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2.  Morphologic Evidence for Spatially Clustered Spines in Apical Dendrites of Monkey Neocortical Pyramidal Cells 
The Journal of comparative neurology  2012;520(13):2888-2902.
The general organization of neocortical connectivity in rhesus monkey is relatively well understood. However, mounting evidence points to an organizing principle that involves clustered synapses at the level of individual dendrites. Several synaptic plasticity studies have reported cooperative interaction between neighboring synapses on a given dendritic branch, which may potentially induce synapse clusters. Additionally, theoretical models have predicted that such cooperativity is advantageous, in that it greatly enhances a neuron’s computational repertoire. However, largely because of the lack of sufficient morphologic data, the existence of clustered synapses in neurons on a global scale has never been established. The majority of excitatory synapses are found within dendritic spines. In this study, we demonstrate that spine clusters do exist on pyramidal neurons by analyzing the three-dimensional locations of ~40,000 spines on 280 apical dendritic branches in layer III of the rhesus monkey prefrontal cortex. By using clustering algorithms and Monte Carlo simulations, we quantify the probability that the observed extent of clustering does not occur randomly. This provides a measure that tests for spine clustering on a global scale, whenever high-resolution morphologic data are available. Here we demonstrate that spine clusters occur significantly more frequently than expected by pure chance and that spine clustering is concentrated in apical terminal branches. These findings indicate that spine clustering is driven by systematic biological processes. We also found that mushroom-shaped and stubby spines are predominant in clusters on dendritic segments that display prolific clustering, independently supporting a causal link between spine morphology and synaptic clustering.
doi:10.1002/cne.23070
PMCID: PMC3573331  PMID: 22315181
clustering; dendritic spines; plasticity; morphology; image analysis
3.  The IRG Mouse: A Two-Color Fluorescent Reporter for Assessing Cre-Mediated Recombination and Imaging Complex Cellular Relationships In Situ 
Genesis (New York, N.y. : 2000)  2008;46(6):308-317.
Summary
The Cre-loxP system is widely used for making conditional alterations to the mouse genome. Cre-mediated recombination is frequently monitored using reporter lines in which Cre expression activates a reporter gene driven by a ubiquitous promoter. Given the distinct advantages of fluorescent reporters, we developed a transgenic reporter line, termed IRG, in which DsRed-Express, a red fluorescent protein (RFP) is expressed ubiquitously prior to Cre-mediated recombination and an enhanced green fluorescent protein (EGFP) following recombination. Besides their utility for monitoring Cre-mediated recombination, we show that in IRG mice red and green native fluorescence can be imaged simultaneously in thick tissue sections by confocal microscopy allowing for complex reconstructions to be created that are suitable for analysis of neuronal morphologies as well as neurovascular interactions in brain. IRG mice should provide a versatile tool for analyzing complex cellular relationships in both neural and nonneural tissues.†
doi:10.1002/dvg.20400
PMCID: PMC2928670  PMID: 18543298
Cre recombinase; loxP; conditional gene activation; DsRed-express; red fluorescent protein; enhanced green fluorescent protein; transgenic mice
4.  Mixed Electrical–Chemical Synapses in Adult Rat Hippocampus are Primarily Glutamatergic and Coupled by Connexin-36 
Dendrodendritic electrical signaling via gap junctions is now an accepted feature of neuronal communication in mammalian brain, whereas axodendritic and axosomatic gap junctions have rarely been described. We present ultrastructural, immunocytochemical, and dye-coupling evidence for “mixed” (electrical/chemical) synapses on both principal cells and interneurons in adult rat hippocampus. Thin-section electron microscopic images of small gap junction-like appositions were found at mossy fiber (MF) terminals on thorny excrescences of CA3 pyramidal neurons (CA3pyr), apparently forming glutamatergic mixed synapses. Lucifer Yellow injected into weakly fixed CA3pyr was detected in MF axons that contacted four injected CA3pyr, supporting gap junction-mediated coupling between those two types of principal cells. Freeze-fracture replica immunogold labeling revealed diverse sizes and morphologies of connexin-36-containing gap junctions throughout hippocampus. Of 20 immunogold-labeled gap junctions, seven were large (328–1140 connexons), three of which were consistent with electrical synapses between interneurons; but nine were at axon terminal synapses, three of which were immediately adjacent to distinctive glutamate receptor-containing postsynaptic densities, forming mixed glutamatergic synapses. Four others were adjacent to small clusters of immunogold-labeled 10-nm E-face intramembrane particles, apparently representing extrasynaptic glutamate receptor particles. Gap junctions also were on spines in stratum lucidum, stratum oriens, dentate gyrus, and hilus, on both interneurons and unidentified neurons. In addition, one putative GABAergic mixed synapse was found in thin-section images of a CA3pyr, but none were found by immunogold labeling, suggesting the rarity of GABAergic mixed synapses. Cx36-containing gap junctions throughout hippocampus suggest the possibility of reciprocal modulation of electrical and chemical signals in diverse hippocampal neurons.
doi:10.3389/fnana.2012.00013
PMCID: PMC3351785  PMID: 22615687
CA3; dentate gyrus; interneuron; pyramidal neuron; principal cell; mossy fiber; gap junction
5.  Characterization of MSB Synapses in Dissociated Hippocampal Culture with Simultaneous Pre- and Postsynaptic Live Microscopy 
PLoS ONE  2011;6(10):e26478.
Multisynaptic boutons (MSBs) are presynaptic boutons in contact with multiple postsynaptic partners. Although MSB synapses have been studied with static imaging techniques such as electron microscopy (EM), the dynamics of individual MSB synapses have not been directly evaluated. It is known that the number of MSB synapses increases with synaptogenesis and plasticity but the formation, behavior, and fate of individual MSB synapses remains largely unknown. To address this, we developed a means of live imaging MSB synapses to observe them directly over time. With time lapse confocal microscopy of GFP-filled dendrites in contact with VAMP2-DsRed-labeled boutons, we recorded both MSBs and their contacting spines hourly over 15 or more hours. Our live microscopy showed that, compared to spines contacting single synaptic boutons (SSBs), MSB-contacting spines exhibit elevated dynamic behavior. These results are consistent with the idea that MSBs serve as intermediates in synaptic development and plasticity.
doi:10.1371/journal.pone.0026478
PMCID: PMC3197663  PMID: 22028887
6.  Three-Dimensional Neuron Tracing by Voxel Scooping 
Journal of neuroscience methods  2009;184(1):169-175.
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.
doi:10.1016/j.jneumeth.2009.07.021
PMCID: PMC2753723  PMID: 19632273
Centerline Extraction; Neuron Tracing; Image Analysis; Medial Axis
7.  The Electrotonic Structure of Pyramidal Neurons Contributing to Prefrontal Cortical Circuits in Macaque Monkeys Is Significantly Altered in Aging 
Cerebral Cortex (New York, NY)  2009;19(10):2248-2268.
Whereas neuronal numbers are largely preserved in normal aging, subtle morphological changes occur in dendrites and spines, whose electrotonic consequences remain unexplored. We examined age-related morphological alterations in 2 types of pyramidal neurons contributing to working memory circuits in the macaque prefrontal cortex (PFC): neurons in the superior temporal cortex forming “long” projections to the PFC and “local” projection neurons within the PFC. Global dendritic mass homeostasis, measured by 3-dimensional scaling analysis, was conserved with aging in both neuron types. Spine densities, dendrite diameters, lengths, and branching complexity were all significantly reduced in apical dendrites of long projection neurons with aging, but only spine parameters were altered in local projection neurons. Despite these differences, voltage attenuation due to passive electrotonic structure, assuming equivalent cable parameters, was significantly reduced with aging in the apical dendrites of both neuron classes. Confirming the electrotonic analysis, simulated passive backpropagating action potential efficacy was significantly higher in apical but not basal dendrites of old neurons. Unless compensated by changes in passive cable parameters, active membrane properties, or altered synaptic properties, these effects will increase the excitability of pyramidal neurons, compromising the precisely tuned activity required for working memory, ultimately resulting in age-related PFC dysfunction.
doi:10.1093/cercor/bhn242
PMCID: PMC2742588  PMID: 19150923
3-D morphometry; brain aging; dendritic spines; dendrites; electrotonic properties; pyramidal neurons; working memory
8.  REPEATED STRESS ALTERS DENDRITIC SPINE MORPHOLOGY IN THE RAT MEDIAL PREFRONTAL CORTEX 
The Journal of comparative neurology  2008;507(1):1141-1150.
Anatomical alterations in the medial prefrontal cortex (mPFC) are associated with hypothalamo-pituitary adrenal (HPA) axis dysregulation, altered stress hormone levels, and psychiatric symptoms of stress-related mental illnesses. Functional imaging studies reveal impairment and shrinkage of the mPFC in such conditions, and these findings are paralleled by experimental studies showing dendritic retraction and spine loss following repeated stress in rodents. Here we extend this characterization to how repeated stress affects dendritic spine morphology in mPFC through the utilization of an automated approach which rapidly digitizes, reconstructs 3-dimensionally, and calculates geometric features of neurons. Rats were perfused after being subjected to 3 weeks of daily restraint stress (6 hours/day), and intracellular injections of Lucifer Yellow were made in layers II/III pyramidal neurons in the dorsal mPFC. To reveal spines in all angles of orientation, deconvolved high-resolution confocal laser scanning microscopy image stacks of dendritic segments were reconstructed and analyzed for spine volume, surface area, and length using a Rayburst-based automated approach (8,091 and 8,987 spines for control and stress, respectively). We found that repeated stress results in an overall decrease in mean dendritic spine volume and surface area, which was most pronounced in the distal portion of apical dendritic fields. Moreover, we observed an overall shift in the population of spines, manifested by a reduction in large spines and increase in small spines. These results suggest a failure of spines to mature and stabilize following repeated stress, and are likely to have major repercussions on function, receptor expression, and synaptic efficacy.
doi:10.1002/cne.21588
PMCID: PMC2796421  PMID: 18157834
dendritic spine; morphometry; plasticity; prefrontal cortex; stress
9.  Percolation theory relates corticocancellous architecture to mechanical function in vertebrae of inbred mouse strains 
Bone  2007;42(4):743-750.
Complex corticocancellous skeletal sites such as the vertebra or proximal femur are connected networks of bone capable of transferring mechanical loads. Characterizing these structures as networks may allow us to quantify the load transferring behavior of the emergent system as a function of the connected cortical and trabecular components. By defining the relationship between certain physical bone traits and mechanical load transfer pathways, a clearer picture of the genetic determinants of skeletal fragility can be developed. We tested the hypothesis that the measures provided by network percolation theory will reveal that different combinations of cortical, trabecular, and compositional traits lead to significantly different load transfer pathways within the vertebral bodies among inbred mouse strains. Gross morphologic, micro-architectural, and compositional traits of L5 vertebrae from 15 week old A/J (A), C57BL6/J (B6), and C3H/HeJ (C3H) inbred mice (n=10/strain) were determined using micro-computed tomography. Measures included total cross-sectional area, bone volume fraction, trabecular number, thickness, spacing, cortical area, and tissue mineral density. Two-dimensional coronal sections were converted to network graphs with the cortical shell considered as one highly connected node. Percolation parameters including correlation length (average number of connected nodes between superior and inferior surfaces), chemical length (minimum number of connected nodes between surfaces), and backbone mass (strut number) were measured. Analysis of the topology of the connected bone networks showed that A and B6 mice transfer load through trabecular pathways in the middle of the vertebral body in addition to the cortical shell. C3H mice transfer load primarily through the highly mineralized cortical shell. Thus, the measures provided by percolation theory provide a quantitative approach to study how different combinations of cortical and trabecular traits lead to mechanically functional structures. The data further emphasize the interdependent nature of these physical bone traits suggesting similar genetic variants may affect both trabecular and cortical bone. Therefore, developing a network approach to study corticocancellous architecture during growth should further our understanding of the biological basis of skeletal fragility and, thus, provide novel engineering approaches to studying the genetic basis of fracture risk.
doi:10.1016/j.bone.2007.12.009
PMCID: PMC2650241  PMID: 18258502
Percolation theory; Inbred mouse strains; Vertebrae; Corticocancellous architecture; Trabecular network; Biomechanics
10.  Changes in the structural complexity of the aged brain 
Aging cell  2007;6(3):275-284.
Summary
Structural changes of neurons in the brain during aging are complex and not well understood. Neurons have significant homeostatic control of essential brain functions, including synaptic excitability, gene expression, and metabolic regulation. Any deviations from the norm can have severe consequences as seen in aging and injury. In this review, we present some of the structural adaptations that neurons undergo throughout normal and pathological aging and discuss their effects on electrophysiological properties and cognition. During aging, it is evident that neurons undergo morphological changes such as a reduction in the complexity of dendrite arborization and dendritic length. Spine numbers are also decreased, and because spines are the major sites for excitatory synapses, changes in their numbers could reflect a change in synaptic densities. This idea has been supported by studies that demonstrate a decrease in the overall frequency of spontaneous glutamate receptor-mediated excitatory responses, as well as a decrease in the levels of α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid and N-methyl-d-aspartate receptor expression. Other properties such as γ-aminobutyric acid A receptor-mediated inhibitory responses and action potential firing rates are both significantly increased with age. These findings suggest that age-related neuronal dysfunction, which must underlie observed decline in cognitive function, probably involves a host of other subtle changes within the cortex that could include alterations in receptors, loss of dendrites, and spines and myelin dystrophy, as well as the alterations in synaptic transmission. Together these multiple alterations in the brain may constitute the substrate for age-related loss of cognitive function.
doi:10.1111/j.1474-9726.2007.00289.x
PMCID: PMC2441530  PMID: 17465981
Aging; Alzheimer’s disease; neuroscience; spatial complexity; electrophysiology; dendrites; spines
11.  Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images 
PLoS ONE  2008;3(4):e1997.
A fundamental challenge in understanding how dendritic spine morphology controls learning and memory has been quantifying three-dimensional (3D) spine shapes with sufficient precision to distinguish morphologic types, and sufficient throughput for robust statistical analysis. The necessity to analyze large volumetric data sets accurately, efficiently, and in true 3D has been a major bottleneck in deriving reliable relationships between altered neuronal function and changes in spine morphology. We introduce a novel system for automated detection, shape analysis and classification of dendritic spines from laser scanning microscopy (LSM) images that directly addresses these limitations. The system is more accurate, and at least an order of magnitude faster, than existing technologies. By operating fully in 3D the algorithm resolves spines that are undetectable with standard two-dimensional (2D) tools. Adaptive local thresholding, voxel clustering and Rayburst Sampling generate a profile of diameter estimates used to classify spines into morphologic types, while minimizing optical smear and quantization artifacts. The technique opens new horizons on the objective evaluation of spine changes with synaptic plasticity, normal development and aging, and with neurodegenerative disorders that impair cognitive function.
doi:10.1371/journal.pone.0001997
PMCID: PMC2292261  PMID: 18431482
12.  Neuronal Firing Sensitivity to Morphologic and Active Membrane Parameters 
PLoS Computational Biology  2008;4(1):e11.
Both the excitability of a neuron's membrane, driven by active ion channels, and dendritic morphology contribute to neuronal firing dynamics, but the relative importance and interactions between these features remain poorly understood. Recent modeling studies have shown that different combinations of active conductances can evoke similar firing patterns, but have neglected how morphology might contribute to homeostasis. Parameterizing the morphology of a cylindrical dendrite, we introduce a novel application of mathematical sensitivity analysis that quantifies how dendritic length, diameter, and surface area influence neuronal firing, and compares these effects directly against those of active parameters. The method was applied to a model of neurons from goldfish Area II. These neurons exhibit, and likely contribute to, persistent activity in eye velocity storage, a simple model of working memory. We introduce sensitivity landscapes, defined by local sensitivity analyses of firing rate and gain to each parameter, performed globally across the parameter space. Principal directions over which sensitivity to all parameters varied most revealed intrinsic currents that most controlled model output. We found domains where different groups of parameters had the highest sensitivities, suggesting that interactions within each group shaped firing behaviors within each specific domain. Application of our method, and its characterization of which models were sensitive to general morphologic features, will lead to advances in understanding how realistic morphology participates in functional homeostasis. Significantly, we can predict which active conductances, and how many of them, will compensate for a given age- or development-related structural change, or will offset a morphologic perturbation resulting from trauma or neurodegenerative disorder, to restore normal function. Our method can be adapted to analyze any computational model. Thus, sensitivity landscapes, and the quantitative predictions they provide, can give new insight into mechanisms of homeostasis in any biological system.
Author Summary
Homeostasis is a process that allows a system to maintain a certain level of output over a long time, even though the inputs controlling the output are changing. Recently, studies of neurons and neuronal networks have shown that the “active” parameters that describe the movement of ions across the cell membrane contribute to homeostasis, since these parameters can be combined in different ways to maintain a specific output. There is also evidence that the physical shape (“morphology”) of the neuron may play a role in homeostasis, but this possibility has not been explored in computational models. We have developed a method that uses sensitivity analysis to evaluate how different kinds of parameters, like active and morphologic ones, affect model output. Across a multi-dimensional parameter space, we identified both local and global trends in parameter sensitivities that indicate regions where different parameters, even morphologic ones, contribute strongly to homeostasis. Significantly, the authors used sensitivities to predict which parameters should change, and by how much, to compensate for changes in another parameter to restore normal function. These predictions may prove important to neuronal aging, disease, and trauma research, but the method can be used to analyze any computational model.
doi:10.1371/journal.pcbi.0040011
PMCID: PMC2211531  PMID: 18208320
13.  Neuronal Firing Sensitivity to Morphologic and Active Membrane Parameters 
PLoS Computational Biology  2008;4(1):e11.
Both the excitability of a neuron's membrane, driven by active ion channels, and dendritic morphology contribute to neuronal firing dynamics, but the relative importance and interactions between these features remain poorly understood. Recent modeling studies have shown that different combinations of active conductances can evoke similar firing patterns, but have neglected how morphology might contribute to homeostasis. Parameterizing the morphology of a cylindrical dendrite, we introduce a novel application of mathematical sensitivity analysis that quantifies how dendritic length, diameter, and surface area influence neuronal firing, and compares these effects directly against those of active parameters. The method was applied to a model of neurons from goldfish Area II. These neurons exhibit, and likely contribute to, persistent activity in eye velocity storage, a simple model of working memory. We introduce sensitivity landscapes, defined by local sensitivity analyses of firing rate and gain to each parameter, performed globally across the parameter space. Principal directions over which sensitivity to all parameters varied most revealed intrinsic currents that most controlled model output. We found domains where different groups of parameters had the highest sensitivities, suggesting that interactions within each group shaped firing behaviors within each specific domain. Application of our method, and its characterization of which models were sensitive to general morphologic features, will lead to advances in understanding how realistic morphology participates in functional homeostasis. Significantly, we can predict which active conductances, and how many of them, will compensate for a given age- or development-related structural change, or will offset a morphologic perturbation resulting from trauma or neurodegenerative disorder, to restore normal function. Our method can be adapted to analyze any computational model. Thus, sensitivity landscapes, and the quantitative predictions they provide, can give new insight into mechanisms of homeostasis in any biological system.
Author Summary
Homeostasis is a process that allows a system to maintain a certain level of output over a long time, even though the inputs controlling the output are changing. Recently, studies of neurons and neuronal networks have shown that the “active” parameters that describe the movement of ions across the cell membrane contribute to homeostasis, since these parameters can be combined in different ways to maintain a specific output. There is also evidence that the physical shape (“morphology”) of the neuron may play a role in homeostasis, but this possibility has not been explored in computational models. We have developed a method that uses sensitivity analysis to evaluate how different kinds of parameters, like active and morphologic ones, affect model output. Across a multi-dimensional parameter space, we identified both local and global trends in parameter sensitivities that indicate regions where different parameters, even morphologic ones, contribute strongly to homeostasis. Significantly, the authors used sensitivities to predict which parameters should change, and by how much, to compensate for changes in another parameter to restore normal function. These predictions may prove important to neuronal aging, disease, and trauma research, but the method can be used to analyze any computational model.
doi:10.1371/journal.pcbi.0040011
PMCID: PMC2211531  PMID: 18208320
14.  Dendritic vulnerability in neurodegenerative disease: insights from analyses of cortical pyramidal neurons in transgenic mouse models 
Brain structure & function  2010;214(2-3):181-199.
In neurodegenerative disorders, such as Alzheimer’s disease, neuronal dendrites and dendritic spines undergo significant pathological changes. Because of the determinant role of these highly dynamic structures in signaling by individual neurons and ultimately in the functionality of neuronal networks that mediate cognitive functions, a detailed understanding of these changes is of paramount importance. Mutant murine models, such as the Tg2576 APP mutant mouse and the rTg4510 tau mutant mouse have been developed to provide insight into pathogenesis involving the abnormal production and aggregation of amyloid and tau proteins, because of the key role that these proteins play in neurodegenerative disease. This review showcases the multidimensional approach taken by our collaborative group to increase understanding of pathological mechanisms in neurodegenerative disease using these mouse models. This approach includes analyses of empirical 3D morphological and electrophysiological data acquired from frontal cortical pyramidal neurons using confocal laser scanning microscopy and whole-cell patch-clamp recording techniques, combined with computational modeling methodologies. These collaborative studies are designed to shed insight on the repercussions of dystrophic changes in neocortical neurons, define the cellular phenotype of differential neuronal vulnerability in relevant models of neurodegenerative disease, and provide a basis upon which to develop meaningful therapeutic strategies aimed at preventing, reversing, or compensating for neurodegenerative changes in dementia.
doi:10.1007/s00429-010-0244-2
PMCID: PMC3045830  PMID: 20177698
Alzheimer’s disease; Amyloid; Computational modeling; Dendritic spine; Tau; Whole-cell patch-clamp

Results 1-14 (14)