), with the fluorescent H-line YFP mouse. This novel bigenic mouse model of AD, which we have named the 5XY mouse, expresses YFP in principal neurons in the cortex such that even fine details of cells are clearly visible. Such bright fluorescence allowed us to use high-resolution confocal microscopy to quantify changes in spine density in the somatosensory cortex, prefrontal cortex, and hippocampus at 2, 4, and 6 months of age. A significant loss of spines on basal dendrites in the somatosensory and prefrontal cortices of 6-month-old 5XY female mice was found. There was no observed spine loss at 6 months of age on the oblique dendrites of the hippocampus in the same mice. These data suggest that spine loss is an early event in the degeneration of the neocortical neurons in 5xFAD mice and a likely contributor to the cognitive impairments reported previously in this AD mouse model.

NEuronMOrphological analysis tool: open-source software for quantitative morphometrics

Morphometric analysis of neurons and brain tissue is relevant to the study of neuron circuitry development during the first phases of brain growth or for probing the link between microstructural morphology and degenerative diseases. As neural imaging techniques become ever more sophisticated, so does the amount and complexity of data generated. The NEuronMOrphological analysis tool NEMO was purposely developed to handle and process large numbers of optical microscopy image files of neurons in culture or slices in order to automatically run batch routines, store data and apply multivariate classification and feature extraction using 3-way principal component analysis (PCA). Here we describe the software's main features, underlining the differences between NEMO and other commercial and non-commercial image processing tools, and show an example of how NEMO can be used to classify neurons from wild-type mice and from animal models of autism.

Influence of highly distinctive structural properties on the excitability of pyramidal neurons in monkey visual and prefrontal cortices

Whole-cell patch-clamp recordings and high-resolution 3D morphometric analyses of layer 3 pyramidal neurons in in vitro slices of monkey primary visual cortex (V1) and dorsolateral granular prefrontal cortex (dlPFC) revealed that neurons in these two brain areas possess highly distinctive structural and functional properties. Area V1 pyramidal neurons are much smaller than dlPFC neurons, with significantly less extensive dendritic arbors and far fewer dendritic spines. Relative to dlPFC neurons, V1 neurons have a significantly higher input resistance, depolarized resting membrane potential, and higher action potential (AP) firing rates. Most V1 neurons exhibit both phasic and regular-spiking tonic AP firing patterns, while dlPFC neurons exhibit only tonic firing. Spontaneous postsynaptic currents are lower in amplitude and have faster kinetics in V1 than in dlPFC neurons, but are no different in frequency. Three-dimensional reconstructions of V1 and dlPFC neurons were incorporated into computational models containing Hodgkin-Huxley and AMPA receptor and GABA(A) receptor gated channels. Morphology alone largely accounted for observed passive physiological properties, but led to AP firing rates that differed more than observed empirically, and to synaptic responses that opposed empirical results. Accordingly, modeling predicts that active channel conductances differ between V1 and dlPFC neurons. The unique features of V1 and dlPFC neurons are likely fundamental determinants of area-specific network behavior. The compact electrotonic arbor and increased excitability of V1 neurons support the rapid signal integration required for early processing of visual information. The greater connectivity and dendritic complexity of dlPFC neurons likely support higher level cognitive functions including working memory and planning.

Derepression of a neuronal inhibitor due to miRNA dysregulation in a schizophrenia-related microdeletion

22q11.2 microdeletions result in specific cognitive deficits and schizophrenia. Analysis of Df(16)A(+/-) mice, which model this microdeletion, revealed abnormalities in the formation of neuronal dendrites and spines, as well as altered brain microRNAs. Here, we show a drastic reduction of miR-185, which resides within the 22q11.2 locus, to levels more than expected by a hemizygous deletion, and we demonstrate that this reduction alters dendritic and spine development. miR-185 represses, through an evolutionarily conserved target site, a previously unknown inhibitor of these processes that resides in the Golgi apparatus and shows higher prenatal brain expression. Sustained derepression of this inhibitor after birth represents the most robust transcriptional disturbance in the brains of Df(16)A(+/-) mice and results in structural alterations in the hippocampus. Reduction of miR-185 also has milder age- and region-specific effects on the expression of some Golgi-related genes. Our findings illuminate the contribution of microRNAs in psychiatric disorders and cognitive dysfunction.

Electrophysiological changes precede morphological changes to frontal cortical pyramidal neurons in the rTg4510 mouse model of progressive tauopathy

Whole-cell patch-clamp recordings and high-resolution morphometry were used to assess functional and structural properties of layer 3 pyramidal neurons in early (<4 months) and advanced (>8 months) stages of tauopathy in frontal cortical slices prepared from rTg4510 tau mutant (P301L) mice. In early tauopathy, dendritic architecture is preserved. In advanced tauopathy, neurons can be categorized as either "atrophic" (58 %)-exhibiting marked atrophy of the apical tuft, or "intact" (42 %)-with normal apical tufts and, in some instances, proliferative sprouting of oblique branches of the apical trunk. Approximately equal numbers of atrophic and intact neurons contain neurofibrillary tangles (NFTs) or are tangle-free, lending further support to the idea that NFTs per se are not toxic. Spine density is decreased due to a specific reduction in mushroom spines, but filopodia are increased in both atrophic and intact neurons. By contrast to these morphological changes, which are robust only in the advanced stage, significant electrophysiological changes are present in the early stage and persist in the advanced stage in both atrophic and intact neurons. The most marked of these changes are: a depolarized resting membrane potential, an increased depolarizing sag potential and increased action potential firing rates-all indicative of hyperexcitability. Spontaneous excitatory postsynaptic currents are not reduced in frequency or amplitude in either stage. The difference in the time course of functionally important electrophysiological changes versus regressive morphological changes implies differences in pathogenic mechanisms underlying functional and structural changes to neurons during progressive tauopathy.

Functional and structural properties of dentate granule cells with hilar basal dendrites in mouse entorhino-hippocampal slice cultures

During postnatal development hippocampal dentate granule cells (GCs) often extend dendrites from the basal pole of their cell bodies into the hilar region. These so-called hilar basal dendrites (hBD) usually regress with maturation. However, hBDs may persist in a subset of mature GCs under certain conditions (both physiological and pathological). The functional role of these hBD-GCs remains not well understood. Here, we have studied hBD-GCs in mature (≥18 days in vitro) mouse entorhino-hippocampal slice cultures under control conditions and have compared their basic functional properties (basic intrinsic and synaptic properties) and structural properties (dendritic arborisation and spine densities) to those of neighboring GCs without hBDs in the same set of cultures. Except for the presence of hBDs, we did not detect major differences between the two GC populations. Furthermore, paired recordings of neighboring GCs with and without hBDs did not reveal evidence for a heavy aberrant GC-to-GC connectivity. Taken together, our data suggest that in control cultures the presence of hBDs on GCs is neither sufficient to predict alterations in the basic functional and structural properties of these GCs nor indicative of a heavy GC-to-GC connectivity between neighboring GCs.

D1 receptor modulation of action potential firing in a subpopulation of layer 5 pyramidal neurons in the prefrontal cortex

Dopamine modulation in the prefrontal cortex is important for cognitive processing and disrupted in diverse neuropsychiatric diseases. Activation of D1 receptors is thought to enable working memory by enhancing the firing properties of pyramidal neurons. However, these receptors are only sparsely expressed in the prefrontal cortex, and how they impact individual neurons remains unknown. Here we study D1 receptor modulation of layer 5 pyramidal neurons in acute slices of the mouse prefrontal cortex. Using whole-cell recordings and two-photon microscopy, we show that neurons expressing D1 receptors have unique morphological and physiological properties. We then demonstrate that activation of these receptors selectively enhances the firing of these neurons by signaling via the protein kinase A pathway. This finding of robust D1 receptor modulation in only a subpopulation of neurons has important implications for cognitive function and disease.

MSK1 regulates homeostatic and experience-dependent synaptic plasticity

The ability of neurons to modulate synaptic strength underpins synaptic plasticity, learning and memory, and adaptation to sensory experience. Despite the importance of synaptic adaptation in directing, reinforcing, and revising the behavioral response to environmental influences, the cellular and molecular mechanisms underlying synaptic adaptation are far from clear. Brain-derived neurotrophic factor (BDNF) is a prime initiator of structural and functional synaptic adaptation. However, the signaling cascade activated by BDNF to initiate these adaptive changes has not been elucidated. We have previously shown that BDNF activates mitogen- and stress-activated kinase 1 (MSK1), which regulates gene transcription via the phosphorylation of both CREB and histone H3. Using mice with a kinase-dead knock-in mutation of MSK1, we now show that MSK1 is necessary for the upregulation of synaptic strength in response to environmental enrichment in vivo. Furthermore, neurons from MSK1 kinase-dead mice failed to show scaling of synaptic transmission in response to activity deprivation in vitro, a deficit that could be rescued by reintroduction of wild-type MSK1. We also show that MSK1 forms part of a BDNF- and MAPK-dependent signaling cascade required for homeostatic synaptic scaling, which likely resides in the ability of MSK1 to regulate cell surface GluA1 expression via the induction of Arc/Arg3.1. These results demonstrate that MSK1 is an integral part of a signaling pathway that underlies the adaptive response to synaptic and environmental experience. MSK1 may thus act as a key homeostat in the activity- and experience-dependent regulation of synaptic strength.

Amyloid precursor protein (APP) regulates synaptic structure and function

The amyloid precursor protein (APP) plays a critical role in Alzheimer's disease (AD) pathogenesis. APP is proteolytically cleaved by β- and γ-secretases to generate the amyloid β-protein (Aβ), the core protein component of senile plaques in AD. It is also cleaved by α-secretase to release the large soluble APP (sAPP) luminal domain that has been shown to exhibit trophic properties. Increasing evidence points to the development of synaptic deficits and dendritic spine loss prior to deposition of amyloid in transgenic mouse models that overexpress APP and Aβ peptides. The consequence of loss of APP, however, is unsettled. In this study, we investigated whether APP itself plays a role in regulating synaptic structure and function using an APP knock-out (APP-/-) mouse model. We examined dendritic spines in primary cultures of hippocampal neurons and CA1 neurons of hippocampus from APP-/- mice. In the cultured neurons, there was a significant decrease (~35%) in spine density in neurons derived from APP-/- mice compared to littermate control neurons that were partially restored with sAPPα-conditioned medium. In APP-/- mice in vivo, spine numbers were also significantly reduced but by a smaller magnitude (~15%). Furthermore, apical dendritic length and dendritic arborization were markedly diminished in hippocampal neurons. These abnormalities in neuronal morphology were accompanied by reduction in long-term potentiation. Strikingly, all these changes in vivo were only seen in mice that were 12-15 months in age but not in younger animals. We propose that APP, specifically sAPP, is necessary for the maintenance of dendritic integrity in the hippocampus in an age-associated manner. Finally, these age-related changes may contribute to AD pathology independent of Aβ-mediated synaptic toxicity.

Modulation of synaptic plasticity in the hippocampus by hippocampus-derived estrogen and androgen

The hippocampus synthesizes estrogen and androgen in addition to the circulating sex steroids. Synaptic modulation by hippocampus-derived estrogen or androgen is essential to maintain healthy memory processes. Rapid actions (1-2h) of 17β-estradiol (17β-E2) occur via synapse-localized receptors (ERα or ERβ), while slow genomic E2 actions (6-48h) occur via classical nuclear receptors (ERα or ERβ). The long-term potentiation (LTP), induced by strong tetanus or theta-burst stimulation, is not further enhanced by E2 perfusion in adult rats. Interestingly, E2 perfusion can rescue corticosterone (stress hormone)-induced suppression of LTP. The long-term depression is modulated rapidly by E2 perfusion. Elevation of the E2 concentration changes rapidly the density and head structure of spines in neurons. ERα, but not ERβ, drives this enhancement of spinogenesis. Kinase networks are involved downstream of ERα. Testosterone (T) or dihydrotestosterone (DHT) also rapidly modulates spinogenesis. Newly developed Spiso-3D mathematical analysis is used to distinguish these complex effects by sex steroids and kinases. It has been doubted that the level of hippocampus-derived estrogen and androgen may not be high enough to modulate synaptic plasticity. Determination of the accurate concentration of E2, T or DHT in the hippocampus is enabled by mass-spectrometric analysis in combination with new steroid-derivatization methods. The E2 level in the hippocampus is approximately 8nM for the male and 0.5-2nM for the female, which is much higher than that in circulation. The level of T and DHT is also higher than that in circulation. Taken together, hippocampus-derived E2, T, and DHT play a major role in modulation of synaptic plasticity.

Guidance-cue control of horizontal cell morphology, lamination, and synapse formation in the mammalian outer retina

In the vertebrate retina, neuronal circuitry required for visual perception is organized within specific laminae. Photoreceptors convey external visual information to bipolar and horizontal cells at triad ribbon synapses established within the outer plexiform layer (OPL), initiating retinal visual processing. However, the molecular mechanisms that organize these three classes of neuronal processes within the OPL, thereby ensuring appropriate ribbon synapse formation, remain largely unknown. Here we show that mice with null mutations in Sema6A or PlexinA4 (PlexA4) exhibit a pronounced defect in OPL stratification of horizontal cell axons without any apparent deficits in bipolar cell dendrite or photoreceptor axon targeting. Furthermore, these mutant horizontal cells exhibit aberrant dendritic arborization and reduced dendritic self-avoidance within the OPL. Ultrastructural analysis shows that the horizontal cell contribution to rod ribbon synapse formation in PlexA4⁻/⁻ retinas is disrupted. These findings define molecular components required for outer retina lamination and ribbon synapse formation.

Segmentation and tracing of single neurons from 3D confocal microscope images

In order to understand the brain, we need to first understand the morphology of neurons. In the neurobiology community, there have been recent pushes to analyze both neuron connectivity and the influence of structure on function. Currently, a technical road block that stands in the way of these studies is the inability to automatically trace neuronal structure from microscopy. On the image processing side, proposed tracing algorithms face difficulties in low contrast, indistinct boundaries, clutter, and complex branching structure. To tackle these difficulties, we develop Tree2Tree, a robust automatic neuron segmentation and morphology generation algorithm. Tree2Tree uses a local medial tree generation strategy in combination with a global tree linking to build a maximum likelihood global tree. Recasting the neuron tracing problem in a graph-theoretic context enables Tree2Tree to estimate bifurcations naturally, which is currently a challenge for current neuron tracing algorithms. Tests on cluttered confocal microscopy images of Drosophila neurons give results that correspond to ground truth within a margin of ±2.75% normalized mean absolute error.

SpineLab: tool for three-dimensional reconstruction of neuronal cell morphology

SpineLab is a software tool developed for reconstructing neuronal feature skeletons from three-dimensional single- or multi-photon image stacks. These images often suffer from limited resolution and a low signal-to-noise ratio, making the extraction of morphometric information difficult. To overcome this limitation, we have developed a software tool that offers the possibility to create feature skeletons in various modes-automatically as well as with manual interaction. We have named this novel tool SpineLab. In a first step, an investigator adjusts a set of parameters for automatic analysis in an interactive manner, i.e., with online visual feedback, followed by a second step, in which the neuronal feature skeleton can be modified by hand. We validate the ability of SpineLab to reconstruct the entire dendritic tree of identified GFP-expressing neurons and evaluate the accuracy of dendritic spine detection. We report that SpineLab is capable of significantly facilitating the reconstruction of dendrites and spines. Moreover, the automatic approach appears sufficient to detect spine density changes in time-lapse imaging experiments. Taken together, we conclude that SpineLab is an ideal software tool for partially automatic reconstruction of neural cell morphology.

Neuronal tracing for connectomic studies

Reconstruction of the complete wiring diagram, or connectome, of a neural circuit provides an alternative approach to conventional circuit analysis. One major obstacle of connectomics lies in segmenting and tracing neuronal processes from the vast number of images obtained with optical or electron microscopy. Here I review recent progress in automated tracing algorithms for connectomic reconstruction with fluorescence and electron microscopy, and discuss the challenges to image analysis posed by novel optical imaging techniques.

Automated reconstruction of neuronal morphology based on local geometrical and global structural models

Digital reconstruction of neurons from microscope images is an important and challenging problem in neuroscience. In this paper, we propose a model-based method to tackle this problem. We first formulate a model structure, then develop an algorithm for computing it by carefully taking into account morphological characteristics of neurons, as well as the image properties under typical imaging protocols. The method has been tested on the data sets used in the DIADEM competition and produced promising results for four out of the five data sets.

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.

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.

Deletion of the amyloid precursor-like protein 2 (APLP2) does not affect hippocampal neuron morphology or function

Amyloid precursor protein (APP), the parent molecule to amyloid β peptide, is part of a larger gene family with two mammalian homologues, amyloid precursor-like protein 1 (APLP1) and amyloid precursor-like protein 2 (APLP2). Initial knock-out studies demonstrated that while single APP family gene deletions produced relatively mild phenotypes, deficiency of APLP2 and one other member of the gene family resulted in perinatal lethality, suggesting vital roles masked by functional redundancy of the other homologues. Because of the importance of APP in Alzheimer's disease, the vast majority of studies to date have concentrated on the neuronal functions of APP, leaving limited data on its homologues. APLP2 is of particular interest as it contains high sequence homology with APP, is processed similarly, is expressed in overlapping spatial and temporal patterns, and is obligatory for lethality when combined with deficiency of either APLP1 or APP but does not contain the toxic amyloid β sequence. Here we sought to test the role of APLP2 on neuronal structure and function using a combined approach involving in vitro and in vivo techniques in young and aged animals. Surprisingly, we found that unlike APP, APLP2 appears not to be essential for maintenance of dendritic structure, spine density, or synaptic function. Thus, there is clear divergence in the functional redundancy between APP and APLP2.

Dynamic O-GlcNAc modification regulates CREB-mediated gene expression and memory formation

The transcription factor CREB is a key regulator of many neuronal processes, including brain development, circadian rhythm, and long-term memory. Studies of CREB have focused on its phosphorylation, although the diversity of CREB functions in the brain suggests additional forms of regulation. Here we expand on a chemoenzymatic strategy for quantifying glycosylation stoichiometries to characterize the functional roles of CREB glycosylation in neurons. We show that CREB is dynamically O-GlcNAc-modified in response to neuronal activity and glycosylation represses CREB-dependent transcription by impairing its association with the co-activator CRTC/TORC. Blocking glycosylation of CREB altered cellular function and behavioral plasticity, enhancing both axonal and dendritic growth and long-term memory consolidation. Our findings demonstrate a new role for O-glycosylation in memory formation and provide a mechanistic understanding of how glycosylation contributes to critical neuronal functions. Moreover, we identify a previously unknown mechanism for the regulation of activity-dependent gene expression, neural development, and memory.

Automatic 3D neuron tracing using all-path pruning

Motivation: Digital reconstruction, or tracing, of 3D neuron structures is critical toward reverse engineering the wiring and functions of a brain. However, despite a number of existing studies, this task is still challenging, especially when a 3D microscopic image has low signal-to-noise ratio (SNR) and fragmented neuron segments. Published work can handle these hard situations only by introducing global prior information, such as where a neurite segment starts and terminates. However, manual incorporation of such global information can be very time consuming. Thus, a completely automatic approach for these hard situations is highly desirable.

Results: We have developed an automatic graph algorithm, called the all-path pruning (APP), to trace the 3D structure of a neuron. To avoid potential mis-tracing of some parts of a neuron, an APP first produces an initial over-reconstruction, by tracing the optimal geodesic shortest path from the seed location to every possible destination voxel/pixel location in the image. Since the initial reconstruction contains all the possible paths and thus could contain redundant structural components (SC), we simplify the entire reconstruction without compromising its connectedness by pruning the redundant structural elements, using a new maximal-covering minimal-redundant (MCMR) subgraph algorithm. We show that MCMR has a linear computational complexity and will converge. We examined the performance of our method using challenging 3D neuronal image datasets of model organisms (e.g. fruit fly).

Availability: The software is available upon request. We plan to eventually release the software as a plugin of the V3D-Neuron package at http://penglab.janelia.org/proj/v3d.

Contact:pengh@janelia.hhmi.org

Automated 4D analysis of dendritic spine morphology: applications to stimulus-induced spine remodeling and pharmacological rescue in a disease model

Uncovering the mechanisms that regulate dendritic spine morphology has been limited, in part, by the lack of efficient and unbiased methods for analyzing spines. Here, we describe an automated 3D spine morphometry method and its application to spine remodeling in live neurons and spine abnormalities in a disease model. We anticipate that this approach will advance studies of synapse structure and function in brain development, plasticity, and disease.

Topoisomerase IIbeta is required for lamina-specific targeting of retinal ganglion cell axons and dendrites

The specific partnering of synaptically connected neurons is central to nervous system function. Proper wiring requires the interchange of signals between a postmitotic neuron and its environment, a distinct pattern of transcription in the nucleus, and deployment of guidance and adhesion cues to the cell surface. To identify genes involved in neurite targeting by retinal ganglion cells (GCs), their presynaptic partners in the retina, and their postsynaptic targets in the optic tectum, we undertook a forward genetic screen for mutations disrupting visual responses in zebrafish. This rapid primary screen was subsequently refined by immunohistochemical labeling of retinal and tectal neurites to detect patterning errors. From this unbiased screen, the notorious (noto) mutant exhibited the most specific phenotypes: intact retinal and tectal differentiation but multiple neurite targeting defects in the retinal inner plexiform layer (IPL) and tectal neuropil. Positional cloning and morpholino phenocopy revealed that the mutation disrupts Topoisomerase IIβ (Top2b), a broadly distributed nuclear protein involved in chromatin modifications during postmitotic differentiation. Top2b-DNA interactions are known to regulate transcription of developmentally important genes, including axon guidance factors and cell adhesion molecules, but a specific role in local synaptic targeting has not been previously described. The neurite targeting defects among GC axons are largely restricted to crossovers between sublaminae of a specific layer, SFGS, and were shown by mosaic analysis to be autonomous to the GC axons. The noto mutant provides the first example of the importance of an epigenetic regulator, Top2b, in the intricate series of events that lead to a properly wired visual system.

Stress risk factors and stress-related pathology: neuroplasticity, epigenetics and endophenotypes

This paper highlights a symposium on stress risk factors and stress susceptibility, presented at the Neurobiology of Stress workshop in Boulder, CO, in June 2010. This symposium addressed factors linking stress plasticity and reactivity to stress pathology in animal models and in humans. Dr. J. Radley discussed studies demonstrating prefrontal cortical neuroplasticity and prefrontal control of hypothalamo-pituitary-adrenocortical axis function in rats, highlighting the emerging evidence of the critical role that this region plays in normal and pathological stress integration. Dr. M. Kabbaj summarized his studies of possible epigenetic mechanisms underlying behavioral differences in rat populations bred for differential stress reactivity. Dr. L. Jacobson described studies using a mouse model to explore the diverse actions of antidepressants in brain, suggesting mechanisms whereby antidepressants may be differentially effective in treating specific depression endophenotypes. Dr. R. Yehuda discussed the role of glucocorticoids in post-traumatic stress disorder (PTSD), indicating that low cortisol level may be a trait that predisposes the individual to development of the disorder. Furthermore, she presented evidence indicating that traumatic events can have transgenerational impact on cortisol reactivity and development of PTSD symptoms. Together, the symposium highlighted emerging themes regarding the role of brain reorganization, individual differences, and epigenetics in determining stress plasticity and pathology.

Localization of presynaptic inputs on dendrites of individually labeled neurons in three dimensional space using a center distance algorithm

The spatial distribution of synaptic inputs on the dendritic tree of a neuron can have significant influence on neuronal function. Consequently, accurate anatomical reconstructions of neuron morphology and synaptic localization are critical when modeling and predicting physiological responses of individual neurons. Historically, generation of three-dimensional (3D) neuronal reconstructions together with comprehensive mapping of synaptic inputs has been an extensive task requiring manual identification of putative synaptic contacts directly from tissue samples or digital images. Recent developments in neuronal tracing software applications have improved the speed and accuracy of 3D reconstructions, but localization of synaptic sites through the use of pre- and/or post-synaptic markers has remained largely a manual process. To address this problem, we have developed an algorithm, based on 3D distance measurements between putative pre-synaptic terminals and the post-synaptic dendrite, to automate synaptic contact detection on dendrites of individually labeled neurons from 3D immunofluorescence image sets. In this study, the algorithm is implemented with custom routines in Matlab, and its effectiveness is evaluated through analysis of primary sensory afferent terminals on motor neurons. Optimization of algorithm parameters enabled automated identification of synaptic contacts that matched those identified by manual inspection with low incidence of error. Substantial time savings and the elimination of variability in contact detection introduced by different users are significant advantages of this method.

NeurphologyJ: an automatic neuronal morphology quantification method and its application in pharmacological discovery

Background

Automatic quantification of neuronal morphology from images of fluorescence microscopy plays an increasingly important role in high-content screenings. However, there exist very few freeware tools and methods which provide automatic neuronal morphology quantification for pharmacological discovery.

Results

This study proposes an effective quantification method, called NeurphologyJ, capable of automatically quantifying neuronal morphologies such as soma number and size, neurite length, and neurite branching complexity (which is highly related to the numbers of attachment points and ending points). NeurphologyJ is implemented as a plugin to ImageJ, an open-source Java-based image processing and analysis platform. The high performance of NeurphologyJ arises mainly from an elegant image enhancement method. Consequently, some morphology operations of image processing can be efficiently applied. We evaluated NeurphologyJ by comparing it with both the computer-aided manual tracing method NeuronJ and an existing ImageJ-based plugin method NeuriteTracer. Our results reveal that NeurphologyJ is comparable to NeuronJ, that the coefficient correlation between the estimated neurite lengths is as high as 0.992. NeurphologyJ can accurately measure neurite length, soma number, neurite attachment points, and neurite ending points from a single image. Furthermore, the quantification result of nocodazole perturbation is consistent with its known inhibitory effect on neurite outgrowth. We were also able to calculate the IC50 of nocodazole using NeurphologyJ. This reveals that NeurphologyJ is effective enough to be utilized in applications of pharmacological discoveries.

Conclusions

This study proposes an automatic and fast neuronal quantification method NeurphologyJ. The ImageJ plugin with supports of batch processing is easily customized for dealing with high-content screening applications. The source codes of NeurphologyJ (interactive and high-throughput versions) and the images used for testing are freely available (see Availability).

Self-organization of developing embryo using scale-invariant approach

BACKGROUND

Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos.

METHODS

In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing C. elegans during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions (fd). Diffusion-limited aggregation (DLA) was used to validate the SIPL method.

RESULTS AND CONCLUSION

The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fd determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2.