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Sample records for model large cortical

  1. Investigation of Large Scale Cortical Models on Clustered Multi-Core Processors

    Science.gov (United States)

    2013-02-01

    Acceleration platforms examined. x86 Cell GPGPU HTM [22] × × Dean [25] × × Izhikevich [26] × × × Hodgkin- Huxley [27] × × × Morris Lecar [28...examined. These are the Hodgkin- Huxley [27], Izhikevich [26], Wilson [29], and Morris-Lecar [28] models. The Hodgkin– Huxley model is considered to be...and inactivation of Na currents). Table 2 compares the computation properties of the four models. The Hodgkin– Huxley model utilizes exponential

  2. Modeling cortical circuits.

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    Rohrer, Brandon Robinson; Rothganger, Fredrick H.; Verzi, Stephen J.; Xavier, Patrick Gordon

    2010-09-01

    The neocortex is perhaps the highest region of the human brain, where audio and visual perception takes place along with many important cognitive functions. An important research goal is to describe the mechanisms implemented by the neocortex. There is an apparent regularity in the structure of the neocortex [Brodmann 1909, Mountcastle 1957] which may help simplify this task. The work reported here addresses the problem of how to describe the putative repeated units ('cortical circuits') in a manner that is easily understood and manipulated, with the long-term goal of developing a mathematical and algorithmic description of their function. The approach is to reduce each algorithm to an enhanced perceptron-like structure and describe its computation using difference equations. We organize this algorithmic processing into larger structures based on physiological observations, and implement key modeling concepts in software which runs on parallel computing hardware.

  3. Large-Scale Mass Spectrometry Imaging Investigation of Consequences of Cortical Spreading Depression in a Transgenic Mouse Model of Migraine

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    Carreira, Ricardo J.; Shyti, Reinald; Balluff, Benjamin; Abdelmoula, Walid M.; van Heiningen, Sandra H.; van Zeijl, Rene J.; Dijkstra, Jouke; Ferrari, Michel D.; Tolner, Else A.; McDonnell, Liam A.; van den Maagdenberg, Arn M. J. M.

    2015-06-01

    Cortical spreading depression (CSD) is the electrophysiological correlate of migraine aura. Transgenic mice carrying the R192Q missense mutation in the Cacna1a gene, which in patients causes familial hemiplegic migraine type 1 (FHM1), exhibit increased propensity to CSD. Herein, mass spectrometry imaging (MSI) was applied for the first time to an animal cohort of transgenic and wild type mice to study the biomolecular changes following CSD in the brain. Ninety-six coronal brain sections from 32 mice were analyzed by MALDI-MSI. All MSI datasets were registered to the Allen Brain Atlas reference atlas of the mouse brain so that the molecular signatures of distinct brain regions could be compared. A number of metabolites and peptides showed substantial changes in the brain associated with CSD. Among those, different mass spectral features showed significant ( t-test, P migraine pathophysiology. The results also demonstrate the utility of aligning MSI datasets to a common reference atlas for large-scale MSI investigations.

  4. Using a Large-scale Neural Model of Cortical Object Processing to Investigate the Neural Substrate for Managing Multiple Items in Short-term Memory.

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    Liu, Qin; Ulloa, Antonio; Horwitz, Barry

    2017-07-07

    Many cognitive and computational models have been proposed to help understand working memory. In this article, we present a simulation study of cortical processing of visual objects during several working memory tasks using an extended version of a previously constructed large-scale neural model [Tagamets, M. A., & Horwitz, B. Integrating electrophysiological and anatomical experimental data to create a large-scale model that simulates a delayed match-to-sample human brain imaging study. Cerebral Cortex, 8, 310-320, 1998]. The original model consisted of arrays of Wilson-Cowan type of neuronal populations representing primary and secondary visual cortices, inferotemporal (IT) cortex, and pFC. We added a module representing entorhinal cortex, which functions as a gating module. We successfully implemented multiple working memory tasks using the same model and produced neuronal patterns in visual cortex, IT cortex, and pFC that match experimental findings. These working memory tasks can include distractor stimuli or can require that multiple items be retained in mind during a delay period (Sternberg's task). Besides electrophysiology data and behavioral data, we also generated fMRI BOLD time series from our simulation. Our results support the involvement of IT cortex in working memory maintenance and suggest the cortical architecture underlying the neural mechanisms mediating particular working memory tasks. Furthermore, we noticed that, during simulations of memorizing a list of objects, the first and last items in the sequence were recalled best, which may implicate the neural mechanism behind this important psychological effect (i.e., the primacy and recency effect).

  5. Analysis of Cortical Flow Models In Vivo

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    Benink, Hélène A.; Mandato, Craig A.; Bement, William M.

    2000-01-01

    Cortical flow, the directed movement of cortical F-actin and cortical organelles, is a basic cellular motility process. Microtubules are thought to somehow direct cortical flow, but whether they do so by stimulating or inhibiting contraction of the cortical actin cytoskeleton is the subject of debate. Treatment of Xenopus oocytes with phorbol 12-myristate 13-acetate (PMA) triggers cortical flow toward the animal pole of the oocyte; this flow is suppressed by microtubules. To determine how this suppression occurs and whether it can control the direction of cortical flow, oocytes were subjected to localized manipulation of either the contractile stimulus (PMA) or microtubules. Localized PMA application resulted in redirection of cortical flow toward the site of application, as judged by movement of cortical pigment granules, cortical F-actin, and cortical myosin-2A. Such redirected flow was accelerated by microtubule depolymerization, showing that the suppression of cortical flow by microtubules is independent of the direction of flow. Direct observation of cortical F-actin by time-lapse confocal analysis in combination with photobleaching showed that cortical flow is driven by contraction of the cortical F-actin network and that microtubules suppress this contraction. The oocyte germinal vesicle serves as a microtubule organizing center in Xenopus oocytes; experimental displacement of the germinal vesicle toward the animal pole resulted in localized flow away from the animal pole. The results show that 1) cortical flow is directed toward areas of localized contraction of the cortical F-actin cytoskeleton; 2) microtubules suppress cortical flow by inhibiting contraction of the cortical F-actin cytoskeleton; and 3) localized, microtubule-dependent suppression of actomyosin-based contraction can control the direction of cortical flow. We discuss these findings in light of current models of cortical flow. PMID:10930453

  6. Models of cortical malformation--Chemical and physical.

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    Luhmann, Heiko J

    2016-02-15

    Pharmaco-resistant epilepsies, and also some neuropsychiatric disorders, are often associated with malformations in hippocampal and neocortical structures. The mechanisms leading to these cortical malformations causing an imbalance between the excitatory and inhibitory system are largely unknown. Animal models using chemical or physical manipulations reproduce different human pathologies by interfering with cell generation and neuronal migration. The model of in utero injection of methylazoxymethanol (MAM) acetate mimics periventricular nodular heterotopia. The freeze lesion model reproduces (poly)microgyria, focal heterotopia and schizencephaly. The in utero irradiation model causes microgyria and heterotopia. Intraperitoneal injections of carmustine 1-3-bis-chloroethyl-nitrosurea (BCNU) to pregnant rats produces laminar disorganization, heterotopias and cytomegalic neurons. The ibotenic acid model induces focal cortical malformations, which resemble human microgyria and ulegyria. Cortical dysplasia can be also observed following prenatal exposure to ethanol, cocaine or antiepileptic drugs. All these models of cortical malformations are characterized by a pronounced hyperexcitability, few of them also produce spontaneous epileptic seizures. This dysfunction results from an impairment in GABAergic inhibition and/or an increase in glutamatergic synaptic transmission. The cortical region initiating or contributing to this hyperexcitability may not necessarily correspond to the site of the focal malformation. In some models wide-spread molecular and functional changes can be observed in remote regions of the brain, where they cause pathophysiological activities. This paper gives an overview on different animal models of cortical malformations, which are mostly used in rodents and which mimic the pathology and to some extent the pathophysiology of neuronal migration disorders associated with epilepsy in humans.

  7. In vivo models of cortical acquired epilepsy

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    Chauvette, Sylvain; Soltani, Sara; Seigneur, Josée; Timofeev, Igor

    2015-01-01

    The neocortex is the site of origin of several forms of acquired epilepsy. Here we provide a brief review of experimental models that were recently developed to study neocortical epileptogenesis as well as some major results obtained with these methods. Most of neocortical seizures appear to be nocturnal and it is known that neuronal activities reveal high levels of synchrony during slow-wave sleep. Therefore, we start the review with a description of mechanisms of neuronal synchronization and major forms of synchronized normal and pathological activities. Then, we describe three experimental models of seizures and epileptogenesis: ketamine-xylazine anesthesia as feline seizure triggered factor, cortical undercut as cortical penetrating wound model and neocortical kindling. Besides specific technical details describing these models we also provide major features of pathological brain activities recorded during epileptogenesis and seizures. The most common feature of all models of neocortical epileptogenesis is the increased duration of network silent states that up-regulates neuronal excitability and eventually leads to epilepsy. PMID:26343530

  8. In vivo models of cortical acquired epilepsy.

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    Chauvette, Sylvain; Soltani, Sara; Seigneur, Josée; Timofeev, Igor

    2016-02-15

    The neocortex is the site of origin of several forms of acquired epilepsy. Here we provide a brief review of experimental models that were recently developed to study neocortical epileptogenesis as well as some major results obtained with these methods. Most of neocortical seizures appear to be nocturnal and it is known that neuronal activities reveal high levels of synchrony during slow-wave sleep. Therefore, we start the review with a description of mechanisms of neuronal synchronization and major forms of synchronized normal and pathological activities. Then, we describe three experimental models of seizures and epileptogenesis: ketamine-xylazine anesthesia as feline seizure triggered factor, cortical undercut as cortical penetrating wound model and neocortical kindling. Besides specific technical details describing these models we also provide major features of pathological brain activities recorded during epileptogenesis and seizures. The most common feature of all models of neocortical epileptogenesis is the increased duration of network silent states that up-regulates neuronal excitability and eventually leads to epilepsy.

  9. Modelling Human Cortical Network in Real Brain Space

    Institute of Scientific and Technical Information of China (English)

    ZHAO Qing-Bai; FENG Hong-Bo; TANG Yi-Yuan

    2007-01-01

    Highly specific structural organization is of great significance in the topology of cortical networks.We introduce a human cortical network model.taking the specific cortical structure into account,in which nodes are brain sites placed in the actual positions of cerebral cortex and the establishment of edges depends on the spatial path length rather than the linear distance.The resulting network exhibits the essential features of cortical connectivity,properties of small-world networks and multiple clusters structure.Additionally.assortative mixing is also found in this roodel.All of these findings may be attributed to the spedtic cortical architecture.

  10. Electrophysiological Data and the Biophysical Modelling of Local Cortical Circuits

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    Dimitris Pinotsis

    2014-03-01

    empirical MEG data and looked for potential determinants of the spectral properties of an individual's gamma response, and how they relate to underlying visual cortex microcircuitry and excitation/inhibition balance. We found correlations between peak gamma frequency and cortical inhibition (parameterized by the excitatory drive to inhibitory cell populations over subjects. This constitutes a compelling illustration of how non-invasive data can provide quantitative estimates of the spatial properties of neural sources and explain systematic variations in the dynamics those sources generate. Furthermore, the conclusions fitted comfortably with studies of contextual interactions and orientation discrimination suggesting that local contextual interactions in V1 are weaker in individuals with a large V1 area [13, 14]. Finally, we will use dynamic causal modeling and neural fields to test specific hypotheses about precision and gain control based on predictive coding formulations of neuronal processing. We exploited finely sampled electrophysiological responses from awake-behaving monkeys and an experimental manipulation (the contrast of visual stimuli to look at changes in the gain and balance of excitatory and inhibitory influences. Our results suggest that increasing contrast effectively increases the sensitivity or gain of superficial pyramidal cells to inputs from spiny stellate populations. Furthermore, they are consistent with intriguing results showing that the receptive fields of V1 units shrinks with increasing visual contrast. The approach we will illustrate in this paper rests on neural field models that are optimized in relation to observed gamma responses from the visual cortex and are – crucially – compared in terms of their evidence. This provides a principled way to address questions about cortical structure, function and the architectures that underlie neuronal computations.

  11. Lateral thinking, from the Hopfield model to cortical dynamics.

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    Akrami, Athena; Russo, Eleonora; Treves, Alessandro

    2012-01-24

    Self-organizing attractor networks may comprise the building blocks for cortical dynamics, providing the basic operations of categorization, including analog-to-digital conversion, association and auto-association, which are then expressed as components of distinct cognitive functions depending on the contents of the neural codes in each region. To assess the viability of this scenario, we first review how a local cortical patch may be modeled as an attractor network, in which memory representations are not artificially stored as prescribed binary patterns of activity as in the Hopfield model, but self-organize as continuously graded patterns induced by afferent input. Recordings in macaques indicate that such cortical attractor networks may express retrieval dynamics over cognitively plausible rapid time scales, shorter than those dominated by neuronal fatigue. A cortical network encompassing many local attractor networks, and incorporating a realistic description of adaptation dynamics, may be captured by a Potts model. This network model has the capacity to engage long-range associations into sustained iterative attractor dynamics at a cortical scale, in what may be regarded as a mathematical model of spontaneous lateral thought. This article is part of a Special Issue entitled: Neural Coding.

  12. Influence of wiring cost on the large-scale architecture of human cortical connectivity.

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    Samu, David; Seth, Anil K; Nowotny, Thomas

    2014-04-01

    In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained ('random'), connection length preserving ('spatial'), and connection length optimised ('reduced') surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast

  13. Influence of wiring cost on the large-scale architecture of human cortical connectivity.

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    David Samu

    2014-04-01

    Full Text Available In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained ('random', connection length preserving ('spatial', and connection length optimised ('reduced' surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints

  14. A large scale simulation of excitation propagation in layer 2/3 of primary and secondary visual cortices of mice.

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    Ohtsu, Shoya; Nomura, Taishin; Uno, Shota; Maeda, Kazuki; Hayashida, Yuki; Yagi, Tetsuya

    2015-01-01

    Analyzing network architecture and spatio-temporal dynamics of the visual cortical areas can facilitate understanding visual information processing in the brain. Recently, several physiological experiments utilizing the fast in-vivo imaging technique have demonstrated that the primary visual cortex (V1) and the secondary visual cortex (V2) in mice exhibit complex properties of the responses to visual and electrical stimuli. In order to provide a tool for quantitatively analyzing such a complex dynamics of the cortices at the level of neurons and circuits, here, we constructed a physiologically plausible large-scale network model of the layers 2/3 of V1 and V2, composed of 14,056 multi-compartment neuron models. The Message-Passing-Interface-based parallel simulations of our network model were able to reproduce, at least quantitatively, the neural responses experimentally observed in mouse V1 and V2 with the voltage-sensitive dye imaging.

  15. Spatiotemporal receptive fields: a dynamical model derived from cortical architectonics.

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    Krone, G; Mallot, H; Palm, G; Schüz, A

    1986-01-22

    We assume that the mammalian neocortex is built up out of some six layers which differ in their morphology and their external connections. Intrinsic connectivity is largely excitatory, leading to a considerable amount of positive feedback. The majority of cortical neurons can be divided into two main classes: the pyramidal cells, which are said to be excitatory, and local cells (most notably the non-spiny stellate cells), which are said to be inhibitory. The form of the dendritic and axonal arborizations of both groups is discussed in detail. This results in a simplified model of the cortex as a stack of six layers with mutual connections determined by the principles of fibre anatomy. This stack can be treated as a multi-input-multi-output system by means of the linear systems theory of homogeneous layers. The detailed equations for the simulation are derived in the Appendix. The results of the simulations show that the temporal and spatial behaviour of an excitation distribution cannot be treated separately. Further, they indicate specific processing in the different layers and some independence from details of wiring. Finally, the simulation results are applied to the theory of visual receptive fields. This yields some insight into the mechanisms possibly underlying hypercomplexity, putative nonlinearities, lateral inhibition, oscillating cell responses, and velocity-dependent tuning curves.

  16. Self-organizing model of motor cortical activities during drawing

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    Lin, Siming H.; Si, Jennie; Schwartz, Andrew B.

    1996-05-01

    The population vector algorithm has been developed to combine the simultaneous direction- related activities of a population of motor cortical neurons to predict the trajectory of the arm movement. In our study, we consider a self-organizing model of a neural representation of the arm trajectory based on neuronal discharge rates. Self-organizing feature mapping (SOFM) is used to select the optimal set of weights in the model to determine the contribution of individual neuron to the overall movement. The correspondence between the movement directions and the discharge patterns of the motor cortical neurons is established in the output map. The topology preserving property of the SOFM is used to analyze real recorded data of a behavior monkey. The data used in this analysis were taken while the monkey was drawing spirals and doing the center out movement. Using such a statistical model, the monkey's arm moving directions could be well predicted based on the motor cortex neuronal firing information.

  17. Dampened hippocampal oscillations and enhanced spindle activity in an asymptomatic model of developmental cortical malformations

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    Cid, Elena; Gomez-Dominguez, Daniel; Martin-Lopez, David; Gal, Beatriz; Laurent, François; Ibarz, Jose M.; Francis, Fiona; Menendez de la Prida, Liset

    2014-01-01

    Developmental cortical malformations comprise a large spectrum of histopathological brain abnormalities and syndromes. Their genetic, developmental and clinical complexity suggests they should be better understood in terms of the complementary action of independently timed perturbations (i.e., the multiple-hit hypothesis). However, understanding the underlying biological processes remains puzzling. Here we induced developmental cortical malformations in offspring, after intraventricular injection of methylazoxymethanol (MAM) in utero in mice. We combined extensive histological and electrophysiological studies to characterize the model. We found that MAM injections at E14 and E15 induced a range of cortical and hippocampal malformations resembling histological alterations of specific genetic mutations and transplacental mitotoxic agent injections. However, in contrast to most of these models, intraventricularly MAM-injected mice remained asymptomatic and showed no clear epilepsy-related phenotype as tested in long-term chronic recordings and with pharmacological manipulations. Instead, they exhibited a non-specific reduction of hippocampal-related brain oscillations (mostly in CA1); including theta, gamma and HFOs; and enhanced thalamocortical spindle activity during non-REM sleep. These data suggest that developmental cortical malformations do not necessarily correlate with epileptiform activity. We propose that the intraventricular in utero MAM approach exhibiting a range of rhythmopathies is a suitable model for multiple-hit studies of associated neurological disorders. PMID:24782720

  18. Dampened hippocampal oscillations and enhanced spindle activity in an asymptomatic model of developmental cortical malformations

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    Elena eCid

    2014-04-01

    Full Text Available Developmental cortical malformations comprise a large spectrum of histopathological brain abnormalities and syndromes. Their genetic, developmental and clinical complexity suggests they should be better understood in terms of the complementary action of independently timed perturbations (i.e. the multiple-hit hypothesis. However, understanding the underlying biological processes remains puzzling. Here we induced developmental cortical malformations in offspring, after intraventricular injection of methylazoxymethanol (MAM in utero in mice. We combined extensive histological and electrophysiological studies to characterize the model. We found that MAM injections at E14 and E15 induced a range of cortical and hippocampal malformations resembling histological alterations of specific genetic mutations and transplacental mitotoxic agent injections. However, in contrast to most of these models, intraventricularly MAM-injected mice remained asymptomatic and showed no clear epilepsy-related phenotype as tested in long-term chronic recordings and with pharmacological manipulations. Instead, they exhibited a non-specific reduction of hippocampal-related brain oscillations (mostly in CA1; including theta, gamma and HFOs; and enhanced thalamocortical spindle activity during non-REM sleep. These data suggest that developmental cortical malformations do not necessarily correlate with epileptiform activity. We propose that the intraventricular in utero MAM approach exhibiting a range of rhythmopathies is a suitable model for multiple-hit studies of associated neurological disorders.

  19. Cortical factor feedback model for cellular locomotion and cytofission.

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    Shin I Nishimura

    2009-03-01

    Full Text Available Eukaryotic cells can move spontaneously without being guided by external cues. For such spontaneous movements, a variety of different modes have been observed, including the amoeboid-like locomotion with protrusion of multiple pseudopods, the keratocyte-like locomotion with a widely spread lamellipodium, cell division with two daughter cells crawling in opposite directions, and fragmentations of a cell to multiple pieces. Mutagenesis studies have revealed that cells exhibit these modes depending on which genes are deficient, suggesting that seemingly different modes are the manifestation of a common mechanism to regulate cell motion. In this paper, we propose a hypothesis that the positive feedback mechanism working through the inhomogeneous distribution of regulatory proteins underlies this variety of cell locomotion and cytofission. In this hypothesis, a set of regulatory proteins, which we call cortical factors, suppress actin polymerization. These suppressing factors are diluted at the extending front and accumulated at the retracting rear of cell, which establishes a cellular polarity and enhances the cell motility, leading to the further accumulation of cortical factors at the rear. Stochastic simulation of cell movement shows that the positive feedback mechanism of cortical factors stabilizes or destabilizes modes of movement and determines the cell migration pattern. The model predicts that the pattern is selected by changing the rate of formation of the actin-filament network or the threshold to initiate the network formation.

  20. Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly.

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    Liem, Franziskus; Mérillat, Susan; Bezzola, Ladina; Hirsiger, Sarah; Philipp, Michel; Madhyastha, Tara; Jäncke, Lutz

    2015-03-01

    FreeSurfer is a tool to quantify cortical and subcortical brain anatomy automatically and noninvasively. Previous studies have reported reliability and statistical power analyses in relatively small samples or only selected one aspect of brain anatomy. Here, we investigated reliability and statistical power of cortical thickness, surface area, volume, and the volume of subcortical structures in a large sample (N=189) of healthy elderly subjects (64+ years). Reliability (intraclass correlation coefficient) of cortical and subcortical parameters is generally high (cortical: ICCs>0.87, subcortical: ICCs>0.95). Surface-based smoothing increases reliability of cortical thickness maps, while it decreases reliability of cortical surface area and volume. Nevertheless, statistical power of all measures benefits from smoothing. When aiming to detect a 10% difference between groups, the number of subjects required to test effects with sufficient power over the entire cortex varies between cortical measures (cortical thickness: N=39, surface area: N=21, volume: N=81; 10mm smoothing, power=0.8, α=0.05). For subcortical regions this number is between 16 and 76 subjects, depending on the region. We also demonstrate the advantage of within-subject designs over between-subject designs. Furthermore, we publicly provide a tool that allows researchers to perform a priori power analysis and sensitivity analysis to help evaluate previously published studies and to design future studies with sufficient statistical power.

  1. Optogenetic stimulation of a meso-scale human cortical model

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    Selvaraj, Prashanth; Szeri, Andrew; Sleigh, Jamie; Kirsch, Heidi

    2015-03-01

    Neurological phenomena like sleep and seizures depend not only on the activity of individual neurons, but on the dynamics of neuron populations as well. Meso-scale models of cortical activity provide a means to study neural dynamics at the level of neuron populations. Additionally, they offer a safe and economical way to test the effects and efficacy of stimulation techniques on the dynamics of the cortex. Here, we use a physiologically relevant meso-scale model of the cortex to study the hypersynchronous activity of neuron populations during epileptic seizures. The model consists of a set of stochastic, highly non-linear partial differential equations. Next, we use optogenetic stimulation to control seizures in a hyperexcited cortex, and to induce seizures in a normally functioning cortex. The high spatial and temporal resolution this method offers makes a strong case for the use of optogenetics in treating meso scale cortical disorders such as epileptic seizures. We use bifurcation analysis to investigate the effect of optogenetic stimulation in the meso scale model, and its efficacy in suppressing the non-linear dynamics of seizures.

  2. Columnar architecture improves noise robustness in a model cortical network.

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    Paul C Bush

    Full Text Available Cortical columnar architecture was discovered decades ago yet there is no agreed upon explanation for its function. Indeed, some have suggested that it has no function, it is simply an epiphenomenon of developmental processes. To investigate this problem we have constructed a computer model of one square millimeter of layer 2/3 of the primary visual cortex (V1 of the cat. Model cells are connected according to data from recent paired cell studies, in particular the connection probability between pyramidal cells is inversely proportional both to the distance separating the cells and to the distance between the preferred parameters (features of the cells. We find that these constraints, together with a columnar architecture, produce more tightly clustered populations of cells when compared to the random architecture seen in, for example, rodents. This causes the columnar network to converge more quickly and accurately on the pattern representing a particular stimulus in the presence of noise, suggesting that columnar connectivity functions to improve pattern recognition in cortical circuits. The model also suggests that synaptic failure, a phenomenon exhibited by weak synapses, may conserve metabolic resources by reducing transmitter release at these connections that do not contribute to network function.

  3. Altered Cortical Ensembles in Mouse Models of Schizophrenia.

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    Hamm, Jordan P; Peterka, Darcy S; Gogos, Joseph A; Yuste, Rafael

    2017-04-05

    In schizophrenia, brain-wide alterations have been identified at the molecular and cellular levels, yet how these phenomena affect cortical circuit activity remains unclear. We studied two mouse models of schizophrenia-relevant disease processes: chronic ketamine (KET) administration and Df(16)A(+/-), modeling 22q11.2 microdeletions, a genetic variant highly penetrant for schizophrenia. Local field potential recordings in visual cortex confirmed gamma-band abnormalities similar to patient studies. Two-photon calcium imaging of local cortical populations revealed in both models a deficit in the reliability of neuronal coactivity patterns (ensembles), which was not a simple consequence of altered single-neuron activity. This effect was present in ongoing and sensory-evoked activity and was not replicated by acute ketamine administration or pharmacogenetic parvalbumin-interneuron suppression. These results are consistent with the hypothesis that schizophrenia is an "attractor" disease and demonstrate that degraded neuronal ensembles are a common consequence of diverse genetic, cellular, and synaptic alterations seen in chronic schizophrenia. Published by Elsevier Inc.

  4. Differences in human cortical gene expression match the temporal properties of large-scale functional networks.

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    Claudia Cioli

    Full Text Available We explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas. Previous work suggests that functional cortical networks (resting state and task based are organized as two large networks (differentiated by their preferred information processing mode shaped like two rings. The first ring--Visual-Sensorimotor-Auditory (VSA--comprises visual, auditory, somatosensory, and motor cortices that process real time world interactions. The second ring--Parieto-Temporo-Frontal (PTF--comprises parietal, temporal, and frontal regions with networks dedicated to cognitive functions, emotions, biological needs, and internally driven rhythms. We found--with correspondence analysis--that the patterns of expression of the 938 genes most differentially expressed across the cortex organized the cortex into two sets of regions that match the two rings. We confirmed this result using discriminant correspondence analysis by showing that the genetic profiles of cortical regions can reliably predict to what ring these regions belong. We found that several of the proteins--coded by genes that most differentiate the rings--were involved in neuronal information processing such as ionic channels and neurotransmitter release. The systematic study of families of genes revealed specific proteins within families preferentially expressed in each ring. The results showed strong congruence between the preferential expression of subsets of genes, temporal properties of the proteins they code, and the preferred processing modes of the rings. Ionic channels and release-related proteins more expressed in the VSA ring favor temporal precision of fast evoked neural transmission (Sodium channels SCNA1, SCNB1 potassium channel KCNA1, calcium channel CACNA2D2, Synaptotagmin SYT2, Complexin CPLX1, Synaptobrevin VAMP1. Conversely, genes expressed in the PTF ring favor slower, sustained, or rhythmic activation (Sodium

  5. Cortical oscillatory dynamics in a social interaction model.

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    Knyazev, Gennady G; Slobodskoj-Plusnin, Jaroslav Y; Bocharov, Andrey V; Pylkova, Liudmila V

    2013-03-15

    In this study we sought to investigate cortical oscillatory dynamics accompanying three major kinds of social behavior: aggressive, friendly, and avoidant. Behavioral and EEG data were collected in 48 participants during a computer game modeling social interactions with virtual 'persons'. 3D source reconstruction and independent component analysis were applied to EEG data. Results showed that social behavior was partly reactive and partly proactive with subject's personality playing an important role in shaping this behavior. Most salient differences were found between avoidance and approach behaviors, whereas the two kinds of approach behavior (i.e., aggression and friendship) did not differ from each other. Comparative to avoidance, approach behaviors were associated with higher induced responses in most frequency bands which were mostly observed in cortical areas overlapping with the default mode network. The difference between approach- and avoidance-related oscillatory dynamics was more salient in subjects predisposed to approach behaviors (i.e., in aggressive or sociable subjects) and was less pronounced in subjects predisposed to avoidance behavior (i.e., in high trait anxiety scorers). There was a trend to higher low frequency phase-locking in motor area in approach than in avoid condition. Results are discussed in light of the concept linking induced responses with top-down and evoked responses with bottom-up processes. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. Does the presence of tumor-induced cortical bone destruction at CT have any prognostic value in newly diagnosed diffuse large B-cell lymphoma?

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    Adams, Hugo J.A.; Nievelstein, Rutger A.J.; Kwee, Thomas C. [University Medical Center Utrecht, Department of Radiology and Nuclear Medicine, Utrecht (Netherlands); Klerk, John M.H. de [Meander Medical Center, Department of Nuclear Medicine, Amersfoort (Netherlands); Fijnheer, Rob [Meander Medical Center, Department of Hematology, Amersfoort (Netherlands); Heggelman, Ben G.F. [Meander Medical Center, Department of Radiology, Amersfoort (Netherlands); Dubois, Stefan V. [Meander Medical Center, Department of Pathology, Amersfoort (Netherlands)

    2015-05-01

    To determine the prognostic value of tumor-induced cortical bone destruction at computed tomography (CT) in newly diagnosed diffuse large B-cell lymphoma (DLBCL). This retrospective study included 105 patients with newly diagnosed DLBCL who had undergone CT and bone marrow biopsy (BMB) before R-CHOP (rituximab, cyclophosphamide, hydroxydaunorubicin, Oncovin, and prednisolone) chemo-immunotherapy. Cox regression analyses were used to determine the associations of cortical bone status at CT (absence vs. presence of tumor-induced cortical bone destruction), BMB findings (negative vs. positive for lymphomatous involvement), and dichotomized National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI) strata (low risk vs. high risk) with progression-free survival (PFS) and overall survival (OS). Univariate Cox regression analysis indicated that cortical bone status at CT was no significant predictor of either PFS or OS (p = 0.358 and p = 0.560, respectively), whereas BMB findings (p = 0.002 and p = 0.013, respectively) and dichotomized NCCN-IPI risk strata (p = 0.002 and p = 0.003, respectively) were significant predictors of both PFS and OS. In the multivariate Cox proportional hazards model, only the dichotomized NCCN-IPI score was an independent predictive factor of PFS and OS (p = 0.004 and p = 0.003, respectively). The presence of tumor-induced cortical bone destruction at CT was not found to have any prognostic implications in newly diagnosed DLBCL. (orig.)

  7. A Model for Cortically Mediated Behaviors: A "New Think" Model for Some Old Thought Processes.

    Science.gov (United States)

    Anderson, James A.

    A model for dealing with ordinary, cortically-mediated behaviors is presented. The model's foundation is the set of motivational systems existing in the mature organism. Construction of the model follows the stimulus-response paradigm as interpreted by recent physiological research. The purpose of the model is that it requires a multivariate…

  8. Modeling of cortical signals using echo state networks

    Science.gov (United States)

    Zhou, Hanying; Wang, Yongji; Huang, Jiangshuai

    2009-10-01

    Diverse modeling frameworks have been utilized with the ultimate goal of translating brain cortical signals into prediction of visible behavior. The inputs to these models are usually multidimensional neural recordings collected from relevant regions of a monkey's brain while the outputs are the associated behavior which is typically the 2-D or 3-D hand position of a primate. Here our task is to set up a proper model in order to figure out the move trajectories by input the neural signals which are simultaneously collected in the experiment. In this paper, we propose to use Echo State Networks (ESN) to map the neural firing activities into hand positions. ESN is a newly developed recurrent neural network(RNN) model. Besides its dynamic property and short term memory just as other recurrent neural networks have, it has a special echo state property which endows it with the ability to model nonlinear dynamic systems powerfully. What distinguished it from transitional recurrent neural networks most significantly is its special learning method. In this paper we train this net with a refined version of its typical training method and get a better model.

  9. Estimation of neural dynamics from MEG/EEG cortical current density maps: application to the reconstruction of large-scale cortical synchrony.

    Science.gov (United States)

    David, Olivier; Garnero, Line; Cosmelli, Diego; Varela, Francisco J

    2002-09-01

    There is a growing interest in elucidating the role of specific patterns of neural dynamics--such as transient synchronization between distant cell assemblies--in brain functions. Magnetoencephalography (MEG)/electroencephalography (EEG) recordings consist in the spatial integration of the activity from large and multiple remotely located populations of neurons. Massive diffusive effects and poor signal-to-noise ratio (SNR) preclude the proper estimation of indices related to cortical dynamics from nonaveraged MEG/EEG surface recordings. Source localization from MEG/EEG surface recordings with its excellent time resolution could contribute to a better understanding of the working brain. We propose a robust and original approach to the MEG/EEG distributed inverse problem to better estimate neural dynamics of cortical sources. For this, the surrogate data method is introduced in the MEG/EEG inverse problem framework. We apply this approach on nonaveraged data with poor SNR using the minimum norm estimator and find source localization results weakly sensitive to noise. Surrogates allow the reduction of the source space in order to reconstruct MEG/EEG data with reduced biases in both source localization and time-series dynamics. Monte Carlo simulations and results obtained from real MEG data indicate it is possible to estimate non invasively an important part of cortical source locations and dynamic and, therefore, to reveal brain functional networks.

  10. Cortical information flow in Parkinson's disease: a composite network/field model

    Directory of Open Access Journals (Sweden)

    Cliff C. Kerr

    2013-04-01

    Full Text Available The basal ganglia play a crucial role in the execution of movements, as demonstrated by the severe motor deficits that accompany Parkinson's disease (PD. Since motor commands originate in the cortex, an important question is how the basal ganglia influence cortical information flow, and how this influence becomes pathological in PD. To explore this, we developed a composite neuronal network/neural field model. The network model consisted of 4950 spiking neurons, divided into 15 excitatory and inhibitory cell populations in the thalamus and cortex. The field model consisted of the cortex, thalamus, striatum, subthalamic nucleus, and globus pallidus. Both models have been separately validated in previous work. Three field models were used: one with basal ganglia parameters based on data from healthy individuals, one based on data from individuals with PD, and one purely thalamocortical model. Spikes generated by these field models were then used to drive the network model. Compared to the network driven by the healthy model, the PD-driven network had lower firing rates, a shift in spectral power towards lower frequencies, and higher probability of bursting; each of these findings is consistent with empirical data on PD. In the healthy model, we found strong Granger causality in the beta and low gamma bands between cortical layers, but this was largely absent in the PD model. In particular, the reduction in Granger causality from the main "input" layer of the cortex (layer 4 to the main "output" layer (layer 5 was pronounced. This may account for symptoms of PD that seem to reflect deficits in information flow, such as bradykinesia. In general, these results demonstrate that the brain's large-scale oscillatory environment, represented here by the field model, strongly influences the information processing that occurs within its subnetworks. Hence, it may be preferable to drive spiking network models with physiologically realistic inputs rather than

  11. Mathematical approaches to modeling of cortical spreading depression

    Science.gov (United States)

    Miura, Robert M.; Huang, Huaxiong; Wylie, Jonathan J.

    2013-12-01

    Migraine with aura (MwA) is a debilitating disease that afflicts about 25%-30% of migraine sufferers. During MwA, a visual illusion propagates in the visual field, then disappears, and is followed by a sustained headache. MwA was conjectured by Lashley to be related to some neurological phenomenon. A few years later, Leão observed electrophysiological waves in the brain that are now known as cortical spreading depression (CSD). CSD waves were soon conjectured to be the neurological phenomenon underlying MwA that had been suggested by Lashley. However, the confirmation of the link between MwA and CSD was not made until 2001 by Hadjikhani et al. [Proc. Natl. Acad. Sci. U.S.A. 98, 4687-4692 (2001)] using functional MRI techniques. Despite the fact that CSD has been studied continuously since its discovery in 1944, our detailed understandings of the interactions between the mechanisms underlying CSD waves have remained elusive. The connection between MwA and CSD makes the understanding of CSD even more compelling and urgent. In addition to all of the information gleaned from the many experimental studies on CSD since its discovery, mathematical modeling studies provide a general and in some sense more precise alternative method for exploring a variety of mechanisms, which may be important to develop a comprehensive picture of the diverse mechanisms leading to CSD wave instigation and propagation. Some of the mechanisms that are believed to be important include ion diffusion, membrane ionic currents, osmotic effects, spatial buffering, neurotransmitter substances, gap junctions, metabolic pumps, and synaptic connections. Discrete and continuum models of CSD consist of coupled nonlinear differential equations for the ion concentrations. In this review of the current quantitative understanding of CSD, we focus on these modeling paradigms and various mechanisms that are felt to be important for CSD.

  12. Modeling Pediatric Brain Trauma: Piglet Model of Controlled Cortical Impact.

    Science.gov (United States)

    Pareja, Jennifer C Munoz; Keeley, Kristen; Duhaime, Ann-Christine; Dodge, Carter P

    2016-01-01

    The brain has different responses to traumatic injury as a function of its developmental stage. As a model of injury to the immature brain, the piglet shares numerous similarities in regards to morphology and neurodevelopmental sequence compared to humans. This chapter describes a piglet scaled focal contusion model of traumatic brain injury that accounts for the changes in mass and morphology of the brain as it matures, facilitating the study of age-dependent differences in response to a comparable mechanical trauma.

  13. CNTF-Treated Astrocyte Conditioned Medium Enhances Large-Conductance Calcium-Activated Potassium Channel Activity in Rat Cortical Neurons.

    Science.gov (United States)

    Sun, Meiqun; Liu, Hongli; Xu, Huanbai; Wang, Hongtao; Wang, Xiaojing

    2016-08-01

    Seizure activity is linked to astrocyte activation as well as dysfunctional cortical neuron excitability produced from changes in calcium-activated potassium (KCa) channel function. Ciliary neurotrophic factor-treated astrocyte conditioned medium (CNTF-ACM) can be used to investigate the peripheral effects of activated astrocytes upon cortical neurons. However, CNTF-ACM's effect upon KCa channel activity in cultured cortical neurons has not yet been investigated. Whole-cell patch clamp recordings were performed in rat cortical neurons to evaluate CNTF-ACM's effects upon charybdotoxin-sensitive large-conductance KCa (BK) channel currents and apamin-sensitive small-conductance KCa (SK) channel current. Biotinylation and RT-PCR were applied to assess CNTF-ACM's effects upon the protein and mRNA expression, respectively, of the SK channel subunits SK2 and SK3 and the BK channel subunits BKα1 and BKβ3. An anti-fibroblast growth factor-2 (FGF-2) monoclonal neutralizing antibody was used to assess the effects of the FGF-2 component of CNTF-ACM. CNTF-ACM significantly increased KCa channel current density, which was predominantly attributable to gains in BK channel activity (p ACM produced a significant increase in BKα1 and BKβ3 expression (p  0.05). Blocking FGF-2 produced significant reductions in KCa channel current density (p > 0.05) as well as BKα1 and BKβ3 expression in CNTF-ACM-treated neurons (p > 0.05). CNTF-ACM significantly enhances BK channel activity in rat cortical neurons and that FGF-2 is partially responsible for these effects. CNTF-induced astrocyte activation results in secretion of neuroactive factors which may affect neuronal excitability and resultant seizure activity in mammalian cortical neurons.

  14. Complement inhibition and statins prevent fetal brain cortical abnormalities in a mouse model of preterm birth.

    Science.gov (United States)

    Pedroni, Silvia M A; Gonzalez, Juan M; Wade, Jean; Jansen, Maurits A; Serio, Andrea; Marshall, Ian; Lennen, Ross J; Girardi, Guillermina

    2014-01-01

    Premature babies are particularly vulnerable to brain injury. In this study we focus on cortical brain damage associated with long-term cognitive, behavioral, attentional or socialization deficits in children born preterm. Using a mouse model of preterm birth (PTB), we demonstrated that complement component C5a contributes to fetal cortical brain injury. Disruption of cortical dendritic and axonal cytoarchitecture was observed in PTB-mice. Fetuses deficient in C5aR (-/-) did not show cortical brain damage. Treatment with antibody anti-C5, that prevents generation of C5a, also prevented cortical fetal brain injury in PTB-mice. C5a also showed a detrimental effect on fetal cortical neuron development and survival in vitro. Increased glutamate release was observed in cortical neurons in culture exposed to C5a. Blockade of C5aR prevented glutamate increase and restored neurons dendritic and axonal growth and survival. Similarly, increased glutamate levels - measured by (1)HMRS - were observed in vivo in PTB-fetuses compared to age-matched controls. The blockade of glutamate receptors prevented C5a-induced abnormal growth and increased cell death in isolated fetal cortical neurons. Simvastatin and pravastatin prevented cortical fetal brain developmental and metabolic abnormalities -in vivo and in vitro. Neuroprotective effects of statins were mediated by Akt/PKB signaling pathways. This study shows that complement activation plays a crucial role in cortical fetal brain injury in PTL and suggests that complement inhibitors and statins might be good therapeutic options to improve neonatal outcomes in preterm birth. © 2013.

  15. Estimation of cortical connectivity from EEG using state-space models.

    Science.gov (United States)

    Cheung, Bing Leung Patrick; Riedner, Brady Alexander; Tononi, Giulio; Van Veen, Barry D

    2010-09-01

    A state-space formulation is introduced for estimating multivariate autoregressive (MVAR) models of cortical connectivity from noisy, scalp-recorded EEG. A state equation represents the MVAR model of cortical dynamics, while an observation equation describes the physics relating the cortical signals to the measured EEG and the presence of spatially correlated noise. We assume that the cortical signals originate from known regions of cortex, but the spatial distribution of activity within each region is unknown. An expectation-maximization algorithm is developed to directly estimate the MVAR model parameters, the spatial activity distribution components, and the spatial covariance matrix of the noise from the measured EEG. Simulation and analysis demonstrate that this integrated approach is less sensitive to noise than two-stage approaches in which the cortical signals are first estimated from EEG measurements, and next, an MVAR model is fit to the estimated cortical signals. The method is further demonstrated by estimating conditional Granger causality using EEG data collected while subjects passively watch a movie.

  16. Synapse-Centric Mapping of Cortical Models to the SpiNNaker Neuromorphic Architecture.

    Science.gov (United States)

    Knight, James C; Furber, Steve B

    2016-01-01

    While the adult human brain has approximately 8.8 × 10(10) neurons, this number is dwarfed by its 1 × 10(15) synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows 4× more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously.

  17. Synapse-centric mapping of cortical models to the SpiNNaker neuromorphic architecture

    Directory of Open Access Journals (Sweden)

    James Courtney Knight

    2016-09-01

    Full Text Available While the adult human brain has approximately 8.8x10^10 neurons, this number is dwarfed by its 1x10^15 synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously.

  18. Cortical stimulation and tooth pulp evoked potentials in rats: a model of direct anti-nociception.

    Science.gov (United States)

    Rusina, Robert; Barek, Stephane; Vaculin, Simon; Azérad, Jean; Rokyta, Richard

    2010-01-01

    While the effect of cortex stimulation on pain control is widely accepted, its physiological basis remains poorly understood. We chose an animal model of pain to study the influence of sensorimotor cortex stimulation on tooth pulp stimulation evoked potentials (TPEPs). Fifteen awake rats implanted with tooth pulp, cerebral cortex, and digastric muscle electrodes were divided into three groups, receiving 60 Hz, 40 Hz and no cortical stimulation, respectively. TPEPs were recorded before, one, three and five hours after continuous stimulation. We observed an inverse relationship between TPEP amplitude and latency with increasing tooth pulp stimulation. The amplitudes of the early components of TPEPs increased and their latency decreased with increasing tooth pulp stimulation intensity. Cortical stimulation decreased the amplitude of TPEPs; however, neither the latencies of TPEPs nor the jaw-opening reflex were changed after cortical stimulation. The decrease in amplitude of TPEPs after cortical stimulation may reflect its anti-nociceptive effect.

  19. Large Unifying Hybrid Supernetwork Model

    Institute of Scientific and Technical Information of China (English)

    LIU; Qiang; FANG; Jin-qing; LI; Yong

    2015-01-01

    For depicting multi-hybrid process,large unifying hybrid network model(so called LUHNM)has two sub-hybrid ratios except dr.They are deterministic hybrid ratio(so called fd)and random hybrid ratio(so called gr),respectively.

  20. Large N Expansion. Vector Models

    CERN Document Server

    Nissimov, E; Nissimov, Emil; Pacheva, Svetlana

    2006-01-01

    Preliminary version of a contribution to the "Quantum Field Theory. Non-Perturbative QFT" topical area of "Modern Encyclopedia of Mathematical Physics" (SELECTA), eds. Aref'eva I, and Sternheimer D, Springer (2007). Consists of two parts - "main article" (Large N Expansion. Vector Models) and a "brief article" (BPHZL Renormalization).

  1. A Computational Growth Model for Measuring Dynamic Cortical Development in the First Year of Life

    Science.gov (United States)

    Nie, Jingxin; Li, Gang; Wang, Li; Gilmore, John H.; Lin, Weili

    2012-01-01

    Human cerebral cortex develops extremely fast in the first year of life. Quantitative measurement of cortical development during this early stage plays an important role in revealing the relationship between cortical structural and high-level functional development. This paper presents a computational growth model to simulate the dynamic development of the cerebral cortex from birth to 1 year old by modeling the cerebral cortex as a deformable elastoplasticity surface driven via a growth model. To achieve a high accuracy, a guidance model is also incorporated to estimate the growth parameters and cortical shapes at later developmental stages. The proposed growth model has been applied to 10 healthy subjects with longitudinal brain MR images acquired at every 3 months from birth to 1 year old. The experimental results show that our proposed method can capture the dynamic developmental process of the cortex, with the average surface distance error smaller than 0.6 mm compared with the ground truth surfaces, and the results also show that 1) the curvedness and sharpness decrease from 2 weeks to 12 months and 2) the frontal lobe shows rapidly increasing cortical folding during this period, with relatively slower increase of the cortical folding in the occipital and parietal lobes. PMID:22047969

  2. Resistor mesh model of a spherical head: part 2: a review of applications to cortical mapping.

    Science.gov (United States)

    Chauveau, N; Morucci, J P; Franceries, X; Celsis, P; Rigaud, B

    2005-11-01

    A resistor mesh model (RMM) has been validated with reference to the analytical model by consideration of a set of four dipoles close to the cortex. The application of the RMM to scalp potential interpolation was detailed in Part 1. Using the RMM and the same four dipoles, the different methods of cortical mapping were compared and have shown the potentiality of this RMM for obtaining current and potential cortical distributions. The lead-field matrices are well-adapted tools, but the use of a square matrix of high dimension does not permit the inverse solution to be improved in the presence of noise, as a regularisation technique is necessary with noisy data. With the RMM, the transfer matrix and the cortical imaging technique proved to be easy to implement. Further development of the RMM will include application to more realistic head models with more accurate conductivities.

  3. A thalamo-cortical neural mass model for the simulation of brain rhythms during sleep.

    Science.gov (United States)

    Cona, F; Lacanna, M; Ursino, M

    2014-08-01

    Cortico-thalamic interactions are known to play a pivotal role in many brain phenomena, including sleep, attention, memory consolidation and rhythm generation. Hence, simple mathematical models that can simulate the dialogue between the cortex and the thalamus, at a mesoscopic level, have a great cognitive value. In the present work we describe a neural mass model of a cortico-thalamic module, based on neurophysiological mechanisms. The model includes two thalamic populations (a thalamo-cortical relay cell population, TCR, and its related thalamic reticular nucleus, TRN), and a cortical column consisting of four connected populations (pyramidal neurons, excitatory interneurons, inhibitory interneurons with slow and fast kinetics). Moreover, thalamic neurons exhibit two firing modes: bursting and tonic. Finally, cortical synapses among pyramidal neurons incorporate a disfacilitation mechanism following prolonged activity. Simulations show that the model is able to mimic the different patterns of rhythmic activity in cortical and thalamic neurons (beta and alpha waves, spindles, delta waves, K-complexes, slow sleep waves) and their progressive changes from wakefulness to deep sleep, by just acting on modulatory inputs. Moreover, simulations performed by providing short sensory inputs to the TCR show that brain rhythms during sleep preserve the cortex from external perturbations, still allowing a high cortical activity necessary to drive synaptic plasticity and memory consolidation. In perspective, the present model may be used within larger cortico-thalamic networks, to gain a deeper understanding of mechanisms beneath synaptic changes during sleep, to investigate the specific role of brain rhythms, and to explore cortical synchronization achieved via thalamic influences.

  4. A new cortical thickness mapping method with application to an in vivo finite element model.

    Science.gov (United States)

    Kim, Young Ho; Kim, Jong-Eun; Eberhardt, Alan W

    2014-01-01

    Finite element modelling of musculoskeletal systems, with geometrical structures constructed from computed tomography (CT) scans, is a useful and powerful tool for biomechanical studies. The use of CT scans from living human subjects, however, is still limited. Accurate reconstruction of thin cortical bone structures from CT scans of living human subjects is especially problematic, due to low CT resolution that results from mandatory low radiation doses and/or involuntary movements of the subject. In this study, a new method for mapping cortical thickness is described. Using the method, cortical thickness measurements of a coxal (pelvis) bone obtained from CT scans of a cadaver were mapped to the coxal geometry as obtained through CT scans of a live human subject, resulting in accurate cortical thickness while maintaining geometric fidelity of the live subject. The mapping procedure includes shape-preserving parameterisation, mesh movement and interpolation of thickness using a search algorithm. The methodology is applicable to modelling of other bones where accurate cortical thickness is needed and for which such data exist.

  5. Neural network models for spatial data mining, map production, and cortical direction selectivity

    Science.gov (United States)

    Parsons, Olga

    A family of ARTMAP neural networks for incremental supervised learning has been developed over the last decade. The Sensor Exploitation Group of MIT Lincoln Laboratory (LL) has incorporated an early version of this network as the recognition engine of a hierarchical system for fusion and data mining of multiple registered geospatial images. The LL system has been successfully fielded, but it is limited to target vs. non-target identifications and does not produce whole maps. This dissertation expands the capabilities of the LL system so that it learns to identify arbitrarily many target classes at once and can thus produce a whole map. This new spatial data mining system is designed particularly to cope with the highly skewed class distributions of typical mapping problems. Specification of a consistent procedure and a benchmark testbed has permitted the evaluation of candidate recognition networks as well as pre- and post-processing and feature extraction options. The resulting default ARTMAP network and mapping methodology set a standard for a variety of related mapping problems and application domains. The second part of the dissertation investigates the development of cortical direction selectivity. The possible role of visual experience and oculomotor behavior in the maturation of cells in the primary visual cortex is studied. The responses of neurons in the thalamus and cortex of the cat are modeled when natural scenes are scanned by several types of eye movements. Inspired by the Hebbian-like synaptic plasticity, which is based upon correlations between cell activations, the second-order statistical structure of thalamo-cortical activity is examined. In the simulations, patterns of neural activity that lead to a correct refinement of cell responses are observed during visual fixation, when small ocular movements occur, but are not observed in the presence of large saccades. Simulations also replicate experiments in which kittens are reared under stroboscopic

  6. Cortico-cortical communication dynamics

    Directory of Open Access Journals (Sweden)

    Per E Roland

    2014-05-01

    Full Text Available IIn principle, cortico-cortical communication dynamics is simple: neurons in one cortical area communicate by sending action potentials that release glutamate and excite their target neurons in other cortical areas. In practice, knowledge about cortico-cortical communication dynamics is minute. One reason is that no current technique can capture the fast spatio-temporal cortico-cortical evolution of action potential transmission and membrane conductances with sufficient spatial resolution. A combination of optogenetics and monosynaptic tracing with virus can reveal the spatio-temporal cortico-cortical dynamics of specific neurons and their targets, but does not reveal how the dynamics evolves under natural conditions. Spontaneous ongoing action potentials also spread across cortical areas and are difficult to separate from structured evoked and intrinsic brain activity such as thinking. At a certain state of evolution, the dynamics may engage larger populations of neurons to drive the brain to decisions, percepts and behaviors. For example, successfully evolving dynamics to sensory transients can appear at the mesoscopic scale revealing how the transient is perceived. As a consequence of these methodological and conceptual difficulties, studies in this field comprise a wide range of computational models, large-scale measurements (e.g., by MEG, EEG, and a combination of invasive measurements in animal experiments. Further obstacles and challenges of studying cortico-cortical communication dynamics are outlined in this critical review.

  7. High-conductance states in a mean-field cortical network model

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Ahmadi, Mandana; Hertz, John

    2004-01-01

    cortical network model with random connectivity and conductance-based synapses. We employ mean-field theory with correctly colored noise to describe temporal correlations in the neuronal activity. Our results illuminate the connection between two independent experimental findings: high-conductance states......Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1, indicating a tendency toward spikes being clustered. We show that this behavior emerges naturally in a balanced...... of cortical neurons in their natural environment, and variable non-Poissonian spike statistics with Fano factors greater than 1. (C) 2004 Elsevier B.V. All rights reserved....

  8. Models of large scale structure

    Energy Technology Data Exchange (ETDEWEB)

    Frenk, C.S. (Physics Dept., Univ. of Durham (UK))

    1991-01-01

    The ingredients required to construct models of the cosmic large scale structure are discussed. Input from particle physics leads to a considerable simplification by offering concrete proposals for the geometry of the universe, the nature of the dark matter and the primordial fluctuations that seed the growth of structure. The remaining ingredient is the physical interaction that governs dynamical evolution. Empirical evidence provided by an analysis of a redshift survey of IRAS galaxies suggests that gravity is the main agent shaping the large-scale structure. In addition, this survey implies large values of the mean cosmic density, {Omega}> or approx.0.5, and is consistent with a flat geometry if IRAS galaxies are somewhat more clustered than the underlying mass. Together with current limits on the density of baryons from Big Bang nucleosynthesis, this lends support to the idea of a universe dominated by non-baryonic dark matter. Results from cosmological N-body simulations evolved from a variety of initial conditions are reviewed. In particular, neutrino dominated and cold dark matter dominated universes are discussed in detail. Finally, it is shown that apparent periodicities in the redshift distributions in pencil-beam surveys arise frequently from distributions which have no intrinsic periodicity but are clustered on small scales. (orig.).

  9. Persistence of cortical sensory processing during absence seizures in human and an animal model: evidence from EEG and intracellular recordings.

    Directory of Open Access Journals (Sweden)

    Mathilde Chipaux

    Full Text Available Absence seizures are caused by brief periods of abnormal synchronized oscillations in the thalamocortical loops, resulting in widespread spike-and-wave discharges (SWDs in the electroencephalogram (EEG. SWDs are concomitant with a complete or partial impairment of consciousness, notably expressed by an interruption of ongoing behaviour together with a lack of conscious perception of external stimuli. It is largely considered that the paroxysmal synchronizations during the epileptic episode transiently render the thalamocortical system incapable of transmitting primary sensory information to the cortex. Here, we examined in young patients and in the Genetic Absence Epilepsy Rats from Strasbourg (GAERS, a well-established genetic model of absence epilepsy, how sensory inputs are processed in the related cortical areas during SWDs. In epileptic patients, visual event-related potentials (ERPs were still present in the occipital EEG when the stimuli were delivered during seizures, with a significant increase in amplitude compared to interictal periods and a decrease in latency compared to that measured from non-epileptic subjects. Using simultaneous in vivo EEG and intracellular recordings from the primary somatosensory cortex of GAERS and non-epileptic rats, we found that ERPs and firing responses of related pyramidal neurons to whisker deflection were not significantly modified during SWDs. However, the intracellular subthreshold synaptic responses in somatosensory cortical neurons during seizures had larger amplitude compared to quiescent situations. These convergent findings from human patients and a rodent genetic model show the persistence of cortical responses to sensory stimulations during SWDs, indicating that the brain can still process external stimuli during absence seizures. They also demonstrate that the disruption of conscious perception during absences is not due to an obliteration of information transfer in the thalamocortical system

  10. Microstructural changes in ischemic cortical gray matter predicted by a model of diffusion-weighted MRI

    DEFF Research Database (Denmark)

    Vestergaard-Poulsen, Peter; Hansen, Brian; Østergaard, Leif

    2007-01-01

    PURPOSE: To understand the diffusion attenuated MR signal from normal and ischemic brain tissue in order to extract structural and physiological information using mathematical modeling, taking into account the transverse relaxation rates in gray matter. MATERIALS AND METHODS: We fit our diffusion...... model to the diffusion-weighted MR signal obtained from cortical gray matter in healthy subjects. Our model includes variable volume fractions, intracellular restriction effects, and exchange between compartments in addition to individual diffusion coefficients and transverse relaxation rates for each...

  11. A GPU-accelerated cortical neural network model for visually guided robot navigation.

    Science.gov (United States)

    Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L

    2015-12-01

    Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls.

  12. A structured model of video reproduces primary visual cortical organisation.

    Directory of Open Access Journals (Sweden)

    Pietro Berkes

    2009-09-01

    Full Text Available The visual system must learn to infer the presence of objects and features in the world from the images it encounters, and as such it must, either implicitly or explicitly, model the way these elements interact to create the image. Do the response properties of cells in the mammalian visual system reflect this constraint? To address this question, we constructed a probabilistic model in which the identity and attributes of simple visual elements were represented explicitly and learnt the parameters of this model from unparsed, natural video sequences. After learning, the behaviour and grouping of variables in the probabilistic model corresponded closely to functional and anatomical properties of simple and complex cells in the primary visual cortex (V1. In particular, feature identity variables were activated in a way that resembled the activity of complex cells, while feature attribute variables responded much like simple cells. Furthermore, the grouping of the attributes within the model closely parallelled the reported anatomical grouping of simple cells in cat V1. Thus, this generative model makes explicit an interpretation of complex and simple cells as elements in the segmentation of a visual scene into basic independent features, along with a parametrisation of their moment-by-moment appearances. We speculate that such a segmentation may form the initial stage of a hierarchical system that progressively separates the identity and appearance of more articulated visual elements, culminating in view-invariant object recognition.

  13. Investigation of hyperelastic models for nonlinear elastic behavior of demineralized and deproteinized bovine cortical femur bone.

    Science.gov (United States)

    Hosseinzadeh, M; Ghoreishi, M; Narooei, K

    2016-06-01

    In this study, the hyperelastic models of demineralized and deproteinized bovine cortical femur bone were investigated and appropriate models were developed. Using uniaxial compression test data, the strain energy versus stretch was calculated and the appropriate hyperelastic strain energy functions were fitted on data in order to calculate the material parameters. To obtain the mechanical behavior in other loading conditions, the hyperelastic strain energy equations were investigated for pure shear and equi-biaxial tension loadings. The results showed the Mooney-Rivlin and Ogden models cannot predict the mechanical response of demineralized and deproteinized bovine cortical femur bone accurately, while the general exponential-exponential and general exponential-power law models have a good agreement with the experimental results. To investigate the sensitivity of the hyperelastic models, a variation of 10% in material parameters was performed and the results indicated an acceptable stability for the general exponential-exponential and general exponential-power law models. Finally, the uniaxial tension and compression of cortical femur bone were studied using the finite element method in VUMAT user subroutine of ABAQUS software and the computed stress-stretch curves were shown a good agreement with the experimental data.

  14. Leukocyte deformability: finite element modeling of large viscoelastic deformation.

    Science.gov (United States)

    Dong, C; Skalak, R

    1992-09-21

    An axisymmetric deformation of a viscoelastic sphere bounded by a prestressed elastic thin shell in response to external pressure is studied by a finite element method. The research is motivated by the need for understanding the passive behavior of human leukocytes (white blood cells) and interpreting extensive experimental data in terms of the mechanical properties. The cell at rest is modeled as a sphere consisting of a cortical prestressed shell with incompressible Maxwell fluid interior. A large-strain deformation theory is developed based on the proposed model. General non-linear, large strain constitutive relations for the cortical shell are derived by neglecting the bending stiffness. A representation of the constitutive equations in the form of an integral of strain history for the incompressible Maxwell interior is used in the formulation of numerical scheme. A finite element program is developed, in which a sliding boundary condition is imposed on all contact surfaces. The mathematical model developed is applied to evaluate experimental data of pipette tests and observations of blood flow.

  15. Drilling in cortical bone: a finite element model and experimental investigations.

    Science.gov (United States)

    Lughmani, Waqas A; Bouazza-Marouf, Kaddour; Ashcroft, Ian

    2015-02-01

    Bone drilling is an essential part of many orthopaedic surgery procedures, including those for internal fixation and for attaching prosthetics. Estimation and control of bone drilling forces are critical to prevent drill-bit breakthrough, excessive heat generation, and mechanical damage to the bone. An experimental and computational study of drilling in cortical bone has been conducted. A 3D finite element (FE) model for prediction of thrust forces experienced during bone drilling has been developed. The model incorporates the dynamic characteristics involved in the process along with geometrical considerations. An elastic-plastic material model is used to predict the behaviour of cortical bone during drilling. The average critical thrust forces and torques obtained using FE analysis are found to be in good agreement with the experimental results.

  16. Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders

    Science.gov (United States)

    Kana, Rajesh K.; Libero, Lauren E.; Moore, Marie S.

    2011-12-01

    such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD.

  17. Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders.

    Science.gov (United States)

    Kana, Rajesh K; Libero, Lauren E; Moore, Marie S

    2011-12-01

    as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD.

  18. Functional deficits in glutamate transporters and astrocyte biophysical properties in a rodent model of focal cortical dysplasia

    Directory of Open Access Journals (Sweden)

    Susan L Campbell

    2014-12-01

    Full Text Available Cortical dysplasia is associated with intractable epilepsy and developmental delay in young children. Recent work with the rat freeze-induced focal cortical dysplasia (FCD model has demonstrated that hyperexcitability in the dysplastic cortex is due in part to higher levels of extracellular glutamate. Astrocyte glutamate transporters play a pivotal role in cortical maintaining extracellular glutamate concentrations. Here we examined the function of astrocytic glutamate transporters in a FCD model in rats. Neocortical freeze lesions were made in postnatal day (PN 1 rat pups and whole cell electrophysiological recordings and biochemical studies were performed at PN 21-28. Synaptically evoked glutamate transporter currents in astrocytes showed a near 10-fold reduction in amplitude compared to sham operated controls. Astrocyte glutamate transporter currents from lesioned animals were also significantly reduced when challenged exogenously applied glutamate. Reduced astrocytic glutamate transport clearance contributed to increased NMDA receptor-mediated current decay kinetics in lesioned animals. The electrophysiological profile of astrocytes in the lesion group was also markedly changed compared to sham operated animals. Control astrocytes demonstrate large-amplitude linear leak currents in response to voltage-steps whereas astrocytes in lesioned animals demonstrated significantly smaller voltage-activated inward and outward currents. Significant decreases in astrocyte resting membrane potential and increases in input resistance were observed in lesioned animals. However, Western blotting, immunohistochemistry and quantitative PCR demonstrated no differences in the expression of the astrocytic glutamate transporter GLT-1 in lesioned animals relative to controls. These data suggest that, in the absence of changes in protein or mRNA expression levels, functional changes in astrocytic glutamate transporters contribute to neuronal hyperexcitability in

  19. Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.

    Directory of Open Access Journals (Sweden)

    Maxwell R Bennett

    Full Text Available Measurements of blood oxygenation level dependent (BOLD signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular connections.

  20. Nonlinear hierarchical multiscale modeling of cortical bone considering its nanoscale microstructure.

    Science.gov (United States)

    Ghanbari, J; Naghdabadi, R

    2009-07-22

    We have used a hierarchical multiscale modeling scheme for the analysis of cortical bone considering it as a nanocomposite. This scheme consists of definition of two boundary value problems, one for macroscale, and another for microscale. The coupling between these scales is done by using the homogenization technique. At every material point in which the constitutive model is needed, a microscale boundary value problem is defined using a macroscopic kinematical quantity and solved. Using the described scheme, we have studied elastic properties of cortical bone considering its nanoscale microstructural constituents with various mineral volume fractions. Since the microstructure of bone consists of mineral platelet with nanometer size embedded in a protein matrix, it is similar to the microstructure of soft matrix nanocomposites reinforced with hard nanostructures. Considering a representative volume element (RVE) of the microstructure of bone as the microscale problem in our hierarchical multiscale modeling scheme, the global behavior of bone is obtained under various macroscopic loading conditions. This scheme may be suitable for modeling arbitrary bone geometries subjected to a variety of loading conditions. Using the presented method, mechanical properties of cortical bone including elastic moduli and Poisson's ratios in two major directions and shear modulus is obtained for different mineral volume fractions.

  1. Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses.

    Science.gov (United States)

    Bennett, Maxwell R; Farnell, Les; Gibson, William G; Lagopoulos, Jim

    2015-01-01

    Measurements of blood oxygenation level dependent (BOLD) signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular) connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular) connections.

  2. Cellular mechanisms underlying spontaneous interictal spikes in an acute model of focal cortical epileptogenesis.

    Science.gov (United States)

    de Curtis, M; Radici, C; Forti, M

    1999-01-01

    The cellular mechanisms involved in the generation of spontaneous epileptiform potentials were investigated in the pirifom cortex of the in vitro isolated guinea-pig brain. A single, unilateral injection of bicuculline (150-200 nmol) in the anterior piriform cortex induced locally spontaneous interictal spikes that recurred with a period of 8.81+/-4.47 s and propagated caudally to the ipsi- and contralateral hemispheres. Simultaneous extra- and intracellular recordings from layer II and III principal cells showed that the spontaneous interictal spike correlates to a burst of action potentials followed by a large afterdepolarization. Intracellular application of the sodium conductance blocker, QX-314 (80 mM), abolished bursting activity and unmasked a high-threshold slow spike enhanced by the calcium chelator EGTA (50 mM). The slow spike was abolished by membrane hyperpolarization and by local perfusion with 2 mM cadmium. The depolarizing potential that followed the primary burst was reduced by arterial perfusion with the N-methyl-D-aspartate receptor antagonist, DL-2-amino-5-phosphonopentanoic acid (100-200 microM). The non-N-methyl-D-aspartate glutamate receptor antagonist, 6-cyano-7-nitroquinoxaline-2,3-dione (20 microM), completely and reversibly blocked the spontaneous spikes. The interictal spikes were terminated by a large afterpotential blocked either by intracellular QX-314 (80 mM) or by extracellular application of phaclofen and 2-hydroxysaclofen (10 and 4 mM, respectively). The present study demonstrates that, in an acute model of epileptogenesis, spontaneous interictal spikes are fostered by a primary burst of fast action potentials that ride on a regenerative high-threshold, possibly calcium-mediated spike, which activates a recurrent, glutamate-mediated potential responsible for the entrainment of adjacent and remote cortical regions. The bursting activity is controlled by a GABA(B) receptor-mediated inhibitory synaptic potential.

  3. Increased persistent sodium current determines cortical hyperexcitability in a genetic model of amyotrophic lateral sclerosis.

    Science.gov (United States)

    Pieri, Massimo; Carunchio, Irene; Curcio, Livia; Mercuri, Nicola Biagio; Zona, Cristina

    2009-02-01

    Cortical hyperexcitability has been observed in Amyotrophic Lateral Sclerosis (ALS) patients. Familial ALS accounts for 10% of all cases and mutations of the Cu,Zn superoxide dismutase (SOD1) gene have been identified in about 20% of the familial cases. The aim of this study was to investigate whether in a mouse model of ALS the cortical neurons developed hyperexcitability due to intrinsic properties of the single cell. We first examined the passive membrane properties and the pattern of repetitive firing in cultured cortical neurons from Control mice and transgenic mice expressing high levels of the human mutated protein (Gly(93)-->Ala, G93A). The former did not display significantly differing values between Control and G93A cortical neurons. However, the threshold potential and time of the first action potential decreased significantly and the firing frequency increased significantly in the G93A compared to Control neurons. The analysis of the voltage-dependent sodium currents revealed that the fast transient sodium current was unaffected by the SOD1 mutation whereas the persistent sodium current was significantly higher in the mutated neurons. Finally, Riluzole, a selective blocker of the persistent sodium current at low concentrations, decreased the firing frequency in G93A neurons, strongly indicating an involvement of this current in the observed hyperexcitability. These are the first data that demonstrate an intrinsic hyperexcitability in the G93A cortical neurons due to a higher current density of the persistent sodium current in the mutated neurons and open up new prospects of understanding ALS disease etiopathology.

  4. Assessment and Treatment of Peritumoral Cortical Veins in Parasagittal Meningiomas with Application of 3-Dimensional Imaging Fusion Model.

    Science.gov (United States)

    Yin, Tengkun; Gu, Jianjun; Huang, Yinxing; Wei, Liangfeng; Gao, Jinxi; Wang, Shousen

    2017-08-01

    Operation of cortical veins is the keystone of parasagittal meningioma (PSM) resection. Little is known about pathologic changes of the veins and proper treatment. We built 3-dimensional (3D) image fusion models by neuronavigation to analyze the features of peritumoral cortical veins for PSMs and explore intraoperative treatment options. We performed a prospective study of 42 consecutive surgically treated PSM patients who underwent preoperative evaluation of peritumoral cortical veins using a 3D venous-tumor fusion model established by a neuronavigation system. We categorized cortical veins into 3 types: single-end anastomosis (type a), tumor-to-end anastomosis (type b), and end-to-end anastomosis (type c). We present surgical strategies to operate these veins. Preoperative evaluation demonstrated 39 patients with peritumoral cortical veins. The 3D models show 100% of the veins (95 in total), which were confirmed intraoperation. The postoperative complication rates after vein injury were 60% (type a), 16.7% (type c), and 0% (type b). Ten patients (23.8%) had residual tumor because of venous protection (equal to Simpson grade III). After correlation analysis, type b and c cortical veins were positively correlated with tumor volume. The anastomoses of cortical veins may provide compensation for venous transaction. There may be a time-evolution relationship between different cortical veins (type a to c to b). Treatment of cortical veins should follow the following principles: single-end veins must be protected, tumor-to-end veins should be transacted directly, and end-to-end veins could be cut selectivity based on the degree of occlusion of the superior sagittal sinus. Detailed preoperative assessment of peritumoral cortical veins is critical for proper treatment. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Canonical Cortical Circuit Model Explains Rivalry, Intermittent Rivalry, and Rivalry Memory.

    Directory of Open Access Journals (Sweden)

    Shashaank Vattikuti

    2016-05-01

    Full Text Available It has been shown that the same canonical cortical circuit model with mutual inhibition and a fatigue process can explain perceptual rivalry and other neurophysiological responses to a range of static stimuli. However, it has been proposed that this model cannot explain responses to dynamic inputs such as found in intermittent rivalry and rivalry memory, where maintenance of a percept when the stimulus is absent is required. This challenges the universality of the basic canonical cortical circuit. Here, we show that by including an overlooked realistic small nonspecific background neural activity, the same basic model can reproduce intermittent rivalry and rivalry memory without compromising static rivalry and other cortical phenomena. The background activity induces a mutual-inhibition mechanism for short-term memory, which is robust to noise and where fine-tuning of recurrent excitation or inclusion of sub-threshold currents or synaptic facilitation is unnecessary. We prove existence conditions for the mechanism and show that it can explain experimental results from the quartet apparent motion illusion, which is a prototypical intermittent rivalry stimulus.

  6. Large Representation Recurrences in Large N Random Unitary Matrix Models

    CERN Document Server

    Karczmarek, Joanna L

    2011-01-01

    In a random unitary matrix model at large N, we study the properties of the expectation value of the character of the unitary matrix in the rank k symmetric tensor representation. We address the problem of whether the standard semiclassical technique for solving the model in the large N limit can be applied when the representation is very large, with k of order N. We find that the eigenvalues do indeed localize on an extremum of the effective potential; however, for finite but sufficiently large k/N, it is not possible to replace the discrete eigenvalue density with a continuous one. Nonetheless, the expectation value of the character has a well-defined large N limit, and when the discreteness of the eigenvalues is properly accounted for, it shows an intriguing approximate periodicity as a function of k/N.

  7. Effect of Anatomically Realistic Full-Head Model on Activation of Cortical Neurons in Subdural Cortical Stimulation—A Computational Study

    Science.gov (United States)

    Seo, Hyeon; Kim, Donghyeon; Jun, Sung Chan

    2016-06-01

    Electrical brain stimulation (EBS) is an emerging therapy for the treatment of neurological disorders, and computational modeling studies of EBS have been used to determine the optimal parameters for highly cost-effective electrotherapy. Recent notable growth in computing capability has enabled researchers to consider an anatomically realistic head model that represents the full head and complex geometry of the brain rather than the previous simplified partial head model (extruded slab) that represents only the precentral gyrus. In this work, subdural cortical stimulation (SuCS) was found to offer a better understanding of the differential activation of cortical neurons in the anatomically realistic full-head model than in the simplified partial-head models. We observed that layer 3 pyramidal neurons had comparable stimulation thresholds in both head models, while layer 5 pyramidal neurons showed a notable discrepancy between the models; in particular, layer 5 pyramidal neurons demonstrated asymmetry in the thresholds and action potential initiation sites in the anatomically realistic full-head model. Overall, the anatomically realistic full-head model may offer a better understanding of layer 5 pyramidal neuronal responses. Accordingly, the effects of using the realistic full-head model in SuCS are compelling in computational modeling studies, even though this modeling requires substantially more effort.

  8. Disrupted Cortical Connectivity as an Explanatory Model for Autism Spectrum Disorder

    Directory of Open Access Journals (Sweden)

    Jenniefer Drude Borup

    2014-02-01

    Full Text Available The aim of this article is to explain the theory of Disrupted Cortical Connectivity and discuss whether or not it can integrate the following three theories: Theory of Mind, Executive Functioning, and Weak Central Coherence that dominate the field of autism spectrum disorder research. Due to a lack of existing literature discussing this potential integration, we have consequentially undertaken such an endeavour. In our opinion, integration appears to be possible since this explanatory model can account for difficulties in both social cognition and executive functioning commonly found in autism spectrum disorder. Moreover, the theory of Disrupted Cortical Connectivity could be described as an extension of the theory of Weak Central Coherence.

  9. Cortical sources of ERP in prosaccade and antisaccade eye movements using realistic source models

    Science.gov (United States)

    Richards, John E.

    2013-01-01

    The cortical sources of event-related-potentials (ERP) using realistic source models were examined in a prosaccade and antisaccade procedure. College-age participants were presented with a preparatory interval and a target that indicated the direction of the eye movement that was to be made. In some blocks a cue was given in the peripheral location where the target was to be presented and in other blocks no cue was given. In Experiment 1 the prosaccade and antisaccade trials were presented randomly within a block; in Experiment 2 procedures were compared in which either prosaccade and antisaccade trials were mixed in the same block, or trials were presented in separate blocks with only one type of eye movement. There was a central negative slow wave occurring prior to the target, a slow positive wave over the parietal scalp prior to the saccade, and a parietal spike potential immediately prior to saccade onset. Cortical source analysis of these ERP components showed a common set of sources in the ventral anterior cingulate and orbital frontal gyrus for the presaccadic positive slow wave and the spike potential. In Experiment 2 the same cued- and non-cued blocks were used, but prosaccade and antisaccade trials were presented in separate blocks. This resulted in a smaller difference in reaction time between prosaccade and antisaccade trials. Unlike the first experiment, the central negative slow wave was larger on antisaccade than on prosaccade trials, and this effect on the ERP component had its cortical source primarily in the parietal and mid-central cortical areas contralateral to the direction of the eye movement. These results suggest that blocked prosaccade and antisaccade trials results in preparatory or set effects that decreases reaction time, eliminates some cueing effects, and is based on contralateral parietal-central brain areas. PMID:23847476

  10. Cortical Sources of ERP in Prosaccade and Antisaccade Eye Movements using Realistic Source Models

    Directory of Open Access Journals (Sweden)

    John E Richards

    2013-07-01

    Full Text Available The cortical sources of event-related-potentials (ERP using realistic source models were examined in a prosaccade and antisaccade task. College-age participants were presented with a preparatory interval and a target that indicated the direction of the eye movement that was to be made. In some blocks a cue was given in the peripheral location where the target was to be presented and in other blocks no cue was given. In Experiment 1 the prosaccade and antisaccade trials were presented randomly within a block; in Experiment 2 procedures were compared in which either prosaccade and antisaccade trials were mixed in the same block, or trials were presented in separate blocks with only one type of eye movement. There was a central negative slow wave occurring prior to the target, a slow positive wave over the parietal scalp prior to the saccade, and a parietal spike potential immediately prior to saccade onset. Cortical source analysis of these ERP components showed a common set of sources in the ventral anterior cingulate and orbital frontal gyrus for the presaccadic positive slow wave and the spike potential. In Experiment 2 the same cued- and non-cued blocks were used, but prosaccade and antisaccade trials were presented in separate blocks. This resulted in a smaller difference in reaction time between prosaccade and antisaccade trials. Unlike the first experiment, the central negative slow wave was larger on antisaccade than on prosaccade trials, and this effect on the ERP component had its cortical source primarily in the parietal and mid-central cortical areas contralateral to the direction of the eye movement. These results suggest that blocked prosaccade and antisaccade trials results in preparatory or set effects that decreases reaction time, eliminates some cueing effects, and is based on contralateral parietal-central brain areas.

  11. Cortical Thickness Abnormalities in Autism Spectrum Disorders Through Late Childhood, Adolescence, and Adulthood: A Large-Scale MRI Study.

    Science.gov (United States)

    Khundrakpam, Budhachandra S; Lewis, John D; Kostopoulos, Penelope; Carbonell, Felix; Evans, Alan C

    2017-03-01

    Neuroimaging studies in autism spectrum disorders (ASDs) have provided inconsistent evidence of cortical abnormality. This is probably due to the small sample sizes used in most studies, and important differences in sample characteristics, particularly age, as well as to the heterogeneity of the disorder. To address these issues, we assessed abnormalities in ASD within the Autism Brain Imaging Data Exchange data set, which comprises data from approximately 1100 individuals (~6-55 years). A subset of these data that met stringent quality control and inclusion criteria (560 male subjects; 266 ASD; age = 6-35 years) were used to compute age-specific differences in cortical thickness in ASD and the relationship of any such differences to symptom severity of ASD. Our results show widespread increased cortical thickness in ASD, primarily left lateralized, from 6 years onwards, with differences diminishing during adulthood. The severity of symptoms related to social affect and communication correlated with these cortical abnormalities. These results are consistent with the conjecture that developmental patterns of cortical thickness abnormalities reflect delayed cortical maturation and highlight the dynamic nature of morphological abnormalities in ASD. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. Structuring very large domain models

    DEFF Research Database (Denmark)

    Störrle, Harald

    2010-01-01

    View/Viewpoint approaches like IEEE 1471-2000, or Kruchten's 4+1-view model are used to structure software architectures at a high level of granularity. While research has focused on architectural languages and with consistency between multiple views, practical questions such as the structuring a...

  13. Predicting cortical ROIs via joint modeling of anatomical and connectional profiles.

    Science.gov (United States)

    Zhang, Tuo; Zhu, Dajiang; Jiang, Xi; Ge, Bao; Hu, Xintao; Han, Junwei; Guo, Lei; Liu, Tianming

    2013-08-01

    Localization of cortical regions of interests (ROIs) in structural neuroimaging data such as diffusion tensor imaging (DTI) and T1-weighted MRI images has significant importance in basic and clinical neurosciences. However, this problem is considerably challenging due to the lack of quantitative mapping between brain structure and function, which relies on the availability of multimodal training data including benchmark task-based functional MRI (fMRI) images and effective machine learning algorithms. This paper presents a novel joint modeling approach that learns predictive models of ROIs from concurrent task-based fMRI, DTI, and T1-weighted MRI datasets. In particular, the effective generalized multiple kernel learning (GMKL) algorithm and ROI coordinate principal component analysis (PCA) model are employed to infer the intrinsic relationships between anatomical T1-weighted MRI/connectional DTI features and task-based fMRI-derived functional ROIs. Then, these predictive models of cortical ROIs are evaluated by cross-validation studies, independent datasets, and reproducibility studies. Experimental results are promising. We envision that these predictive models can be potentially applied in many scenarios that have only DTI and/or T1-weighted MRI data, but without task-based fMRI data. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. Very Large System Dynamics Models - Lessons Learned

    Energy Technology Data Exchange (ETDEWEB)

    Jacob J. Jacobson; Leonard Malczynski

    2008-10-01

    This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.

  15. Relating Alpha Power and Phase to Population Firing and Hemodynamic Activity Using a Thalamo-cortical Neural Mass Model.

    Directory of Open Access Journals (Sweden)

    Robert Becker

    2015-09-01

    Full Text Available Oscillations are ubiquitous phenomena in the animal and human brain. Among them, the alpha rhythm in human EEG is one of the most prominent examples. However, its precise mechanisms of generation are still poorly understood. It was mainly this lack of knowledge that motivated a number of simultaneous electroencephalography (EEG - functional magnetic resonance imaging (fMRI studies. This approach revealed how oscillatory neuronal signatures such as the alpha rhythm are paralleled by changes of the blood oxygenation level dependent (BOLD signal. Several such studies revealed a negative correlation between the alpha rhythm and the hemodynamic BOLD signal in visual cortex and a positive correlation in the thalamus. In this study we explore the potential generative mechanisms that lead to those observations. We use a bursting capable Stefanescu-Jirsa 3D (SJ3D neural-mass model that reproduces a wide repertoire of prominent features of local neuronal-population dynamics. We construct a thalamo-cortical network of coupled SJ3D nodes considering excitatory and inhibitory directed connections. The model suggests that an inverse correlation between cortical multi-unit activity, i.e. the firing of neuronal populations, and narrow band local field potential oscillations in the alpha band underlies the empirically observed negative correlation between alpha-rhythm power and fMRI signal in visual cortex. Furthermore the model suggests that the interplay between tonic and bursting mode in thalamus and cortex is critical for this relation. This demonstrates how biophysically meaningful modelling can generate precise and testable hypotheses about the underpinnings of large-scale neuroimaging signals.

  16. Apoptosis is not an invariable component of in vitro models of cortical cerebral ischaemia

    Institute of Scientific and Technical Information of China (English)

    Paul Alexander JONES; Gillian Ruth MAY; Joyce Ann MCLUCKIE; Akinori IWASHITA; John SHARKEY

    2004-01-01

    Characterising the mechanisms of cell death following focal cerebral ischaemia has been hampered by a lack of an in vitro assay emulating both the apoptotic and necrotic features observed in vivo. The present study systematically characterised oxygen-glucose-deprivation (OGD) in primary rat cortical neurones to establish a reproducible model with components of both cell-death endpoints. OGD induced a time-dependent reduction in cell viability, with 80% cell death occurring 24 h after 3 h exposure to 0% O2 and 0.5 mM glucose. Indicative of a necrotic component to OGDinduced cell death, N-methyl-D-aspartate (NMDA) receptor inhibition with MK-801 attenuated neuronal loss by 60%.The lack of protection by the caspase inhibitors DEVD-CHO and z-VAD-fmk suggested that under these conditions neurones did not die by an apoptotic mechanism. Moderating the severity of the insult by decreasing OGD exposure to 60 min did not reduce the amount of necrosis, but did induce a small degree of apoptosis (a slight reduction in cell death was observed in the presence of 10 μtM DEVD-CHO). In separate experiments purported to enhance the apoptotic component, cells were gradually deprived of O2, exposed to 4% O2 (as opposed to 0%) during the OGD period, or maintained in serum-containing media throughout. While NMDA receptor antagonism significantly reduced cortical cell death under all conditions, a caspase-inhibitor sensitive component of cell death was not uncovered. These studies suggest that OGD of cultured cortical cells models the excitotoxic, but not the apoptotic component of cell death observed in vivo.

  17. Predicting functional cortical ROIs via DTI-derived fiber shape models.

    Science.gov (United States)

    Zhang, Tuo; Guo, Lei; Li, Kaiming; Jing, Changfeng; Yin, Yan; Zhu, Dajiang; Cui, Guangbin; Li, Lingjiang; Liu, Tianming

    2012-04-01

    Studying structural and functional connectivities of human cerebral cortex has drawn significant interest and effort recently. A fundamental and challenging problem arises when attempting to measure the structural and/or functional connectivities of specific cortical networks: how to identify and localize the best possible regions of interests (ROIs) on the cortex? In our view, the major challenges come from uncertainties in ROI boundary definition, the remarkable structural and functional variability across individuals and high nonlinearities within and around ROIs. In this paper, we present a novel ROI prediction framework that localizes ROIs in individual brains based on their learned fiber shape models from multimodal task-based functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data. In the training stage, shape models of white matter fibers are learnt from those emanating from the functional ROIs, which are activated brain regions detected from task-based fMRI data. In the prediction stage, functional ROIs are predicted in individual brains based only on DTI data. Our experiment results show that the average ROI prediction error is around 3.94 mm, in comparison with benchmark data provided by working memory and visual task-based fMRI. Our work demonstrated that fiber bundle shape models derived from DTI data are good predictors of functional cortical ROIs.

  18. Moving Objects Detection Using Intersecting Cortical Model in Enhanced Fish-eye Image

    Institute of Scientific and Technical Information of China (English)

    WU Jian-hui; YANG Kun-tao; DU Jian-rong; ZHANG Nan-yang-sheng

    2009-01-01

    A new method of the moving objects detection using the enhanced fish-eye lens and the intersecting cortical model (ICM) algorithm is proposed. The improved fish-eye lens is designed through controlling the entrance pupils of the lens.This lens has an ultra field of view about 183 degrees,and can image resolution.The ICM is a model based on pulse coupled neural network(PCNN) which is especially designed for image processing.It is derived from several visual cortex models and is basically the intersection of these models.The theoretical foundation of the ICM is given.An improved ICM algorithm in which some parameters are modified is used to detect moving objects specially.The experiment indicated that moving objects can be detected reliably and efficiently using ICM algorithm from the elliptical fish-eye image.It can be used in the field of traffic monitoring and other security domains.

  19. Large Scale Computations in Air Pollution Modelling

    DEFF Research Database (Denmark)

    Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.

    Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

  20. Large Scale Computations in Air Pollution Modelling

    DEFF Research Database (Denmark)

    Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.

    Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

  1. Changes in long-range connectivity and neuronal reorganization in partial cortical deafferentation model of epileptogenesis.

    Science.gov (United States)

    Kuśmierczak, M; Lajeunesse, F; Grand, L; Timofeev, I

    2015-01-22

    Severe brain injuries can trigger epileptogenesis, a latent period that eventually leads to epilepsy. Previous studies have demonstrated that changes in local connectivity between cortical neurons are a part of the epileptogenic processes. In the present study we aimed to investigate whether changes in long-range connectivity are also involved in epileptogenesis. We performed a large unilateral transection (undercut) of the white matter below the suprasylvian gyrus in cats. After about 2 months, we either injected retrograde tracer (cholera toxin, sub-unit B, CTB) or performed Golgi staining. We analyzed distribution of retrogradely labeled neurons, counted dendritic spines in the neocortex (Golgi staining), and analyzed dendritic orientation in control conditions and after the injury. We found a significant increase in the number of detected cells at the frontal parts of the injured hemisphere, which suggests that the process of axonal sprouting occurs in the deafferented area. The increase in the number of retrogradely stained neurons was accompanied with a significant decrease in neocortical spine density in the undercut area, a reduction in vertical and an increase in horizontal orientation of neuronal processes. The present study shows global morphological changes underlying epileptogenesis. An increased connectivity in the injured cortical regions accompanied with a decrease in spine density suggests that excitatory synapses might be formed on dendritic shafts, which probably contributes to the altered neuronal excitability that was described in previous studies on epileptogenesis.

  2. Fusion of intraoperative cortical images with preoperative models for neurosurgical planning and guidance

    Science.gov (United States)

    Wang, An; Mirsattari, Seyed M.; Parrent, Andrew G.; Peters, Terry M.

    2009-02-01

    During surgery for epilepsy it is important for the surgeon to correlate the preoperative cortical morphology (from preoperative images) with the intraoperative environment. We extend our visualization method presented earlier, to achieves this goal by fusing a direct (photographic) view of the surgical field with the 3D patient model. To correlate the preoperative plan with the intraoperative surgical scene, an intensity-based perspective 3D-2D registration was employed for camera pose estimation. The 2D photographic image was then texture-mapped onto the 3D preoperative model using the solved camera pose. In the proposed method, we employ direct volume rendering to obtain a perspective view of the brain image using GPU-accelerated ray-casting. This is advantageous compared to the point-based or other feature-based registration since no intermediate processing is required. To validate our registration algorithm, we used a point-based 3D-2D registration, that was validated using ground truth from simulated data, and then the intensity-based 3D-2D registration method was validated using the point-based registration result as the gold standard. The registration error of the intensity-based 3D- 2D method was around 3mm when the initial pose is close to the gold standard. Application of the proposed method for correlating fMRI maps with intraoperative cortical stimulation is shown for surgical planning in an epilepsy patient.

  3. Progressive brain damage, synaptic reorganization and NMDA activation in a model of epileptogenic cortical dysplasia.

    Directory of Open Access Journals (Sweden)

    Francesca Colciaghi

    Full Text Available Whether severe epilepsy could be a progressive disorder remains as yet unresolved. We previously demonstrated in a rat model of acquired focal cortical dysplasia, the methylazoxymethanol/pilocarpine - MAM/pilocarpine - rats, that the occurrence of status epilepticus (SE and subsequent seizures fostered a pathologic process capable of modifying the morphology of cortical pyramidal neurons and NMDA receptor expression/localization. We have here extended our analysis by evaluating neocortical and hippocampal changes in MAM/pilocarpine rats at different epilepsy stages, from few days after onset up to six months of chronic epilepsy. Our findings indicate that the process triggered by SE and subsequent seizures in the malformed brain i is steadily progressive, deeply altering neocortical and hippocampal morphology, with atrophy of neocortex and CA regions and progressive increase of granule cell layer dispersion; ii changes dramatically the fine morphology of neurons in neocortex and hippocampus, by increasing cell size and decreasing both dendrite arborization and spine density; iii induces reorganization of glutamatergic and GABAergic networks in both neocortex and hippocampus, favoring excitatory vs inhibitory input; iv activates NMDA regulatory subunits. Taken together, our data indicate that, at least in experimental models of brain malformations, severe seizure activity, i.e., SE plus recurrent seizures, may lead to a widespread, steadily progressive architectural, neuronal and synaptic reorganization in the brain. They also suggest the mechanistic relevance of glutamate/NMDA hyper-activation in the seizure-related brain pathologic plasticity.

  4. Disruption of prefrontal cortical-hippocampal balance in a developmental model of schizophrenia: reversal by sulpiride.

    Science.gov (United States)

    Belujon, Pauline; Patton, Mary H; Grace, Anthony A

    2013-04-01

    The nucleus accumbens (NAc) receives converging inputs from the medial prefrontal cortex (mPFC) and the hippocampus which have competitive interactions in the NAc to influence motivational drive. We have previously shown altered synaptic plasticity in the hippocampal-NAc pathway in the methylazoxymethanol acetate (MAM) developmental model of schizophrenia in rodents that is dependent on cortical inputs. Thus, because mPFC-hippocampal balance is known to be partially altered in this model, we investigated potential pathological changes in the hippocampal influence over cortex-driven NAc spike activity. Here we show that the reciprocal interaction between the hippocampus and mPFC is absent in MAM animals but is able to be reinstated with administration of the antipsychotic drug, sulpiride. The lack of interaction between these structures in this model could explain the attentional deficits in schizophrenia patients and shed light onto their inability to focus on a single task.

  5. Cortical and trabecular bone adaptation to incremental load magnitudes using the mouse tibial axial compression loading model.

    Science.gov (United States)

    Weatherholt, Alyssa M; Fuchs, Robyn K; Warden, Stuart J

    2013-01-01

    The mouse tibial axial compression loading model has recently been described to allow simultaneous exploration of cortical and trabecular bone adaptation within the same loaded element. However, the model frequently induces cortical woven bone formation and has produced inconsistent results with regards to trabecular bone adaptation. The aim of this study was to investigate bone adaptation to incremental load magnitudes using the mouse tibial axial compression loading model, with the ultimate goal of revealing a load that simultaneously induced lamellar cortical and trabecular bone adaptation. Adult (16 weeks old) female C57BL/6 mice were randomly divided into three load magnitude groups (5, 7 and 9N), and had their right tibia axially loaded using a continuous 2-Hz haversine waveform for 360 cycles/day, 3 days/week for 4 consecutive weeks. In vivo peripheral quantitative computed tomography was used to longitudinally assess midshaft tibia cortical bone adaptation, while ex vivo micro-computed tomography and histomorphometry were used to assess both midshaft tibia cortical and proximal tibia trabecular bone adaptation. A dose response to loading magnitude was observed within cortical bone, with increasing load magnitude inducing increasing levels of lamellar cortical bone adaptation within the upper two thirds of the tibial diaphysis. Greatest cortical bone adaptation was observed at the midshaft where there was a 42% increase in estimated mechanical properties (polar moment of inertia) in the highest (9N) load group. A dose response to load magnitude was not clearly evident within trabecular bone, with only the highest load (9N) being able to induce measureable adaptation (31% increase in trabecular bone volume fraction at the proximal tibia). The ultimate finding was that a load of 9N (engendering a tensile strain of 1833 με on medial surface of the midshaft tibia) was able to simultaneously induce measurable lamellar cortical and trabecular bone adaptation

  6. Effect of canagliflozin and metformin on cortical neurotransmitters in a diabetic rat model.

    Science.gov (United States)

    Arafa, Nadia M S; Marie, Mohamed-Assem S; AlAzimi, Sara Abdullah Mubarak

    2016-10-25

    The rapid economic development in the Arabian Gulf has resulted in lifestyle changes that have increased the prevalence of obesity and type 2 diabetes, with the greatest increases observed in Kuwait. Dyslipidemia and diabetes are risk factors for disruptions in cortical neurotransmitter homeostasis. This study investigated the effect of the antidiabetic medications canagliflozin (CAN) and metformin (MET) on the levels of cortical neurotransmitters in a diabetic rat model. The rats were assigned to the control (C) group, the diabetic group that did not receive treatment (D) or the diabetic group treated with either CAN (10 mg/kg) or MET (100 mg/kg) for 2 or 4 weeks. Blood and urine glucose levels and cortical acetylcholinesterase (AChE) activity were assayed, and amino acid and monoamine levels were measured using HPLC. The diabetic group exhibited a significant increase in AChE activity and a decrease in monoamine and amino acid neurotransmitter levels. In the CAN group, AChE was significantly lower than that in the D and D + MET groups after 2 weeks of treatment. In addition, a significant increase in some cortical monoamines and amino acids was observed in the D + MET and D + CAN groups compared with the D group. Histopathological analysis revealed the presence of severe focal hemorrhage, neuronal degeneration, and cerebral blood vessel congestion, with gliosis in the cerebrum of rats in the D group. The CAN-treated group exhibited severe cerebral blood vessel congestion after 2 weeks of treatment and focal gliosis in the cerebrum after 4 weeks of treatment. Focal gliosis in the cerebrum of rats in the MET-treated group was observed after 2 and 4 weeks of treatment. We conclude that the effect of CAN and MET on neurotransmitters is potentially mediated by their antihyperglycemic and antihyperlipidemic effects. In addition, the effects of CAN on neurotransmitters might be associated with its receptor activity, and the effect of MET on neurotransmitters

  7. Inherited cortical HCN1 channel loss amplifies dendritic calcium electrogenesis and burst firing in a rat absence epilepsy model.

    Science.gov (United States)

    Kole, Maarten H P; Bräuer, Anja U; Stuart, Greg J

    2007-01-15

    While idiopathic generalized epilepsies are thought to evolve from temporal highly synchronized oscillations between thalamic and cortical networks, their cellular basis remains poorly understood. Here we show in a genetic rat model of absence epilepsy (WAG/Rij) that a rapid decline in expression of hyperpolarization-activated cyclic-nucleotide gated (HCN1) channels (I(h)) precedes the onset of seizures, suggesting that the loss of HCN1 channel expression is inherited rather than acquired. Loss of HCN1 occurs primarily in the apical dendrites of layer 5 pyramidal neurons in the cortex, leading to a spatially uniform 2-fold reduction in dendritic HCN current throughout the entire somato-dendritic axis. Dual whole-cell recordings from the soma and apical dendrites demonstrate that loss of HCN1 increases somato-dendritic coupling and significantly reduces the frequency threshold for generation of dendritic Ca2+ spikes by backpropagating action potentials. As a result of increased dendritic Ca2+ electrogenesis a large population of WAG/Rij layer 5 neurons showed intrinsic high-frequency burst firing. Using morphologically realistic models of layer 5 pyramidal neurons from control Wistar and WAG/Rij animals we show that the experimentally observed loss of dendritic I(h) recruits dendritic Ca2+ channels to amplify action potential-triggered dendritic Ca2+ spikes and increase burst firing. Thus, loss of function of dendritic HCN1 channels in layer 5 pyramidal neurons provides a somato-dendritic mechanism for increasing the synchronization of cortical output, and is therefore likely to play an important role in the generation of absence seizures.

  8. Composite model with large mixing of neutrinos

    CERN Document Server

    Haba, N

    1999-01-01

    We suggest a simple composite model that induces the large flavor mixing of neutrino in the supersymmetric theory. This model has only one hyper-color in addition to the standard gauge group, which makes composite states of preons. In this model, {\\bf 10} and {\\bf 1} representations in SU(5) grand unified theory are composite states and produce the mass hierarchy. This explains why the large mixing is realized in the lepton sector, while the small mixing is realized in the quark sector. This model can naturally solve the atmospheric neutrino problem. We can also solve the solar neutrino problem by improving the model.

  9. GABAergic synaptic inhibition is reduced before seizure onset in a genetic model of cortical malformation.

    Science.gov (United States)

    Trotter, Stacey A; Kapur, Jaideep; Anzivino, Matthew J; Lee, Kevin S

    2006-10-18

    Malformations of the neocortex are a common cause of human epilepsy; however, the critical issue of how disturbances in cortical organization render neurons epileptogenic remains controversial. The present study addressed this issue by studying inhibitory structure and function before seizure onset in the telencephalic internal structural heterotopia (tish) rat, which is a genetic model of heightened seizure susceptibility associated with a prominent neocortical malformation. Both normally positioned (normotopic) and misplaced (heterotopic) pyramidal neurons in the tish neocortex exhibited lower resting membrane potentials and a tendency toward higher input resistance compared with pyramidal neurons from control brains. GABAergic synaptic transmission was attenuated in the tish cortex, characterized by significant reductions in the frequency of spontaneous IPSCs (sIPSCs) and miniature IPSCs recorded from pyramidal neurons. In addition, the amplitudes of sIPSCs were reduced in the tish neocortex, an effect that was more profound in the normotopic cells. Immunohistochemical assessment of presynaptic GABAergic terminals showed a reduction in terminals surrounding pyramidal cell somata in normotopic and heterotopic tish neocortex. The attenuation of inhibitory innervation was more prominent for normotopic neurons and was associated with a reduction in a subset of GABAergic interneurons expressing the calcium-binding protein parvalbumin. Together, these findings indicate that key facets of inhibitory GABAergic neurotransmission are disturbed before seizure onset in a brain predisposed to developing seizures. Such alterations represent a rational substrate for reduced seizure thresholds associated with certain cortical malformations.

  10. Developmental abnormalities of cortical interneurons precede symptoms onset in a mouse model of Rett syndrome.

    Science.gov (United States)

    Tomassy, Giulio Srubek; Morello, Noemi; Calcagno, Eleonora; Giustetto, Maurizio

    2014-10-01

    Rett syndrome (RTT, MIM312750), a neurodevelopmental disorder predominantly occurring in females, is caused in the majority of cases by sporadic mutations in the gene encoding the transcriptional modulator methyl-CpG-binding protein 2 (MECP2). In mice, impaired MeCP2 function results in severe motor, cognitive, and emotional defects. The lack of Mecp2 in γ-aminobutyric acid-(GABA) releasing forebrain interneurons (INs) recapitulate many RTT features, however, the role of this gene in the development of the cortical inhibitory system is still unknown. Here, we found that MeCP2 expression varies among the three major classes of cortical INs and its nuclear localization differs between neuronal types. The density of calretinin(+) and parvalbumin(+) INs increases in Mecp2 knockout mice (Mecp2(-/y) ) already at early post-natal developmental stages. In contrast, the density of somatostatin(+) INs is not affected. We also found that the development of multipolar-calretinin(+) INs is selectively affected by the absence of Mecp2. Additionally, we show that in Mecp2 heterozygous female mice, a model closely mimicking human RTT condition, IN abnormalities are similar to those observed in Mecp2(-/y) mice. Together, our study indicates that loss of function of Mecp2 strongly interferes with the correct establishment of the neocortical inhibitory system producing effects that are specific to different IN subtypes.

  11. Cortical Spreading Depression Causes Unique Dysregulation of Inflammatory Pathways in a Transgenic Mouse Model of Migraine.

    Science.gov (United States)

    Eising, Else; Shyti, Reinald; 't Hoen, Peter A C; Vijfhuizen, Lisanne S; Huisman, Sjoerd M H; Broos, Ludo A M; Mahfouz, Ahmed; Reinders, Marcel J T; Ferrari, Michel D; Tolner, Else A; de Vries, Boukje; van den Maagdenberg, Arn M J M

    2017-05-01

    Familial hemiplegic migraine type 1 (FHM1) is a rare monogenic subtype of migraine with aura caused by mutations in CACNA1A that encodes the α1A subunit of voltage-gated CaV2.1 calcium channels. Transgenic knock-in mice that carry the human FHM1 R192Q missense mutation ('FHM1 R192Q mice') exhibit an increased susceptibility to cortical spreading depression (CSD), the mechanism underlying migraine aura. Here, we analysed gene expression profiles from isolated cortical tissue of FHM1 R192Q mice 24 h after experimentally induced CSD in order to identify molecular pathways affected by CSD. Gene expression profiles were generated using deep serial analysis of gene expression sequencing. Our data reveal a signature of inflammatory signalling upon CSD in the cortex of both mutant and wild-type mice. However, only in the brains of FHM1 R192Q mice specific genes are up-regulated in response to CSD that are implicated in interferon-related inflammatory signalling. Our findings show that CSD modulates inflammatory processes in both wild-type and mutant brains, but that an additional unique inflammatory signature becomes expressed after CSD in a relevant mouse model of migraine.

  12. Refactoring Process Models in Large Process Repositories.

    NARCIS (Netherlands)

    Weber, B.; Reichert, M.U.

    2008-01-01

    With the increasing adoption of process-aware information systems (PAIS), large process model repositories have emerged. Over time respective models have to be re-aligned to the real-world business processes through customization or adaptation. This bears the risk that model redundancies are introdu

  13. Refactoring Process Models in Large Process Repositories.

    NARCIS (Netherlands)

    Weber, B.; Reichert, M.U.

    With the increasing adoption of process-aware information systems (PAIS), large process model repositories have emerged. Over time respective models have to be re-aligned to the real-world business processes through customization or adaptation. This bears the risk that model redundancies are

  14. Gamma distribution model describes maturational curves for delta wave amplitude, cortical metabolic rate and synaptic density.

    Science.gov (United States)

    Feinberg, I; Thode, H C; Chugani, H T; March, J D

    1990-01-23

    We analyzed the available ontogenetic data (birth to 30 years of age) for: amplitude of delta EEG (DA) waves during sleep; cortical metabolic rate (CMR) measured with positron emission tomography; and synaptic density (SD) in frontal cortex. Each is at the adult level at birth, increases to about twice this level by 3 years of age, and then gradually falls back to the adult level over the next two decades. Statistical analyses revealed that individual gamma distribution models fit each data set as well as did the best ad hoc polynomial. A test of whether a single gamma distribution model could describe all three data sets gave good results for DA and CMR but the fit was unsatisfactory for SD. However, because so few data were available for SD, this test was not conclusive. We proposed the following model to account for these changes. First, cortical neurons are stimulated by birth to enter a proliferative state (PS) that creates many connections. Next, as a result of interactions in the PS, neurons are triggered into a transient organizational state (OS) in which they make enduring connections. The OS has a finite duration (minutes to years), and is characterized by high rates of information-processing and metabolism. Levels of CMR, SD and DA, therefore, are proportional to the number of neurons in the OS at any time. Thus, the cortex after birth duplicates, over a vastly greater time scale, the overproduction and regression of neural elements that occurs repeatedly in embryonic development. Finally, we discussed the implications of post-natal brain changes for normal and abnormal brain function. Mental disorders that have their onset after puberty (notably schizophrenia and manic-depressive psychoses) might be caused by errors in these late maturational processes. In addition to age of onset, this neurodevelopmental hypothesis might explain several other puzzling features of these subtle disorders.

  15. Increased susceptibility to cortical spreading depression in the mouse model of familial hemiplegic migraine type 2.

    Directory of Open Access Journals (Sweden)

    Loredana Leo

    2011-06-01

    Full Text Available Familial hemiplegic migraine type 2 (FHM2 is an autosomal dominant form of migraine with aura that is caused by mutations of the α2-subunit of the Na,K-ATPase, an isoform almost exclusively expressed in astrocytes in the adult brain. We generated the first FHM2 knock-in mouse model carrying the human W887R mutation in the Atp1a2 orthologous gene. Homozygous Atp1a2(R887/R887 mutants died just after birth, while heterozygous Atp1a2(+/R887 mice showed no apparent clinical phenotype. The mutant α2 Na,K-ATPase protein was barely detectable in the brain of homozygous mutants and strongly reduced in the brain of heterozygous mutants, likely as a consequence of endoplasmic reticulum retention and subsequent proteasomal degradation, as we demonstrate in transfected cells. In vivo analysis of cortical spreading depression (CSD, the phenomenon underlying migraine aura, revealed a decreased induction threshold and an increased velocity of propagation in the heterozygous FHM2 mouse. Since several lines of evidence involve a specific role of the glial α2 Na,K pump in active reuptake of glutamate from the synaptic cleft, we hypothesize that CSD facilitation in the FHM2 mouse model is sustained by inefficient glutamate clearance by astrocytes and consequent increased cortical excitatory neurotransmission. The demonstration that FHM2 and FHM1 mutations share the ability to facilitate induction and propagation of CSD in mouse models further support the role of CSD as a key migraine trigger.

  16. GABAA Receptor-Mediated Activity in a Model of Cortical Dysplasia

    Science.gov (United States)

    2012-06-29

    epilepsy, autism and schizophrenia, and results from failure of immature neurons to appropriately migrate to their cortical targets. We developed a...schizophrenia, and autism , and results from failure of immature neurons to appropriately migrate and reach their cortical targets (Taylor et al., 1971; Choi and...appropriate cortical target is regulated by Brn1 and Brn2, POU-domain transcription factors that regulate the reelin /DAB1 pathway, and cyclin

  17. A Model for Cortical 40 Hz oscillations invokes inter-area interactions

    DEFF Research Database (Denmark)

    Cotterill, Rodney M J; Helix Nielsen, Claus

    1991-01-01

    COMPUTER simulation of the dynamics of neuronal assemblies within minicolumns, and of the interactions between minicolumns in different cortical areas, has produced a quantitative explanation of the 35-60 Hz oscillations recently observed in adult cat striate cortices. The observed behavior...... suggests an association mechanism that exploits the NMDA receptor's properties. Detectable oscillations are predicted in cortical areas not directly stimulated, provided these are associatively linked with areas receiving sensory input....

  18. Trial-by-Trial Motor Cortical Correlates of a Rapidly Adapting Visuomotor Internal Model.

    Science.gov (United States)

    Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

    2017-02-15

    Accurate motor control is mediated by internal models of how neural activity generates movement. We examined neural correlates of an adapting internal model of visuomotor gain in motor cortex while two macaques performed a reaching task in which the gain scaling between the hand and a presented cursor was varied. Previous studies of cortical changes during visuomotor adaptation focused on preparatory and perimovement epochs and analyzed trial-averaged neural data. Here, we recorded simultaneous neural population activity using multielectrode arrays and focused our analysis on neural differences in the period before the target appeared. We found that we could estimate the monkey's internal model of the gain using the neural population state during this pretarget epoch. This neural correlate depended on the gain experienced during recent trials and it predicted the speed of the subsequent reach. To explore the utility of this internal model estimate for brain-machine interfaces, we performed an offline analysis showing that it can be used to compensate for upcoming reach extent errors. Together, these results demonstrate that pretarget neural activity in motor cortex reflects the monkey's internal model of visuomotor gain on single trials and can potentially be used to improve neural prostheses.SIGNIFICANCE STATEMENT When generating movement commands, the brain is believed to use internal models of the relationship between neural activity and the body's movement. Visuomotor adaptation tasks have revealed neural correlates of these computations in multiple brain areas during movement preparation and execution. Here, we describe motor cortical changes in a visuomotor gain change task even before a specific movement is cued. We were able to estimate the gain internal model from these pretarget neural correlates and relate it to single-trial behavior. This is an important step toward understanding the sensorimotor system's algorithms for updating its internal models

  19. Medical Image Fusion Based on Rolling Guidance Filter and Spiking Cortical Model.

    Science.gov (United States)

    Shuaiqi, Liu; Jie, Zhao; Mingzhu, Shi

    2015-01-01

    Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. Although numerous medical image fusion methods have been proposed, most of these approaches are sensitive to the noise and usually lead to fusion image distortion, and image information loss. Furthermore, they lack universality when dealing with different kinds of medical images. In this paper, we propose a new medical image fusion to overcome the aforementioned issues of the existing methods. It is achieved by combining with rolling guidance filter (RGF) and spiking cortical model (SCM). Firstly, saliency of medical images can be captured by RGF. Secondly, a self-adaptive threshold of SCM is gained by utilizing the mean and variance of the source images. Finally, fused image can be gotten by SCM motivated by RGF coefficients. Experimental results show that the proposed method is superior to other current popular ones in both subjectively visual performance and objective criteria.

  20. Cross-correlations in high-conductance states of a model cortical network

    DEFF Research Database (Denmark)

    Hertz, John

    2010-01-01

    (dansk abstrakt findes ikke) Neuronal firing correlations are studied using simulations of a simple network model for a cortical column in a high-conductance state with dynamically balanced excitation and inhibition.  Although correlations between individual pairs of neurons exhibit considerable...... heterogeneity, population averages show systematic behavior. When the network is in a stationary state, the average correlations are generically small: correlation coefficients are of order 1/N, where N is the number of neurons in the network. However, when the input to the network varies strongly in time, much...... larger values are found. In this situation, the network is out of balance, and the synaptic conductance is low, at times when the strongest firing occurs.  However, examination of the correlation functions of synaptic currents reveals that after these bursts, balance is restored within a few ms...

  1. Spiking cortical model-based nonlocal means method for speckle reduction in optical coherence tomography images

    Science.gov (United States)

    Zhang, Xuming; Li, Liu; Zhu, Fei; Hou, Wenguang; Chen, Xinjian

    2014-06-01

    Optical coherence tomography (OCT) images are usually degraded by significant speckle noise, which will strongly hamper their quantitative analysis. However, speckle noise reduction in OCT images is particularly challenging because of the difficulty in differentiating between noise and the information components of the speckle pattern. To address this problem, the spiking cortical model (SCM)-based nonlocal means method is presented. The proposed method explores self-similarities of OCT images based on rotation-invariant features of image patches extracted by SCM and then restores the speckled images by averaging the similar patches. This method can provide sufficient speckle reduction while preserving image details very well due to its effectiveness in finding reliable similar patches under high speckle noise contamination. When applied to the retinal OCT image, this method provides signal-to-noise ratio improvements of >16 dB with a small 5.4% loss of similarity.

  2. Spiking cortical model-based nonlocal means method for speckle reduction in optical coherence tomography images.

    Science.gov (United States)

    Zhang, Xuming; Li, Liu; Zhu, Fei; Hou, Wenguang; Chen, Xinjian

    2014-06-01

    Optical coherence tomography (OCT) images are usually degraded by significant speckle noise, which will strongly hamper their quantitative analysis. However, speckle noise reduction in OCT images is particularly challenging because of the difficulty in differentiating between noise and the information components of the speckle pattern. To address this problem, the spiking cortical model (SCM)-based nonlocal means method is presented. The proposed method explores self-similarities of OCT images based on rotation-invariant features of image patches extracted by SCM and then restores the speckled images by averaging the similar patches. This method can provide sufficient speckle reduction while preserving image details very well due to its effectiveness in finding reliable similar patches under high speckle noise contamination. When applied to the retinal OCT image, this method provides signal-to-noise ratio improvements of >16  dB with a small 5.4% loss of similarity.

  3. Medical Image Fusion Based on Rolling Guidance Filter and Spiking Cortical Model

    Directory of Open Access Journals (Sweden)

    Liu Shuaiqi

    2015-01-01

    Full Text Available Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. Although numerous medical image fusion methods have been proposed, most of these approaches are sensitive to the noise and usually lead to fusion image distortion, and image information loss. Furthermore, they lack universality when dealing with different kinds of medical images. In this paper, we propose a new medical image fusion to overcome the aforementioned issues of the existing methods. It is achieved by combining with rolling guidance filter (RGF and spiking cortical model (SCM. Firstly, saliency of medical images can be captured by RGF. Secondly, a self-adaptive threshold of SCM is gained by utilizing the mean and variance of the source images. Finally, fused image can be gotten by SCM motivated by RGF coefficients. Experimental results show that the proposed method is superior to other current popular ones in both subjectively visual performance and objective criteria.

  4. Formation and Dynamics of Waves in a Cortical Model of Cholinergic Modulation.

    Directory of Open Access Journals (Sweden)

    James P Roach

    2015-08-01

    Full Text Available Acetylcholine (ACh is a regulator of neural excitability and one of the neurochemical substrates of sleep. Amongst the cellular effects induced by cholinergic modulation are a reduction in spike-frequency adaptation (SFA and a shift in the phase response curve (PRC. We demonstrate in a biophysical model how changes in neural excitability and network structure interact to create three distinct functional regimes: localized asynchronous, traveling asynchronous, and traveling synchronous. Our results qualitatively match those observed experimentally. Cortical activity during slow wave sleep (SWS differs from that during REM sleep or waking states. During SWS there are traveling patterns of activity in the cortex; in other states stationary patterns occur. Our model is a network composed of Hodgkin-Huxley type neurons with a M-current regulated by ACh. Regulation of ACh level can account for dynamical changes between functional regimes. Reduction of the magnitude of this current recreates the reduction in SFA the shift from a type 2 to a type 1 PRC observed in the presence of ACh. When SFA is minimal (in waking or REM sleep state, high ACh patterns of activity are localized and easily pinned by network inhomogeneities. When SFA is present (decreasing ACh, traveling waves of activity naturally arise. A further decrease in ACh leads to a high degree of synchrony within traveling waves. We also show that the level of ACh determines how sensitive network activity is to synaptic heterogeneity. These regimes may have a profound functional significance as stationary patterns may play a role in the proper encoding of external input as memory and traveling waves could lead to synaptic regularization, giving unique insights into the role and significance of ACh in determining patterns of cortical activity and functional differences arising from the patterns.

  5. Oxygen flux reduces Cux1 positive neurons and cortical growth in a gestational rodent model of growth restriction.

    Science.gov (United States)

    Fletcher, Elaine; Wade, Jean; Georgala, Petrina A; Gillespie, Trudi L; Price, David J; Pilley, Elizabeth; Becher, Julie-Clare

    2017-03-01

    The mammalian cerebral cortex forms in an inside-out manner, establishing deep cortical layers before superficial layers and is regulated by transcription factors which influence cell differentiation. Preterm birth interrupts the trajectory of normal neurodevelopment and adverse perinatal exposures have been implicated in cortical injury. We hypothesise that growth restriction (GR) and fluctuating hyperoxia (ΔO2) impair cortical laminar development. Sprague-Dawley rats received 18% (non-restricted, NR) or 9% (growth restricted, GR) protein diet from E15-P7. Litters were reared in air or fluctuating hyperoxia (circa 10kPa) from P0 to P7. Cortical laminae were stained and measured. Neuronal subtypes were quantified using immunofluorescence for subtype-specific transcription factors (Satb2, Cux1, Ctip2, Tbr1). ΔO2 did not affect brain weight at P7 but reduced cortical thickness in both NR (pdevelopment in a rodent model with preferential disadvantage to superficial neurons. Copyright © 2016 Elsevier GmbH. All rights reserved.

  6. Including long-range dependence in integrate-and-fire models of the high interspike-interval variability of cortical neurons.

    Science.gov (United States)

    Jackson, B Scott

    2004-10-01

    Many different types of integrate-and-fire models have been designed in order to explain how it is possible for a cortical neuron to integrate over many independent inputs while still producing highly variable spike trains. Within this context, the variability of spike trains has been almost exclusively measured using the coefficient of variation of interspike intervals. However, another important statistical property that has been found in cortical spike trains and is closely associated with their high firing variability is long-range dependence. We investigate the conditions, if any, under which such models produce output spike trains with both interspike-interval variability and long-range dependence similar to those that have previously been measured from actual cortical neurons. We first show analytically that a large class of high-variability integrate-and-fire models is incapable of producing such outputs based on the fact that their output spike trains are always mathematically equivalent to renewal processes. This class of models subsumes a majority of previously published models, including those that use excitation-inhibition balance, correlated inputs, partial reset, or nonlinear leakage to produce outputs with high variability. Next, we study integrate-and-fire models that have (nonPoissonian) renewal point process inputs instead of the Poisson point process inputs used in the preceding class of models. The confluence of our analytical and simulation results implies that the renewal-input model is capable of producing high variability and long-range dependence comparable to that seen in spike trains recorded from cortical neurons, but only if the interspike intervals of the inputs have infinite variance, a physiologically unrealistic condition. Finally, we suggest a new integrate-and-fire model that does not suffer any of the previously mentioned shortcomings. By analyzing simulation results for this model, we show that it is capable of producing output

  7. Formulaic language in cortical and subcortical disease: Evidence of the dual process model.

    Directory of Open Access Journals (Sweden)

    Kelly Bridges

    2014-04-01

    Full Text Available Introduction: It is known that an intact cortical left hemisphere is crucial for language production. Recently, more credit is given to the right hemisphere and subcortical areas in the production of non-novel language, including formulaic language. John Hughlings Jackson (1874/1958, first described how propositional and non-propositional speech are differentially affected by neural impairment. Non-propositional language is often preserved following left hemisphere stroke even when aphasia is present (Code, 1982; Sidtis et al., 2009; Van Lancker Sidtis & Postman, 2006. With right hemisphere and subcortical stroke, formulaic language is reduced (Sidtis et al., 2009; Van Lancker Sidtis & Postman, 2006; Speedie et al., 1993. The dual process model of language competence states that propositional and non-propositional speech are processed differently in the brain, with novel speech controlled by the left hemisphere, and a right hemisphere/subcortical circuit modulating formulaic language (Van Lancker Sidtis, 2004; 2012. Two studies of formulaic language will be presented as further evidence of the dual process model: a study of formulaic language in Alzheimer’s disease, and a study of recited speech in Parkinson’s disease. Formulaic language includes overlearned words, phrases or longer linguistic units that are known to the native speaker, occur naturally in discourse, and are important for normal social interaction (Fillmore, 1979; Pawley & Syder, 1983; Van Lancker, 1988; Van Lancker Sidtis, 2004; Wray, 2002. Formulaic expressions include conversational speech formulas, idioms, proverbs, expletives, pause fillers, discourse elements, and sentence stems (stereotyped sentence-initials. Longer units of linguistic material, such as prayers, rhymes, and poems, termed recited speech, is another subtype of formulaic language that is learned in childhood and recited periodically throughout life. Cortical disease: Alzheimer’s disease and formulaic

  8. Altered Theta Oscillations and Aberrant Cortical Excitatory Activity in the 5XFAD Model of Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Magdalena Elisabeth Siwek

    2015-01-01

    Full Text Available Alzheimer’s disease (AD is an age-related neurodegenerative disorder characterized by impairment of memory function. The 5XFAD mouse model was analyzed and compared with wild-type (WT controls for aberrant cortical excitability and hippocampal theta oscillations by using simultaneous video-electroencephalogram (EEG monitoring. Seizure staging revealed that 5XFAD mice exhibited cortical hyperexcitability whereas controls did not. In addition, 5XFAD mice displayed a significant increase in hippocampal theta activity from the light to dark phase during nonmotor activity. We also observed a reduction in mean theta frequency in 5XFAD mice compared to controls that was again most prominent during nonmotor activity. Transcriptome analysis of hippocampal probes and subsequent qPCR validation revealed an upregulation of Plcd4 that might be indicative of enhanced muscarinic signalling. Our results suggest that 5XFAD mice exhibit altered cortical excitability, hippocampal dysrhythmicity, and potential changes in muscarinic signaling.

  9. Comparative proteomics of rat brain in the BCNU-induced model of cortical dysplasia

    Institute of Scientific and Technical Information of China (English)

    郭谊

    2014-01-01

    Objective To screen the differential proteins in the brain(neocortex and hippocampus)between the rats with cortical dysplasia(CD)and control ones,and investigate the role of their alteration in the development of epilepsy in CD.Methods Cortical dysplasia was induced in rat pups via in utero delivery of BCNU.A two-dimensional electrophoresis

  10. Unilateral and bilateral cortical resection: Effects on spike-wave discharges in a genetic absence epilepsy model

    NARCIS (Netherlands)

    Scicchitano, F.; Rijn, C.M. van; Luijtelaar, E.L.J.M. van

    2015-01-01

    Research Question Recent discoveries have challenged the traditional view that the thalamus is the primary source driving spike-and-wave discharges (SWDs). At odds, SWDs in genetic absence models have a cortical focal origin in the deep layers of the perioral region of the somatosensory cortex. The

  11. The functional roles of alpha-band phase synchronization in local and large-scale cortical networks

    Directory of Open Access Journals (Sweden)

    Satu ePalva

    2011-09-01

    Full Text Available Alpha-frequency band (8-14 Hz oscillations are among the most salient phenomena in human electroencephalography (EEG recordings and yet their functional roles have remained unclear. Much of research on alpha oscillations in human EEG has focused on peri-stimulus amplitude dynamics, which phenomenologically support an idea of alpha oscillations being negatively correlated with local cortical excitability and having a role in the suppression of task-irrelevant neuronal processing. This kind of an inhibitory role for alpha oscillations is also supported by several functional magnetic resonance imaging (fMRI and trans-cranial magnetic stimulation (TMS studies. Nevertheless, investigations of local and inter-areal alpha phase dynamics suggest that the alpha-frequency band rhythmicity may play a role also in active task-relevant neuronal processing. These data imply that inter-areal alpha phase synchronization could support attentional, executive, and contextual functions. In this review, we outline evidence supporting different views on the roles of alpha oscillations in cortical networks and unresolved issues that should be addressed to resolve or reconcile these apparently contrasting hypotheses.

  12. Computational model of cerebral blood flow redistribution during cortical spreading depression

    Science.gov (United States)

    Verisokin, Andrey Y.; Verveyko, Darya V.; Postnov, Dmitry E.

    2016-04-01

    In recent decades modelling studies on cortical spreading depression (CSD) and migraine waves successfully contributed to formation of modern view on these fundamental phenomena of brain physiology. However, due to the extreme complexity of object under study (brain cortex) and the diversity of involved physiological pathways, the development of new mathematical models of CSD is still a very relevant and challenging research problem. In our study we follow the functional modelling approach aimed to map the action of known physiological pathways to the specific nonlinear mechanisms that govern formation and evolution of CSD wave patterns. Specifically, we address the role of cerebral blood flow (CBF) redistribution that is caused by excessive neuronal activity by means of neurovascular coupling and mediates a spatial pattern of oxygen and glucose delivery. This in turn changes the local metabolic status of neural tissue. To build the model we simplify the web of known cell-to-cell interactions within a neurovascular unit by selecting the most relevant ones, such as local neuron-induced elevation of extracellular potassium concentration and biphasic response of arteriole radius. We propose the lumped description of distance-dependent hemodynamic coupling that fits the most recent experimental findings.

  13. Modeling the Formation Process of Grouping Stimuli Sets through Cortical Columns and Microcircuits to Feature Neurons

    Directory of Open Access Journals (Sweden)

    Frank Klefenz

    2013-01-01

    Full Text Available A computational model of a self-structuring neuronal net is presented in which repetitively applied pattern sets induce the formation of cortical columns and microcircuits which decode distinct patterns after a learning phase. In a case study, it is demonstrated how specific neurons in a feature classifier layer become orientation selective if they receive bar patterns of different slopes from an input layer. The input layer is mapped and intertwined by self-evolving neuronal microcircuits to the feature classifier layer. In this topical overview, several models are discussed which indicate that the net formation converges in its functionality to a mathematical transform which maps the input pattern space to a feature representing output space. The self-learning of the mathematical transform is discussed and its implications are interpreted. Model assumptions are deduced which serve as a guide to apply model derived repetitive stimuli pattern sets to in vitro cultures of neuron ensembles to condition them to learn and execute a mathematical transform.

  14. Laboratory Modeling of Aspects of Large Fires,

    Science.gov (United States)

    1984-04-30

    7 -7 g~L AD-A153 152 DNA-TR- 84-18 LABORATORY MODELING OF ASPECTS OF LARGE FIRES G.F. Carrier "URARY F.E. Fendell b DVSO R.D. Fleeter N. Got L.M...I1I TITLE (include Socurty Olassihicarion) LABORATORY MODELING OF ASPECTS OF LARGE FIRES 12. PERSONAL AUrHoR(S G.F. Carrier F.E. Fendell R.D. Fleeter N...Motorbuch Verlag.___ Caidin, M. (1960). A Torch to the Enemy: the Fire Raid on Tokyo. New York, NY: Ballantine. Carrier, G. F., Fendell , F. E., and

  15. Large scale topic modeling made practical

    DEFF Research Database (Denmark)

    Wahlgreen, Bjarne Ørum; Hansen, Lars Kai

    2011-01-01

    Topic models are of broad interest. They can be used for query expansion and result structuring in information retrieval and as an important component in services such as recommender systems and user adaptive advertising. In large scale applications both the size of the database (number of docume......Topic models are of broad interest. They can be used for query expansion and result structuring in information retrieval and as an important component in services such as recommender systems and user adaptive advertising. In large scale applications both the size of the database (number...... topics at par with a much larger case specific vocabulary....

  16. Minimum-norm cortical source estimation in layered head models is robust against skull conductivity error.

    Science.gov (United States)

    Stenroos, Matti; Hauk, Olaf

    2013-11-01

    The conductivity profile of the head has a major effect on EEG signals, but unfortunately the conductivity for the most important compartment, skull, is only poorly known. In dipole modeling studies, errors in modeled skull conductivity have been considered to have a detrimental effect on EEG source estimation. However, as dipole models are very restrictive, those results cannot be generalized to other source estimation methods. In this work, we studied the sensitivity of EEG and combined MEG+EEG source estimation to errors in skull conductivity using a distributed source model and minimum-norm (MN) estimation. We used a MEG/EEG modeling set-up that reflected state-of-the-art practices of experimental research. Cortical surfaces were segmented and realistically-shaped three-layer anatomical head models were constructed, and forward models were built with Galerkin boundary element method while varying the skull conductivity. Lead-field topographies and MN spatial filter vectors were compared across conductivities, and the localization and spatial spread of the MN estimators were assessed using intuitive resolution metrics. The results showed that the MN estimator is robust against errors in skull conductivity: the conductivity had a moderate effect on amplitudes of lead fields and spatial filter vectors, but the effect on corresponding morphologies was small. The localization performance of the EEG or combined MEG+EEG MN estimator was only minimally affected by the conductivity error, while the spread of the estimate varied slightly. Thus, the uncertainty with respect to skull conductivity should not prevent researchers from applying minimum norm estimation to EEG or combined MEG+EEG data. Comparing our results to those obtained earlier with dipole models shows that general judgment on the performance of an imaging modality should not be based on analysis with one source estimation method only.

  17. Cortical metabolites as biomarkers in the R6/2 model of Huntington's disease.

    Science.gov (United States)

    Zacharoff, Lori; Tkac, Ivan; Song, Qingfeng; Tang, Chuanning; Bolan, Patrick J; Mangia, Silvia; Henry, Pierre-Gilles; Li, Tongbin; Dubinsky, Janet M

    2012-03-01

    To improve the ability to move from preclinical trials in mouse models of Huntington's disease (HD) to clinical trials in humans, biomarkers are needed that can track similar aspects of disease progression across species. Brain metabolites, detectable by magnetic resonance spectroscopy (MRS), have been suggested as potential biomarkers in HD. In this study, the R6/2 transgenic mouse model of HD was used to investigate the relative sensitivity of the metabolite profiling and the brain volumetry to anticipate the disease progression. Magnetic resonance imaging (MRI) and (1)H MRS data were acquired at 9.4 T from the R6/2 mice and wild-type littermates at 4, 8, 12, and 15 weeks. Brain shrinkage was detectable in striatum, cortex, thalamus, and hypothalamus by 12 weeks. Metabolite changes in cortex paralleled and sometimes preceded those in striatum. The entire set of metabolite changes was compressed into principal components (PCs) using Partial Least Squares-Discriminant Analysis (PLS-DA) to increase the sensitivity for monitoring disease progression. In comparing the efficacy of volume and metabolite measurements, the cortical PC1 emerged as the most sensitive single biomarker, distinguishing R6/2 mice from littermates at all time points. Thus, neurochemical changes precede volume shrinkage and become potential biomarkers for HD mouse models.

  18. A mathematical model of cortical bone remodeling at cellular level under mechanical stimulus

    Institute of Scientific and Technical Information of China (English)

    Qing-Hua Qin; Ya-Nan Wang

    2012-01-01

    A bone cell population dynamics model for cortical bone remodeling under mechanical stimulus is developed in this paper.The external experiments extracted from the literature which have not been used in the creation of the model are used to test the validity of the model.Not only can the model compare reasonably well with these experimental results such as the increase percentage of final values of bone mineral content (BMC) and bone fracture energy (BFE) among different loading schemes (which proves the validity of the model),but also predict the realtime development pattern of BMC and BFE,as well as the dynamics of osteoblasts (OBA),osteoclasts (OCA),nitric oxide (NO) and prostaglandin E2 (PGE2) for each loading scheme,which can hardly be monitored through experiment.In conclusion,the model is the first of its kind that is able to provide an insight into the quantitative mechanism of bone remodeling at cellular level by which bone cells are activated by mechanical stimulus in order to start resorption/formation of bone mass.More importantly,this model has laid a solid foundation based on which future work such as systemic control theory analysis of bone remodeling under mechanical stimulus can be investigated.The to-be identified control mechanism will help to develop effective drugs and combined nonpharmacological therapies to combat bone loss pathologies.Also this deeper understanding of how mechanical forces quantitatively interact with skeletal tissue is essential for the generation of bone tissue for tissue replacement purposes in tissue engineering.

  19. An in silico agent-based model demonstrates Reelin function in directing lamination of neurons during cortical development.

    Directory of Open Access Journals (Sweden)

    James R Caffrey

    Full Text Available The characteristic six-layered appearance of the neocortex arises from the correct positioning of pyramidal neurons during development and alterations in this process can cause intellectual disabilities and developmental delay. Malformations in cortical development arise when neurons either fail to migrate properly from the germinal zones or fail to cease migration in the correct laminar position within the cortical plate. The Reelin signalling pathway is vital for correct neuronal positioning as loss of Reelin leads to a partially inverted cortex. The precise biological function of Reelin remains controversial and debate surrounds its role as a chemoattractant or stop signal for migrating neurons. To investigate this further we developed an in silico agent-based model of cortical layer formation. Using this model we tested four biologically plausible hypotheses for neuron motility and four biologically plausible hypotheses for the loss of neuron motility (conversion from migration. A matrix of 16 combinations of motility and conversion rules was applied against the known structure of mouse cortical layers in the wild-type cortex, the Reelin-null mutant, the Dab1-null mutant and a conditional Dab1 mutant. Using this approach, many combinations of motility and conversion mechanisms can be rejected. For example, the model does not support Reelin acting as a repelling or as a stopping signal. In contrast, the study lends very strong support to the notion that the glycoprotein Reelin acts as a chemoattractant for neurons. Furthermore, the most viable proposition for the conversion mechanism is one in which conversion is affected by a motile neuron sensing in the near vicinity neurons that have already converted. Therefore, this model helps elucidate the function of Reelin during neuronal migration and cortical development.

  20. Modeling capillary forces for large displacements

    NARCIS (Netherlands)

    Mastrangeli, M.; Arutinov, G.; Smits, E.C.P.; Lambert, P.

    2014-01-01

    Originally applied to the accurate, passive positioning of submillimetric devices, recent works proved capillary self-alignment as effective also for larger components and relatively large initial offsets. In this paper, we describe an analytic quasi-static model of 1D capillary restoring forces tha

  1. Pronunciation Modeling for Large Vocabulary Speech Recognition

    Science.gov (United States)

    Kantor, Arthur

    2010-01-01

    The large pronunciation variability of words in conversational speech is one of the major causes of low accuracy in automatic speech recognition (ASR). Many pronunciation modeling approaches have been developed to address this problem. Some explicitly manipulate the pronunciation dictionary as well as the set of the units used to define the…

  2. Inverse modeling for Large-Eddy simulation

    NARCIS (Netherlands)

    Geurts, Bernardus J.

    1998-01-01

    Approximate higher order polynomial inversion of the top-hat filter is developed with which the turbulent stress tensor in Large-Eddy Simulation can be consistently represented using the filtered field. Generalized (mixed) similarity models are proposed which improved the agreement with the kinetic

  3. Reconstructing cortical current density by exploring sparseness in the transform domain.

    Science.gov (United States)

    Ding, Lei

    2009-05-07

    In the present study, we have developed a novel electromagnetic source imaging approach to reconstruct extended cortical sources by means of cortical current density (CCD) modeling and a novel EEG imaging algorithm which explores sparseness in cortical source representations through the use of L1-norm in objective functions. The new sparse cortical current density (SCCD) imaging algorithm is unique since it reconstructs cortical sources by attaining sparseness in a transform domain (the variation map of cortical source distributions). While large variations are expected to occur along boundaries (sparseness) between active and inactive cortical regions, cortical sources can be reconstructed and their spatial extents can be estimated by locating these boundaries. We studied the SCCD algorithm using numerous simulations to investigate its capability in reconstructing cortical sources with different extents and in reconstructing multiple cortical sources with different extent contrasts. The SCCD algorithm was compared with two L2-norm solutions, i.e. weighted minimum norm estimate (wMNE) and cortical LORETA. Our simulation data from the comparison study show that the proposed sparse source imaging algorithm is able to accurately and efficiently recover extended cortical sources and is promising to provide high-accuracy estimation of cortical source extents.

  4. Spatial learning and action planning in a prefrontal cortical network model.

    Science.gov (United States)

    Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

    2011-05-01

    The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive "insight" capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates.

  5. A mathematical model relating cortical oxygenated and deoxygenated hemoglobin flows and volumes to neural activity

    Science.gov (United States)

    Cornelius, Nathan R.; Nishimura, Nozomi; Suh, Minah; Schwartz, Theodore H.; Doerschuk, Peter C.

    2015-08-01

    Objective. To describe a toolkit of components for mathematical models of the relationship between cortical neural activity and space-resolved and time-resolved flows and volumes of oxygenated and deoxygenated hemoglobin motivated by optical intrinsic signal imaging (OISI). Approach. Both blood flow and blood volume and both oxygenated and deoxygenated hemoglobin and their interconversion are accounted for. Flow and volume are described by including analogies to both resistive and capacitive electrical circuit elements. Oxygenated and deoxygenated hemoglobin and their interconversion are described by generalization of Kirchhoff's laws based on well-mixed compartments. Main results. Mathematical models built from this toolkit are able to reproduce experimental single-stimulus OISI results that are described in papers from other research groups and are able to describe the response to multiple-stimuli experiments as a sublinear superposition of responses to the individual stimuli. Significance. The same assembly of tools from the toolkit but with different parameter values is able to describe effects that are considered distinctive, such as the presence or absence of an initial decrease in oxygenated hemoglobin concentration, indicating that the differences might be due to unique parameter values in a subject rather than different fundamental mechanisms.

  6. Automated Sperm Head Detection Using Intersecting Cortical Model Optimised by Particle Swarm Optimization

    Science.gov (United States)

    Tan, Weng Chun; Mat Isa, Nor Ashidi

    2016-01-01

    In human sperm motility analysis, sperm segmentation plays an important role to determine the location of multiple sperms. To ensure an improved segmentation result, the Laplacian of Gaussian filter is implemented as a kernel in a pre-processing step before applying the image segmentation process to automatically segment and detect human spermatozoa. This study proposes an intersecting cortical model (ICM), which was derived from several visual cortex models, to segment the sperm head region. However, the proposed method suffered from parameter selection; thus, the ICM network is optimised using particle swarm optimization where feature mutual information is introduced as the new fitness function. The final results showed that the proposed method is more accurate and robust than four state-of-the-art segmentation methods. The proposed method resulted in rates of 98.14%, 98.82%, 86.46% and 99.81% in accuracy, sensitivity, specificity and precision, respectively, after testing with 1200 sperms. The proposed algorithm is expected to be implemented in analysing sperm motility because of the robustness and capability of this algorithm. PMID:27632581

  7. Mutation of Semaphorin-6A disrupts limbic and cortical connectivity and models neurodevelopmental psychopathology.

    LENUS (Irish Health Repository)

    2011-01-01

    Psychiatric disorders such as schizophrenia and autism are characterised by cellular disorganisation and dysconnectivity across the brain and can be caused by mutations in genes that control neurodevelopmental processes. To examine how neurodevelopmental defects can affect brain function and behaviour, we have comprehensively investigated the consequences of mutation of one such gene, Semaphorin-6A, on cellular organisation, axonal projection patterns, behaviour and physiology in mice. These analyses reveal a spectrum of widespread but subtle anatomical defects in Sema6A mutants, notably in limbic and cortical cellular organisation, lamination and connectivity. These mutants display concomitant alterations in the electroencephalogram and hyper-exploratory behaviour, which are characteristic of models of psychosis and reversible by the antipsychotic clozapine. They also show altered social interaction and deficits in object recognition and working memory. Mice with mutations in Sema6A or the interacting genes may thus represent a highly informative model for how neurodevelopmental defects can lead to anatomical dysconnectivity, resulting, either directly or through reactive mechanisms, in dysfunction at the level of neuronal networks with associated behavioural phenotypes of relevance to psychiatric disorders. The biological data presented here also make these genes plausible candidates to explain human linkage findings for schizophrenia and autism.

  8. Spatial learning and action planning in a prefrontal cortical network model.

    Directory of Open Access Journals (Sweden)

    Louis-Emmanuel Martinet

    2011-05-01

    Full Text Available The interplay between hippocampus and prefrontal cortex (PFC is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive "insight" capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates.

  9. Spatial occupancy models for large data sets

    Science.gov (United States)

    Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

    2013-01-01

    Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

  10. [Cortical blindness].

    Science.gov (United States)

    Chokron, S

    2014-02-01

    Cortical blindness refers to a visual loss induced by a bilateral occipital lesion. The very strong cooperation between psychophysics, cognitive psychology, neurophysiology and neuropsychology these latter twenty years as well as recent progress in cerebral imagery have led to a better understanding of neurovisual deficits, such as cortical blindness. It thus becomes possible now to propose an earlier diagnosis of cortical blindness as well as new perspectives for rehabilitation in children as well as in adults. On the other hand, studying complex neurovisual deficits, such as cortical blindness is a way to infer normal functioning of the visual system.

  11. Reduced GABAergic inhibition explains cortical hyperexcitability in the wobbler mouse model of ALS

    DEFF Research Database (Denmark)

    Nieto-Gonzalez, Jose Luis; Moser, Jakob; Lauritzen, Martin

    2011-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive degenerative disease of the central nervous system. Symptomatic and presymptomatic ALS patients demonstrate cortical hyperexcitability, which raises the possibility that alterations in inhibitory gamma-aminobutyric acid (GABA)ergic system could...

  12. Evolving Models of Pavlovian Conditioning : Cerebellar Cortical Dynamics in Awake Behaving Mice

    NARCIS (Netherlands)

    Ten Brinke, Michiel M; Boele, Henk-Jan; Spanke, Jochen K; Potters, Jan-Willem; Kornysheva, Katja; Wulff, Peer; IJpelaar, Anna C H G; Koekkoek, Sebastiaan K E; De Zeeuw, Chris I

    2015-01-01

    Three decades of electrophysiological research on cerebellar cortical activity underlying Pavlovian conditioning have expanded our understanding of motor learning in the brain. Purkinje cell simple spike suppression is considered to be crucial in the expression of conditional blink responses (CRs).

  13. Design and Fabrication of 3D printed Scaffolds with a Mechanical Strength Comparable to Cortical Bone to Repair Large Bone Defects.

    Science.gov (United States)

    Roohani-Esfahani, Seyed-Iman; Newman, Peter; Zreiqat, Hala

    2016-01-19

    A challenge in regenerating large bone defects under load is to create scaffolds with large and interconnected pores while providing a compressive strength comparable to cortical bone (100-150 MPa). Here we design a novel hexagonal architecture for a glass-ceramic scaffold to fabricate an anisotropic, highly porous three dimensional scaffolds with a compressive strength of 110 MPa. Scaffolds with hexagonal design demonstrated a high fatigue resistance (1,000,000 cycles at 1-10 MPa compressive cyclic load), failure reliability and flexural strength (30 MPa) compared with those for conventional architecture. The obtained strength is 150 times greater than values reported for polymeric and composite scaffolds and 5 times greater than reported values for ceramic and glass scaffolds at similar porosity. These scaffolds open avenues for treatment of load bearing bone defects in orthopaedic, dental and maxillofacial applications.

  14. Design and Fabrication of 3D printed Scaffolds with a Mechanical Strength Comparable to Cortical Bone to Repair Large Bone Defects

    Science.gov (United States)

    Roohani-Esfahani, Seyed-Iman; Newman, Peter; Zreiqat, Hala

    2016-01-01

    A challenge in regenerating large bone defects under load is to create scaffolds with large and interconnected pores while providing a compressive strength comparable to cortical bone (100–150 MPa). Here we design a novel hexagonal architecture for a glass-ceramic scaffold to fabricate an anisotropic, highly porous three dimensional scaffolds with a compressive strength of 110 MPa. Scaffolds with hexagonal design demonstrated a high fatigue resistance (1,000,000 cycles at 1–10 MPa compressive cyclic load), failure reliability and flexural strength (30 MPa) compared with those for conventional architecture. The obtained strength is 150 times greater than values reported for polymeric and composite scaffolds and 5 times greater than reported values for ceramic and glass scaffolds at similar porosity. These scaffolds open avenues for treatment of load bearing bone defects in orthopaedic, dental and maxillofacial applications.

  15. Computational Modeling of Large Wildfires: A Roadmap

    KAUST Repository

    Coen, Janice L.

    2010-08-01

    Wildland fire behavior, particularly that of large, uncontrolled wildfires, has not been well understood or predicted. Our methodology to simulate this phenomenon uses high-resolution dynamic models made of numerical weather prediction (NWP) models coupled to fire behavior models to simulate fire behavior. NWP models are capable of modeling very high resolution (< 100 m) atmospheric flows. The wildland fire component is based upon semi-empirical formulas for fireline rate of spread, post-frontal heat release, and a canopy fire. The fire behavior is coupled to the atmospheric model such that low level winds drive the spread of the surface fire, which in turn releases sensible heat, latent heat, and smoke fluxes into the lower atmosphere, feeding back to affect the winds directing the fire. These coupled dynamic models capture the rapid spread downwind, flank runs up canyons, bifurcations of the fire into two heads, and rough agreement in area, shape, and direction of spread at periods for which fire location data is available. Yet, intriguing computational science questions arise in applying such models in a predictive manner, including physical processes that span a vast range of scales, processes such as spotting that cannot be modeled deterministically, estimating the consequences of uncertainty, the efforts to steer simulations with field data ("data assimilation"), lingering issues with short term forecasting of weather that may show skill only on the order of a few hours, and the difficulty of gathering pertinent data for verification and initialization in a dangerous environment. © 2010 IEEE.

  16. A 3D Multiscale Modelling of Cortical Bone Structure, Using the Inverse Identification Method: Microfibril Scale Study

    CERN Document Server

    Barkaoui, Abdelwahed

    2011-01-01

    Complexity and heterogeneity of bone tissue require a multiscale modelling to understand their mechanical behaviour and their remodelling mechanism. Human cortical bone structure consists of six structural scale levels which are the (macroscopic) cortical bone, osteonal, lamellar, fibrous, fibril and microfibril. In this paper, a 3D model based on finite elements method was achieved to study the nanomechanical behaviour of collagen Microfibril. The mechanical properties and the geometry (gap, overlap and diameter) of both tropocollagen and mineral were taken into consideration as well as the effects of cross-links. An inverse identification method has been applied to determine equivalent averaged properties in order to link up these nanoscopic characteristics to the macroscopic mechanical behaviour of bone tissue. Results of nanostructure modelling of the nanomechanical properties of strain deformation under varying cross-links were investigated in this work.

  17. Improved dimensionally-reduced visual cortical network using stochastic noise modeling.

    Science.gov (United States)

    Tao, Louis; Praissman, Jeremy; Sornborger, Andrew T

    2012-04-01

    In this paper, we extend our framework for constructing low-dimensional dynamical system models of large-scale neuronal networks of mammalian primary visual cortex. Our dimensional reduction procedure consists of performing a suitable linear change of variables and then systematically truncating the new set of equations. The extended framework includes modeling the effect of neglected modes as a stochastic process. By parametrizing and including stochasticity in one of two ways we show that we can improve the systems-level characterization of our dimensionally reduced neuronal network model. We examined orientation selectivity maps calculated from the firing rate distribution of large-scale simulations and stochastic dimensionally reduced models and found that by using stochastic processes to model the neglected modes, we were able to better reproduce the mean and variance of firing rates in the original large-scale simulations while still accurately predicting the orientation preference distribution.

  18. Ion channel density and threshold dynamics of repetitive firing in a cortical neuron model.

    Science.gov (United States)

    Arhem, Peter; Blomberg, Clas

    2007-01-01

    Modifying the density and distribution of ion channels in a neuron (by natural up- and down-regulation, by pharmacological intervention or by spontaneous mutations) changes its activity pattern. In the present investigation, we analyze how the impulse patterns are regulated by the density of voltage-gated channels in a model neuron, based on voltage clamp measurements of hippocampal interneurons. At least three distinct oscillatory patterns, associated with three distinct regions in the Na-K channel density plane, were found. A stability analysis showed that the different regions are characterized by saddle-node, double-orbit, and Hopf bifurcation threshold dynamics, respectively. Single strongly graded action potentials occur in an area outside the oscillatory regions, but less graded action potentials occur together with repetitive firing over a considerable range of channel densities. The presently found relationship between channel densities and oscillatory behavior may be relevance for understanding principal spiking patterns of cortical neurons (regular firing and fast spiking). It may also be of relevance for understanding the action of pharmacological compounds on brain oscillatory activity.

  19. Spiking cortical model based non-local means method for despeckling multiframe optical coherence tomography data

    Science.gov (United States)

    Gu, Yameng; Zhang, Xuming

    2017-05-01

    Optical coherence tomography (OCT) images are severely degraded by speckle noise. Existing methods for despeckling multiframe OCT data cannot deliver sufficient speckle suppression while preserving image details well. To address this problem, the spiking cortical model (SCM) based non-local means (NLM) method has been proposed in this letter. In the proposed method, the considered frame and two neighboring frames are input into three SCMs to generate the temporal series of pulse outputs. The normalized moment of inertia (NMI) of the considered patches in the pulse outputs is extracted to represent the rotational and scaling invariant features of the corresponding patches in each frame. The pixel similarity is computed based on the Euclidean distance between the NMI features and used as the weight. Each pixel in the considered frame is restored by the weighted averaging of all pixels in the pre-defined search window in the three frames. Experiments on the real multiframe OCT data of the pig eye demonstrate the advantage of the proposed method over the frame averaging method, the multiscale sparsity based tomographic denoising method, the wavelet-based method and the traditional NLM method in terms of visual inspection and objective metrics such as signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), equivalent number of looks (ENL) and cross-correlation (XCOR).

  20. Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

    Science.gov (United States)

    Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

    2016-09-15

    Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.

  1. Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor

    Directory of Open Access Journals (Sweden)

    Xuming Zhang

    2016-09-01

    Full Text Available Multimodal medical image fusion (MIF plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.

  2. Nonlinear analysis and modeling of cortical activation and deactivation patterns in the immature fetal electrocorticogram

    Science.gov (United States)

    Schwab, Karin; Groh, Tobias; Schwab, Matthias; Witte, Herbert

    2009-03-01

    An approach combining time-continuous nonlinear stability analysis and a parametric bispectral method was introduced to better describe cortical activation and deactivation patterns in the immature fetal electroencephalogram (EEG). Signal models and data-driven investigations were performed to find optimal parameters of the nonlinear methods and to confirm the occurrence of nonlinear sections in the fetal EEG. The resulting measures were applied to the in utero electrocorticogram (ECoG) of fetal sheep at 0.7 gestation when organized sleep states were not developed and compared to previous results at 0.9 gestation. Cycling of the nonlinear stability of the fetal ECoG occurred already at this early gestational age, suggesting the presence of premature sleep states. This was accompanied by cycling of the time-variant biamplitude which reflected ECoG synchronization effects during premature sleep states associated with nonrapid eye movement sleep later in gestation. Thus, the combined nonlinear and time-variant approach was able to provide important insights into the properties of the immature fetal ECoG.

  3. Progesterone Treatment Shows Benefit in Female Rats in a Pediatric Model of Controlled Cortical Impact Injury.

    Directory of Open Access Journals (Sweden)

    Rastafa I Geddes

    Full Text Available We recently showed that progesterone treatment can reduce lesion size and behavioral deficits after moderate-to-severe bilateral injury to the medial prefrontal cortex in immature male rats. Whether there are important sex differences in response to injury and progesterone treatment in very young subjects has not been given sufficient attention. Here we investigated progesterone's effects in the same model of brain injury but with pre-pubescent females.Twenty-eight-day-old female Sprague-Dawley rats received sham (n = 14 or controlled cortical impact (CCI (n = 21 injury, were given progesterone (8 mg/kg body weight or vehicle injections on post-injury days (PID 1-7, and underwent behavioral testing from PID 9-27. Brains were evaluated for lesion size at PID 28.Lesion size in vehicle-treated female rats with CCI injury was smaller than that previously reported for similarly treated age-matched male rats. Treatment with progesterone reduced the effect of CCI on extent of damage and behavioral deficits.Pre-pubescent female rats with midline CCI injury to the frontal cortex have reduced morphological and functional deficits following progesterone treatment. While gender differences in susceptibility to this injury were observed, progesterone treatment produced beneficial effects in young rats of both sexes following CCI.

  4. An economic model of large Medicaid practices.

    Science.gov (United States)

    Cromwell, J; Mitchell, J B

    1984-06-01

    Public attention given to Medicaid "mills" prompted this more general investigation of the origins of large Medicaid practices. A dual market demand model is proposed showing how Medicaid competes with private insurers for scarce physician time. Various program parameters--fee schedules, coverage, collection costs--are analyzed along with physician preferences, specialties, and other supply-side characteristics. Maximum likelihood techniques are used to test the model. The principal finding is that in raising Medicaid fees, as many physicians opt into the program as expand their Medicaid caseloads to exceptional levels, leaving the maldistribution of patients unaffected while notably improving access. Still, the fact that Medicaid fees are lower than those of private insurers does lead to reduced access to more qualified practitioners. Where anti-Medicaid sentiment is stronger, access is also reduced and large Medicaid practices more likely to flourish.

  5. Engineering large animal models of human disease.

    Science.gov (United States)

    Whitelaw, C Bruce A; Sheets, Timothy P; Lillico, Simon G; Telugu, Bhanu P

    2016-01-01

    The recent development of gene editing tools and methodology for use in livestock enables the production of new animal disease models. These tools facilitate site-specific mutation of the genome, allowing animals carrying known human disease mutations to be produced. In this review, we describe the various gene editing tools and how they can be used for a range of large animal models of diseases. This genomic technology is in its infancy but the expectation is that through the use of gene editing tools we will see a dramatic increase in animal model resources available for both the study of human disease and the translation of this knowledge into the clinic. Comparative pathology will be central to the productive use of these animal models and the successful translation of new therapeutic strategies.

  6. Large-scale multimedia modeling applications

    Energy Technology Data Exchange (ETDEWEB)

    Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.

    1995-08-01

    Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications.

  7. The relationship of three cortical regions to an information-processing model.

    Science.gov (United States)

    Anderson, John R; Qin, Yulin; Stenger, V Andrew; Carter, Cameron S

    2004-05-01

    This research tests a model of the computational role of three cortical regions in tasks like algebra equation solving. The model assumes that there is a left parietal region-of-interest (ROI) where the problem expression is represented and transformed, a left prefrontal ROI where information for solving the task is retrieved, and a motor ROI where hand movements to produce the answer are programmed. A functional magnetic resonance imaging (fMRI) study of an abstract symbol-manipulation task was performed to articulate the roles of these three regions. Participants learned to associate words with instructions for transforming strings of letters. The study manipulated the need to retrieve these instructions, the need to transform the strings, and whether there was a delay between calculation of the answer and the output of the answer. As predicted, the left parietal ROI mainly reflected the need for a transformation and the left prefrontal ROI the need for retrieval. Homologous right ROIs showed similar but weaker responses. Neither the prefrontal nor the parietal ROIs responded to delay, but the motor ROI did respond to delay, implying motor rehearsal over the delay. Except for the motor ROI, these patterns of activity did not vary with response hand. In an ACT-R model, it was shown that the activity of an imaginal buffer predicted the blood oxygen level-dependent (BOLD) response of the parietal ROI, the activity of a retrieval buffer predicted the response of the prefrontal ROI, and the activity of a manual buffer predicted the response of the motor ROI.

  8. Cortical and hippocampal correlates of deliberation during model-based decisions for rewards in humans.

    Directory of Open Access Journals (Sweden)

    Aaron M Bornstein

    Full Text Available How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward - such as when planning routes using a cognitive map or chess moves using predicted countermoves - and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to

  9. Cortical imaging on a head template: a simulation study using a resistor mesh model (RMM).

    Science.gov (United States)

    Chauveau, Nicolas; Franceries, Xavier; Aubry, Florent; Celsis, Pierre; Rigaud, Bernard

    2008-09-01

    The T1 head template model used in Statistical Parametric Mapping Version 2000 (SPM2), was segmented into five layers (scalp, skull, CSF, grey and white matter) and implemented in 2 mm voxels. We designed a resistor mesh model (RMM), based on the finite volume method (FVM) to simulate the electrical properties of this head model along the three axes for each voxel. Then, we introduced four dipoles of high eccentricity (about 0.8) in this RMM, separately and simultaneously, to compute the potentials for two sets of conductivities. We used the direct cortical imaging technique (CIT) to recover the simulated dipoles, using 60 or 107 electrodes and with or without addition of Gaussian white noise (GWN). The use of realistic conductivities gave better CIT results than standard conductivities, lowering the blurring effect on scalp potentials and displaying more accurate position areas when CIT was applied to single dipoles. Simultaneous dipoles were less accurately localized, but good qualitative and stable quantitative results were obtained up to 5% noise level for 107 electrodes and up to 10% noise level for 60 electrodes, showing that a compromise must be found to optimize both the number of electrodes and the noise level. With the RMM defined in 2 mm voxels, the standard 128-electrode cap and 5% noise appears to be the upper limit providing reliable source positions when direct CIT is used. The admittance matrix defining the RMM is easy to modify so as to adapt to different conductivities. The next step will be the adaptation of individual real head T2 images to the RMM template and the introduction of anisotropy using diffusion imaging (DI).

  10. Overweight is not associated with cortical thickness alterations in children

    Directory of Open Access Journals (Sweden)

    Rachel Jane Sharkey

    2015-02-01

    Full Text Available IntroductionSeveral studies report an association between body mass index (BMI and cortical thickness in adults. Some studies demonstrate diffuse cortical thinning in obesity, while others report effects in areas that are associated with self-regulation, such as lateral prefrontal cortex. MethodsThis study used multilevel modelling of data from the NIH Pediatric MRI Data Repository, a mixed longitudinal and cross-sectional database, to examine the relationship between cortical thickness and body weight in children. Cortical thickness was computed at 81,942 vertices of 716 MRI scans from 378 children aged between 4 and 18 years. Body mass index Z score for age was computed for each participant. We preformed vertex-wise statistical analysis of the relationship between cortical thickness and BMI, accounting for age and gender. In addition, cortical thickness was extracted from regions of interest in prefrontal cortex and insula.ResultsNo significant association between cortical thickness and BMI was found, either by statistical parametric mapping or by region of interest analysis. Results remained negative when the analysis was restricted to children aged 12-18.ConclusionsThe correlation between BMI and cortical thickness was not found in this large pediatric sample. The association between BMI and cortical thinning develops after adolescence. This has implications for the nature of the relationship between brain anatomy and weight gain.

  11. Large genetic animal models of Huntington's Disease.

    Science.gov (United States)

    Morton, A Jennifer; Howland, David S

    2013-01-01

    The dominant nature of the Huntington's disease gene mutation has allowed genetic models to be developed in multiple species, with the mutation causing an abnormal neurological phenotype in all animals in which it is expressed. Many different rodent models have been generated. The most widely used of these, the transgenic R6/2 mouse, carries the mutation in a fragment of the human huntingtin gene and has a rapidly progressive and fatal neurological phenotype with many relevant pathological changes. Nevertheless, their rapid decline has been frequently questioned in the context of a disease that takes years to manifest in humans, and strenuous efforts have been made to make rodent models that are genetically more 'relevant' to the human condition, including full length huntingtin gene transgenic and knock-in mice. While there is no doubt that we have learned, and continue to learn much from rodent models, their usefulness is limited by two species constraints. First, the brains of rodents differ significantly from humans in both their small size and their neuroanatomical organization. Second, rodents have much shorter lifespans than humans. Here, we review new approaches taken to these challenges in the development of models of Huntington's disease in large brained, long-lived animals. We discuss the need for such models, and how they might be used to fill specific niches in preclinical Huntington's disease research, particularly in testing gene-based therapeutics. We discuss the advantages and disadvantages of animals in which the prodromal period of disease extends over a long time span. We suggest that there is considerable 'value added' for large animal models in preclinical Huntington's disease research.

  12. How the cortex gets its folds: an inside-out, connectivity-driven model for the scaling of mammalian cortical folding

    Directory of Open Access Journals (Sweden)

    Bruno eMota

    2012-02-01

    Full Text Available Larger mammalian cerebral cortices tend to have increasingly folded surfaces, often considered to result from the lateral expansion of the grey matter (GM, which, in a volume constrained by the cranium, causes mechanical compression that is relieved by inward folding of the white matter (WM, or to result from differential expansion of cortical layers. Across species, thinner cortices, presumably more pliable, would offer less resistance and hence become more folded than thicker cortices of a same size. However, such models do not acknowledge evidence in favor of a tension-based pull onto the GM from the inside, holding it in place even when the constraint imposed by the cranium is removed. Here we propose a testable, quantitative model of cortical folding driven by tension along the length of axons in the WM that assumes that connections through the WM are formed early in development, at the same time as the GM becomes folded, and considers that axonal connections through the WM generate tension that leads to inward folding of the WM surface, which pulls the GM surface inwards. Cortical folding is thus driven by WM connectivity, and is a function of the fraction of cortical neurons connected through the WM, the average length and the average cross-sectional area of the axons in the WM. Our model predicts that the different scaling of cortical folding across mammalian orders corresponds to different combinations of scaling of connectivity, axonal cross-sectional area and tension along WM axons, instead of being a simple function of the number of GM neurons. Our model also explains variations in cortical thickness as a result of the factors that lead to cortical folding, rather than as a determinant of folding; predicts that for a same tension, folding increases with connectivity through the WM and increased axonal cross-section; and that, for a same number of neurons, higher connectivity through the WM leads to a higher degree of folding as well

  13. Trading speed and accuracy by coding time: a coupled-circuit cortical model.

    Directory of Open Access Journals (Sweden)

    Dominic Standage

    2013-04-01

    Full Text Available Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by 'climbing' activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification.

  14. Identifiability of large phylogenetic mixture models.

    Science.gov (United States)

    Rhodes, John A; Sullivant, Seth

    2012-01-01

    Phylogenetic mixture models are statistical models of character evolution allowing for heterogeneity. Each of the classes in some unknown partition of the characters may evolve by different processes, or even along different trees. Such models are of increasing interest for data analysis, as they can capture the variety of evolutionary processes that may be occurring across long sequences of DNA or proteins. The fundamental question of whether parameters of such a model are identifiable is difficult to address, due to the complexity of the parameterization. Identifiability is, however, essential to their use for statistical inference.We analyze mixture models on large trees, with many mixture components, showing that both numerical and tree parameters are indeed identifiable in these models when all trees are the same. This provides a theoretical justification for some current empirical studies, and indicates that extensions to even more mixture components should be theoretically well behaved. We also extend our results to certain mixtures on different trees, using the same algebraic techniques.

  15. Large animal models for stem cell therapy.

    Science.gov (United States)

    Harding, John; Roberts, R Michael; Mirochnitchenko, Oleg

    2013-03-28

    The field of regenerative medicine is approaching translation to clinical practice, and significant safety concerns and knowledge gaps have become clear as clinical practitioners are considering the potential risks and benefits of cell-based therapy. It is necessary to understand the full spectrum of stem cell actions and preclinical evidence for safety and therapeutic efficacy. The role of animal models for gaining this information has increased substantially. There is an urgent need for novel animal models to expand the range of current studies, most of which have been conducted in rodents. Extant models are providing important information but have limitations for a variety of disease categories and can have different size and physiology relative to humans. These differences can preclude the ability to reproduce the results of animal-based preclinical studies in human trials. Larger animal species, such as rabbits, dogs, pigs, sheep, goats, and non-human primates, are better predictors of responses in humans than are rodents, but in each case it will be necessary to choose the best model for a specific application. There is a wide spectrum of potential stem cell-based products that can be used for regenerative medicine, including embryonic and induced pluripotent stem cells, somatic stem cells, and differentiated cellular progeny. The state of knowledge and availability of these cells from large animals vary among species. In most cases, significant effort is required for establishing and characterizing cell lines, comparing behavior to human analogs, and testing potential applications. Stem cell-based therapies present significant safety challenges, which cannot be addressed by traditional procedures and require the development of new protocols and test systems, for which the rigorous use of larger animal species more closely resembling human behavior will be required. In this article, we discuss the current status and challenges of and several major directions

  16. Development of large Area Covering Height Model

    Science.gov (United States)

    Jacobsen, K.

    2014-04-01

    Height information is a basic part of topographic mapping. Only in special areas frequent update of height models is required, usually the update cycle is quite lower as for horizontal map information. Some height models are available free of charge in the internet; for commercial height models a fee has to be paid. Mostly digital surface models (DSM) with the height of the visible surface are given and not the bare ground height, as required for standard mapping. Nevertheless by filtering of DSM, digital terrain models (DTM) with the height of the bare ground can be generated with the exception of dense forest areas where no height of the bare ground is available. These height models may be better as the DTM of some survey administrations. In addition several DTM from national survey administrations are classified, so as alternative the commercial or free of charge available information from internet can be used. The widely used SRTM DSM is available also as ACE-2 GDEM corrected by altimeter data for systematic height errors caused by vegetation and orientation errors. But the ACE-2 GDEM did not respect neighbourhood information. With the worldwide covering TanDEM-X height model, distributed starting 2014 by Airbus Defence and Space (former ASTRIUM) as WorldDEM, higher level of details and accuracy is reached as with other large area covering height models. At first the raw-version of WorldDEM will be available, followed by an edited version and finally as WorldDEM-DTM a height model of the bare ground. With 12 m spacing and a relative standard deviation of 1.2 m within an area of 1° x 1° an accuracy and resolution level is reached, satisfying also for larger map scales. For limited areas with the HDEM also a height model with 6 m spacing and a relative vertical accuracy of 0.5 m can be generated on demand. By bathymetric LiDAR and stereo images also the height of the sea floor can be determined if the water has satisfying transparency. Another method of getting

  17. Linking physics with physiology in TMS: a sphere field model to determine the cortical stimulation site in TMS.

    Science.gov (United States)

    Thielscher, Axel; Kammer, Thomas

    2002-11-01

    A fundamental problem of transcranial magnetic stimulation (TMS) is determining the site and size of the stimulated cortical area. In the motor system, the most common procedure for this is motor mapping. The obtained two-dimensional distribution of coil positions with associated muscle responses is used to calculate a center of gravity on the skull. However, even in motor mapping the exact stimulation site on the cortex is not known and only rough estimates of its size are possible. We report a new method which combines physiological measurements with a physical model used to predict the electric field induced by the TMS coil. In four subjects motor responses in a small hand muscle were mapped with 9-13 stimulation sites at the head perpendicular to the central sulcus in order to keep the induced current direction constant in a given cortical region of interest. Input-output functions from these head locations were used to determine stimulator intensities that elicit half-maximal muscle responses. Based on these stimulator intensities the field distribution on the individual cortical surface was calculated as rendered from anatomical MR data. The region on the cortical surface in which the different stimulation sites produced the same electric field strength (minimal variance, 4.2 +/- 0.8%.) was determined as the most likely stimulation site on the cortex. In all subjects, it was located at the lateral part of the hand knob in the motor cortex. Comparisons of model calculations with the solutions obtained in this manner reveal that the stimulated cortex area innervating the target muscle is substantially smaller than the size of the electric field induced by the coil. Our results help to resolve fundamental questions raised by motor mapping studies as well as motor threshold measurements.

  18. Evolving Models of Pavlovian Conditioning: Cerebellar Cortical Dynamics in Awake Behaving Mice

    NARCIS (Netherlands)

    M. tenBrinke (MichielM.); H.J. Boele (Henk-Jan); J.K. Spanke (Jochen); J.W. Potters (Jan Willem); K. Kornysheva (Katja); P. Wulff (Peer); A.C.H.G. IJpelaar (Anna C.H.G.); S.K.E. Koekkoek (Bas); C.I. DeZeeuw (Chris)

    2015-01-01

    textabstractThree decades of electrophysiological research on cerebellar cortical activity underlying Pavlovian conditioning have expanded our understanding of motor learning in the brain. Purkinje cell simple spike suppression is considered to be crucial in the expression of conditional blink respo

  19. Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data

    DEFF Research Database (Denmark)

    Greve, Douglas N; Svarer, Claus; Fisher, Patrick M

    2014-01-01

    intersubject variance than when volume smoothing was used. This translates into more than 4 times fewer subjects needed in a group analysis to achieve similarly powered statistical tests. Surface-based smoothing has less bias and variance because it respects cortical geometry by smoothing the PET data only...

  20. Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields.

    Science.gov (United States)

    Ruffini, Giulio; Fox, Michael D; Ripolles, Oscar; Miranda, Pedro Cavaleiro; Pascual-Leone, Alvaro

    2014-04-01

    Recently, multifocal transcranial current stimulation (tCS) devices using several relatively small electrodes have been used to achieve more focal stimulation of specific cortical targets. However, it is becoming increasingly recognized that many behavioral manifestations of neurological and psychiatric disease are not solely the result of abnormality in one isolated brain region but represent alterations in brain networks. In this paper we describe a method for optimizing the configuration of multifocal tCS for stimulation of brain networks, represented by spatially extended cortical targets. We show how, based on fMRI, PET, EEG or other data specifying a target map on the cortical surface for excitatory, inhibitory or neutral stimulation and a constraint on the maximal number of electrodes, a solution can be produced with the optimal currents and locations of the electrodes. The method described here relies on a fast calculation of multifocal tCS electric fields (including components normal and tangential to the cortical boundaries) using a five layer finite element model of a realistic head. Based on the hypothesis that the effects of current stimulation are to first order due to the interaction of electric fields with populations of elongated cortical neurons, it is argued that the optimization problem for tCS stimulation can be defined in terms of the component of the electric field normal to the cortical surface. Solutions are found using constrained least squares to optimize current intensities, while electrode number and their locations are selected using a genetic algorithm. For direct current tCS (tDCS) applications, we provide some examples of this technique using an available tCS system providing 8 small Ag/AgCl stimulation electrodes. We demonstrate the approach both for localized and spatially extended targets defined using rs-fcMRI and PET data, with clinical applications in stroke and depression. Finally, we extend these ideas to more general

  1. Motor Cortex and Motor Cortical Interhemispheric Communication in Walking After Stroke: The Roles of Transcranial Magnetic Stimulation and Animal Models in Our Current and Future Understanding.

    Science.gov (United States)

    Charalambous, Charalambos C; Bowden, Mark G; Adkins, DeAnna L

    2016-01-01

    Despite the plethora of human neurophysiological research, the bilateral involvement of the leg motor cortical areas and their interhemispheric interaction during both normal and impaired human walking is poorly understood. Using transcranial magnetic stimulation (TMS), we have expanded our understanding of the role upper-extremity motor cortical areas play in normal movements and how stroke alters this role, and probed the efficacy of interventions to improve post-stroke arm function. However, similar investigations of the legs have lagged behind, in part, due to the anatomical difficulty in using TMS to stimulate the leg motor cortical areas. Additionally, leg movements are predominately bilaterally controlled and require interlimb coordination that may involve both hemispheres. The sensitive, but invasive, tools used in animal models of locomotion hold great potential for increasing our understanding of the bihemispheric motor cortical control of walking. In this review, we discuss 3 themes associated with the bihemispheric motor cortical control of walking after stroke: (a) what is known about the role of the bihemispheric motor cortical control in healthy and poststroke leg movements, (b) how the neural remodeling of the contralesional hemisphere can affect walking recovery after a stroke, and (c) what is the effect of behavioral rehabilitation training of walking on the neural remodeling of the motor cortical areas bilaterally. For each theme, we discuss how rodent models can enhance the present knowledge on human walking by testing hypotheses that cannot be investigated in humans, and how these findings can then be back-translated into the neurorehabilitation of poststroke walking.

  2. Non-Invasive Brain Stimulation to Enhance Upper Limb Motor Practice Poststroke: A Model for Selection of Cortical Site

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    Michelle L. Harris-Love

    2017-05-01

    Full Text Available Motor practice is an essential part of upper limb motor recovery following stroke. To be effective, it must be intensive with a high number of repetitions. Despite the time and effort required, gains made from practice alone are often relatively limited, and substantial residual impairment remains. Using non-invasive brain stimulation to modulate cortical excitability prior to practice could enhance the effects of practice and provide greater returns on the investment of time and effort. However, determining which cortical area to target is not trivial. The implications of relevant conceptual frameworks such as Interhemispheric Competition and Bimodal Balance Recovery are discussed. In addition, we introduce the STAC (Structural reserve, Task Attributes, Connectivity framework, which incorporates patient-, site-, and task-specific factors. An example is provided of how this framework can assist in selecting a cortical region to target for priming prior to reaching practice poststroke. We suggest that this expanded patient-, site-, and task-specific approach provides a useful model for guiding the development of more successful approaches to neuromodulation for enhancing motor recovery after stroke.

  3. Unsupervised learning of generative and discriminative weights encoding elementary image components in a predictive coding model of cortical function.

    Science.gov (United States)

    Spratling, M W

    2012-01-01

    A method is presented for learning the reciprocal feedforward and feedback connections required by the predictive coding model of cortical function. When this method is used, feedforward and feedback connections are learned simultaneously and independently in a biologically plausible manner. The performance of the proposed algorithm is evaluated by applying it to learning the elementary components of artificial and natural images. For artificial images, the bars problem is employed, and the proposed algorithm is shown to produce state-of-the-art performance on this task. For natural images, components resembling Gabor functions are learned in the first processing stage, and neurons responsive to corners are learned in the second processing stage. The properties of these learned representations are in good agreement with neurophysiological data from V1 and V2. The proposed algorithm demonstrates for the first time that a single computational theory can explain the formation of cortical RFs and also the response properties of cortical neurons once those RFs have been learned.

  4. Modeling of large area hot embossing

    CERN Document Server

    Worgull, M; Marcotte, J -P; Hétu, J -F; Heckele, M

    2008-01-01

    Today, hot embossing and injection molding belong to the established plastic molding processes in microengineering. Based on experimental findings, a variety of microstructures have been replicated so far using the processes. However, with increasing requirements regarding the embossing surface and the simultaneous decrease of the structure size down into the nanorange, increasing know-how is needed to adapt hot embossing to industrial standards. To reach this objective, a German-Canadian cooperation project has been launched to study hot embossing theoretically by a process simulation and experimentally. The present publication shall report about the first results of the simulation - the modeling and simulation of large area replication based on an eight inch microstructured mold.

  5. Model cortical association fields account for the time course and dependence on target complexity of human contour perception.

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    Vadas Gintautas

    2011-10-01

    Full Text Available Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas distributed among groups of randomly rotated fragments (clutter. The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms, followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least [Formula: see text] ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas.

  6. Linking microcircuit dysfunction to cognitive impairment: effects of disinhibition associated with schizophrenia in a cortical working memory model.

    Science.gov (United States)

    Murray, John D; Anticevic, Alan; Gancsos, Mark; Ichinose, Megan; Corlett, Philip R; Krystal, John H; Wang, Xiao-Jing

    2014-04-01

    Excitation-inhibition balance (E/I balance) is a fundamental property of cortical microcircuitry. Disruption of E/I balance in prefrontal cortex is hypothesized to underlie cognitive deficits observed in neuropsychiatric illnesses such as schizophrenia. To elucidate the link between these phenomena, we incorporated synaptic disinhibition, via N-methyl-D-aspartate receptor perturbation on interneurons, into a network model of spatial working memory (WM). At the neural level, disinhibition broadens the tuning of WM-related, stimulus-selective persistent activity patterns. The model predicts that this change at the neural level leads to 2 primary behavioral deficits: 1) increased behavioral variability that degrades the precision of stored information and 2) decreased ability to filter out distractors during WM maintenance. We specifically tested the main model prediction, broadened WM representation under disinhibition, using behavioral data from human subjects performing a spatial WM task combined with ketamine infusion, a pharmacological model of schizophrenia hypothesized to induce disinhibition. Ketamine increased errors in a pattern predicted by the model. Finally, as proof-of-principle, we demonstrate that WM deteriorations in the model can be ameliorated by compensations that restore E/I balance. Our findings identify specific ways by which cortical disinhibition affects WM, suggesting new experimental designs for probing the brain mechanisms of WM deficits in schizophrenia.

  7. Modeling and Simulation. III. Simulation of a Model for Development of Visual Cortical Specificity.

    Science.gov (United States)

    1986-12-15

    of parameter values. Experiment, model, and simulation 5’ The simulations we consider mimic, in form, classic deprivation experiments. Kittens are...second paper of the series (ref. 8) reviews the results of numerous experiments on the neuronal development of kitten visual cortex. We have...restricted to a very limited range of oriented contours (see citations in ref. 8). Kittens were raised, for example, viewing only horizontal or only vertical

  8. Large Scale, High Resolution, Mantle Dynamics Modeling

    Science.gov (United States)

    Geenen, T.; Berg, A. V.; Spakman, W.

    2007-12-01

    To model the geodynamic evolution of plate convergence, subduction and collision and to allow for a connection to various types of observational data, geophysical, geodetical and geological, we developed a 4D (space-time) numerical mantle convection code. The model is based on a spherical 3D Eulerian fem model, with quadratic elements, on top of which we constructed a 3D Lagrangian particle in cell(PIC) method. We use the PIC method to transport material properties and to incorporate a viscoelastic rheology. Since capturing small scale processes associated with localization phenomena require a high resolution, we spend a considerable effort on implementing solvers suitable to solve for models with over 100 million degrees of freedom. We implemented Additive Schwartz type ILU based methods in combination with a Krylov solver, GMRES. However we found that for problems with over 500 thousend degrees of freedom the convergence of the solver degraded severely. This observation is known from the literature [Saad, 2003] and results from the local character of the ILU preconditioner resulting in a poor approximation of the inverse of A for large A. The size of A for which ILU is no longer usable depends on the condition of A and on the amount of fill in allowed for the ILU preconditioner. We found that for our problems with over 5×105 degrees of freedom convergence became to slow to solve the system within an acceptable amount of walltime, one minute, even when allowing for considerable amount of fill in. We also implemented MUMPS and found good scaling results for problems up to 107 degrees of freedom for up to 32 CPU¡¯s. For problems with over 100 million degrees of freedom we implemented Algebraic Multigrid type methods (AMG) from the ML library [Sala, 2006]. Since multigrid methods are most effective for single parameter problems, we rebuild our model to use the SIMPLE method in the Stokes solver [Patankar, 1980]. We present scaling results from these solvers for 3D

  9. Deep supervised, but not unsupervised, models may explain IT cortical representation.

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    Seyed-Mahdi Khaligh-Razavi

    2014-11-01

    Full Text Available Inferior temporal (IT cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total, testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network. We compared the representational dissimilarity matrices (RDMs of the model representations with the RDMs obtained from human IT (measured with fMRI and monkey IT (measured with cell recording for the same set of stimuli (not used in training the models. Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining

  10. Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation

    Science.gov (United States)

    Khaligh-Razavi, Seyed-Mahdi; Kriegeskorte, Nikolaus

    2014-01-01

    Inferior temporal (IT) cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total), testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet) along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network). We compared the representational dissimilarity matrices (RDMs) of the model representations with the RDMs obtained from human IT (measured with fMRI) and monkey IT (measured with cell recording) for the same set of stimuli (not used in training the models). Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining IT requires

  11. Quantifying the Effects of Formalin Fixation on the Mechanical Properties of Cortical Bone Using Beam Theory and Optimization Methodology With Specimen-Specific Finite Element Models.

    Science.gov (United States)

    Zhang, Guan-Jun; Yang, Jie; Guan, Feng-Jiao; Chen, Dan; Li, Na; Cao, Libo; Mao, Haojie

    2016-09-01

    The effects of formalin fixation on bone material properties remain debatable. In this study, we collected 36 fresh-frozen cuboid-shaped cortical specimens from five male bovine femurs and immersed half of the specimens into 4% formalin fixation liquid for 30 days. We then conducted three-point bending tests and used both beam theory method and an optimization method combined with specimen-specific finite element (FE) models to identify material parameters. Through the optimization FE method, the formalin-fixed bones showed a significantly lower Young's modulus (-12%) compared to the fresh-frozen specimens, while no difference was observed using the beam theory method. Meanwhile, both the optimization FE and beam theory methods revealed higher effective failure strains for formalin-fixed bones compared to fresh-frozen ones (52% higher through the optimization FE method and 84% higher through the beam theory method). Hence, we conclude that the formalin fixation has a significant effect on bovine cortical bones at small, elastic, as well as large, plastic deformations.

  12. Evolving Models of Pavlovian Conditioning: Cerebellar Cortical Dynamics in Awake Behaving Mice

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    Michiel M. ten Brinke

    2015-12-01

    Full Text Available Three decades of electrophysiological research on cerebellar cortical activity underlying Pavlovian conditioning have expanded our understanding of motor learning in the brain. Purkinje cell simple spike suppression is considered to be crucial in the expression of conditional blink responses (CRs. However, trial-by-trial quantification of this link in awake behaving animals is lacking, and current hypotheses regarding the underlying plasticity mechanisms have diverged from the classical parallel fiber one to the Purkinje cell synapse LTD hypothesis. Here, we establish that acquired simple spike suppression, acquired conditioned stimulus (CS-related complex spike responses, and molecular layer interneuron (MLI activity predict the expression of CRs on a trial-by-trial basis using awake behaving mice. Additionally, we show that two independent transgenic mouse mutants with impaired MLI function exhibit motor learning deficits. Our findings suggest multiple cerebellar cortical plasticity mechanisms underlying simple spike suppression, and they implicate the broader involvement of the olivocerebellar module within the interstimulus interval.

  13. Cortical regulation of striatal projection neurons and interneurons in a Parkinson's disease rat model

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    Jia-jia Wu

    2016-01-01

    Full Text Available Striatal neurons can be either projection neurons or interneurons, with each type exhibiting distinct susceptibility to various types of brain damage. In this study, 6-hydroxydopamine was injected into the right medial forebrain bundle to induce dopamine depletion, and/or ibotenic acid was injected into the M1 cortex to induce motor cortex lesions. Immunohistochemistry and western blot assay showed that dopaminergic depletion results in significant loss of striatal projection neurons marked by dopamine- and cyclic adenosine monophosphate-regulated phosphoprotein, molecular weight 32 kDa, calbindin, and μ-opioid receptor, while cortical lesions reversed these pathological changes. After dopaminergic deletion, the number of neuropeptide Y-positive striatal interneurons markedly increased, which was also inhibited by cortical lesioning. No noticeable change in the number of parvalbumin-positive interneurons was found in 6-hydroxydopamine-treated rats. Striatal projection neurons and interneurons show different susceptibility to dopaminergic depletion. Further, cortical lesions inhibit striatal dysfunction and damage induced by 6-hydroxydopamine, which provides a new possibility for clinical treatment of Parkinson's disease.

  14. Development of a strain rate dependent material model of human cortical bone for computer-aided reconstruction of injury mechanisms.

    Science.gov (United States)

    Asgharpour, Zahra; Zioupos, Peter; Graw, Matthias; Peldschus, Steffen

    2014-03-01

    Computer-aided methods such as finite-element simulation offer a great potential in the forensic reconstruction of injury mechanisms. Numerous studies have been performed on understanding and analysing the mechanical properties of bone and the mechanism of its fracture. Determination of the mechanical properties of bones is made on the same basis used for other structural materials. The mechanical behaviour of bones is affected by the mechanical properties of the bone material, the geometry, the loading direction and mode and of course the loading rate. Strain rate dependency of mechanical properties of cortical bone has been well demonstrated in literature studies, but as many of these were performed on animal bones and at non-physiological strain rates it is questionable how these will apply in the human situations. High strain-rates dominate in a lot of forensic applications in automotive crashes and assault scenarios. There is an overwhelming need to a model which can describe the complex behaviour of bone at lower strain rates as well as higher ones. Some attempts have been made to model the viscoelastic and viscoplastic properties of the bone at high strain rates using constitutive mathematical models with little demonstrated success. The main objective of the present study is to model the rate dependent behaviour of the bones based on experimental data. An isotropic material model of human cortical bone with strain rate dependency effects is implemented using the LS-DYNA material library. We employed a human finite element model called THUMS (Total Human Model for Safety), developed by Toyota R&D Labs and the Wayne State University, USA. The finite element model of the human femur is extracted from the THUMS model. Different methods have been employed to develop a strain rate dependent material model for the femur bone. Results of one the recent experimental studies on human femur have been employed to obtain the numerical model for cortical femur. A

  15. Geometric Representation Of Visual Data In The Cortex Of Primates: Computer Reconstruction And Modeling Of Neo-Cortical Map And Column Systems

    Science.gov (United States)

    Schwartz, Eric

    1988-08-01

    Much of vertebrate midbrain and mammalian cortex is dedicated to two-dimensional "maps" in which two or more stimulus parameters are encoded by the position of neural activation in the map. Moreover, there are a large number of such maps which interact in an unknown fashion to yield a unified perception of the world. Our research program is based on studying the structure and function of brain maps. In the present paper, we review a recently constructed system of computer aided neuro-anatomy which allows high resolution texture mapped models of cortical surfaces in two and three dimensions to be displayed and manipulated. At the same time, this work demonstrates some of the basic geometric patterns of architecture of the primate brain, such as columnar and topographic mapping.

  16. Large field-of-view and depth-specific cortical microvascular imaging underlies regional differences in ischemic brain

    Science.gov (United States)

    Qin, Jia; Shi, Lei; Dziennis, Suzan; Wang, Ruikang K.

    2014-02-01

    Ability to non-invasively monitor and quantify of blood flow, blood vessel morphology, oxygenation and tissue morphology is important for improved diagnosis, treatment and management of various neurovascular disorders, e.g., stroke. Currently, no imaging technique is available that can satisfactorily extract these parameters from in vivo microcirculatory tissue beds, with large field of view and sufficient resolution at defined depth without any harm to the tissue. In order for more effective therapeutics, we need to determine the area of brain that is damaged but not yet dead after focal ischemia. Here we develop an integrated multi-functional imaging system, in which SDW-LSCI (synchronized dual wavelength laser speckle imaging) is used as a guiding tool for OMAG (optical microangiography) to investigate the fine detail of tissue hemodynamics, such as vessel flow, profile, and flow direction. We determine the utility of the integrated system for serial monitoring afore mentioned parameters in experimental stroke, middle cerebral artery occlusion (MCAO) in mice. For 90 min MCAO, onsite and 24 hours following reperfusion, we use SDW-LSCI to determine distinct flow and oxygenation variations for differentiation of the infarction, peri-infarct, reduced flow and contralateral regions. The blood volumes are quantifiable and distinct in afore mentioned regions. We also demonstrate the behaviors of flow and flow direction in the arterials connected to MCA play important role in the time course of MCAO. These achievements may improve our understanding of vascular involvement under pathologic and physiological conditions, and ultimately facilitate clinical diagnosis, monitoring and therapeutic interventions of neurovascular diseases, such as ischemic stroke.

  17. Early development of synchrony in cortical activations in the human.

    Science.gov (United States)

    Koolen, N; Dereymaeker, A; Räsänen, O; Jansen, K; Vervisch, J; Matic, V; Naulaers, G; De Vos, M; Van Huffel, S; Vanhatalo, S

    2016-05-13

    Early intermittent cortical activity is thought to play a crucial role in the growth of neuronal network development, and large scale brain networks are known to provide the basis for higher brain functions. Yet, the early development of the large scale synchrony in cortical activations is unknown. Here, we tested the hypothesis that the early intermittent cortical activations seen in the human scalp EEG show a clear developmental course during the last trimester of pregnancy, the period of intensive growth of cortico-cortical connections. We recorded scalp EEG from altogether 22 premature infants at post-menstrual age between 30 and 44 weeks, and the early cortical synchrony was quantified using recently introduced activation synchrony index (ASI). The developmental correlations of ASI were computed for individual EEG signals as well as anatomically and mathematically defined spatial subgroups. We report two main findings. First, we observed a robust and statistically significant increase in ASI in all cortical areas. Second, there were significant spatial gradients in the synchrony in fronto-occipital and left-to-right directions. These findings provide evidence that early cortical activity is increasingly synchronized across the neocortex. The ASI-based metrics introduced in our work allow direct translational comparison to in vivo animal models, as well as hold promise for implementation as a functional developmental biomarker in future research on human neonates.

  18. Efficient derivation of cortical glutamatergic neurons from human pluripotent stem cells: a model system to study neurotoxicity in Alzheimer's disease.

    Science.gov (United States)

    Vazin, Tandis; Ball, K Aurelia; Lu, Hui; Park, Hyungju; Ataeijannati, Yasaman; Head-Gordon, Teresa; Poo, Mu-ming; Schaffer, David V

    2014-02-01

    Alzheimer's disease (AD) is among the most prevalent forms of dementia affecting the aging population, and pharmacological therapies to date have not been successful in preventing disease progression. Future therapeutic efforts may benefit from the development of models that enable basic investigation of early disease pathology. In particular, disease-relevant models based on human pluripotent stem cells (hPSCs) may be promising approaches to assess the impact of neurotoxic agents in AD on specific neuronal populations and thereby facilitate the development of novel interventions to avert early disease mechanisms. We implemented an efficient paradigm to convert hPSCs into enriched populations of cortical glutamatergic neurons emerging from dorsal forebrain neural progenitors, aided by modulating Sonic hedgehog (Shh) signaling. Since AD is generally known to be toxic to glutamatergic circuits, we exposed glutamatergic neurons derived from hESCs to an oligomeric pre-fibrillar forms of Aβ known as "globulomers", which have shown strong correlation with the level of cognitive deficits in AD. Administration of such Aβ oligomers yielded signs of the disease, including cell culture age-dependent binding of Aβ and cell death in the glutamatergic populations. Furthermore, consistent with previous findings in postmortem human AD brain, Aβ-induced toxicity was selective for glutamatergic rather than GABAeric neurons present in our cultures. This in vitro model of cortical glutamatergic neurons thus offers a system for future mechanistic investigation and therapeutic development for AD pathology using human cell types specifically affected by this disease. © 2013.

  19. Sound to language: different cortical processing for first and second languages in elementary school children as revealed by a large-scale study using fNIRS.

    Science.gov (United States)

    Sugiura, Lisa; Ojima, Shiro; Matsuba-Kurita, Hiroko; Dan, Ippeita; Tsuzuki, Daisuke; Katura, Takusige; Hagiwara, Hiroko

    2011-10-01

    A large-scale study of 484 elementary school children (6-10 years) performing word repetition tasks in their native language (L1-Japanese) and a second language (L2-English) was conducted using functional near-infrared spectroscopy. Three factors presumably associated with cortical activation, language (L1/L2), word frequency (high/low), and hemisphere (left/right), were investigated. L1 words elicited significantly greater brain activation than L2 words, regardless of semantic knowledge, particularly in the superior/middle temporal and inferior parietal regions (angular/supramarginal gyri). The greater L1-elicited activation in these regions suggests that they are phonological loci, reflecting processes tuned to the phonology of the native language, while phonologically unfamiliar L2 words were processed like nonword auditory stimuli. The activation was bilateral in the auditory and superior/middle temporal regions. Hemispheric asymmetry was observed in the inferior frontal region (right dominant), and in the inferior parietal region with interactions: low-frequency words elicited more right-hemispheric activation (particularly in the supramarginal gyrus), while high-frequency words elicited more left-hemispheric activation (particularly in the angular gyrus). The present results reveal the strong involvement of a bilateral language network in children's brains depending more on right-hemispheric processing while acquiring unfamiliar/low-frequency words. A right-to-left shift in laterality should occur in the inferior parietal region, as lexical knowledge increases irrespective of language.

  20. Sound to Language: Different Cortical Processing for First and Second Languages in Elementary School Children as Revealed by a Large-Scale Study Using fNIRS

    Science.gov (United States)

    Ojima, Shiro; Matsuba-Kurita, Hiroko; Dan, Ippeita; Tsuzuki, Daisuke; Katura, Takusige; Hagiwara, Hiroko

    2011-01-01

    A large-scale study of 484 elementary school children (6–10 years) performing word repetition tasks in their native language (L1-Japanese) and a second language (L2-English) was conducted using functional near-infrared spectroscopy. Three factors presumably associated with cortical activation, language (L1/L2), word frequency (high/low), and hemisphere (left/right), were investigated. L1 words elicited significantly greater brain activation than L2 words, regardless of semantic knowledge, particularly in the superior/middle temporal and inferior parietal regions (angular/supramarginal gyri). The greater L1-elicited activation in these regions suggests that they are phonological loci, reflecting processes tuned to the phonology of the native language, while phonologically unfamiliar L2 words were processed like nonword auditory stimuli. The activation was bilateral in the auditory and superior/middle temporal regions. Hemispheric asymmetry was observed in the inferior frontal region (right dominant), and in the inferior parietal region with interactions: low-frequency words elicited more right-hemispheric activation (particularly in the supramarginal gyrus), while high-frequency words elicited more left-hemispheric activation (particularly in the angular gyrus). The present results reveal the strong involvement of a bilateral language network in children’s brains depending more on right-hemispheric processing while acquiring unfamiliar/low-frequency words. A right-to-left shift in laterality should occur in the inferior parietal region, as lexical knowledge increases irrespective of language. PMID:21350046

  1. Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation Is State-Dependent.

    Directory of Open Access Journals (Sweden)

    Sankaraleengam Alagapan

    2016-03-01

    Full Text Available Cortical oscillations play a fundamental role in organizing large-scale functional brain networks. Noninvasive brain stimulation with temporally patterned waveforms such as repetitive transcranial magnetic stimulation (rTMS and transcranial alternating current stimulation (tACS have been proposed to modulate these oscillations. Thus, these stimulation modalities represent promising new approaches for the treatment of psychiatric illnesses in which these oscillations are impaired. However, the mechanism by which periodic brain stimulation alters endogenous oscillation dynamics is debated and appears to depend on brain state. Here, we demonstrate with a static model and a neural oscillator model that recurrent excitation in the thalamo-cortical circuit, together with recruitment of cortico-cortical connections, can explain the enhancement of oscillations by brain stimulation as a function of brain state. We then performed concurrent invasive recording and stimulation of the human cortical surface to elucidate the response of cortical oscillations to periodic stimulation and support the findings from the computational models. We found that (1 stimulation enhanced the targeted oscillation power, (2 this enhancement outlasted stimulation, and (3 the effect of stimulation depended on behavioral state. Together, our results show successful target engagement of oscillations by periodic brain stimulation and highlight the role of nonlinear interaction between endogenous network oscillations and stimulation. These mechanistic insights will contribute to the design of adaptive, more targeted stimulation paradigms.

  2. The magnetic field of cortical current sources: the application of a spatial filtering model to the forward and inverse problems.

    Science.gov (United States)

    Tan, S; Roth, B J; Wikswo, J P

    1990-07-01

    We extend our theoretical model based on spatial filtering to determine the ability of a SQUID magnetometer to resolve 2 localized current sources in the brain. We find that in order to resolve 2 separated but coaxial cortical sources, the source-to-pickup coil distance must be comparable to the distance between the 2 sources. The size of the current sources affects the resolving power of a magnetometer, but an anisotropy of 3 in the cortical tissue does not produce a significant effect. The model also provides a solution of the inverse calculation, either to reconstruct the original current source distribution from the measured magnetic field, or to continue the field at the magnetometer inward towards the sources. Both the inverse and inward calculations are limited by the fact that the inverse filter function serves as a high-pass filter, which leads to instabilities at high spatial frequencies, particularly in the presence of noise. The instabilities can be minimized by choosing an appropriate window to attenuate the noise, but this in turn reduces the spatial resolution.

  3. Estimation of the effective and functional human cortical connectivity with structural equation modeling and directed transfer function applied to high-resolution EEG.

    Science.gov (United States)

    Astolfi, Laura; Cincotti, Febo; Mattia, Donatella; Salinari, Serenella; Babiloni, Claudio; Basilisco, Alessandra; Rossini, Paolo Maria; Ding, Lei; Ni, Ying; He, Bin; Marciani, Maria Grazia; Babiloni, Fabio

    2004-12-01

    Different brain imaging devices are presently available to provide images of the human functional cortical activity, based on hemodynamic, metabolic or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions are interconnected. The concept of brain connectivity plays a central role in the neuroscience, and different definitions of connectivity, functional and effective, have been adopted in literature. While the functional connectivity is defined as the temporal coherence among the activities of different brain areas, the effective connectivity is defined as the simplest brain circuit that would produce the same temporal relationship as observed experimentally among cortical sites. The structural equation modeling (SEM) is the most used method to estimate effective connectivity in neuroscience, and its typical application is on data related to brain hemodynamic behavior tested by functional magnetic resonance imaging (fMRI), whereas the directed transfer function (DTF) method is a frequency-domain approach based on both a multivariate autoregressive (MVAR) modeling of time series and on the concept of Granger causality. This study presents advanced methods for the estimation of cortical connectivity by applying SEM and DTF on the cortical signals estimated from high-resolution electroencephalography (EEG) recordings, since these signals exhibit a higher spatial resolution than conventional cerebral electromagnetic measures. To estimate correctly the cortical signals, we used a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from individual MRI, a distributed source model and a regularized linear inverse source estimates of cortical current density. Before the application of SEM and DTF methodology to the cortical waveforms estimated from high-resolution EEG data, we performed a simulation study, in which different main factors

  4. Voxel-based statistical analysis of cerebral glucose metabolism in the rat cortical deafness model by 3D reconstruction of brain from autoradiographic images

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jae Sung; Park, Kwang Suk [Seoul National University College of Medicine, Department of Nuclear Medicine, 28 Yungun-Dong, Chongno-Ku, Seoul (Korea); Seoul National University College of Medicine, Department of Biomedical Engineering, Seoul (Korea); Ahn, Soon-Hyun; Oh, Seung Ha; Kim, Chong Sun; Chung, June-Key; Lee, Myung Chul [Seoul National University College of Medicine, Department of Otolaryngology, Head and Neck Surgery, Seoul (Korea); Lee, Dong Soo; Jeong, Jae Min [Seoul National University College of Medicine, Department of Nuclear Medicine, 28 Yungun-Dong, Chongno-Ku, Seoul (Korea)

    2005-06-01

    Animal models of cortical deafness are essential for investigation of the cerebral glucose metabolism in congenital or prelingual deafness. Autoradiographic imaging is mainly used to assess the cerebral glucose metabolism in rodents. In this study, procedures for the 3D voxel-based statistical analysis of autoradiographic data were established to enable investigations of the within-modal and cross-modal plasticity through entire areas of the brain of sensory-deprived animals without lumping together heterogeneous subregions within each brain structure into a large region of interest. Thirteen 2-[1-{sup 14}C]-deoxy-D-glucose autoradiographic images were acquired from six deaf and seven age-matched normal rats (age 6-10 weeks). The deafness was induced by surgical ablation. For the 3D voxel-based statistical analysis, brain slices were extracted semiautomatically from the autoradiographic images, which contained the coronal sections of the brain, and were stacked into 3D volume data. Using principal axes matching and mutual information maximization algorithms, the adjacent coronal sections were co-registered using a rigid body transformation, and all sections were realigned to the first section. A study-specific template was composed and the realigned images were spatially normalized onto the template. Following count normalization, voxel-wise t tests were performed to reveal the areas with significant differences in cerebral glucose metabolism between the deaf and the control rats. Continuous and clear edges were detected in each image after registration between the coronal sections, and the internal and external landmarks extracted from the spatially normalized images were well matched, demonstrating the reliability of the spatial processing procedures. Voxel-wise t tests showed that the glucose metabolism in the bilateral auditory cortices of the deaf rats was significantly (P<0.001) lower than that in the controls. There was no significantly reduced metabolism in

  5. Faithful SGCE imprinting in iPSC-derived cortical neurons: an endogenous cellular model of myoclonus-dystonia

    Science.gov (United States)

    Grütz, Karen; Seibler, Philip; Weissbach, Anne; Lohmann, Katja; Carlisle, Francesca A.; Blake, Derek J.; Westenberger, Ana; Klein, Christine; Grünewald, Anne

    2017-01-01

    In neuropathology research, induced pluripotent stem cell (iPSC)-derived neurons are considered a tool closely resembling the patient brain. Albeit in respect to epigenetics, this concept has been challenged. We generated iPSC-derived cortical neurons from myoclonus-dystonia patients with mutations (W100G and R102X) in the maternally imprinted ε-sarcoglycan (SGCE) gene and analysed properties such as imprinting, mRNA and protein expression. Comparison of the promoter during reprogramming and differentiation showed tissue-independent differential methylation. DNA sequencing with methylation-specific primers and cDNA analysis in patient neurons indicated selective expression of the mutated paternal SGCE allele. While fibroblasts only expressed the ubiquitous mRNA isoform, brain-specific SGCE mRNA and ε-sarcoglycan protein were detected in iPSC-derived control neurons. However, neuronal protein levels were reduced in both mutants. Our phenotypic characterization highlights the suitability of iPSC-derived cortical neurons with SGCE mutations for myoclonus-dystonia research and, in more general terms, prompts the use of iPSC-derived cellular models to study epigenetic mechanisms impacting on health and disease. PMID:28155872

  6. A cortically-inspired model for inverse kinematics computation of a humanoid finger with mechanically coupled joints.

    Science.gov (United States)

    Gentili, Rodolphe J; Oh, Hyuk; Kregling, Alissa V; Reggia, James A

    2016-05-19

    The human hand's versatility allows for robust and flexible grasping. To obtain such efficiency, many robotic hands include human biomechanical features such as fingers having their two last joints mechanically coupled. Although such coupling enables human-like grasping, controlling the inverse kinematics of such mechanical systems is challenging. Here we propose a cortical model for fine motor control of a humanoid finger, having its two last joints coupled, that learns the inverse kinematics of the effector. This neural model functionally mimics the population vector coding as well as sensorimotor prediction processes of the brain's motor/premotor and parietal regions, respectively. After learning, this neural architecture could both overtly (actual execution) and covertly (mental execution or motor imagery) perform accurate, robust and flexible finger movements while reproducing the main human finger kinematic states. This work contributes to developing neuro-mimetic controllers for dexterous humanoid robotic/prosthetic upper-extremities, and has the potential to promote human-robot interactions.

  7. Modeling astrocytoma pathogenesis in vitro and in vivo using cortical astrocytes or neural stem cells from conditional, genetically engineered mice.

    Science.gov (United States)

    McNeill, Robert S; Schmid, Ralf S; Bash, Ryan E; Vitucci, Mark; White, Kristen K; Werneke, Andrea M; Constance, Brian H; Huff, Byron; Miller, C Ryan

    2014-08-12

    Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro and in vivo and may be useful in preclinical drug development for these devastating diseases.

  8. Visual search and line bisection in hemianopia: computational modelling of cortical compensatory mechanisms and comparison with hemineglect.

    Science.gov (United States)

    Lanyon, Linda J; Barton, Jason J S

    2013-01-01

    Hemianopia patients have lost vision from the contralateral hemifield, but make behavioural adjustments to compensate for this field loss. As a result, their visual performance and behaviour contrast with those of hemineglect patients who fail to attend to objects contralateral to their lesion. These conditions differ in their ocular fixations and perceptual judgments. During visual search, hemianopic patients make more fixations in contralesional space while hemineglect patients make fewer. During line bisection, hemianopic patients fixate the contralesional line segment more and make a small contralesional bisection error, while hemineglect patients make few contralesional fixations and a larger ipsilesional bisection error. Hence, there is an attentional failure for contralesional space in hemineglect but a compensatory adaptation to attend more to the blind side in hemianopia. A challenge for models of visual attentional processes is to show how compensation is achieved in hemianopia, and why such processes are hindered or inaccessible in hemineglect. We used a neurophysiology-derived computational model to examine possible cortical compensatory processes in simulated hemianopia from a V1 lesion and compared results with those obtained with the same processes under conditions of simulated hemineglect from a parietal lesion. A spatial compensatory bias to increase attention contralesionally replicated hemianopic scanning patterns during visual search but not during line bisection. To reproduce the latter required a second process, an extrastriate lateral connectivity facilitating form completion into the blind field: this allowed accurate placement of fixations on contralesional stimuli and reproduced fixation patterns and the contralesional bisection error of hemianopia. Neither of these two cortical compensatory processes was effective in ameliorating the ipsilesional bias in the hemineglect model. Our results replicate normal and pathological patterns of

  9. Visual search and line bisection in hemianopia: computational modelling of cortical compensatory mechanisms and comparison with hemineglect.

    Directory of Open Access Journals (Sweden)

    Linda J Lanyon

    Full Text Available Hemianopia patients have lost vision from the contralateral hemifield, but make behavioural adjustments to compensate for this field loss. As a result, their visual performance and behaviour contrast with those of hemineglect patients who fail to attend to objects contralateral to their lesion. These conditions differ in their ocular fixations and perceptual judgments. During visual search, hemianopic patients make more fixations in contralesional space while hemineglect patients make fewer. During line bisection, hemianopic patients fixate the contralesional line segment more and make a small contralesional bisection error, while hemineglect patients make few contralesional fixations and a larger ipsilesional bisection error. Hence, there is an attentional failure for contralesional space in hemineglect but a compensatory adaptation to attend more to the blind side in hemianopia. A challenge for models of visual attentional processes is to show how compensation is achieved in hemianopia, and why such processes are hindered or inaccessible in hemineglect. We used a neurophysiology-derived computational model to examine possible cortical compensatory processes in simulated hemianopia from a V1 lesion and compared results with those obtained with the same processes under conditions of simulated hemineglect from a parietal lesion. A spatial compensatory bias to increase attention contralesionally replicated hemianopic scanning patterns during visual search but not during line bisection. To reproduce the latter required a second process, an extrastriate lateral connectivity facilitating form completion into the blind field: this allowed accurate placement of fixations on contralesional stimuli and reproduced fixation patterns and the contralesional bisection error of hemianopia. Neither of these two cortical compensatory processes was effective in ameliorating the ipsilesional bias in the hemineglect model. Our results replicate normal and

  10. Modeling and Theories of Pathophysiology and Physiology of the Basal Ganglia–Thalamic–Cortical System: Critical Analysis

    Science.gov (United States)

    Montgomery Jr., Erwin B.

    2016-01-01

    Theories impact the movement disorders clinic, not only affecting the development of new therapies but determining how current therapies are used. Models are theories that are procedural rather than declarative. Theories and models are important because, as argued by Kant, one cannot know the thing-in-itself (das Ding an sich) and only a model is knowable. Further, biological variability forces higher level abstraction relevant for all variants. It is that abstraction that is raison d’être of theories and models. Theories “connect the dots” to move from correlation to causation. The necessity of theory makes theories helpful or counterproductive. Theories and models of the pathophysiology and physiology of the basal ganglia–thalamic–cortical system do not spontaneously arise but have a history and consequently are legacies. Over the last 40 years, numerous theories and models of the basal ganglia have been proposed only to be forgotten or dismissed, rarely critiqued. It is not harsh to say that current popular theories positing increased neuronal activities in the Globus Pallidus Interna (GPi), excessive beta oscillations and increased synchronization not only fail to provide an adequate explication but are inconsistent with many observations. It is likely that their shared intellectual and epistemic inheritance plays a factor in their shared failures. These issues are critically examined. How one is to derive theories and models and have hope these will be better is explored as well. PMID:27708569

  11. Advances in large-scale crop modeling

    Science.gov (United States)

    Scholze, Marko; Bondeau, Alberte; Ewert, Frank; Kucharik, Chris; Priess, Jörg; Smith, Pascalle

    Intensified human activity and a growing population have changed the climate and the land biosphere. One of the most widely recognized human perturbations is the emission of carbon dioxide (C02) by fossil fuel burning and land-use change. As the terrestrial biosphere is an active player in the global carbon cycle, changes in land use feed back to the climate of the Earth through regulation of the content of atmospheric CO2, the most important greenhouse gas,and changing albedo (e.g., energy partitioning).Recently, the climate modeling community has started to develop more complex Earthsystem models that include marine and terrestrial biogeochemical processes in addition to the representation of atmospheric and oceanic circulation. However, most terrestrial biosphere models simulate only natural, or so-called potential, vegetation and do not account for managed ecosystems such as croplands and pastures, which make up nearly one-third of the Earth's land surface.

  12. Constraining models with a large scalar multiplet

    CERN Document Server

    Earl, Kevin; Logan, Heather E; Pilkington, Terry

    2013-01-01

    Models in which the Higgs sector is extended by a single electroweak scalar multiplet X can possess an accidental global U(1) symmetry at the renormalizable level if X has isospin T greater or equal to 2. We show that all such U(1)-symmetric models are excluded by the interplay of the cosmological relic density of the lightest (neutral) component of X and its direct detection cross section via Z exchange. The sole exception is the T=2 multiplet, whose lightest member decays on a few-day to few-year timescale via a Planck-suppressed dimension-5 operator.

  13. COST MODEL FOR LARGE URBAN SCHOOLS.

    Science.gov (United States)

    O'BRIEN, RICHARD J.

    THIS DOCUMENT CONTAINS A COST SUBMODEL OF AN URBAN EDUCATIONAL SYSTEM. THIS MODEL REQUIRES THAT PUPIL POPULATION AND PROPOSED SCHOOL BUILDING ARE KNOWN. THE COST ELEMENTS ARE--(1) CONSTRUCTION COSTS OF NEW PLANTS, (2) ACQUISITION AND DEVELOPMENT COSTS OF BUILDING SITES, (3) CURRENT OPERATING EXPENSES OF THE PROPOSED SCHOOL, (4) PUPIL…

  14. Treatment of patients with acromioclavicular joint injuries(Rockwood II-VI) with modeled Kirschner wire and cortical screw

    Institute of Scientific and Technical Information of China (English)

    Ivan; Viktorovich; Borozda; Mikhail; Anatolievich; Danilov; Kirill; Sergeevich; Golokhvast

    2015-01-01

    Objective: To propose an original method of surgical treatment for the acromial extremity of the clavicle rupture(Rockwood II-VI) with modeled Kirschner wire and cortical screw. Methods: Anatomical study and a test method were applied to 43 cadavers of both sexes. During the period between 2000 and 2013, 34 patients of both sexes were operated upon using the new method. In the comparison group(n = 120), the fixation of the acromial extremity of the clavicle rupture was performed with hamate plate, Lee hook and Kirschner wires.Results: Its application allows, according to the evaluation scale of Constant and Murley(1987), 10% more preservation of the function of the shoulder compared with traditional methods of surgical treatment, and shortens the required hospital treatment and temporary disability periods.Conclusions: It is shown that the proposed author’s method combines low invasiveness, minimum dimensions of the construction and low-cost treatment.

  15. Treatment of patients with acromioclavicular joint injuries (Rockwood II-VI) with modeled Kirschner wire and cortical screw

    Institute of Scientific and Technical Information of China (English)

    Ivan Viktorovich Borozda; Mikhail Anatolievich Danilov; Kirill Sergeevich Golokhvast

    2015-01-01

    Objective:To propose an original method of surgical treatment for the acromial extremity of the clavicle rupture (Rockwood II-VI) with modeled Kirschner wire and cortical screw. Methods:Anatomical study and a test method were applied to 43 cadavers of both sexes. During the period between 2000 and 2013, 34 patients of both sexes were operated upon using the new method. In the comparison group (n=120), the fixation of the acromial extremity of the clavicle rupture was performed with hamate plate, Lee hook and Kirschner wires. Results:Its application allows, according to the evaluation scale of Constant and Murley (1987), 10%more preservation of the function of the shoulder compared with traditional methods of surgical treatment, and shortens the required hospital treatment and temporary disability periods. Conclusions: It is shown that the proposed author’s method combines low invasiveness, minimum dimensions of the construction and low-cost treatment.

  16. Prefrontal cortical α2A-adrenoceptors and a possible primate model of attention deficit and hyperactivity disorder.

    Science.gov (United States)

    Ma, Chao-Lin; Sun, Xuan; Luo, Fei; Li, Bao-Ming

    2015-04-01

    Attention deficit and hyperactivity disorder (ADHD), a prevalent syndrome in children worldwide, is characterized by impulsivity, inappropriate inattention, and/or hyperactivity. It seriously afflicts cognitive development in childhood, and may lead to chronic under-achievement, academic failure, problematic peer relationships, and low self-esteem. There are at least three challenges for the treatment of ADHD. First, the neurobiological bases of its symptoms are still not clear. Second, the commonly prescribed medications, most showing short-term therapeutic efficacy but with a high risk of serious side-effects, are mainly based on a dopamine mechanism. Third, more novel and efficient animal models, especially in nonhuman primates, are required to accelerate the development of new medications. In this article, we review research progress in the related fields, focusing on our previous studies showing that blockade of prefrontal cortical α2A-adrenoceptors in monkeys produces almost all the typical behavioral symptoms of ADHD.

  17. The influence of ion concentrations on the dynamic behavior of the Hodgkin-Huxley model-based cortical network.

    Science.gov (United States)

    Tagluk, M Emin; Tekin, Ramazan

    2014-08-01

    Action potentials (APs) in the form of very short pulses arise when the cell is excited by any internal or external stimulus exceeding the critical threshold of the membrane. During AP generation, the membrane potential completes its natural cycle through typical phases that can be formatted by ion channels, gates and ion concentrations, as well as the synaptic excitation rate. On the basis of the Hodgkin-Huxley cell model, a cortical network consistent with the real anatomic structure is realized with randomly interrelated small population of neurons to simulate a cerebral cortex segment. Using this model, we investigated the effects of Na(+) and K(+) ion concentrations on the outcome of this network in terms of regularity, phase locking, and synchronization. The results suggested that Na(+) concentration does slightly affect the amplitude but not considerably affects the other parameters specified by depolarization and repolarization. K(+) concentration significantly influences the form, regularity, and synchrony of the network-generated APs. No previous study dealing directly with the effects of both Na(+) and K(+) ion concentrations on regularity and synchronization of the simulated cortical network-generated APs, allowing for the comparison of results obtained using our methods, was encountered in the literature. The results, however, were consistent with those obtained through studies concerning resonance and synchronization from another perspective and with the information revealed through physiological and pharmacological experiments concerning changing ion concentrations or blocking ion channels. Our results demonstrated that the regularity and reliability of brain functions have a strong relationship with cellular ion concentrations, and suggested the management of the dynamic behavior of the cellular network with ion concentrations.

  18. Modeling and Control of Large Flexible Structures.

    Science.gov (United States)

    1984-07-31

    systems with hybrid (lumped and distributed) structure. * -3.Development of stabilizing control strategies for nonlinear distributed models, including...process, but much more needs to be done. el .It ;,, "..- ,. ,-,,o’,, .4. : ") Part I: :i: ’i" ’" Wierner-Hopf Methods for Design of Stabilizing ... Control Systems :: Z’" ..-- -~ . . . . .. . . . . . . ... . . . . .......- ~ .. . . S 5 * * .5 .. ** .*% - * 5*55 * . . . . % % ’ * . ’ % , . :.:. -A

  19. Modeling Social Influence in Large Populations

    Science.gov (United States)

    2010-07-13

    feature selection,” The Journal of Machine Learning Research, vol. 3, 2003, pp. 1157– 1182. I. Ajzen , “The theory of planned behavior ,” Organizational...ANSI Std Z39-18 Theory and Introduction 2 Theory : human collectivities are composed of individuals with different meaningful identities, and these...Intrinsically represent a window of time (e.g., before, after, or during a simulation event) Constructed via a theory to model translation of a

  20. Benefits of multi-modal fusion analysis on a large-scale dataset: life-span patterns of inter-subject variability in cortical morphometry and white matter microstructure.

    Science.gov (United States)

    Groves, Adrian R; Smith, Stephen M; Fjell, Anders M; Tamnes, Christian K; Walhovd, Kristine B; Douaud, Gwenaëlle; Woolrich, Mark W; Westlye, Lars T

    2012-10-15

    Neuroimaging studies have become increasingly multimodal in recent years, with researchers typically acquiring several different types of MRI data and processing them along separate pipelines that provide a set of complementary windows into each subject's brain. However, few attempts have been made to integrate the various modalities in the same analysis. Linked ICA is a robust data fusion model that takes multi-modal data and characterizes inter-subject variability in terms of a set of multi-modal components. This paper examines the types of components found when running Linked ICA on a large magnetic resonance imaging (MRI) morphometric and diffusion tensor imaging (DTI) data set comprising 484 healthy subjects ranging from 8 to 85 years of age. We find several strong global features related to age, sex, and intracranial volume; in particular, one component predicts age to a high accuracy (r=0.95). Most of the remaining components describe spatially localized modes of variability in white or gray matter, with many components including both tissue types. The multimodal components tend to be located in anatomically-related brain areas, suggesting a morphological and possibly functional relationship. The local components show relationships between surface-based cortical thickness and arealization, voxel-based morphometry (VBM), and between three different DTI measures. Further, we report components related to artifacts (e.g. scanner software upgrades) which would be expected in a dataset of this size. Most of the 100 extracted components showed interpretable spatial patterns and were found to be reliable using split-half validation. This work provides novel information about normal inter-subject variability in brain structure, and demonstrates the potential of Linked ICA as a feature-extracting data fusion approach across modalities. This exploratory approach automatically generates models to explain structure in the data, and may prove especially powerful for large

  1. Computational model of thalamo-cortical networks: dynamical control of alpha rhythms in relation to focal attention.

    Science.gov (United States)

    Suffczynski, P; Kalitzin, S; Pfurtscheller, G; Lopes da Silva, F H

    2001-12-01

    EEG/MEG rhythmic activities such as alpha rhythms, of the visual or of the somato-sensory cortex, are commonly modulated as subjects perform certain tasks or react to specific stimuli. In general, these activities change depending on extrinsic or intrinsic events. A decrease of the amplitude of alpha rhythmic activity occurring after a given event, which manifests as a decrease of a spectral peak, is called event-related desynchronization (ERD), whereas the inverse is called event-related synchronization (ERS), since it is assumed that the power of a spectral peak is related to the degree of synchrony of the underlying oscillating neuronal populations. An intriguing observation in this respect [Pfurtscheller and Neuper, Neurosci. Lett. 174 (1994) 93-96] was that ERD of alpha rhythms recorded over the central areas was accompanied by ERS, within the same frequency band, recorded over neighboring areas. In case the event was a hand movement, ERD was recorded over the scalp overlying the hand cortical area, whereas ERS was concomitantly recorded over the midline, whereas if the movement was of the foot the opposite was found. We called this phenomenon 'focal ERD/surround ERS'. The question of how this phenomenon may be generated was approached by means of a computational model of thalamo-cortical networks, that incorporates basic properties of neurons and synaptic interactions. These simulation studies revealed that this antagonistic ERD/ERS phenomenon depends on the functional interaction between the populations of thalamo-cortical cells (TCR) and reticular nucleus cells (RE) and on how this interaction is modulated by cholinergic inputs. An essential feature of this interaction is the existence of cross-talk between different sectors of RE that correspond to distinct sensory modules (e.g. hand, foot). These observations led us to formulate the hypothesis that this basic neurophysiological mechanism can account for the general observation that enhanced attention

  2. The statistics of repeating patterns of cortical activity can be reproduced by a model network of stochastic binary neurons.

    Science.gov (United States)

    Roxin, Alex; Hakim, Vincent; Brunel, Nicolas

    2008-10-15

    Calcium imaging of the spontaneous activity in cortical slices has revealed repeating spatiotemporal patterns of transitions between so-called down states and up states (Ikegaya et al., 2004). Here we fit a model network of stochastic binary neurons to data from these experiments, and in doing so reproduce the distributions of such patterns. We use two versions of this model: (1) an unconnected network in which neurons are activated as independent Poisson processes; and (2) a network with an interaction matrix, estimated from the data, representing effective interactions between the neurons. The unconnected model (model 1) is sufficient to account for the statistics of repeating patterns in 11 of the 15 datasets studied. Model 2, with interactions between neurons, is required to account for pattern statistics of the remaining four. Three of these four datasets are the ones that contain the largest number of transitions, suggesting that long datasets are in general necessary to render interactions statistically visible. We then study the topology of the matrix of interactions estimated for these four datasets. For three of the four datasets, we find sparse matrices with long-tailed degree distributions and an overrepresentation of certain network motifs. The remaining dataset exhibits a strongly interconnected, spatially localized subgroup of neurons. In all cases, we find that interactions between neurons facilitate the generation of long patterns that do not repeat exactly.

  3. Individual cortical current density reconstructions of the semantic N400 effect: using a generalized minimum norm model with different constraints (L1 and L2 norm).

    Science.gov (United States)

    Haan, H; Streb, J; Bien, S; Rösler, F

    2000-11-01

    Event-related brain potentials were recorded to study whether verbs and nouns activate topographically distinct cortical generators. Fifteen subjects performed a primed lexical decision task with verb/verb and noun/noun pairs. The relatedness between prime and target items was varied in three steps (unrelated, moderately, and strongly related) and the EEG was recorded from 124 scalp electrodes. The topography of cortical sources of the N400 effect was evaluated by standardized differences scores and by cortical current source estimates which were constrained by the individual MRI-determined cortex anatomy. A behavioral priming effect and a substantial N400 effect was found for both word categories. However, the topography of the grand average N400 effect of verbs and nouns did not differ, neither for raw nor for standardized amplitudes. Cortical current source estimates of the N400 effect revealed a very broad and scattered distribution of active locations with pronounced interindividual differences. Cortical current source estimates obtained with the L1-norm and L2-norm model, respectively, differed in the distribution of sources over the cortex but converged on the same "hot spots." The data give no indication that the N400 effect is generated by word category-specific networks which have a different topography. The marked individual differences are discussed with respect to the involved processes and the current source estimation procedures.

  4. Synaptic maturation at cortical projections to the lateral amygdala in a mouse model of Rett syndrome.

    Directory of Open Access Journals (Sweden)

    Frédéric Gambino

    Full Text Available Rett syndrome (RTT is a neuro-developmental disorder caused by loss of function of Mecp2--methyl-CpG-binding protein 2--an epigenetic factor controlling DNA transcription. In mice, removal of Mecp2 in the forebrain recapitulates most of behavioral deficits found in global Mecp2 deficient mice, including amygdala-related hyper-anxiety and lack of social interaction, pointing a role of Mecp2 in emotional learning. Yet very little is known about the establishment and maintenance of synaptic function in the adult amygdala and the role of Mecp2 in these processes. Here, we performed a longitudinal examination of synaptic properties at excitatory projections to principal cells of the lateral nucleus of the amygdala (LA in Mecp2 mutant mice and their wild-type littermates. We first show that during animal life, Cortico-LA projections switch from a tonic to a phasic mode, whereas Thalamo-LA synapses are phasic at all ages. In parallel, we observed a specific elimination of Cortico-LA synapses and a decrease in their ability of generating presynaptic long term potentiation. In absence of Mecp2, both synaptic maturation and synaptic elimination were exaggerated albeit still specific to cortical projections. Surprisingly, associative LTP was unaffected at Mecp2 deficient synapses suggesting that synaptic maintenance rather than activity-dependent synaptic learning may be causal in RTT physiopathology. Finally, because the timing of synaptic evolution was preserved, we propose that some of the developmental effects of Mecp2 may be exerted within an endogenous program and restricted to synapses which maturate during animal life.

  5. Influence of Deterministic Attachments for Large Unifying Hybrid Network Model

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Large unifying hybrid network model (LUHPM) introduced the deterministic mixing ratio fd on the basis of the harmonious unification hybrid preferential model, to describe the influence of deterministic attachment to the network topology characteristics,

  6. Cortical Visual Impairment

    Science.gov (United States)

    ... Frequently Asked Questions Español Condiciones Chinese Conditions Cortical Visual Impairment En Español Read in Chinese What is cortical visual impairment? Cortical visual impairment (CVI) is a decreased visual ...

  7. Behavioral constraints in the development of neuronal properties: a cortical model embedded in a real-world device.

    Science.gov (United States)

    Almássy, N; Edelman, G M; Sporns, O

    1998-06-01

    The ability of organisms to categorize diverse and often novel stimuli depends on ongoing interactions with their environment. In a modality such as vision, categorization requires the generation of both selective and invariant responses of cortical neurons to complex visual stimuli. How does behavior contribute to shaping the responses of these neurons? Analysis of this question is made difficult by the complex multilevel interactions between many neural and behavioral variables. To mitigate this difficulty, we studied the development and ongoing plasticity of pattern-selective neuronal responses by means of synthetic neural modeling. For this purpose, we constructed Darwin V, which consists of a simulated neuronal model embedded in a real-world device that is capable of motion and autonomous behavior. The neuronal model consists of four major components: a visual system (containing cortical and subcortical networks); a taste system based on conductance; sets of motor neurons capable of triggering behavior; and a diffuse ascending (value) system. The modeled visual cortex consists of two areas: a topographic map responsive to elementary features connected to a higher-order map composed of initially non-selective neuronal units. During behavior over time in its environment, Darwin V encounters numerous objects consisting of black metal cubes displaying different patterns of white blobs and stripes. Initially, the lack of specific higher-order visual responses does not allow visual pattern discrimination, and appetitive and aversive behaviors are triggered by the 'taste' (surface conductivity of objects) alone. In the course of sensory experience, however, changes occur in visual and sensorimotor connection strengths, with two major consequences. First, units within the higher visual area acquire responses that are both pattern selective and translation invariant. Second, as a result of the operation of the value system, these responses become linked to appropriate

  8. Biophysical Model of Cortical Network Activity and the Influence of Electrical Stimulation

    Science.gov (United States)

    2015-11-13

    threshold is most prominent in the case of multipolar neurons with large-diameter basal/apical dendrites that are 1. REPORT DATE (DD-MM-YYYY) 4. TITLE...axonal activation threshold is most prominent in the case of multipolar neurons with large-diameter basal/apical dendrites that are oriented parallel...distal axonal segments in neurons . The most distal axonal segments are locations where presynaptic action potentials can originate regardless of the

  9. Maximizing Sensory Dynamic Range by Tuning the Cortical State to Criticality.

    Directory of Open Access Journals (Sweden)

    Shree Hari Gautam

    2015-12-01

    Full Text Available Modulation of interactions among neurons can manifest as dramatic changes in the state of population dynamics in cerebral cortex. How such transitions in cortical state impact the information processing performed by cortical circuits is not clear. Here we performed experiments and computational modeling to determine how somatosensory dynamic range depends on cortical state. We used microelectrode arrays to record ongoing and whisker stimulus-evoked population spiking activity in somatosensory cortex of urethane anesthetized rats. We observed a continuum of different cortical states; at one extreme population activity exhibited small scale variability and was weakly correlated, the other extreme had large scale fluctuations and strong correlations. In experiments, shifts along the continuum often occurred naturally, without direct manipulation. In addition, in both the experiment and the model we directly tuned the cortical state by manipulating inhibitory synaptic interactions. Our principal finding was that somatosensory dynamic range was maximized in a specific cortical state, called criticality, near the tipping point midway between the ends of the continuum. The optimal cortical state was uniquely characterized by scale-free ongoing population dynamics and moderate correlations, in line with theoretical predictions about criticality. However, to reproduce our experimental findings, we found that existing theory required modifications which account for activity-dependent depression. In conclusion, our experiments indicate that in vivo sensory dynamic range is maximized near criticality and our model revealed an unanticipated role for activity-dependent depression in this basic principle of cortical function.

  10. Maximizing Sensory Dynamic Range by Tuning the Cortical State to Criticality

    Science.gov (United States)

    Gautam, Shree Hari; Hoang, Thanh T.; McClanahan, Kylie; Grady, Stephen K.; Shew, Woodrow L.

    2015-01-01

    Modulation of interactions among neurons can manifest as dramatic changes in the state of population dynamics in cerebral cortex. How such transitions in cortical state impact the information processing performed by cortical circuits is not clear. Here we performed experiments and computational modeling to determine how somatosensory dynamic range depends on cortical state. We used microelectrode arrays to record ongoing and whisker stimulus-evoked population spiking activity in somatosensory cortex of urethane anesthetized rats. We observed a continuum of different cortical states; at one extreme population activity exhibited small scale variability and was weakly correlated, the other extreme had large scale fluctuations and strong correlations. In experiments, shifts along the continuum often occurred naturally, without direct manipulation. In addition, in both the experiment and the model we directly tuned the cortical state by manipulating inhibitory synaptic interactions. Our principal finding was that somatosensory dynamic range was maximized in a specific cortical state, called criticality, near the tipping point midway between the ends of the continuum. The optimal cortical state was uniquely characterized by scale-free ongoing population dynamics and moderate correlations, in line with theoretical predictions about criticality. However, to reproduce our experimental findings, we found that existing theory required modifications which account for activity-dependent depression. In conclusion, our experiments indicate that in vivo sensory dynamic range is maximized near criticality and our model revealed an unanticipated role for activity-dependent depression in this basic principle of cortical function. PMID:26623645

  11. Receptive field self-organization in a model of the fine structure in v1 cortical columns.

    Science.gov (United States)

    Lücke, Jörg

    2009-10-01

    We study a dynamical model of processing and learning in the visual cortex, which reflects the anatomy of V1 cortical columns and properties of their neuronal receptive fields. Based on recent results on the fine-scale structure of columns in V1, we model the activity dynamics in subpopulations of excitatory neurons and their interaction with systems of inhibitory neurons. We find that a dynamical model based on these aspects of columnar anatomy can give rise to specific types of computations that result in self-organization of afferents to the column. For a given type of input, self-organization reliably extracts the basic input components represented by neuronal receptive fields. Self-organization is very noise tolerant and can robustly be applied to different types of input. To quantitatively analyze the system's component extraction capabilities, we use two standard benchmarks: the bars test and natural images. In the bars test, the system shows the highest noise robustness reported so far. If natural image patches are used as input, self-organization results in Gabor-like receptive fields. In quantitative comparison with in vivo measurements, we find that the obtained receptive fields capture statistical properties of V1 simple cells that algorithms such as independent component analysis or sparse coding do not reproduce.

  12. Establishing the ferret as a gyrencephalic animal model of traumatic brain injury: Optimization of controlled cortical impact procedures.

    Science.gov (United States)

    Schwerin, Susan C; Hutchinson, Elizabeth B; Radomski, Kryslaine L; Ngalula, Kapinga P; Pierpaoli, Carlo M; Juliano, Sharon L

    2017-06-15

    Although rodent TBI studies provide valuable information regarding the effects of injury and recovery, an animal model with neuroanatomical characteristics closer to humans may provide a more meaningful basis for clinical translation. The ferret has a high white/gray matter ratio, gyrencephalic neocortex, and ventral hippocampal location. Furthermore, ferrets are amenable to behavioral training, have a body size compatible with pre-clinical MRI, and are cost-effective. We optimized the surgical procedure for controlled cortical impact (CCI) using 9 adult male ferrets. We used subject-specific brain/skull morphometric data from anatomical MRIs to overcome across-subject variability for lesion placement. We also reflected the temporalis muscle, closed the craniotomy, and used antibiotics. We then gathered MRI, behavioral, and immunohistochemical data from 6 additional animals using the optimized surgical protocol: 1 control, 3 mild, and 1 severely injured animals (surviving one week) and 1 moderately injured animal surviving sixteen weeks. The optimized surgical protocol resulted in consistent injury placement. Astrocytic reactivity increased with injury severity showing progressively greater numbers of astrocytes within the white matter. The density and morphological changes of microglia amplified with injury severity or time after injury. Motor and cognitive impairments scaled with injury severity. The optimized surgical methods differ from those used in the rodent, and are integral to success using a ferret model. We optimized ferret CCI surgery for consistent injury placement. The ferret is an excellent animal model to investigate pathophysiological and behavioral changes associated with TBI. Published by Elsevier B.V.

  13. Long-Term Calculations with Large Air Pollution Models

    DEFF Research Database (Denmark)

    1999-01-01

    Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

  14. Long-Term Calculations with Large Air Pollution Models

    DEFF Research Database (Denmark)

    1999-01-01

    Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

  15. The development of neural synchrony and large-scale cortical networks during adolescence: relevance for the pathophysiology of schizophrenia and neurodevelopmental hypothesis.

    Science.gov (United States)

    Uhlhaas, Peter J; Singer, Wolf

    2011-05-01

    Recent data from developmental cognitive neuroscience highlight the profound changes in the organization and function of cortical networks during the transition from adolescence to adulthood. While previous studies have focused on the development of gray and white matter, recent evidence suggests that brain maturation during adolescence extends to fundamental changes in the properties of cortical circuits that in turn promote the precise temporal coding of neural activity. In the current article, we will highlight modifications in the amplitude and synchrony of neural oscillations during adolescence that may be crucial for the emergence of cognitive deficits and psychotic symptoms in schizophrenia. Specifically, we will suggest that schizophrenia is associated with impaired parameters of synchronous oscillations that undergo changes during late brain maturation, suggesting an important role of adolescent brain development for the understanding, treatment, and prevention of the disorder.

  16. Simple cortical and thalamic neuron models for digital arithmetic circuit implementation

    Directory of Open Access Journals (Sweden)

    Takuya eNanami

    2016-05-01

    Full Text Available Trade-off between reproducibility of neuronal activities and computational efficiency is one ofcrucial subjects in computational neuroscience and neuromorphic engineering. A wide variety ofneuronal models have been studied from different viewpoints. The digital spiking silicon neuron(DSSN model is a qualitative model that focuses on efficient implementation by digital arithmeticcircuits. We expanded the DSSN model and found appropriate parameter sets with which itreproduces the dynamical behaviors of the ionic-conductance models of four classes of corticaland thalamic neurons. We first developed a 4-variable model by reducing the number of variablesin the ionic-conductance models and elucidated its mathematical structures using bifurcationanalysis. Then, expanded DSSN models were constructed that reproduce these mathematicalstructures and capture the characteristic behavior of each neuron class. We confirmed thatstatistics of the neuronal spike sequences are similar in the DSSN and the ionic-conductancemodels. Computational cost of the DSSN model is larger than that of the recent sophisticatedIntegrate-and-Fire-based models, but smaller than the ionic-conductance models. This modelis intended to provide another meeting point for above trade-off that satisfies the demand forlarge-scale neuronal network simulation with closer-to-biology models.

  17. Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

    Science.gov (United States)

    Shameldin, Ramez Ahmed; Bowling, Shannon R.

    2010-01-01

    The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

  18. Modeling Large sound sources in a room acoustical calculation program

    DEFF Research Database (Denmark)

    Christensen, Claus Lynge

    1999-01-01

    A room acoustical model capable of modelling point, line and surface sources is presented. Line and surface sources are modelled using a special ray-tracing algorithm detecting the radiation pattern of the surfaces in the room. Point sources are modelled using a hybrid calculation method combining...... this ray-tracing method with Image source modelling. With these three source types, it is possible to model large and complex sound sources in workrooms....

  19. Modeling Large sound sources in a room acoustical calculation program

    DEFF Research Database (Denmark)

    Christensen, Claus Lynge

    1999-01-01

    A room acoustical model capable of modelling point, line and surface sources is presented. Line and surface sources are modelled using a special ray-tracing algorithm detecting the radiation pattern of the surfaces in the room. Point sources are modelled using a hybrid calculation method combining...... this ray-tracing method with Image source modelling. With these three source types, it is possible to model large and complex sound sources in workrooms....

  20. Technique for infrared and visible image fusion based on non-subsampled shearlet transform and spiking cortical model

    Science.gov (United States)

    Kong, Weiwei; Wang, Binghe; Lei, Yang

    2015-07-01

    Fusion of infrared and visible images is an active research area in image processing, and a variety of relevant algorithms have been developed. However, the existing techniques commonly cannot gain good fusion performance and acceptable computational complexity simultaneously. This paper proposes a novel image fusion approach that integrates the non-subsampled shearlet transform (NSST) with spiking cortical model (SCM) to overcome the above drawbacks. On the one hand, using NSST to conduct the decompositions and reconstruction not only consists with human vision characteristics, but also effectively decreases the computational complexity compared with the current popular multi-resolution analysis tools such as non-subsampled contourlet transform (NSCT). On the other hand, SCM, which has been considered to be an optimal neuron network model recently, is responsible for the fusion of sub-images from different scales and directions. Experimental results indicate that the proposed method is promising, and it does significantly improve the fusion quality in both aspects of subjective visual performance and objective comparisons compared with other current popular ones.

  1. Comparison Between Overtopping Discharge in Small and Large Scale Models

    DEFF Research Database (Denmark)

    Helgason, Einar; Burcharth, Hans F.

    2006-01-01

    small and large scale model tests show no clear evidence of scale effects for overtopping above a threshold value. In the large scale model no overtopping was measured for waveheights below Hs = 0.5m as the water sunk into the voids between the stones on the crest. For low overtopping scale effects...... are presented as the small-scale model underpredicts the overtopping discharge....

  2. Relating Cortical Atrophy in Temporal Lobe Epilepsy with Graph Diffusion-Based Network Models

    Science.gov (United States)

    Abdelnour, Farras; Mueller, Susanne; Raj, Ashish

    2015-01-01

    Mesial temporal lobe epilepsy (TLE) is characterized by stereotyped origination and spread pattern of epileptogenic activity, which is reflected in stereotyped topographic distribution of neuronal atrophy on magnetic resonance imaging (MRI). Both epileptogenic activity and atrophy spread appear to follow white matter connections. We model the networked spread of activity and atrophy in TLE from first principles via two simple first order network diffusion models. Atrophy distribution is modeled as a simple consequence of the propagation of epileptogenic activity in one model, and as a progressive degenerative process in the other. We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no). Statistical validation at the group level suggests high correlation with measured atrophy (R = 0.586 for TLE-MTS, R = 0.283 for TLE-no). We conclude that atrophy spread model out-performs the hyperactivity spread model. These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning. PMID:26513579

  3. Relating Cortical Atrophy in Temporal Lobe Epilepsy with Graph Diffusion-Based Network Models.

    Science.gov (United States)

    Abdelnour, Farras; Mueller, Susanne; Raj, Ashish

    2015-10-01

    Mesial temporal lobe epilepsy (TLE) is characterized by stereotyped origination and spread pattern of epileptogenic activity, which is reflected in stereotyped topographic distribution of neuronal atrophy on magnetic resonance imaging (MRI). Both epileptogenic activity and atrophy spread appear to follow white matter connections. We model the networked spread of activity and atrophy in TLE from first principles via two simple first order network diffusion models. Atrophy distribution is modeled as a simple consequence of the propagation of epileptogenic activity in one model, and as a progressive degenerative process in the other. We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no). Statistical validation at the group level suggests high correlation with measured atrophy (R = 0.586 for TLE-MTS, R = 0.283 for TLE-no). We conclude that atrophy spread model out-performs the hyperactivity spread model. These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning.

  4. Altered 13C glucose metabolism in the cortico-striato-thalamo-cortical loop in the MK-801 rat model of schizophrenia

    DEFF Research Database (Denmark)

    Eyjolfsson, Elvar M; Nilsen, Linn Hege; Kondziella, Daniel;

    2011-01-01

    Using a modified MK-801 (dizocilpine) N-methyl-D-aspartic acid (NMDA) receptor hypofunction model for schizophrenia, we analyzed glycolysis, as well as glutamatergic, GABAergic, and monoaminergic neurotransmitter synthesis and degradation. Rats received an injection of MK-801 daily for 6 days...... in all regions. In conclusion, neurotransmitter metabolism in the cortico-striato-thalamo-cortical loop is severely impaired in the MK-801 (dizocilpine) NMDA receptor hypofunction animal model for schizophrenia....

  5. [Study of cortico-cortical functional connectivity with vector autoregressive model of multichannel EEG].

    Science.gov (United States)

    Kurganskiĭ, A V

    2010-01-01

    This review focuses on some practical issues of using vector autoregressive model (VAR) for multichannel EEG analysis. Those issues include: EEG preprocessing, checking if the necessary conditions of VAR model applicability are met, optimal order selection, and assessment of the validity of fitted VAR model. Both non-directed (ordinary coherence and imaginary part of the complex-valued coherency) and directed (directed coherence, directed transfer function and partial directed coherence) measures of the strength of inter-channel coupling are discussed. These measures are analyzed with respect to their properties (scale invariance) and known problems in using them (spurious interactions, volume conduction).

  6. [Posterior cortical atrophy].

    Science.gov (United States)

    Solyga, Volker Moræus; Western, Elin; Solheim, Hanne; Hassel, Bjørnar; Kerty, Emilia

    2015-06-02

    Posterior cortical atrophy is a neurodegenerative condition with atrophy of posterior parts of the cerebral cortex, including the visual cortex and parts of the parietal and temporal cortices. It presents early, in the 50s or 60s, with nonspecific visual disturbances that are often misinterpreted as ophthalmological, which can delay the diagnosis. The purpose of this article is to present current knowledge about symptoms, diagnostics and treatment of this condition. The review is based on a selection of relevant articles in PubMed and on the authors' own experience with the patient group. Posterior cortical atrophy causes gradually increasing impairment in reading, distance judgement, and the ability to perceive complex images. Examination of higher visual functions, neuropsychological testing, and neuroimaging contribute to diagnosis. In the early stages, patients do not have problems with memory or insight, but cognitive impairment and dementia can develop. It is unclear whether the condition is a variant of Alzheimer's disease, or whether it is a separate disease entity. There is no established treatment, but practical measures such as the aid of social care workers, telephones with large keypads, computers with voice recognition software and audiobooks can be useful. Currently available treatment has very limited effect on the disease itself. Nevertheless it is important to identify and diagnose the condition in its early stages in order to be able to offer patients practical assistance in their daily lives.

  7. Modelling Large sound sources in a room acoustical calculation program

    DEFF Research Database (Denmark)

    Christensen, Claus Lynge

    1999-01-01

    A room acoustical model capable of modelling point, line and surface sources is presented. Line and surfacesources are modelled using a special ray-tracing algorithm detecting the radiation pattern of the surfaces in the room.Point sources are modelled using a hybrid calculation method combining...... this ray-tracing method with Image sourcemodelling. With these three source types, it is possible to model large and complex sound sources in workrooms....

  8. Modelling Large sound sources in a room acoustical calculation program

    DEFF Research Database (Denmark)

    Christensen, Claus Lynge

    1999-01-01

    A room acoustical model capable of modelling point, line and surface sources is presented. Line and surfacesources are modelled using a special ray-tracing algorithm detecting the radiation pattern of the surfaces in the room.Point sources are modelled using a hybrid calculation method combining...... this ray-tracing method with Image sourcemodelling. With these three source types, it is possible to model large and complex sound sources in workrooms....

  9. A quantitative framework to evaluate modeling of cortical development by neural stem cells

    Science.gov (United States)

    Stein, Jason L.; de la Torre-Ubieta, Luis; Tian, Yuan; Parikshak, Neelroop N.; Hernandez, Israel A.; Marchetto, Maria C.; Baker, Dylan K.; Lu, Daning; Hinman, Cassidy R.; Lowe, Jennifer K.; Wexler, Eric M.; Muotri, Alysson R.; Gage, Fred H.; Kosik, Kenneth S.; Geschwind, Daniel H.

    2014-01-01

    Summary Neural stem cells have been adopted to model a wide range of neuropsychiatric conditions in vitro. However, how well such models correspond to in vivo brain has not been evaluated in an unbiased, comprehensive manner. We used transcriptomic analyses to compare in vitro systems to developing human fetal brain and observed strong conservation of in vivo gene expression and network architecture in differentiating primary human neural progenitor cells (phNPCs). Conserved modules are enriched in genes associated with ASD, supporting the utility of phNPCs for studying neuropsychiatric disease. We also developed and validated a machine learning approach called CoNTExT that identifies the developmental maturity and regional identity of in vitro models. We observed strong differences between in vitro models, including hiPSC-derived neural progenitors from multiple laboratories. This work provides a systems biology framework for evaluating in vitro systems and supports their value in studying the molecular mechanisms of human neurodevelopmental disease. PMID:24991955

  10. Large scale stochastic spatio-temporal modelling with PCRaster

    Science.gov (United States)

    Karssenberg, Derek; Drost, Niels; Schmitz, Oliver; de Jong, Kor; Bierkens, Marc F. P.

    2013-04-01

    PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model builders as Python functions. The software comes with Python framework classes providing control flow for spatio-temporal modelling, Monte Carlo simulation, and data assimilation (Ensemble Kalman Filter and Particle Filter). Models are built by combining the spatial operations in these framework classes. This approach enables modellers without specialist programming experience to construct large, rather complicated models, as many technical details of modelling (e.g., data storage, solving spatial operations, data assimilation algorithms) are taken care of by the PCRaster toolbox. Exploratory modelling is supported by routines for prompt, interactive visualisation of stochastic spatio-temporal data generated by the models. The high computational requirements for stochastic spatio-temporal modelling, and an increasing demand to run models over large areas at high resolution, e.g. in global hydrological modelling, require an optimal use of available, heterogeneous computing resources by the modelling framework. Current work in the context of the eWaterCycle project is on a parallel implementation of the modelling engine, capable of running on a high-performance computing infrastructure such as clusters and supercomputers. Model runs will be distributed over multiple compute nodes and multiple processors (GPUs and CPUs). Parallelization will be done by parallel execution of Monte Carlo realizations and sub regions of the modelling domain. In our approach we use multiple levels of parallelism, improving scalability considerably. On the node level we will use OpenCL, the industry standard for low-level high performance computing kernels. To combine multiple nodes we will use

  11. Large scale stochastic spatio-temporal modelling with PCRaster

    NARCIS (Netherlands)

    Karssenberg, D.J.; Drost, N.; Schmitz, O.; Jong, K. de; Bierkens, M.F.P.

    2013-01-01

    PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model

  12. Large scale stochastic spatio-temporal modelling with PCRaster

    NARCIS (Netherlands)

    Karssenberg, D.J.; Drost, N.; Schmitz, O.; Jong, K. de; Bierkens, M.F.P.

    2013-01-01

    PCRaster is a software framework for building spatio-temporal models of land surface processes (http://www.pcraster.eu). Building blocks of models are spatial operations on raster maps, including a large suite of operations for water and sediment routing. These operations are available to model buil

  13. An accurate and simple large signal model of HEMT

    DEFF Research Database (Denmark)

    Liu, Qing

    1989-01-01

    A large-signal model of discrete HEMTs (high-electron-mobility transistors) has been developed. It is simple and suitable for SPICE simulation of hybrid digital ICs. The model parameters are extracted by using computer programs and data provided by the manufacturer. Based on this model, a hybrid...

  14. Aero-acoustic modeling using large eddy simulation

    DEFF Research Database (Denmark)

    Shen, Wen Zhong; Sørensen, Jens Nørkær

    2007-01-01

    The splitting technique for aero-acoustic computations is extended to simulate three-dimensional flow and acoustic waves from airfoils. The aero-acoustic model is coupled to a sub-grid-scale turbulence model for Large-Eddy Simulations. In the first test case, the model is applied to compute laminar...

  15. Large-scale functional models of visual cortex for remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Brumby, Steven P [Los Alamos National Laboratory; Kenyon, Garrett [Los Alamos National Laboratory; Rasmussen, Craig E [Los Alamos National Laboratory; Swaminarayan, Sriram [Los Alamos National Laboratory; Bettencourt, Luis [Los Alamos National Laboratory; Landecker, Will [PORTLAND STATE UNIV.

    2009-01-01

    Neuroscience has revealed many properties of neurons and of the functional organization of visual cortex that are believed to be essential to human vision, but are missing in standard artificial neural networks. Equally important may be the sheer scale of visual cortex requiring {approx}1 petaflop of computation. In a year, the retina delivers {approx}1 petapixel to the brain, leading to massively large opportunities for learning at many levels of the cortical system. We describe work at Los Alamos National Laboratory (LANL) to develop large-scale functional models of visual cortex on LANL's Roadrunner petaflop supercomputer. An initial run of a simple region VI code achieved 1.144 petaflops during trials at the IBM facility in Poughkeepsie, NY (June 2008). Here, we present criteria for assessing when a set of learned local representations is 'complete' along with general criteria for assessing computer vision models based on their projected scaling behavior. Finally, we extend one class of biologically-inspired learning models to problems of remote sensing imagery.

  16. The brain's router: a cortical network model of serial processing in the primate brain.

    Science.gov (United States)

    Zylberberg, Ariel; Fernández Slezak, Diego; Roelfsema, Pieter R; Dehaene, Stanislas; Sigman, Mariano

    2010-04-29

    The human brain efficiently solves certain operations such as object recognition and categorization through a massively parallel network of dedicated processors. However, human cognition also relies on the ability to perform an arbitrarily large set of tasks by flexibly recombining different processors into a novel chain. This flexibility comes at the cost of a severe slowing down and a seriality of operations (100-500 ms per step). A limit on parallel processing is demonstrated in experimental setups such as the psychological refractory period (PRP) and the attentional blink (AB) in which the processing of an element either significantly delays (PRP) or impedes conscious access (AB) of a second, rapidly presented element. Here we present a spiking-neuron implementation of a cognitive architecture where a large number of local parallel processors assemble together to produce goal-driven behavior. The precise mapping of incoming sensory stimuli onto motor representations relies on a "router" network capable of flexibly interconnecting processors and rapidly changing its configuration from one task to another. Simulations show that, when presented with dual-task stimuli, the network exhibits parallel processing at peripheral sensory levels, a memory buffer capable of keeping the result of sensory processing on hold, and a slow serial performance at the router stage, resulting in a performance bottleneck. The network captures the detailed dynamics of human behavior during dual-task-performance, including both mean RTs and RT distributions, and establishes concrete predictions on neuronal dynamics during dual-task experiments in humans and non-human primates.

  17. C1-Inhibitor protects from focal brain trauma in a cortical cryolesion mice model by reducing thrombo-inflammation

    Directory of Open Access Journals (Sweden)

    Christiane eAlbert-Weissenberger

    2014-09-01

    Full Text Available Traumatic brain injury (TBI induces a strong inflammatory response which includes blood-brain barrier damage, edema formation and infiltration of different immune cell subsets. More recently, microvascular thrombosis has been identified as another pathophysiological feature of TBI. The contact-kinin system represents an interface between inflammatory and thrombotic circuits and is activated in different neurological diseases. C1-Inhibitor counteracts activation of the contact-kinin system at multiple levels. We investigated the therapeutic potential of C1-Inhibitor in a model of TBI. Male and female C57BL/6 mice were subjected to cortical cryolesion and treated with C1-Inhibitor after 1 hour. Lesion volumes were assessed between day 1 and day 5 and blood-brain barrier damage, thrombus formation as well as the local inflammatory response were determined post TBI. Treatment of male mice with 15.0 IU C1-Inhibitor, but not 7.5 IU, 1 hour after cryolesion reduced lesion volumes by ~75% on day 1. This protective effect was preserved in female mice and at later stages of trauma. Mechanistically, C1-Inhibitor stabilized the blood-brain barrier and decreased the invasion of immune cells into the brain parenchyma. Moreover, C1-Inhibitor had strong antithrombotic effects. C1-Inhibitor represents a multifaceted antiinflammatory and antithrombotic compound that prevents traumatic neurodegeneration in clinically meaningful settings.

  18. Large field excursions from a few site relaxion model

    Science.gov (United States)

    Fonseca, N.; de Lima, L.; Machado, C. S.; Matheus, R. D.

    2016-07-01

    Relaxion models are an interesting new avenue to explain the radiative stability of the Standard Model scalar sector. They require very large field excursions, which are difficult to generate in a consistent UV completion and to reconcile with the compact field space of the relaxion. We propose an N -site model which naturally generates the large decay constant needed to address these issues. Our model offers distinct advantages with respect to previous proposals: the construction involves non-Abelian fields, allowing for controlled high-energy behavior and more model building possibilities, both in particle physics and inflationary models, and also admits a continuum limit when the number of sites is large, which may be interpreted as a warped extra dimension.

  19. A cortical network model of cognitive and emotional influences in human decision making.

    Science.gov (United States)

    Nazir, Azadeh Hassannejad; Liljenström, Hans

    2015-10-01

    Decision making (DM)(2) is a complex process that appears to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) seem to be essential in human decision making, where both emotional and cognitive aspects are taken into account. In this paper, we present a computational network model representing the neural information processing of DM, from perception to behavior. We model the population dynamics of the three neural structures (amygdala, OFC and LPFC), as well as their interaction. In our model, the neurodynamic activity of amygdala and OFC represents the neural correlates of secondary emotion, while the activity of certain neural populations in OFC alone represents the outcome expectancy of different options. The cognitive/rational aspect of DM is associated with LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in DM under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. Simulation results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on CO2 emissions and climate change.

  20. Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't

    Science.gov (United States)

    Noreika, Valdas; Gueorguiev, David; Shtyrov, Yury; Bekinschtein, Tristan A.; Henson, Richard

    2016-01-01

    There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called “mismatch response”). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an “omission” response). This situation arguably provides a more direct measure of “top-down” predictions in the absence of confounding “bottom-up” input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of “bottom-up” stimuli with the presence versus absence of “top-down” attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward “prediction” connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction. SIGNIFICANCE STATEMENT Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known “mismatch response.” But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain

  1. The effects of glucocorticoid on microarchitecture, collagen, mineral and mechanical properties of sheep femur cortical bone

    DEFF Research Database (Denmark)

    Ding, Ming; Danielsen, Carl C; Overgaard, Søren

    mechanical properties in the glucocorticoid-2. In conclusion, 7 months glucocorticoid treatment with malnutrition had significant impact on cortical microarchitecture of sheep femur midshaft. These changes occurred particularly 3 months after the glucocorticoid cessation suggesting a delayed effect......The effects of glucocorticoid on microarchitecture, collagen, mineral and mechanical properties of sheep femur cortical bone – Validation of large animal model for tissue engineering and biomaterial research Ming Ding,1* Carl Christian Danielsen,2 Søren Overgaard1 1Orthopaedic Research Laboratory...

  2. Mathematical Imaging and Modeling of Cortical Spreading Depression and Wound Healing

    Science.gov (United States)

    2015-02-05

    phase diagram that maps out when a retinal detachment is unstable, or is stable and will likely heal . We have begun to generalize this problem in two...Spreading Depression and W mmd Healing Sb. GRANT NUMBER Sc. PROGRAM ELEMENT NUMBER 611102 6. AUTHORS Sd. PROJECT NUMBER Tom Chou Se. TASK NUMBER...Spreading Depression and Wound Healing ." The research conducted under this grant represents advances made in image analysis, front tracking, modeling

  3. Large field inflation models from higher-dimensional gauge theories

    Science.gov (United States)

    Furuuchi, Kazuyuki; Koyama, Yoji

    2015-02-01

    Motivated by the recent detection of B-mode polarization of CMB by BICEP2 which is possibly of primordial origin, we study large field inflation models which can be obtained from higher-dimensional gauge theories. The constraints from CMB observations on the gauge theory parameters are given, and their naturalness are discussed. Among the models analyzed, Dante's Inferno model turns out to be the most preferred model in this framework.

  4. Large field inflation models from higher-dimensional gauge theories

    Energy Technology Data Exchange (ETDEWEB)

    Furuuchi, Kazuyuki [Manipal Centre for Natural Sciences, Manipal University, Manipal, Karnataka 576104 (India); Koyama, Yoji [Department of Physics, National Tsing-Hua University, Hsinchu 30013, Taiwan R.O.C. (China)

    2015-02-23

    Motivated by the recent detection of B-mode polarization of CMB by BICEP2 which is possibly of primordial origin, we study large field inflation models which can be obtained from higher-dimensional gauge theories. The constraints from CMB observations on the gauge theory parameters are given, and their naturalness are discussed. Among the models analyzed, Dante’s Inferno model turns out to be the most preferred model in this framework.

  5. The Unique Brain Anatomy of Meditation Practitioners: Alterations in Cortical Gyrification

    Directory of Open Access Journals (Sweden)

    Eileen eLuders

    2012-02-01

    Full Text Available Several cortical regions are reported to vary in meditation practitioners. However, since prior analyses were focused on examining gray matter or cortical thickness, additional effects with respect to other cortical features might have remained undetected. Gyrification (the pattern and degree of cortical folding is an important cerebral characteristic related to the geometry of the brain’s surface. Cortical folding occurs early in development and might be linked to behavioral traits. Thus, exploring cortical gyrification in long-term meditators may provide additional clues with respect to the underlying anatomical correlates of meditation. This study examined cortical gyrification in a large sample (n=100 of meditators and controls, carefully matched for sex and age. Cortical gyrification was established via calculating mean curvature across thousands of vertices on individual cortical surface models. Pronounced group differences indicating larger gyrification in meditators were evident within the left precentral gyrus, right fusiform gyrus, right cuneus, as well as left and right anterior dorsal insula (the latter representing the global significance maximum. Although the exact functional implications of larger cortical gyrification remain to be established, these findings suggest the insula to be a key structure involved in aspects of meditation. For example, variations in insular complexity could affect the regulation of well-known distractions in the process of meditation, such as daydreaming, mind-wandering, and projections into past or future. Moreover, given that meditators are masters in introspection, awareness, and emotional control, increased insular gyrification may reflect an ideal integration of autonomic, affective, and cognitive processes. Due to the cross-sectional nature of this study, further research is necessary determine the relative contribution of nature and nurture to links between cortical gyrification and meditation.

  6. Long-term upregulation of cortical glutamatergic AMPA receptors in a mouse model of chronic visceral pain.

    Science.gov (United States)

    Liu, Shui-Bing; Zhang, Ming-Ming; Cheng, Lin-Feng; Shi, Jiao; Lu, Jing-Shan; Zhuo, Min

    2015-11-19

    Irritable bowel syndrome (IBS) is one of the most common functional gastrointestinal disorders and it causes long-lasting visceral pain and discomfort. AMPA receptor mediated long-term potentiation (LTP) has been shown to play a critical role in animal models of neuropathic and inflammatory pain. No report is available for central changes in the ACC of mice with chronic visceral pain. In this study, we used integrative methods to investigate potential central plastic changes in the anterior cingulate cortex (ACC) of a visceral pain mouse model induced by intracolonic injection of zymosan. We found that visceral pain induced an increased expression of AMPA receptors (at the post synapses) in the ACC via an enhanced trafficking of the AMPA receptors to the membrane. Both GluA1 and GluA2/3 subunits were significantly increased. Supporting biochemical changes, excitatory synaptic transmission in the ACC were also significantly enhanced. Microinjection of AMPA receptor inhibitor IEM1460 into the ACC inhibited visceral and spontaneous pain behaviors. Furthermore, we found that the phosphorylation of GluA1 at the Ser845 site was increased, suggesting that GluA1 phosphorylation may contribute to AMPA receptor trafficking. Using genetically knockout mice lacking calcium-calmodulin stimulated adenylyl cyclase subtype 1 (AC1), we found that AMPA receptor phosphorylation and its membrane trafficking induced by zymosan injection were completely blocked. Our results provide direct evidence for cortical AMPA receptors to contribute to zymosan-induced visceral and spontaneous pain and inhibition of AC1 activity may help to reduce chronic visceral pain.

  7. Large N Scalars: From Glueballs to Dynamical Higgs Models

    CERN Document Server

    Sannino, Francesco

    2015-01-01

    We construct effective Lagrangians, and corresponding counting schemes, valid to describe the dynamics of the lowest lying large N stable massive composite state emerging in strongly coupled theories. The large N counting rules can now be employed when computing quantum corrections via an effective Lagrangian description. The framework allows for systematic investigations of composite dynamics of non-Goldstone nature. Relevant examples are the lightest glueball states emerging in any Yang-Mills theory. We further apply the effective approach and associated counting scheme to composite models at the electroweak scale. To illustrate the formalism we consider the possibility that the Higgs emerges as: the lightest glueball of a new composite theory; the large N scalar meson in models of dynamical electroweak symmetry breaking; the large N pseudodilaton useful also for models of near-conformal dynamics. For each of these realisations we determine the leading N corrections to the electroweak precision parameters. ...

  8. Modelling and measurements of wakes in large wind farms

    DEFF Research Database (Denmark)

    Barthelmie, Rebecca Jane; Rathmann, Ole; Frandsen, Sten Tronæs;

    2007-01-01

    The paper presents research conducted in the Flow workpackage of the EU funded UPWIND project which focuses on improving models of flow within and downwind of large wind farms in complex terrain and offshore. The main activity is modelling the behaviour of wind turbine wakes in order to improve...

  9. Modelling and measurements of wakes in large wind farms

    DEFF Research Database (Denmark)

    Barthelmie, Rebecca Jane; Rathmann, Ole; Frandsen, Sten Tronæs

    2007-01-01

    The paper presents research conducted in the Flow workpackage of the EU funded UPWIND project which focuses on improving models of flow within and downwind of large wind farms in complex terrain and offshore. The main activity is modelling the behaviour of wind turbine wakes in order to improve p...

  10. State-space models of impulse hemodynamic responses over motor, somatosensory, and visual cortices.

    Science.gov (United States)

    Hong, Keum-Shik; Nguyen, Hoang-Dung

    2014-06-01

    THE PAPER PRESENTS STATE SPACE MODELS OF THE HEMODYNAMIC RESPONSE (HR) OF FNIRS TO AN IMPULSE STIMULUS IN THREE BRAIN REGIONS: motor cortex (MC), somatosensory cortex (SC), and visual cortex (VC). Nineteen healthy subjects were examined. For each cortex, three impulse HRs experimentally obtained were averaged. The averaged signal was converted to a state space equation by using the subspace method. The activation peak and the undershoot peak of the oxy-hemoglobin (HbO) in MC are noticeably higher than those in SC and VC. The time-to-peaks of the HbO in three brain regions are almost the same (about 6.76 76 ± 0.2 s). The time to undershoot peak in VC is the largest among three. The HbO decreases in the early stage (~0.46 s) in MC and VC, but it is not so in SC. These findings were well described with the developed state space equations. Another advantage of the proposed method is its easy applicability in generating the expected HR to arbitrary stimuli in an online (or real-time) imaging. Experimental results are demonstrated.

  11. Cortical reorganization in recent-onset tinnitus patients by the Heidelberg Model of Music Therapy

    Science.gov (United States)

    Krick, Christoph M.; Grapp, Miriam; Daneshvar-Talebi, Jonas; Reith, Wolfgang; Plinkert, Peter K.; Bolay, Hans Volker

    2015-01-01

    Pathophysiology and treatment of tinnitus still are fields of intensive research. The neuroscientifically motivated Heidelberg Model of Music Therapy, previously developed by the German Center for Music Therapy Research, Heidelberg, Germany, was applied to explore its effects on individual distress and on brain structures. This therapy is a compact and fast application of nine consecutive 50-min sessions of individualized therapy implemented over 1 week. Clinical improvement and long-term effects over several years have previously been published. However, the underlying neural basis of the therapy's success has not yet been explored. In the current study, the therapy was applied to acute tinnitus patients (TG) and healthy active controls (AC). Non-treated patients were also included as passive controls (PTC). As predicted, the therapeutic intervention led to a significant decrease of tinnitus-related distress in TG compared to PTC. Before and after the study week, high-resolution MRT scans were obtained for each subject. Assessment by repeated measures design for several groups (Two-Way ANOVA) revealed structural gray matter (GM) increase in TG compared to PTC, comprising clusters in precuneus, medial superior frontal areas, and in the auditory cortex. This pattern was further applied as mask for general GM changes as induced by the therapy week. The therapy-like procedure in AC also elicited similar GM increases in precuneus and frontal regions. Comparison between structural effects in TG vs. AC was calculated within the mask for general GM changes to obtain specific effects in tinnitus patients, yielding GM increase in right Heschl's gyrus, right Rolandic operculum, and medial superior frontal regions. In line with recent findings on the crucial role of the auditory cortex in maintaining tinnitus-related distress, a causative relation between the therapy-related GM alterations in auditory areas and the long-lasting therapy effects can be assumed. PMID:25745385

  12. Cortical reorganization in recent-onset tinnitus patients by the Heidelberg Model of Music Therapy

    Directory of Open Access Journals (Sweden)

    Christoph Maria Krick

    2015-02-01

    Full Text Available Pathophysiology and treatment of tinnitus still are fields of intensive research. The neuroscientifically motivated Heidelberg Model of Music Therapy, previously developed by the German Center for Music Therapy Research, Heidelberg, Germany, was applied to explore its effects on individual distress and on brain structures. This therapy is a compact and fast application of nine consecutive 50-minutes sessions of individualized therapy implemented over one week. Clinical improvement and long-term effects over several years have previously been published. However the underlying neural basis of the therapy’s success has not yet been explored. In the current study, the therapy was applied to acute tinnitus patients (TG and healthy active controls (AC. Non-treated patients were also included as passive controls (PTC. As predicted, the therapeutic intervention led to a significant decrease of tinnitus-related distress in TG compared to PTC. Before and after the study week, high-resolution MRT scans were obtained for each subject. Assessment by repeated measures design for several groups (two-way ANOVA revealed structural gray matter (GM increase in TG compared to PTC, comprising clusters in precuneus, medial superior frontal areas, and in the auditory cortex. This pattern was further applied as mask for general GM changes as induced by the therapy week. The therapy-like procedure in AC also elicited similar GM increases in precuneus and frontal regions. Comparison between structural effects in TG versus AC was calculated within the mask for general GM changes to obtain specific effects in tinnitus patients, yielding GM increase in right Heschl's gyrus, right Rolandic operculum, and medial superior frontal regions. In line with recent findings on the crucial role of the auditory cortex in maintaining tinnitus-related distress, a causative relation between the therapy-related GM alterations in auditory areas and the long-lasting therapy effects can be

  13. Influence of Slow Oscillation on Hippocampal Activity and Ripples Through Cortico-Hippocampal Synaptic Interactions, Analyzed by a Cortical-CA3-CA1 Network Model

    Directory of Open Access Journals (Sweden)

    Jiannis eTaxidis

    2013-02-01

    Full Text Available Hippocampal sharp wave-ripple complexes (SWRs involve the synchronous discharge of thousands of cells throughout the CA3-CA1-subiculum-entorhinal cortex axis. Their strong transient output affects cortical targets, rendering SWRs a possible means for memory transfer from the hippocampus to the neocortex for long-term storage. Neurophysiological observations of hippocampal activity modulation by the cortical slow oscillation (SO during deep sleep and anesthesia, and correlations between ripples and UP states, support the role of SWRs in memory consolidation through a cortico-hippocampal feedback loop. We couple a cortical network exhibiting SO with a hippocampal CA3-CA1 computational network model exhibiting SWRs, in order to model such cortico-hippocampal correlations and uncover important parameters and coupling mechanisms controlling them. The cortical oscillatory output entrains the CA3 network via connections representing the mossy fiber input, and the CA1 network via the temporoammonic pathway. The spiking activity in CA3 and CA1 is shown to depend on the excitation-to-inhibition ratio, induced by combining the two hippocampal inputs, with mossy fiber input controlling the UP-state correlation of CA3 population bursts and corresponding SWRs, whereas the temporoammonic input affects the overall CA1 spiking activity. Ripple characteristics and pyramidal spiking participation to SWRs are shaped by the strength of the Schaffer collateral drive. A set of in vivo recordings from the rat hippocampus confirms a model-predicted segregation of pyramidal cells into subgroups according to the SO state where they preferentially fire and their response to SWRs. These groups can potentially play distinct functional roles in the replay of spike sequences.

  14. Large scale experiments as a tool for numerical model development

    DEFF Research Database (Denmark)

    Kirkegaard, Jens; Hansen, Erik Asp; Fuchs, Jesper;

    2003-01-01

    for improvement of the reliability of physical model results. This paper demonstrates by examples that numerical modelling benefits in various ways from experimental studies (in large and small laboratory facilities). The examples range from very general hydrodynamic descriptions of wave phenomena to specific......Experimental modelling is an important tool for study of hydrodynamic phenomena. The applicability of experiments can be expanded by the use of numerical models and experiments are important for documentation of the validity of numerical tools. In other cases numerical tools can be applied...... hydrodynamic interaction with structures. The examples also show that numerical model development benefits from international co-operation and sharing of high quality results....

  15. LARGE SIGNAL DISCRETE-TIME MODEL FOR PARALLELED BUCK CONVERTERS

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    As a number of switch-combinations are involved in operation of multi-converter-system, conventional methods for obtaining discrete-time large signal model of these converter systems result in a very complex solution. A simple sampled-data technique for modeling distributed dc-dc PWM converters system (DCS) was proposed. The resulting model is nonlinear and can be linearized for analysis and design of DCS. These models are also suitable for fast simulation of these networks. As the input and output of dc-dc converters are slow varying, suitable model for DCS was obtained in terms of the finite order input/output approximation.

  16. Explaining the high voice superiority effect in polyphonic music: evidence from cortical evoked potentials and peripheral auditory models.

    Science.gov (United States)

    Trainor, Laurel J; Marie, Céline; Bruce, Ian C; Bidelman, Gavin M

    2014-02-01

    Natural auditory environments contain multiple simultaneously-sounding objects and the auditory system must parse the incoming complex sound wave they collectively create into parts that represent each of these individual objects. Music often similarly requires processing of more than one voice or stream at the same time, and behavioral studies demonstrate that human listeners show a systematic perceptual bias in processing the highest voice in multi-voiced music. Here, we review studies utilizing event-related brain potentials (ERPs), which support the notions that (1) separate memory traces are formed for two simultaneous voices (even without conscious awareness) in auditory cortex and (2) adults show more robust encoding (i.e., larger ERP responses) to deviant pitches in the higher than in the lower voice, indicating better encoding of the former. Furthermore, infants also show this high-voice superiority effect, suggesting that the perceptual dominance observed across studies might result from neurophysiological characteristics of the peripheral auditory system. Although musically untrained adults show smaller responses in general than musically trained adults, both groups similarly show a more robust cortical representation of the higher than of the lower voice. Finally, years of experience playing a bass-range instrument reduces but does not reverse the high voice superiority effect, indicating that although it can be modified, it is not highly neuroplastic. Results of new modeling experiments examined the possibility that characteristics of middle-ear filtering and cochlear dynamics (e.g., suppression) reflected in auditory nerve firing patterns might account for the higher-voice superiority effect. Simulations show that both place and temporal AN coding schemes well-predict a high-voice superiority across a wide range of interval spacings and registers. Collectively, we infer an innate, peripheral origin for the higher-voice superiority observed in human

  17. Model of risk of cortical cataract in the US population with exposure to increased ultraviolet radiation due to stratospheric ozone depletion.

    Science.gov (United States)

    West, Sheila K; Longstreth, Janice D; Munoz, Beatriz E; Pitcher, Hugh M; Duncan, Donald D

    2005-12-01

    The authors modeled the possible consequences for US cataract incidence of increases in ultraviolet B radiation due to ozone depletion. Data on the dose-response relation between ocular exposure to ultraviolet B radiation and cortical cataract were derived from a population-based study (the Salisbury Eye Evaluation Project, Salisbury, Maryland) in which extensive data on cataract and ultraviolet radiation were collected in persons aged 65-84 years. Exposure estimates for the US population were derived using estimated ultraviolet radiation fluxes as a function of wavelength. US Census data were used to obtain the age, ethnicity, and sex distribution of the population. Predicted probabilities of cataract were derived from the age-, sex-, and ethnicity-specific ocular ultraviolet exposure data and were modeled under conditions of 5-20% ozone depletion. The analysis indicated that by 2050, the prevalence of cortical cataract will increase above expected levels by 1.3-6.9%. The authors estimate that with 5-20% ozone depletion, there will be 167,000-830,000 additional cases of cortical cataract by 2050. Because of the high prevalence of cataract in older persons, at a 2003 cost of 3,370 dollars per cataract operation, this increase could represent an excess cost of 563 million dollars to 2.8 billion dollars.

  18. Toy Model for Large Non-Symmetric Random Matrices

    CERN Document Server

    Snarska, Małgorzata

    2010-01-01

    Non-symmetric rectangular correlation matrices occur in many problems in economics. We test the method of extracting statistically meaningful correlations between input and output variables of large dimensionality and build a toy model for artificially included correlations in large random time series.The results are then applied to analysis of polish macroeconomic data and can be used as an alternative to classical cointegration approach.

  19. Statistical Modeling of Large-Scale Scientific Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Eliassi-Rad, T; Baldwin, C; Abdulla, G; Critchlow, T

    2003-11-15

    With the advent of massively parallel computer systems, scientists are now able to simulate complex phenomena (e.g., explosions of a stars). Such scientific simulations typically generate large-scale data sets over the spatio-temporal space. Unfortunately, the sheer sizes of the generated data sets make efficient exploration of them impossible. Constructing queriable statistical models is an essential step in helping scientists glean new insight from their computer simulations. We define queriable statistical models to be descriptive statistics that (1) summarize and describe the data within a user-defined modeling error, and (2) are able to answer complex range-based queries over the spatiotemporal dimensions. In this chapter, we describe systems that build queriable statistical models for large-scale scientific simulation data sets. In particular, we present our Ad-hoc Queries for Simulation (AQSim) infrastructure, which reduces the data storage requirements and query access times by (1) creating and storing queriable statistical models of the data at multiple resolutions, and (2) evaluating queries on these models of the data instead of the entire data set. Within AQSim, we focus on three simple but effective statistical modeling techniques. AQSim's first modeling technique (called univariate mean modeler) computes the ''true'' (unbiased) mean of systematic partitions of the data. AQSim's second statistical modeling technique (called univariate goodness-of-fit modeler) uses the Andersen-Darling goodness-of-fit method on systematic partitions of the data. Finally, AQSim's third statistical modeling technique (called multivariate clusterer) utilizes the cosine similarity measure to cluster the data into similar groups. Our experimental evaluations on several scientific simulation data sets illustrate the value of using these statistical models on large-scale simulation data sets.

  20. Satellite image collection modeling for large area hazard emergency response

    Science.gov (United States)

    Liu, Shufan; Hodgson, Michael E.

    2016-08-01

    Timely collection of critical hazard information is the key to intelligent and effective hazard emergency response decisions. Satellite remote sensing imagery provides an effective way to collect critical information. Natural hazards, however, often have large impact areas - larger than a single satellite scene. Additionally, the hazard impact area may be discontinuous, particularly in flooding or tornado hazard events. In this paper, a spatial optimization model is proposed to solve the large area satellite image acquisition planning problem in the context of hazard emergency response. In the model, a large hazard impact area is represented as multiple polygons and image collection priorities for different portion of impact area are addressed. The optimization problem is solved with an exact algorithm. Application results demonstrate that the proposed method can address the satellite image acquisition planning problem. A spatial decision support system supporting the optimization model was developed. Several examples of image acquisition problems are used to demonstrate the complexity of the problem and derive optimized solutions.

  1. Modelling and transient stability of large wind farms

    DEFF Research Database (Denmark)

    Akhmatov, Vladislav; Knudsen, Hans; Nielsen, Arne Hejde

    2003-01-01

    The paper is dealing-with modelling and short-term Voltage stability considerations of large wind farms. A physical model of a large offshore wind farm consisting of a large number of windmills is implemented in the dynamic simulation tool PSS/E. Each windmill in the wind farm is represented...... by a physical model of grid-connected windmills. The windmill generators ate conventional induction generators and the wind farm is ac-connected to the power system. Improvements-of short-term voltage stability in case of failure events in the external power system are treated with use of conventional generator...... of dynamic reactive compensation demands. In case of blade angle control applied at failure events, dynamic reactive compensation is not necessary for maintaining the voltage stability....

  2. Grid cells and cortical representation.

    Science.gov (United States)

    Moser, Edvard I; Roudi, Yasser; Witter, Menno P; Kentros, Clifford; Bonhoeffer, Tobias; Moser, May-Britt

    2014-07-01

    One of the grand challenges in neuroscience is to comprehend neural computation in the association cortices, the parts of the cortex that have shown the largest expansion and differentiation during mammalian evolution and that are thought to contribute profoundly to the emergence of advanced cognition in humans. In this Review, we use grid cells in the medial entorhinal cortex as a gateway to understand network computation at a stage of cortical processing in which firing patterns are shaped not primarily by incoming sensory signals but to a large extent by the intrinsic properties of the local circuit.

  3. Dualities in 3D large N vector models

    Science.gov (United States)

    Muteeb, Nouman; Zayas, Leopoldo A. Pando; Quevedo, Fernando

    2016-05-01

    Using an explicit path integral approach we derive non-abelian bosonization and duality of 3D systems in the large N limit. We first consider a fermionic U( N) vector model coupled to level k Chern-Simons theory, following standard techniques we gauge the original global symmetry and impose the corresponding field strength F μν to vanish introducing a Lagrange multiplier Λ. Exchanging the order of integrations we obtain the bosonized theory with Λ as the propagating field using the large N rather than the previously used large mass limit. Next we follow the same procedure to dualize the scalar U ( N) vector model coupled to Chern-Simons and find its corresponding dual theory. Finally, we compare the partition functions of the two resulting theories and find that they agree in the large N limit including a level/rank duality. This provides a constructive evidence for previous proposals on level/rank duality of 3D vector models in the large N limit. We also present a partial analysis at subleading order in large N and find that the duality does not generically hold at this level.

  4. Dualities in 3D large N vector models

    Energy Technology Data Exchange (ETDEWEB)

    Muteeb, Nouman [The Abdus Salam International Centre for Theoretical Physics, ICTP,Strada Costiera 11, 34014 Trieste (Italy); SISSA,Via Bonomea 265, 34136 Trieste (Italy); Zayas, Leopoldo A. Pando [The Abdus Salam International Centre for Theoretical Physics, ICTP,Strada Costiera 11, 34014 Trieste (Italy); Michigan Center for Theoretical Physics, Department of Physics,University of Michigan, Ann Arbor, MI 48109 (United States); Quevedo, Fernando [The Abdus Salam International Centre for Theoretical Physics, ICTP,Strada Costiera 11, 34014 Trieste (Italy); DAMTP, CMS, University of Cambridge,Wilberforce Road, Cambridge, CB3 0WA (United Kingdom)

    2016-05-09

    Using an explicit path integral approach we derive non-abelian bosonization and duality of 3D systems in the large N limit. We first consider a fermionic U(N) vector model coupled to level k Chern-Simons theory, following standard techniques we gauge the original global symmetry and impose the corresponding field strength F{sub μν} to vanish introducing a Lagrange multiplier Λ. Exchanging the order of integrations we obtain the bosonized theory with Λ as the propagating field using the large N rather than the previously used large mass limit. Next we follow the same procedure to dualize the scalar U(N) vector model coupled to Chern-Simons and find its corresponding dual theory. Finally, we compare the partition functions of the two resulting theories and find that they agree in the large N limit including a level/rank duality. This provides a constructive evidence for previous proposals on level/rank duality of 3D vector models in the large N limit. We also present a partial analysis at subleading order in large N and find that the duality does not generically hold at this level.

  5. Age-dependent alterations in the cortical entrainment of subthalamic nucleus neurons in the YAC128 mouse model of Huntington's disease.

    Science.gov (United States)

    Callahan, Joshua W; Abercrombie, Elizabeth D

    2015-06-01

    Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that results in motor, cognitive and psychiatric abnormalities. Dysfunction in neuronal processing between the cortex and the basal ganglia is fundamental to the onset and progression of the HD phenotype. The corticosubthalamic hyperdirect pathway plays a crucial role in motor selection and blockade of neuronal activity in the subthalamic nucleus (STN) results in hyperkinetic movement abnormalities, similar to the motor symptoms associated with HD. The aim of the present study was to examine whether changes in the fidelity of information transmission between the cortex and the STN emerge as a function of phenotypic severity in the YAC128 mouse model of HD. We obtained in vivo extracellular recordings in the STN and concomitant electrocorticogram (ECoG) recordings during discrete brain states that reflected global cortical network synchronization or desynchronization. At early ages in YAC128 mice, both the cortex and the STN exhibited patterns of hyperexcitability. As symptom severity progressed, cortical entrainment of STN activity was disrupted and there was an increase in the proportion of non-oscillating, tonically firing STN neurons that were less phase-locked to cortical activity. Concomitant to the dissipation of STN entrainment, there was a reduction in the evoked response of STN neurons to focal cortical stimulation. The spontaneous discharge of STN neurons in YAC128 mice also decreased with age and symptom severity. These results indicate dysfunction in the flow of information within the corticosubthalamic circuit and demonstrate progressive age-related disconnection of the hyperdirect pathway in a transgenic mouse model of HD.

  6. Restoration of Progranulin Expression Rescues Cortical Neuron Generation in an Induced Pluripotent Stem Cell Model of Frontotemporal Dementia

    Directory of Open Access Journals (Sweden)

    Susanna Raitano

    2015-01-01

    Full Text Available To understand how haploinsufficiency of progranulin (PGRN causes frontotemporal dementia (FTD, we created induced pluripotent stem cells (iPSCs from patients carrying the GRNIVS1+5G > C mutation (FTD-iPSCs. FTD-iPSCs were fated to cortical neurons, the cells most affected in FTD. Although generation of neuroprogenitors was unaffected, their further differentiation into CTIP2-, FOXP2-, or TBR1-TUJ1 double-positive cortical neurons, but not motorneurons, was significantly decreased in FTD-neural progeny. Zinc finger nuclease-mediated introduction of GRN cDNA into the AAVS1 locus corrected defects in cortical neurogenesis, demonstrating that PGRN haploinsufficiency causes inefficient cortical neuron generation. RNA sequencing analysis confirmed reversal of the altered gene expression profile following genetic correction. We identified the Wnt signaling pathway as one of the top defective pathways in FTD-iPSC-derived neurons, which was reversed following genetic correction. Differentiation of FTD-iPSCs in the presence of a WNT inhibitor mitigated defective corticogenesis. Therefore, we demonstrate that PGRN haploinsufficiency hampers corticogenesis in vitro.

  7. Populations of Radial Glial Cells Respond Differently to Reelin and Neuregulin1 in a Ferret Model of Cortical Dysplasia

    Science.gov (United States)

    2010-10-28

    out of the ventricular zone, but do not play a role in allowing further movement toward the cortical plate. Materials and Methods Ethics Statement...transformation into astrocytes. Anatomy and embryology 156(2): 115–152. 11. Voigt T (1989) Development of glial cells in the cerebral wall of ferrets

  8. Exposing earth surface process model simulations to a large audience

    Science.gov (United States)

    Overeem, I.; Kettner, A. J.; Borkowski, L.; Russell, E. L.; Peddicord, H.

    2015-12-01

    The Community Surface Dynamics Modeling System (CSDMS) represents a diverse group of >1300 scientists who develop and apply numerical models to better understand the Earth's surface. CSDMS has a mandate to make the public more aware of model capabilities and therefore started sharing state-of-the-art surface process modeling results with large audiences. One platform to reach audiences outside the science community is through museum displays on 'Science on a Sphere' (SOS). Developed by NOAA, SOS is a giant globe, linked with computers and multiple projectors and can display data and animations on a sphere. CSDMS has developed and contributed model simulation datasets for the SOS system since 2014, including hydrological processes, coastal processes, and human interactions with the environment. Model simulations of a hydrological and sediment transport model (WBM-SED) illustrate global river discharge patterns. WAVEWATCH III simulations have been specifically processed to show the impacts of hurricanes on ocean waves, with focus on hurricane Katrina and super storm Sandy. A large world dataset of dams built over the last two centuries gives an impression of the profound influence of humans on water management. Given the exposure of SOS, CSDMS aims to contribute at least 2 model datasets a year, and will soon provide displays of global river sediment fluxes and changes of the sea ice free season along the Arctic coast. Over 100 facilities worldwide show these numerical model displays to an estimated 33 million people every year. Datasets storyboards, and teacher follow-up materials associated with the simulations, are developed to address common core science K-12 standards. CSDMS dataset documentation aims to make people aware of the fact that they look at numerical model results, that underlying models have inherent assumptions and simplifications, and that limitations are known. CSDMS contributions aim to familiarize large audiences with the use of numerical

  9. Modeling Study of Planar Flexible Manipulator Undergoing Large Deformation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The planar flexible manipulator undergoing large deformation is investigated by using finite element method (FEM). Three kinds of reference frames are employed to describe the deformation of arbitrary point in the flexible manipulator, which are global frame, body-fixed frame and co-rotational frame. The rigid-flexible coupling dynamic equation of the planar flexible manipulator is derived using the Hamilton's principle. Numerical simulations are carried out in the end of this paper to demonstrate the effectiveness of the proposed model. The simulation results indicate that the proposed model is efficient not only for small deformation but also for large deformation.

  10. Hamilton-Jacobi skeleton on cortical surfaces.

    Science.gov (United States)

    Shi, Y; Thompson, P M; Dinov, I; Toga, A W

    2008-05-01

    In this paper, we propose a new method to construct graphical representations of cortical folding patterns by computing skeletons on triangulated cortical surfaces. In our approach, a cortical surface is first partitioned into sulcal and gyral regions via the solution of a variational problem using graph cuts, which can guarantee global optimality. After that, we extend the method of Hamilton-Jacobi skeleton [1] to subsets of triangulated surfaces, together with a geometrically intuitive pruning process that can trade off between skeleton complexity and the completeness of representing folding patterns. Compared with previous work that uses skeletons of 3-D volumes to represent sulcal patterns, the skeletons on cortical surfaces can be easily decomposed into branches and provide a simpler way to construct graphical representations of cortical morphometry. In our experiments, we demonstrate our method on two different cortical surface models, its ability of capturing major sulcal patterns and its application to compute skeletons of gyral regions.

  11. Cinlar Subgrid Scale Model for Large Eddy Simulation

    CERN Document Server

    Kara, Rukiye

    2016-01-01

    We construct a new subgrid scale (SGS) stress model for representing the small scale effects in large eddy simulation (LES) of incompressible flows. We use the covariance tensor for representing the Reynolds stress and include Clark's model for the cross stress. The Reynolds stress is obtained analytically from Cinlar random velocity field, which is based on vortex structures observed in the ocean at the subgrid scale. The validity of the model is tested with turbulent channel flow computed in OpenFOAM. It is compared with the most frequently used Smagorinsky and one-equation eddy SGS models through DNS data.

  12. Including investment risk in large-scale power market models

    DEFF Research Database (Denmark)

    Lemming, Jørgen Kjærgaard; Meibom, P.

    2003-01-01

    can be included in large-scale partial equilibrium models of the power market. The analyses are divided into a part about risk measures appropriate for power market investors and a more technical part about the combination of a risk-adjustment model and a partial-equilibrium model. To illustrate......Long-term energy market models can be used to examine investments in production technologies, however, with market liberalisation it is crucial that such models include investment risks and investor behaviour. This paper analyses how the effect of investment risk on production technology selection...... the analyses quantitatively, a framework based on an iterative interaction between the equilibrium model and a separate risk-adjustment module was constructed. To illustrate the features of the proposed modelling approach we examined how uncertainty in demand and variable costs affects the optimal choice...

  13. Model Experiments for the Determination of Airflow in Large Spaces

    DEFF Research Database (Denmark)

    Nielsen, Peter V.

    Model experiments are one of the methods used for the determination of airflow in large spaces. This paper will discuss the formation of the governing dimensionless numbers. It is shown that experiments with a reduced scale often will necessitate a fully developed turbulence level of the flow....... Details of the flow from supply openings are very important for the determination of room air distribution. It is in some cases possible to make a simplified supply opening for the model experiment....

  14. A first large-scale flood inundation forecasting model

    Energy Technology Data Exchange (ETDEWEB)

    Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie; Andreadis, Konstantinos M.; Pappenberger, Florian; Phanthuwongpakdee, Kay; Hall, Amanda C.; Bates, Paul D.

    2013-11-04

    At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domain has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode

  15. The shh signaling pathway is upregulated in multiple cell types in cortical ischemia and influences the outcome of stroke in an animal model.

    Science.gov (United States)

    Jin, Yongmin; Raviv, Nataly; Barnett, Austin; Bambakidis, Nicholas C; Filichia, Emily; Luo, Yu

    2015-01-01

    Recently the sonic hedgehog (shh) signaling pathway has been shown to play an important role in regulating repair and regenerative responses after brain injury, including ischemia. However, the precise cellular components that express and upregulate the shh gene and the cellular components that respond to shh signaling remain to be identified. In this study, using a distal MCA occlusion model, our data show that the shh signal is upregulated both at the cortical area near the injury site and in the adjacent striatum. Multiple cell types upregulate shh signaling in ischemic brain, including neurons, reactive astrocytes and nestin-expressing cells. The shh signaling pathway genes are also expressed in the neural stem cells (NSCs) niche in the subventricular zone (SVZ). Conditional deletion of the shh gene in nestin-expressing cells both at the SVZ niche and at the ischemic site lead to significantly more severe behavioral deficits in these shh iKO mice after cortical stroke, measured using an automated open field locomotion apparatus (Student's t-test, pshh signaling agonist (SAG) demonstrated less deficits in behavioral function, compared to vehicle-treated mice. At 7 days after stroke, SAG-treated mice showed higher values in multiple horizontal movement parameters compared to vehicle treated mice (Student's t-test, p0.05). In summary, our data demonstrate that shh signaling plays critical and ongoing roles in response to ischemic injury and modulation of shh signaling in vivo alters the functional outcome after cortical ischemic injury.

  16. "Hyperglutamatergic cortico-striato-thalamo-cortical circuit" breaker drugs alleviate tics in a transgenic circuit model of Tourette׳s syndrome.

    Science.gov (United States)

    Nordstrom, Eric J; Bittner, Katie C; McGrath, Michael J; Parks, Clinton R; Burton, Frank H

    2015-12-10

    The brain circuits underlying tics in Tourette׳s syndrome (TS) are unknown but thought to involve cortico/amygdalo-striato-thalamo-cortical (CSTC) loop hyperactivity. We previously engineered a transgenic mouse "circuit model" of TS by expressing an artificial neuropotentiating transgene (encoding the cAMP-elevating, intracellular A1 subunit of cholera toxin) within a small population of dopamine D1 receptor-expressing somatosensory cortical and limbic neurons that hyperactivate cortico/amygdalostriatal glutamatergic output circuits thought to be hyperactive in TS and comorbid obsessive-compulsive (OC) disorders. As in TS, these D1CT-7 ("Ticcy") transgenic mice׳s tics were alleviated by the TS drugs clonidine and dopamine D2 receptor antagonists; and their chronic glutamate-excited striatal motor output was unbalanced toward hyperactivity of the motoric direct pathway and inactivity of the cataleptic indirect pathway. Here we have examined whether these mice׳s tics are countered by drugs that "break" sequential elements of their hyperactive cortical/amygdalar glutamatergic and efferent striatal circuit: anti-serotonoceptive and anti-noradrenoceptive corticostriatal glutamate output blockers (the serotonin 5-HT2a,c receptor antagonist ritanserin and the NE alpha-1 receptor antagonist prazosin); agmatinergic striatothalamic GABA output blockers (the presynaptic agmatine/imidazoline I1 receptor agonist moxonidine); and nigrostriatal dopamine output blockers (the presynaptic D2 receptor agonist bromocriptine). Each drug class alleviates tics in the Ticcy mice, suggesting a hyperglutamatergic CSTC "tic circuit" could exist in TS wherein cortical/amygdalar pyramidal projection neurons׳ glutamatergic overexcitation of both striatal output neurons and nigrostriatal dopaminergic modulatory neurons unbalances their circuit integration to excite striatothalamic output and create tics, and illuminating new TS drug strategies.

  17. A novel CPU/GPU simulation environment for large-scale biologically realistic neural modeling.

    Science.gov (United States)

    Hoang, Roger V; Tanna, Devyani; Jayet Bray, Laurence C; Dascalu, Sergiu M; Harris, Frederick C

    2013-01-01

    Computational Neuroscience is an emerging field that provides unique opportunities to study complex brain structures through realistic neural simulations. However, as biological details are added to models, the execution time for the simulation becomes longer. Graphics Processing Units (GPUs) are now being utilized to accelerate simulations due to their ability to perform computations in parallel. As such, they have shown significant improvement in execution time compared to Central Processing Units (CPUs). Most neural simulators utilize either multiple CPUs or a single GPU for better performance, but still show limitations in execution time when biological details are not sacrificed. Therefore, we present a novel CPU/GPU simulation environment for large-scale biological networks, the NeoCortical Simulator version 6 (NCS6). NCS6 is a free, open-source, parallelizable, and scalable simulator, designed to run on clusters of multiple machines, potentially with high performance computing devices in each of them. It has built-in leaky-integrate-and-fire (LIF) and Izhikevich (IZH) neuron models, but users also have the capability to design their own plug-in interface for different neuron types as desired. NCS6 is currently able to simulate one million cells and 100 million synapses in quasi real time by distributing data across eight machines with each having two video cards.

  18. Application of Logic Models in a Large Scientific Research Program

    Science.gov (United States)

    O'Keefe, Christine M.; Head, Richard J.

    2011-01-01

    It is the purpose of this article to discuss the development and application of a logic model in the context of a large scientific research program within the Commonwealth Scientific and Industrial Research Organisation (CSIRO). CSIRO is Australia's national science agency and is a publicly funded part of Australia's innovation system. It conducts…

  19. Application of Logic Models in a Large Scientific Research Program

    Science.gov (United States)

    O'Keefe, Christine M.; Head, Richard J.

    2011-01-01

    It is the purpose of this article to discuss the development and application of a logic model in the context of a large scientific research program within the Commonwealth Scientific and Industrial Research Organisation (CSIRO). CSIRO is Australia's national science agency and is a publicly funded part of Australia's innovation system. It conducts…

  20. Large scale semantic 3D modeling of the urban landscape

    NARCIS (Netherlands)

    I. Esteban Lopez

    2012-01-01

    Modeling and understanding large urban areas is becoming an important topic in a world were everything is being digitized. A semantic and accurate 3D representation of a city can be used in many applications such as event and security planning and management, assisted navigation, autonomous operatio

  1. Large scale solar district heating. Evaluation, modelling and designing - Appendices

    Energy Technology Data Exchange (ETDEWEB)

    Heller, A.

    2000-07-01

    The appendices present the following: A) Cad-drawing of the Marstal CSHP design. B) Key values - large-scale solar heating in Denmark. C) Monitoring - a system description. D) WMO-classification of pyranometers (solarimeters). E) The computer simulation model in TRNSYS. F) Selected papers from the author. (EHS)

  2. Order reduction of large-scale linear oscillatory system models

    Energy Technology Data Exchange (ETDEWEB)

    Trudnowksi, D.J. (Pacific Northwest Lab., Richland, WA (United States))

    1994-02-01

    Eigen analysis and signal analysis techniques of deriving representations of power system oscillatory dynamics result in very high-order linear models. In order to apply many modern control design methods, the models must be reduced to a more manageable order while preserving essential characteristics. Presented in this paper is a model reduction method well suited for large-scale power systems. The method searches for the optimal subset of the high-order model that best represents the system. An Akaike information criterion is used to define the optimal reduced model. The method is first presented, and then examples of applying it to Prony analysis and eigenanalysis models of power systems are given.

  3. A numerical shoreline model for shorelines with large curvature

    DEFF Research Database (Denmark)

    Kærgaard, Kasper Hauberg; Fredsøe, Jørgen

    2013-01-01

    This paper presents a new numerical model for shoreline change which can be used to model the evolution of shorelines with large curvature. The model is based on a one-line formulation in terms of coordinates which follow the shape of the shoreline, instead of the more common approach where the two...... orthogonal horizontal directions are used. The volume error in the sediment continuity equation which is thereby introduced is removed through an iterative procedure. The model treats the shoreline changes by computing the sediment transport in a 2D coastal area model, and then integrating the sediment...... transport field across the coastal profile to obtain the longshore sediment transport variation along the shoreline. The model is used to compute the evolution of a shoreline with a 90° change in shoreline orientation; due to this drastic change in orientation a migrating shoreline spit develops...

  4. Pial iontophoresis of ferric chloride versus cortical ferric chloride injection in establishing iron-induced posttraumatic epilepsy animal models

    Institute of Scientific and Technical Information of China (English)

    Jinlan Jin; Hanping Zhuang; Shaoming Liu; Junqiang Si; Ying Chen; Jiamei Yao

    2006-01-01

    BACKGROUND: In order to study the pathogenesis of iron-induced posttraumatic epilepsy (PTE), foreign scholars have established several kinds of PTE animal models, among which, the iron- induced PTE animal models proposed by Willmore is the most famous. The iron-induced PTE animal models can be established by two methods: one is cortical ferric chloride injection (CFCI) and the other one is pial iontophoresis of ferric chloride (PIFC). Because Willmore did not give out the elaboration of the behaviors and electroencephalograms (EEGs) of the iron induced PTE animal models established by these two methods, so we have known little about these animal models.OBJECTIVE: To observe the behaviors and EEGs of the iron-induced PTE animal models established by PIFC and CFCI, in order to compare the differences and the study value of these two methods.DESIGN: Qualitative controlled observation trial.SETTING: Department of Neurosurgery, Urumqi General Hospital, Lanzhou Military Area Command of Chinese PLA.MATERIALS: Forty healthy adult male SD rats, weighing 200 to 250 g, were involved in this experiment.pany, USA), the wireless blue tooth electroencephlograms recording system (Nuocheng electric Co. Ltd,Shanghai), a set of air turbine dental drill unit, dental base acrylic resin powder, microinjector (50 μL), amperemeter (1 mA), a pair of batteries, electric resistance (200 kΩ) , variable resistance (100 kΩ), tubule with endo-meridians of 2 mm (used as import tube), several silver wire segments and several acupuncture needles were employed in this study.METHODS: This study was carried out in the Experimental Animal Center of the Urumqi General Hospital,Lanzhou Military Area Command of Chinese PLA between November 2004 and April 2005. Establishing the PET animal models by CFCI method: Twenty SD rats were taken, intraperitoneally anesthetized with 50 mg/kg barbanylum and fixed on stereotaxic apparatus. A cranial burr hole with the diameter of 2 mm was drilled 3mm behind the

  5. Large Scale Simulations of the Kinetic Ising Model

    Science.gov (United States)

    Münkel, Christian

    We present Monte Carlo simulation results for the dynamical critical exponent z of the two- and three-dimensional kinetic Ising model. The z-values were calculated from the magnetization relaxation from an ordered state into the equilibrium state at Tc for very large systems with up to (169984)2 and (3072)3 spins. To our knowledge, these are the largest Ising-systems simulated todate. We also report the successful simulation of very large lattices on a massively parallel MIMD computer with high speedups of approximately 1000 and an efficiency of about 0.93.

  6. Models for blisks with large blends and small mistuning

    Science.gov (United States)

    Tang, Weihan; Epureanu, Bogdan I.; Filippi, Sergio

    2017-03-01

    Small deviations of the structural properties of individual sectors of blisks, referred to as mistuning, can lead to localization of vibration energy and drastically increased forced responses. Similar phenomena are observed in blisks with large damages or repair blends. Such deviations are best studied statistically because they are random. In the absence of cyclic symmetry, the computational cost to predict the vibration behavior of blisks becomes prohibitively high. That has lead to the development of various reduced-order models (ROMs). Existing approaches are either for small mistuning, or are computationally expensive and thus not effective for statistical analysis. This paper discusses a reduced-order modeling method for blisks with both large and small mistuning, which requires low computational effort. This method utilizes the pristine, rogue and interface modal expansion (PRIME) method to model large blends. PRIME uses only sector-level cyclic modes strategically combined together to create a reduction basis which yields ROMs that efficiently and accurately model large mistuning. To model small mistuning, nodal energy weighted transformation (NEWT) is integrated with PRIME, resulting in N-PRIME, which requires only sector-level calculations to create a ROM which captures both small and large mistuning with minimized computational effort. The combined effects of large blends and small mistuning are studied using N-PRIME for a dual flow path system and for a conventional blisk. The accuracy of the N-PRIME method is validated against full-order finite element analyses for both natural and forced response computations, including displacement amplitudes and surface stresses. Results reveal that N-PRIME is capable of accurately predicting the dynamics of a blisk with severely large mistuning, along with small random mistuning throughout each sector. Also, N-PRIME can accurately capture modes with highly localized motions. A statistical analysis is performed to

  7. A large deformation viscoelastic model for double-network hydrogels

    Science.gov (United States)

    Mao, Yunwei; Lin, Shaoting; Zhao, Xuanhe; Anand, Lallit

    2017-03-01

    We present a large deformation viscoelasticity model for recently synthesized double network hydrogels which consist of a covalently-crosslinked polyacrylamide network with long chains, and an ionically-crosslinked alginate network with short chains. Such double-network gels are highly stretchable and at the same time tough, because when stretched the crosslinks in the ionically-crosslinked alginate network rupture which results in distributed internal microdamage which dissipates a substantial amount of energy, while the configurational entropy of the covalently-crosslinked polyacrylamide network allows the gel to return to its original configuration after deformation. In addition to the large hysteresis during loading and unloading, these double network hydrogels also exhibit a substantial rate-sensitive response during loading, but exhibit almost no rate-sensitivity during unloading. These features of large hysteresis and asymmetric rate-sensitivity are quite different from the response of conventional hydrogels. We limit our attention to modeling the complex viscoelastic response of such hydrogels under isothermal conditions. Our model is restricted in the sense that we have limited our attention to conditions under which one might neglect any diffusion of the water in the hydrogel - as might occur when the gel has a uniform initial value of the concentration of water, and the mobility of the water molecules in the gel is low relative to the time scale of the mechanical deformation. We also do not attempt to model the final fracture of such double-network hydrogels.

  8. Large Animal Models for Foamy Virus Vector Gene Therapy

    Directory of Open Access Journals (Sweden)

    Peter A. Horn

    2012-12-01

    Full Text Available Foamy virus (FV vectors have shown great promise for hematopoietic stem cell (HSC gene therapy. Their ability to efficiently deliver transgenes to multi-lineage long-term repopulating cells in large animal models suggests they will be effective for several human hematopoietic diseases. Here, we review FV vector studies in large animal models, including the use of FV vectors with the mutant O6-methylguanine-DNA methyltransferase, MGMTP140K to increase the number of genetically modified cells after transplantation. In these studies, FV vectors have mediated efficient gene transfer to polyclonal repopulating cells using short ex vivo transduction protocols designed to minimize the negative effects of ex vivo culture on stem cell engraftment. In this regard, FV vectors appear superior to gammaretroviral vectors, which require longer ex vivo culture to effect efficient transduction. FV vectors have also compared favorably with lentiviral vectors when directly compared in the dog model. FV vectors have corrected leukocyte adhesion deficiency and pyruvate kinase deficiency in the dog large animal model. FV vectors also appear safer than gammaretroviral vectors based on a reduced frequency of integrants near promoters and also near proto-oncogenes in canine repopulating cells. Together, these studies suggest that FV vectors should be highly effective for several human hematopoietic diseases, including those that will require relatively high percentages of gene-modified cells to achieve clinical benefit.

  9. Large eddy simulation modelling of combustion for propulsion applications.

    Science.gov (United States)

    Fureby, C

    2009-07-28

    Predictive modelling of turbulent combustion is important for the development of air-breathing engines, internal combustion engines, furnaces and for power generation. Significant advances in modelling non-reactive turbulent flows are now possible with the development of large eddy simulation (LES), in which the large energetic scales of the flow are resolved on the grid while modelling the effects of the small scales. Here, we discuss the use of combustion LES in predictive modelling of propulsion applications such as gas turbine, ramjet and scramjet engines. The LES models used are described in some detail and are validated against laboratory data-of which results from two cases are presented. These validated LES models are then applied to an annular multi-burner gas turbine combustor and a simplified scramjet combustor, for which some additional experimental data are available. For these cases, good agreement with the available reference data is obtained, and the LES predictions are used to elucidate the flow physics in such devices to further enhance our knowledge of these propulsion systems. Particular attention is focused on the influence of the combustion chemistry, turbulence-chemistry interaction, self-ignition, flame holding burner-to-burner interactions and combustion oscillations.

  10. Implementing the cellular mechanisms of synaptic transmission in a neural mass model of the thalamo-cortical circuitry

    Directory of Open Access Journals (Sweden)

    Basabdatta Sen Bhattacharya

    2013-07-01

    Full Text Available A novel direction to existing neural mass modelling technique is proposed where the commonly used `alpha function' for representing synaptic transmission is replaced by a kinetic framework of neurotransmitter and receptor dynamics. The aim is to underpin neuro-transmission dynamics associated with abnormal brain rhythms commonly observed in neurological and psychiatric disorders. An existing thalamocortical neural mass model is modified by using the kinetic framework for modelling synaptic transmission mediated by glutamatergic and GABA (gamma-aminobutyric-acid-ergic receptors. The model output is compared qualitatively with existing literature on in-vitro experimental studies of ferret thalamic slices, as well as on single-neuron-level model based studies of neuro-receptor and transmitter dynamics in the thalamocortical tissue. The results are consistent with these studies: the activation of ligand-gated GABA receptors is essential for generation of spindle waves in the model, while blocking this pathway leads to low-frequency synchronised oscillations such as observed in slow-wave sleep; the frequency of spindle oscillations increase with increased levels of post-synaptic membrane conductance for AMPA (alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic-acid receptors, and blocking this pathway effects a quiescent model output. In terms of computational efficiency, the simulation time is improved by a factor of ten compared to a similar neural mass model based on alpha functions. This implies a dramatic improvement in computational resources for large-scale network simulation using this model. Thus, the model provides a platform for correlating high-level brain oscillatory activity with low-level synaptic attributes, and makes a significant contribution towards advancements in current neural mass modelling paradigm as a potential computational tool to better the understanding of brain oscillations in sickness and in health.

  11. Implementing the cellular mechanisms of synaptic transmission in a neural mass model of the thalamo-cortical circuitry.

    Science.gov (United States)

    Bhattacharya, Basabdatta S

    2013-01-01

    A novel direction to existing neural mass modeling technique is proposed where the commonly used "alpha function" for representing synaptic transmission is replaced by a kinetic framework of neurotransmitter and receptor dynamics. The aim is to underpin neuro-transmission dynamics associated with abnormal brain rhythms commonly observed in neurological and psychiatric disorders. An existing thalamocortical neural mass model is modified by using the kinetic framework for modeling synaptic transmission mediated by glutamatergic and GABA (gamma-aminobutyric-acid)-ergic receptors. The model output is compared qualitatively with existing literature on in vitro experimental studies of ferret thalamic slices, as well as on single-neuron-level model based studies of neuro-receptor and transmitter dynamics in the thalamocortical tissue. The results are consistent with these studies: the activation of ligand-gated GABA receptors is essential for generation of spindle waves in the model, while blocking this pathway leads to low-frequency synchronized oscillations such as observed in slow-wave sleep; the frequency of spindle oscillations increase with increased levels of post-synaptic membrane conductance for AMPA (alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic-acid) receptors, and blocking this pathway effects a quiescent model output. In terms of computational efficiency, the simulation time is improved by a factor of 10 compared to a similar neural mass model based on alpha functions. This implies a dramatic improvement in computational resources for large-scale network simulation using this model. Thus, the model provides a platform for correlating high-level brain oscillatory activity with low-level synaptic attributes, and makes a significant contribution toward advancements in current neural mass modeling paradigm as a potential computational tool to better the understanding of brain oscillations in sickness and in health.

  12. Duct thermal performance models for large commercial buildings

    Energy Technology Data Exchange (ETDEWEB)

    Wray, Craig P.

    2003-10-01

    Despite the potential for significant energy savings by reducing duct leakage or other thermal losses from duct systems in large commercial buildings, California Title 24 has no provisions to credit energy-efficient duct systems in these buildings. A substantial reason is the lack of readily available simulation tools to demonstrate the energy-saving benefits associated with efficient duct systems in large commercial buildings. The overall goal of the Efficient Distribution Systems (EDS) project within the PIER High Performance Commercial Building Systems Program is to bridge the gaps in current duct thermal performance modeling capabilities, and to expand our understanding of duct thermal performance in California large commercial buildings. As steps toward this goal, our strategy in the EDS project involves two parts: (1) developing a whole-building energy simulation approach for analyzing duct thermal performance in large commercial buildings, and (2) using the tool to identify the energy impacts of duct leakage in California large commercial buildings, in support of future recommendations to address duct performance in the Title 24 Energy Efficiency Standards for Nonresidential Buildings. The specific technical objectives for the EDS project were to: (1) Identify a near-term whole-building energy simulation approach that can be used in the impacts analysis task of this project (see Objective 3), with little or no modification. A secondary objective is to recommend how to proceed with long-term development of an improved compliance tool for Title 24 that addresses duct thermal performance. (2) Develop an Alternative Calculation Method (ACM) change proposal to include a new metric for thermal distribution system efficiency in the reporting requirements for the 2005 Title 24 Standards. The metric will facilitate future comparisons of different system types using a common ''yardstick''. (3) Using the selected near-term simulation approach

  13. Testing Proposed Neuronal Models of Effective Connectivity Within the Cortico-basal Ganglia-thalamo-cortical Loop During Loss of Consciousness.

    Science.gov (United States)

    Crone, Julia Sophia; Lutkenhoff, Evan Scott; Bio, Branden Joseph; Laureys, Steven; Monti, Martin Max

    2017-04-01

    In recent years, a number of brain regions and connectivity patterns have been proposed to be crucial for loss and recovery of consciousness but have not been compared in detail. In a 3 T resting-state functional magnetic resonance imaging paradigm, we test the plausibility of these different neuronal models derived from theoretical and empirical knowledge. Specifically, we assess the fit of each model to the dynamic change in effective connectivity between specific cortical and subcortical regions at different consecutive levels of propofol-induced sedation by employing spectral dynamic causal modeling. Surprisingly, our findings indicate that proposed models of impaired consciousness do not fit the observed patterns of effective connectivity. Rather, the data show that loss of consciousness, at least in the context of propofol-induced sedation, is marked by a breakdown of corticopetal projections from the globus pallidus. Effective connectivity between the globus pallidus and the ventral posterior cingulate cortex, present during wakefulness, fades in the transition from lightly sedated to full loss of consciousness and returns gradually as consciousness recovers, thereby, demonstrating the dynamic shift in brain architecture of the posterior cingulate "hub" during changing states of consciousness. These findings highlight the functional role of a previously underappreciated direct pallido-cortical connectivity in supporting consciousness. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Elastic moduli of untreated, demineralized and deproteinized cortical bone: validation of a theoretical model of bone as an interpenetrating composite material.

    Science.gov (United States)

    Hamed, E; Novitskaya, E; Li, J; Chen, P-Y; Jasiuk, I; McKittrick, J

    2012-03-01

    A theoretical experimentally based multi-scale model of the elastic response of cortical bone is presented. It portrays the hierarchical structure of bone as a composite with interpenetrating biopolymers (collagen and non-collagenous proteins) and minerals (hydroxyapatite), together with void spaces (porosity). The model involves a bottom-up approach and employs micromechanics and classical lamination theories of composite materials. Experiments on cortical bone samples from bovine femur include completely demineralized and deproteinized bones as well as untreated bone samples. Porosity and microstructure are characterized using optical and scanning electron microscopy, and micro-computed tomography. Compression testing is used to measure longitudinal and transverse elastic moduli of all three bone types. The characterization of structure and properties of these three bone states provides a deeper understanding of the contributions of the individual components of bone to its elastic response and allows fine tuning of modeling assumptions. Very good agreement is found between theoretical modeling and compression testing results, confirming the validity of the interpretation of bone as an interpenetrating composite material.

  15. A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

    Directory of Open Access Journals (Sweden)

    Roger V Hoang

    2013-10-01

    Full Text Available Computational Neuroscience is an emerging field that provides unique opportunities to studycomplex brain structures through realistic neural simulations. However, as biological details are added tomodels, the execution time for the simulation becomes longer. Graphics Processing Units (GPUs are now being utilized to accelerate simulations due to their ability to perform computations in parallel. As such, they haveshown significant improvement in execution time compared to Central Processing Units (CPUs. Most neural simulators utilize either multiple CPUs or a single GPU for better performance, but still show limitations in execution time when biological details are not sacrificed. Therefore, we present a novel CPU/GPU simulation environment for large-scale biological networks,the NeoCortical Simulator version 6 (NCS6. NCS6 is a free, open-source, parallelizable, and scalable simula-tor, designed to run on clusters of multiple machines, potentially with high performance computing devicesin each of them. It has built-in leaky-integrate-and-fire (LIF and Izhikevich (IZH neuron models, but usersalso have the capability to design their own plug-in interface for different neuron types as desired. NCS6is currently able to simulate one million cells and 100 million synapses in quasi real time by distributing dataacross these heterogeneous clusters of CPUs and GPUs.

  16. Soil carbon management in large-scale Earth system modelling

    DEFF Research Database (Denmark)

    Olin, S.; Lindeskog, M.; Pugh, T. A. M.;

    2015-01-01

    Croplands are vital ecosystems for human well-being and provide important ecosystem services such as crop yields, retention of nitrogen and carbon storage. On large (regional to global)-scale levels, assessment of how these different services will vary in space and time, especially in response to...... modelling C–N interactions in agricultural ecosystems under future environmental change and the effects these have on terrestrial biogeochemical cycles....

  17. Considerations in Scale-Modeling of Large Urban Fires

    Science.gov (United States)

    1984-11-15

    is inconsequential and that all molecular transport processes are unimportant). The nondimensional parameters to be preserved between the model and...fuel bed. Parker, Corlett and B. T. Lee [!3] also come to a similar conclusion based * on the following two points. First, in large fires, molecular ...to USDA Forest Service, Prepared by Instituto Nacional "de Tecnica Aeroespacial, Madrid, Spain, (May, 1967). "" 57. S.L. Lee and G.M. Hellman

  18. One-dimensional adhesion model for large scale structures

    Directory of Open Access Journals (Sweden)

    Kayyunnapara Thomas Joseph

    2010-05-01

    Full Text Available We discuss initial value problems and initial boundary value problems for some systems of partial differential equations appearing in the modelling for the large scale structure formation in the universe. We restrict the initial data to be bounded measurable and locally bounded variation function and use Volpert product to justify the product which appear in the equation. For more general initial data in the class of generalized functions of Colombeau, we construct the solution in the sense of association.

  19. From Large to Small Scales: Global Models of the ISM

    CERN Document Server

    D'Avillez, M A

    2004-01-01

    We review large scale modelling of the ISM with emphasis on the importance to include the disk-halo-disk duty cycle and to use a dynamical refinement of the grid (in regions where steep variations of density and pressure occur) for a realistic modelling of the ISM. We also discuss the necessity of convergence of the simulation results by comparing 0.625, 1.25 and 2.5 pc resolution simulations and show that a minimum grid resolution of 1.25 pc is required for quantitatively reliable results, as there is a rapid convergence for $\\Delta x \\leq 1.1$ pc.

  20. Supervision in Factor Models Using a Large Number of Predictors

    DEFF Research Database (Denmark)

    Boldrini, Lorenzo; Hillebrand, Eric Tobias

    In this paper we investigate the forecasting performance of a particular factor model (FM) in which the factors are extracted from a large number of predictors. We use a semi-parametric state-space representation of the FM in which the forecast objective, as well as the factors, is included.......g. a standard dynamic factor model with separate forecast and state equations....... in the state vector. The factors are informed of the forecast target (supervised) through the state equation dynamics. We propose a way to assess the contribution of the forecast objective on the extracted factors that exploits the Kalman filter recursions. We forecast one target at a time based...

  1. Non-Standard Models, Solar Neutrinos, and Large \\theta_{13}

    CERN Document Server

    Bonventre, R; Klein, J R; Gann, G D Orebi; Seibert, S; Wasalski, O

    2013-01-01

    Solar neutrino experiments have yet to see directly the transition region between matter-enhanced and vacuum oscillations. The transition region is particularly sensitive to models of non-standard neutrino interactions and propagation. We examine several such non-standard models, which predict a lower-energy transition region and a flatter survival probability for the ^{8}B solar neutrinos than the standard large-mixing angle (LMA) model. We find that while some of the non-standard models provide a better fit to the solar neutrino data set, the large measured value of \\theta_{13} and the size of the experimental uncertainties lead to a low statistical significance for these fits. We have also examined whether simple changes to the solar density profile can lead to a flatter ^{8}B survival probability than the LMA prediction, but find that this is not the case for reasonable changes. We conclude that the data in this critical region is still too poor to determine whether any of these models, or LMA, is the bes...

  2. Large-N Analysis of Three Dimensional Nonlinear Sigma Models

    CERN Document Server

    Higashijima, K; Tsuzuki, M; Higashijima, Kiyoshi; Itou, Etsuko; Tsuzuki, Makoto

    2005-01-01

    Non-perturbative renormalization group approach suggests that a large class of nonlinear sigma models are renormalizable in three dimensional space-time, while they are non-renormalizable in perturbation theory. ${\\cal N}=2$ supersymmetric nonlinear sigma models whose target spaces are Einstein-K\\"{a}hler manifolds with positive scalar curvature belongs to this class. hermitian symmetric spaces, being homogeneous, are specially simple examples of these manifolds. To find an independent evidence of the nonperturbative renormalizability of these models, the large N method, another nonperturbative method, is applied to 3-dimensional ${\\cal N}=2$ supersymmetric nonlinear sigma models on the target spaces $CP^{N-1}=SU(N)/[SU(N-1)\\times U(1)]$ and $Q^{N-2}=SO(N)/[SO(N-2)\\times SO(2)]$, two typical examples of hermitian symmetric spaces. We find that $\\beta$ functions in these models agree with the results of the nonperturbative renormalization group approach in the next-to-leading order of 1/N expansion, and have n...

  3. A family of dynamic models for large-eddy simulation

    Science.gov (United States)

    Carati, D.; Jansen, K.; Lund, T.

    1995-01-01

    Since its first application, the dynamic procedure has been recognized as an effective means to compute rather than prescribe the unknown coefficients that appear in a subgrid-scale model for Large-Eddy Simulation (LES). The dynamic procedure is usually used to determine the nondimensional coefficient in the Smagorinsky (1963) model. In reality the procedure is quite general and it is not limited to the Smagorinsky model by any theoretical or practical constraints. The purpose of this note is to consider a generalized family of dynamic eddy viscosity models that do not necessarily rely on the local equilibrium assumption built into the Smagorinsky model. By invoking an inertial range assumption, it will be shown that the coefficients in the new models need not be nondimensional. This additional degree of freedom allows the use of models that are scaled on traditionally unknown quantities such as the dissipation rate. In certain cases, the dynamic models with dimensional coefficients are simpler to implement, and allow for a 30% reduction in the number of required filtering operations.

  4. Multiresolution comparison of precipitation datasets for large-scale models

    Science.gov (United States)

    Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

    2014-12-01

    Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

  5. Comparison of Cortical and White Matter Traumatic Brain Injury Models Reveals Differential Effects in the Subventricular Zone and Divergent Sonic Hedgehog Signaling Pathways in Neuroblasts and Oligodendrocyte Progenitors

    Directory of Open Access Journals (Sweden)

    Amanda J. Mierzwa

    2014-09-01

    Full Text Available The regenerative capacity of the central nervous system must be optimized to promote repair following traumatic brain injury (TBI and may differ with the site and form of damage. Sonic hedgehog (Shh maintains neural stem cells and promotes oligodendrogenesis. We examined whether Shh signaling contributes to neuroblast (doublecortin or oligodendrocyte progenitor (neural/glial antigen 2 [NG2] responses in two distinct TBI models. Shh-responsive cells were heritably labeled in vivo using Gli1-CreERT2;R26-YFP bitransgenic mice with tamoxifen administration on Days 2 and 3 post-TBI. Injury to the cerebral cortex was produced with mild controlled cortical impact. Yellow fluorescent protein (YFP cells decreased in cortical lesions. Total YFP cells increased in the subventricular zone (SVZ, indicating Shh pathway activation in SVZ cells, including doublecortin-labeled neuroblasts. The alternate TBI model produced traumatic axonal injury in the corpus callosum. YFP cells decreased within the SVZ and were rarely double labeled as NG2 progenitors. NG2 progenitors increased in the cortex, with a similar pattern in the corpus callosum. To further test the potential of NG2 progenitors to respond through Shh signaling, Smoothened agonist was microinjected into the corpus callosum to activate Shh signaling. YFP cells and NG2 progenitors increased in the SVZ but were not double labeled. This result indicates that either direct Smoothened activation in NG2 progenitors does not signal through Gli1 or that Smoothened agonist acts indirectly to increase NG2 progenitors. Therefore, in all conditions, neuroblasts exhibited differential Shh pathway utilization compared with oligodendrocyte progenitors. Notably, cortical versus white matter damage from TBI produced opposite responses of Shh-activated cells within the SVZ.

  6. Comparison of cortical and white matter traumatic brain injury models reveals differential effects in the subventricular zone and divergent Sonic hedgehog signaling pathways in neuroblasts and oligodendrocyte progenitors.

    Science.gov (United States)

    Mierzwa, Amanda J; Sullivan, Genevieve M; Beer, Laurel A; Ahn, Sohyun; Armstrong, Regina C

    2014-01-01

    The regenerative capacity of the central nervous system must be optimized to promote repair following traumatic brain injury (TBI) and may differ with the site and form of damage. Sonic hedgehog (Shh) maintains neural stem cells and promotes oligodendrogenesis. We examined whether Shh signaling contributes to neuroblast (doublecortin) or oligodendrocyte progenitor (neural/glial antigen 2 [NG2]) responses in two distinct TBI models. Shh-responsive cells were heritably labeled in vivo using Gli1-CreER(T2);R26-YFP bitransgenic mice with tamoxifen administration on Days 2 and 3 post-TBI. Injury to the cerebral cortex was produced with mild controlled cortical impact. Yellow fluorescent protein (YFP) cells decreased in cortical lesions. Total YFP cells increased in the subventricular zone (SVZ), indicating Shh pathway activation in SVZ cells, including doublecortin-labeled neuroblasts. The alternate TBI model produced traumatic axonal injury in the corpus callosum. YFP cells decreased within the SVZ and were rarely double labeled as NG2 progenitors. NG2 progenitors increased in the cortex, with a similar pattern in the corpus callosum. To further test the potential of NG2 progenitors to respond through Shh signaling, Smoothened agonist was microinjected into the corpus callosum to activate Shh signaling. YFP cells and NG2 progenitors increased in the SVZ but were not double labeled. This result indicates that either direct Smoothened activation in NG2 progenitors does not signal through Gli1 or that Smoothened agonist acts indirectly to increase NG2 progenitors. Therefore, in all conditions, neuroblasts exhibited differential Shh pathway utilization compared with oligodendrocyte progenitors. Notably, cortical versus white matter damage from TBI produced opposite responses of Shh-activated cells within the SVZ.

  7. A new model of strabismic amblyopia: Loss of spatial acuity due to increased temporal dispersion of geniculate X-cell afferents on to cortical neurons.

    Science.gov (United States)

    Crewther, D P; Crewther, S G

    2015-09-01

    Although the neural locus of strabismic amblyopia has been shown to lie at the first site of binocular integration, first in cat and then in primate, an adequate mechanism is still lacking. Here we hypothesise that increased temporal dispersion of LGN X-cell afferents driven by the deviating eye onto single cortical neurons may provide a neural mechanism for strabismic amblyopia. This idea was investigated via single cell extracellular recordings of 93 X and 50 Y type LGN neurons from strabismic and normal cats. Both X and Y neurons driven by the non-deviating eye showed shorter latencies than those driven by either the strabismic or normal eyes. Also the mean latency difference between X and Y neurons was much greater for the strabismic cells compared with the other two groups. The incidence of lagged X-cells driven by the deviating eye of the strabismic cats was higher than that of LGN X-cells from normal animals. Remarkably, none of the cells recorded from the laminae driven by the non-deviating eye were of the lagged class. A simple computational model was constructed in which a mixture of lagged and non-lagged afferents converge on to single cortical neurons. Model cut-off spatial frequencies to a moving grating stimulus were sensitive to the temporal dispersion of the geniculate afferents. Thus strabismic amblyopia could be viewed as a lack of developmental tuning of geniculate lags for neurons driven by the amblyopic eye. Monocular control of fixation by the non-deviating eye is associated with reduced incidence of lagged neurons, suggesting that in normal vision, lagged neurons might play a role in maintaining binocular connections for cortical neurons.

  8. Simulation of large-scale rule-based models

    Energy Technology Data Exchange (ETDEWEB)

    Hlavacek, William S [Los Alamos National Laboratory; Monnie, Michael I [Los Alamos National Laboratory; Colvin, Joshua [NON LANL; Faseder, James [NON LANL

    2008-01-01

    Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models. DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein-protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of STOCHSIM. DYNSTOC differs from STOCHSIM by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions. DYNSTOC is free for non-commercial use. The C source code, supporting documentation and example input files are available at .

  9. Acute hypothalamic suppression significantly affects trabecular bone but not cortical bone following recovery and ovariectomy surgery in a rat model

    Directory of Open Access Journals (Sweden)

    Vanessa R. Yingling

    2016-01-01

    Full Text Available Background. Osteoporosis is “a pediatric disease with geriatric consequences.” Bone morphology and tissue quality co-adapt during ontogeny for sufficient bone stiffness. Altered bone morphology from hypothalamic amenorrhea, a risk factor for low bone mass in women, may affect bone strength later in life. Our purpose was to determine if altered morphology following hypothalamic suppression during development affects cortical bone strength and trabecular bone volume (BV/TV at maturity.Methods. Female rats (25 days old were assigned to a control (C group (n = 45 that received saline injections (.2 cc or an experimental group (GnRH-a (n = 45 that received gonadotropin releasing hormone antagonist injections (.24 mg per dose for 25 days. Fifteen animals from each group were sacrificed immediately after the injection protocol at Day 50 (C, GnRH-a. The remaining animals recovered for 135 days and a subset of each group was sacrificed at Day 185 ((C-R (n = 15 and (G-R (n = 15. The remaining animals had an ovariectomy surgery (OVX at 185 days of age and were sacrificed 40 days later (C-OVX (n = 15 and (G-OVX (n = 15. After sacrifice femurs were mechanically tested and scanned using micro CT. Serum C-terminal telopeptides (CTX and insulin-like growth factor 1 (IGF-1 were measured. Two-way ANOVA (2 groups (GnRH-a and Control X 3 time points (Injection Protocol, Recovery, post-OVX was computed.Results. GnRH-a injections suppressed uterine weights (72% and increased CTX levels by 59%. Bone stiffness was greater in the GnRH-a groups compared to C. Ash content and cortical bone area were similar between groups at all time points. Polar moment of inertia, a measure of bone architecture, was 15% larger in the GnRH-a group and remained larger than C (19% following recovery. Both the polar moment of inertia and cortical area increased linearly with the increases in body weight. Following the injection protocol, trabecular BV/TV was 31% lower in the Gn

  10. Binary choices in small and large groups: A unified model

    Science.gov (United States)

    Bischi, Gian-Italo; Merlone, Ugo

    2010-02-01

    Two different ways to model the diffusion of alternative choices within a population of individuals in the presence of social externalities are known in the literature. While Galam’s model of rumors spreading considers a majority rule for interactions in several groups, Schelling considers individuals interacting in one large group, with payoff functions that describe how collective choices influence individual preferences. We incorporate these two approaches into a unified general discrete-time dynamic model for studying individual interactions in variously sized groups. We first illustrate how the two original models can be obtained as particular cases of the more general model we propose, then we show how several other situations can be analyzed. The model we propose goes beyond a theoretical exercise as it allows modeling situations which are relevant in economic and social systems. We consider also other aspects such as the propensity to switch choices and the behavioral momentum, and show how they may affect the dynamics of the whole population.

  11. ARCHITECTURAL LARGE CONSTRUCTED ENVIRONMENT. MODELING AND INTERACTION USING DYNAMIC SIMULATIONS

    Directory of Open Access Journals (Sweden)

    P. Fiamma

    2012-09-01

    Full Text Available How to use for the architectural design, the simulation coming from a large size data model? The topic is related to the phase coming usually after the acquisition of the data, during the construction of the model and especially after, when designers must have an interaction with the simulation, in order to develop and verify their idea. In the case of study, the concept of interaction includes the concept of real time "flows". The work develops contents and results that can be part of the large debate about the current connection between "architecture" and "movement". The focus of the work, is to realize a collaborative and participative virtual environment on which different specialist actors, client and final users can share knowledge, targets and constraints to better gain the aimed result. The goal is to have used a dynamic micro simulation digital resource that allows all the actors to explore the model in powerful and realistic way and to have a new type of interaction in a complex architectural scenario. On the one hand, the work represents a base of knowledge that can be implemented more and more; on the other hand the work represents a dealt to understand the large constructed architecture simulation as a way of life, a way of being in time and space. The architectural design before, and the architectural fact after, both happen in a sort of "Spatial Analysis System". The way is open to offer to this "system", knowledge and theories, that can support architectural design work for every application and scale. We think that the presented work represents a dealt to understand the large constructed architecture simulation as a way of life, a way of being in time and space. Architecture like a spatial configuration, that can be reconfigurable too through designing.

  12. Challenges of Modeling Flood Risk at Large Scales

    Science.gov (United States)

    Guin, J.; Simic, M.; Rowe, J.

    2009-04-01

    Flood risk management is a major concern for many nations and for the insurance sector in places where this peril is insured. A prerequisite for risk management, whether in the public sector or in the private sector is an accurate estimation of the risk. Mitigation measures and traditional flood management techniques are most successful when the problem is viewed at a large regional scale such that all inter-dependencies in a river network are well understood. From an insurance perspective the jury is still out there on whether flood is an insurable peril. However, with advances in modeling techniques and computer power it is possible to develop models that allow proper risk quantification at the scale suitable for a viable insurance market for flood peril. In order to serve the insurance market a model has to be event-simulation based and has to provide financial risk estimation that forms the basis for risk pricing, risk transfer and risk management at all levels of insurance industry at large. In short, for a collection of properties, henceforth referred to as a portfolio, the critical output of the model is an annual probability distribution of economic losses from a single flood occurrence (flood event) or from an aggregation of all events in any given year. In this paper, the challenges of developing such a model are discussed in the context of Great Britain for which a model has been developed. The model comprises of several, physically motivated components so that the primary attributes of the phenomenon are accounted for. The first component, the rainfall generator simulates a continuous series of rainfall events in space and time over thousands of years, which are physically realistic while maintaining the statistical properties of rainfall at all locations over the model domain. A physically based runoff generation module feeds all the rivers in Great Britain, whose total length of stream links amounts to about 60,000 km. A dynamical flow routing

  13. Large-scale Modeling of Inundation in the Amazon Basin

    Science.gov (United States)

    Luo, X.; Li, H. Y.; Getirana, A.; Leung, L. R.; Tesfa, T. K.

    2015-12-01

    Flood events have impacts on the exchange of energy, water and trace gases between land and atmosphere, hence potentially affecting the climate. The Amazon River basin is the world's largest river basin. Seasonal floods occur in the Amazon Basin each year. The basin being characterized by flat gradients, backwater effects are evident in the river dynamics. This factor, together with large uncertainties in river hydraulic geometry, surface topography and other datasets, contribute to difficulties in simulating flooding processes over this basin. We have developed a large-scale inundation scheme in the framework of the Model for Scale Adaptive River Transport (MOSART) river routing model. Both the kinematic wave and the diffusion wave routing methods are implemented in the model. A new process-based algorithm is designed to represent river channel - floodplain interactions. Uncertainties in the input datasets are partly addressed through model calibration. We will present the comparison of simulated results against satellite and in situ observations and analysis to understand factors that influence inundation processes in the Amazon Basin.

  14. Self-organized two-state membrane potential transitions in a network of realistically modeled cortical neurons.

    Science.gov (United States)

    Kang, Siu; Kitano, Katsunori; Fukai, Tomoki

    2004-04-01

    Recent studies have revealed that in vivo cortical neurons show spontaneous transitions between two subthreshold levels of the membrane potentials, 'up' and 'down' states. The neural mechanism of generating those spontaneous states transitions, however, remains unclear. Recent electrophysiological studies have suggested that those state transitions may occur through activation of a hyperpolarization-activated cation current (H-current), possibly by inhibitory synaptic inputs. Here, we demonstrate that two-state membrane potential fluctuations similar to those exhibited by in vivo neurons can be generated through a spike-timing-dependent self-organizing process in a network of inhibitory neurons and excitatory neurons expressing the H-current.

  15. Top-down feedback in an HMAX-like cortical model of object perception based on hierarchical Bayesian networks and belief propagation.

    Directory of Open Access Journals (Sweden)

    Salvador Dura-Bernal

    Full Text Available Hierarchical generative models, such as Bayesian networks, and belief propagation have been shown to provide a theoretical framework that can account for perceptual processes, including feedforward recognition and feedback modulation. The framework explains both psychophysical and physiological experimental data and maps well onto the hierarchical distributed cortical anatomy. However, the complexity required to model cortical processes makes inference, even using approximate methods, very computationally expensive. Thus, existing object perception models based on this approach are typically limited to tree-structured networks with no loops, use small toy examples or fail to account for certain perceptual aspects such as invariance to transformations or feedback reconstruction. In this study we develop a Bayesian network with an architecture similar to that of HMAX, a biologically-inspired hierarchical model of object recognition, and use loopy belief propagation to approximate the model operations (selectivity and invariance. Crucially, the resulting Bayesian network extends the functionality of HMAX by including top-down recursive feedback. Thus, the proposed model not only achieves successful feedforward recognition invariant to noise, occlusions, and changes in position and size, but is also able to reproduce modulatory effects such as illusory contour completion and attention. Our novel and rigorous methodology covers key aspects such as learning using a layerwise greedy algorithm, combining feedback information from multiple parents and reducing the number of operations required. Overall, this work extends an established model of object recognition to include high-level feedback modulation, based on state-of-the-art probabilistic approaches. The methodology employed, consistent with evidence from the visual cortex, can be potentially generalized to build models of hierarchical perceptual organization that include top-down and bottom

  16. Analytical modeling of large-angle CMBR anisotropies from textures

    CERN Document Server

    Magueijo, J

    1995-01-01

    We propose an analytic method for predicting the large angle CMBR temperature fluctuations induced by model textures. The model makes use of only a small number of phenomenological parameters which ought to be measured from simple simulations. We derive semi-analytically the C^l-spectrum for 2\\leq l\\leq 30 together with its associated non-Gaussian cosmic variance error bars. A slightly tilted spectrum with an extra suppression at low l is found, and we investigate the dependence of the tilt on the parameters of the model. We also produce a prediction for the two point correlation function. We find a high level of cosmic confusion between texture scenarios and standard inflationary theories in any of these quantities. However, we discover that a distinctive non-Gaussian signal ought to be expected at low l, reflecting the prominent effect of the last texture in these multipoles.

  17. Modeling The Large Scale Bias of Neutral Hydrogen

    CERN Document Server

    Marin, Felipe; Seo, Hee-Jong; Vallinotto, Alberto

    2009-01-01

    We present analytical estimates of the large scale bias of neutral Hydrogen (HI) based on the Halo Occupation Distribution formalism. We use a simple, non-parametric model which monotonically relates the total mass of a halo with its HI mass at zero redshift; for earlier times we assume limiting models for the HI density parameter evolution, consistent with the data presently available, as well as two main scenarios for the evolution of our HI mass - Halo mass relation. We find that both the linear and the first non-linear bias terms exhibit a remarkable evolution with redshift, regardless of the specific limiting model assumed for the HI evolution. These analytical predictions are then shown to be consistent with measurements performed on the Millennium Simulation. Additionally, we show that this strong bias evolution does not sensibly affect the measurement of the HI Power Spectrum.

  18. Acquisition Integration Models: How Large Companies Successfully Integrate Startups

    Directory of Open Access Journals (Sweden)

    Peter Carbone

    2011-10-01

    Full Text Available Mergers and acquisitions (M&A have been popular means for many companies to address the increasing pace and level of competition that they face. Large companies have pursued acquisitions to more quickly access technology, markets, and customers, and this approach has always been a viable exit strategy for startups. However, not all deals deliver the anticipated benefits, in large part due to poor integration of the acquired assets into the acquiring company. Integration can greatly impact the success of the acquisition and, indeed, the combined company’s overall market success. In this article, I explore the implementation of several integration models that have been put into place by a large company and extract principles that may assist negotiating parties with maximizing success. This perspective may also be of interest to smaller companies as they explore exit options while trying to ensure continued market success after acquisition. I assert that business success with acquisitions is dependent on an appropriate integration model, but that asset integration is not formulaic. Any integration effort must consider the specific market context and personnel involved.

  19. Dynamical modeling and analysis of large cellular regulatory networks

    Science.gov (United States)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  20. Large-Scale Tests of the DGP Model

    CERN Document Server

    Song, Y S; Hu, W; Song, Yong-Seon; Sawicki, Ignacy; Hu, Wayne

    2006-01-01

    The self-accelerating braneworld model (DGP) can be tested from measurements of the expansion history of the universe and the formation of structure. Current constraints on the expansion history from supernova luminosity distances, the CMB, and the Hubble constant exclude the simplest flat DGP model at about 3sigma. The best-fit open DGP model is, however, only a marginally poorer fit to the data than flat LCDM. Its substantially different expansion history raises structure formation challenges for the model. A dark-energy model with the same expansion history would predict a highly significant discrepancy with the baryon oscillation measurement due the high Hubble constant required and a large enhancement of CMB anisotropies at the lowest multipoles due to the ISW effect. For the DGP model to satisfy these constraints new gravitational phenomena would have to appear at the non-linear and cross-over scales respectively. A prediction of the DGP expansion history in a region where the phenomenology is well unde...

  1. Improved engine wall models for Large Eddy Simulation (LES)

    Science.gov (United States)

    Plengsaard, Chalearmpol

    Improved wall models for Large Eddy Simulation (LES) are presented in this research. The classical Werner-Wengle (WW) wall shear stress model is used along with near-wall sub-grid scale viscosity. A sub-grid scale turbulent kinetic energy is employed in a model for the eddy viscosity. To gain better heat flux results, a modified classical variable-density wall heat transfer model is also used. Because no experimental wall shear stress results are available in engines, the fully turbulent developed flow in a square duct is chosen to validate the new wall models. The model constants in the new wall models are set to 0.01 and 0.8, respectively and are kept constant throughout the investigation. The resulting time- and spatially-averaged velocity and temperature wall functions from the new wall models match well with the law-of-the-wall experimental data at Re = 50,000. In order to study the effect of hot air impinging walls, jet impingement on a flat plate is also tested with the new wall models. The jet Reynolds number is equal to 21,000 and a fixed jet-to-plate spacing of H/D = 2.0. As predicted by the new wall models, the time-averaged skin friction coefficient agrees well with experimental data, while the computed Nusselt number agrees fairly well when r/D > 2.0. Additionally, the model is validated using experimental data from a Caterpillar engine operated with conventional diesel combustion. Sixteen different operating engine conditions are simulated. The majority of the predicted heat flux results from each thermocouple location follow similar trends when compared with experimental data. The magnitude of peak heat fluxes as predicted by the new wall models is in the range of typical measured values in diesel combustion, while most heat flux results from previous LES wall models are over-predicted. The new wall models generate more accurate predictions and agree better with experimental data.

  2. Improving CASINO performance for models with large number of electrons

    Energy Technology Data Exchange (ETDEWEB)

    Anton, L; Alfe, D; Hood, R Q; Tanqueray, D

    2009-05-13

    Quantum Monte Carlo calculations have at their core algorithms based on statistical ensembles of multidimensional random walkers which are straightforward to use on parallel computers. Nevertheless some computations have reached the limit of the memory resources for models with more than 1000 electrons because of the need to store a large amount of electronic orbitals related data. Besides that, for systems with large number of electrons, it is interesting to study if the evolution of one configuration of random walkers can be done faster in parallel. We present a comparative study of two ways to solve these problems: (1) distributed orbital data done with MPI or Unix inter-process communication tools, (2) second level parallelism for configuration computation.

  3. Large animal models for vaccine development and testing.

    Science.gov (United States)

    Gerdts, Volker; Wilson, Heather L; Meurens, Francois; van Drunen Littel-van den Hurk, Sylvia; Wilson, Don; Walker, Stewart; Wheler, Colette; Townsend, Hugh; Potter, Andrew A

    2015-01-01

    The development of human vaccines continues to rely on the use of animals for research. Regulatory authorities require novel vaccine candidates to undergo preclinical assessment in animal models before being permitted to enter the clinical phase in human subjects. Substantial progress has been made in recent years in reducing and replacing the number of animals used for preclinical vaccine research through the use of bioinformatics and computational biology to design new vaccine candidates. However, the ultimate goal of a new vaccine is to instruct the immune system to elicit an effective immune response against the pathogen of interest, and no alternatives to live animal use currently exist for evaluation of this response. Studies identifying the mechanisms of immune protection; determining the optimal route and formulation of vaccines; establishing the duration and onset of immunity, as well as the safety and efficacy of new vaccines, must be performed in a living system. Importantly, no single animal model provides all the information required for advancing a new vaccine through the preclinical stage, and research over the last two decades has highlighted that large animals more accurately predict vaccine outcome in humans than do other models. Here we review the advantages and disadvantages of large animal models for human vaccine development and demonstrate that much of the success in bringing a new vaccine to market depends on choosing the most appropriate animal model for preclinical testing. © The Author 2015. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  4. Large eddy simulation subgrid model for soot prediction

    Science.gov (United States)

    El-Asrag, Hossam Abd El-Raouf Mostafa

    Soot prediction in realistic systems is one of the most challenging problems in theoretical and applied combustion. Soot formation as a chemical process is very complicated and not fully understood. The major difficulty stems from the chemical complexity of the soot formation process as well as its strong coupling with the other thermochemical and fluid processes that occur simultaneously. Soot is a major byproduct of incomplete combustion, having a strong impact on the environment as well as the combustion efficiency. Therefore, innovative methods is needed to predict soot in realistic configurations in an accurate and yet computationally efficient way. In the current study, a new soot formation subgrid model is developed and reported here. The new model is designed to be used within the context of the Large Eddy Simulation (LES) framework, combined with Linear Eddy Mixing (LEM) as a subgrid combustion model. The final model can be applied equally to premixed and non-premixed flames over any required geometry and flow conditions in the free, the transition, and the continuum regimes. The soot dynamics is predicted using a Method of Moments approach with Lagrangian Interpolative Closure (MOMIC) for the fractional moments. Since no prior knowledge of the particles distribution is required, the model is generally applicable. The current model accounts for the basic soot transport phenomena as transport by molecular diffusion and Thermophoretic forces. The model is first validated against experimental results for non-sooting swirling non-premixed and partially premixed flames. Next, a set of canonical premixed sooting flames are simulated, where the effect of turbulence, binary diffusivity and C/O ratio on soot formation are studied. Finally, the model is validated against a non-premixed jet sooting flame. The effect of the flame structure on the different soot formation stages as well as the particle size distribution is described. Good results are predicted with

  5. Scale invariant behavior in a large N matrix model

    CERN Document Server

    Narayanan, Rajamani

    2016-01-01

    Eigenvalue distributions of properly regularized Wilson loop operators are used to study the transition from ultra-violet (UV) behavior to infra-red (IR) behavior in gauge theories coupled to matter that potentially have an IR fixed point (FP). We numerically demonstrate emergence of scale invariance in a matrix model that describes $SU(N)$ gauge theory coupled to two flavors of massless adjoint fermions in the large $N$ limit. The eigenvalue distribution of Wilson loops of varying sizes cannot be described by a universal lattice beta-function connecting the UV to the IR.

  6. Modeling skin effect in large magnetized iron detectors

    CERN Document Server

    Incurvati, M

    2003-01-01

    The experimental problem of the calibration of magnetic field in large iron detectors is discussed. Emphasis is laid on techniques based on ballistic measurements as the ones employed by MINOS or OPERA.In particular, we provide analytical formulas to model the behavior of the apparatus in the transient regime, keeping into account eddy current effects and the finite penetration velocity of the driving fields. These formulas ease substantially the design of the calibration apparatus.Results are compared with experimental data coming from a prototype of the OPERA spectrometer.

  7. Design and modelling of innovative machinery systems for large ships

    DEFF Research Database (Denmark)

    Larsen, Ulrik

    Eighty percent of the growing global merchandise trade is transported by sea. The shipping industry is required to reduce the pollution and increase the energy efficiency of ships in the near future. There is a relatively large potential for approaching these requirements by implementing waste heat...... parameters for marine WHR. Using this mentioned methodology, regression models are derived for the prediction of the maximum obtainable thermal efficiency of ORCs. A unique configuration of the Kalina cycle, the Split-cycle, is analysed to evaluate the fullest potential of the Kalina cycle for the purpose...

  8. Modeling of large-scale oxy-fuel combustion processes

    DEFF Research Database (Denmark)

    Yin, Chungen

    2012-01-01

    , among which radiative heat transfer under oxy-fuel conditions is one of the fundamental issues. This paper demonstrates the nongray-gas effects in modeling of large-scale oxy-fuel combustion processes. Oxy-fuel combustion of natural gas in a 609MW utility boiler is numerically studied, in which....... The simulation results show that the gray and non-gray calculations of the same oxy-fuel WSGGM make distinctly different predictions in the wall radiative heat transfer, incident radiative flux, radiative source, gas temperature and species profiles. In relative to the non-gray implementation, the gray...

  9. A Model for Predicting Thermomechanical Response of Large Space Structures.

    Science.gov (United States)

    1984-06-01

    Dr. Tony Amos (202)767-4937 u.DD FORM 1473, 83 APR EDITION OF I JAN 73 IS OBSOLETE. SECURITY CLASSIFICATION CF THIS PAGE .. ’o 1 v A MODEL FOR...SYMBOL Dr. Tony Amos (202)767-4937 SDD FORM 1473, 83 APR E c , TION OF 1 JAN 73 ,S OBSOLETE. SECLUHITY (CLASSI. ICATION Oi) THI PAGE -i LARGE SPACE...94] for predicting the buckling loads associated with general instability of beam-like lattice trusses. Bazant and Christensen [95] present a

  10. Resin infusion of large composite structures modeling and manufacturing process

    Energy Technology Data Exchange (ETDEWEB)

    Loos, A.C. [Michigan State Univ., Dept. of Mechanical Engineering, East Lansing, MI (United States)

    2006-07-01

    The resin infusion processes resin transfer molding (RTM), resin film infusion (RFI) and vacuum assisted resin transfer molding (VARTM) are cost effective techniques for the fabrication of complex shaped composite structures. The dry fibrous preform is placed in the mold, consolidated, resin impregnated and cured in a single step process. The fibrous performs are often constructed near net shape using highly automated textile processes such as knitting, weaving and braiding. In this paper, the infusion processes RTM, RFI and VARTM are discussed along with the advantages of each technique compared with traditional composite fabrication methods such as prepreg tape lay up and autoclave cure. The large number of processing variables and the complex material behavior during infiltration and cure make experimental optimization of the infusion processes costly and inefficient. Numerical models have been developed which can be used to simulate the resin infusion processes. The model formulation and solution procedures for the VARTM process are presented. A VARTM process simulation of a carbon fiber preform was presented to demonstrate the type of information that can be generated by the model and to compare the model predictions with experimental measurements. Overall, the predicted flow front positions, resin pressures and preform thicknesses agree well with the measured values. The results of the simulation show the potential cost and performance benefits that can be realized by using a simulation model as part of the development process. (au)

  11. Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

    Science.gov (United States)

    Ponce-Alvarez, Adrián; He, Biyu J; Hagmann, Patric; Deco, Gustavo

    2015-08-01

    How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.

  12. Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

    Directory of Open Access Journals (Sweden)

    Adrián Ponce-Alvarez

    2015-08-01

    Full Text Available How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.

  13. Do land parameters matter in large-scale hydrological modelling?

    Science.gov (United States)

    Gudmundsson, Lukas; Seneviratne, Sonia I.

    2013-04-01

    Many of the most pending issues in large-scale hydrology are concerned with predicting hydrological variability at ungauged locations. However, current-generation hydrological and land surface models that are used for their estimation suffer from large uncertainties. These models rely on mathematical approximations of the physical system as well as on mapped values of land parameters (e.g. topography, soil types, land cover) to predict hydrological variables (e.g. evapotranspiration, soil moisture, stream flow) as a function of atmospheric forcing (e.g. precipitation, temperature, humidity). Despite considerable progress in recent years, it remains unclear whether better estimates of land parameters can improve predictions - or - if a refinement of model physics is necessary. To approach this question we suggest scrutinizing our perception of hydrological systems by confronting it with the radical assumption that hydrological variability at any location in space depends on past and present atmospheric forcing only, and not on location-specific land parameters. This so called "Constant Land Parameter Hypothesis (CLPH)" assumes that variables like runoff can be predicted without taking location specific factors such as topography or soil types into account. We demonstrate, using a modern statistical tool, that monthly runoff in Europe can be skilfully estimated using atmospheric forcing alone, without accounting for locally varying land parameters. The resulting runoff estimates are used to benchmark state-of-the-art process models. These are found to have inferior performance, despite their explicit process representation, which accounts for locally varying land parameters. This suggests that progress in the theory of hydrological systems is likely to yield larger improvements in model performance than more precise land parameter estimates. The results also question the current modelling paradigm that is dominated by the attempt to account for locally varying land

  14. Large-Signal DG-MOSFET Modelling for RFID Rectification

    Directory of Open Access Journals (Sweden)

    R. Rodríguez

    2016-01-01

    Full Text Available This paper analyses the undoped DG-MOSFETs capability for the operation of rectifiers for RFIDs and Wireless Power Transmission (WPT at microwave frequencies. For this purpose, a large-signal compact model has been developed and implemented in Verilog-A. The model has been numerically validated with a device simulator (Sentaurus. It is found that the number of stages to achieve the optimal rectifier performance is inferior to that required with conventional MOSFETs. In addition, the DC output voltage could be incremented with the use of appropriate mid-gap metals for the gate, as TiN. Minor impact of short channel effects (SCEs on rectification is also pointed out.

  15. Lattice Boltzmann Large Eddy Simulation Model of MHD

    CERN Document Server

    Flint, Christopher

    2016-01-01

    The work of Ansumali \\textit{et al.}\\cite{Ansumali} is extended to Two Dimensional Magnetohydrodynamic (MHD) turbulence in which energy is cascaded to small spatial scales and thus requires subgrid modeling. Applying large eddy simulation (LES) modeling of the macroscopic fluid equations results in the need to apply ad-hoc closure schemes. LES is applied to a suitable mesoscopic lattice Boltzmann representation from which one can recover the MHD equations in the long wavelength, long time scale Chapman-Enskog limit (i.e., the Knudsen limit). Thus on first performing filter width expansions on the lattice Boltzmann equations followed by the standard small Knudsen expansion on the filtered lattice Boltzmann system results in a closed set of MHD turbulence equations provided we enforce the physical constraint that the subgrid effects first enter the dynamics at the transport time scales. In particular, a multi-time relaxation collision operator is considered for the density distribution function and a single rel...

  16. Large N classical dynamics of holographic matrix models

    CERN Document Server

    Asplund, Curtis T; Dzienkowski, Eric

    2014-01-01

    Using a numerical simulation of the classical dynamics of the plane-wave and flat space matrix models of M-theory, we study the thermalization, equilibrium thermodynamics and fluctuations of these models as we vary the temperature and the size of the matrices, N. We present our numerical implementation in detail and several checks of its precision and consistency. We show evidence for thermalization by matching the time-averaged distributions of the matrix eigenvalues to the distributions of the appropriate Traceless Gaussian Unitary Ensemble of random matrices. We study the autocorrelations and power spectra for various fluctuating observables and observe evidence of the expected chaotic dynamics as well as a hydrodynamic type limit at large N, including near-equilibrium dissipation processes. These configurations are holographically dual to black holes in the dual string theory or M-theory and we discuss how our results could be related to the corresponding supergravity black hole solutions.

  17. Using Flume Experiments to Model Large Woody Debris Transport Dynamics

    Science.gov (United States)

    Braudrick, C. A.; Grant, G. E.

    2001-05-01

    In the last decade there has been increasing interest in quantifying the transport dynamics of large woody debris in a variety of stream types. We used flume experiments to test theoretical models of wood entrainment, transport, and deposition in streams. Because wood moves infrequently during high flows where direct measurement and observation can be difficult and dangerous. Flume experiments provide an excellent setting to study wood dynamics because channel types, flow, log size, and other parameters can be varied relatively easily and extensive data can be collected over a short time period. Our flume experiments verified theoretical model predictions that piece movement is dependent on the diameter of the log and its orientation in large rivers (where piece length is less than channel width). Piece length, often reported as the most important factor in determining piece movement in field studies, was not a factor in these simulated large channels. This is likely due to the importance of banks and vegetation on inhibiting log movement in the field, particularly for pieces longer than channel width. Logs are often at least partially lodged on the banks sometimes upstream of vegetation or other logs which anchors the piece, and increases the force required for entrainment. Rootwads also increased the flow depth required to move individual logs. By raising logs off the channel bed, rootwads decrease the buoyant and drag forces acting on the log. We also developed a theoretical model of wood transport and deposition based upon the ratios of the piece length to channel width, piece length to the radius of curvature of the channel, and piece diameter to water depth. In these experiments we noted that individual logs tend to move down the channel parallel to the channel margin, and deposited on the outside of bends, heads of shallow and exposed bars, and bar crossovers. Our theoretical model was not borne out by the experiments, likely because there were few potential

  18. Longitudinal changes in cortical thickness in autism and typical development

    Science.gov (United States)

    Prigge, Molly B. D.; Nielsen, Jared A.; Froehlich, Alyson L.; Abildskov, Tracy J.; Anderson, Jeffrey S.; Fletcher, P. Thomas; Zygmunt, Kristen M.; Travers, Brittany G.; Lange, Nicholas; Alexander, Andrew L.; Bigler, Erin D.; Lainhart, Janet E.

    2014-01-01

    The natural history of brain growth in autism spectrum disorders remains unclear. Cross-sectional studies have identified regional abnormalities in brain volume and cortical thickness in autism, although substantial discrepancies have been reported. Preliminary longitudinal studies using two time points and small samples have identified specific regional differences in cortical thickness in the disorder. To clarify age-related trajectories of cortical development, we examined longitudinal changes in cortical thickness within a large mixed cross-sectional and longitudinal sample of autistic subjects and age- and gender-matched typically developing controls. Three hundred and forty-five magnetic resonance imaging scans were examined from 97 males with autism (mean age = 16.8 years; range 3–36 years) and 60 males with typical development (mean age = 18 years; range 4–39 years), with an average interscan interval of 2.6 years. FreeSurfer image analysis software was used to parcellate the cortex into 34 regions of interest per hemisphere and to calculate mean cortical thickness for each region. Longitudinal linear mixed effects models were used to further characterize these findings and identify regions with between-group differences in longitudinal age-related trajectories. Using mean age at time of first scan as a reference (15 years), differences were observed in bilateral inferior frontal gyrus, pars opercularis and pars triangularis, right caudal middle frontal and left rostral middle frontal regions, and left frontal pole. However, group differences in cortical thickness varied by developmental stage, and were influenced by IQ. Differences in age-related trajectories emerged in bilateral parietal and occipital regions (postcentral gyrus, cuneus, lingual gyrus, pericalcarine cortex), left frontal regions (pars opercularis, rostral middle frontal and frontal pole), left supramarginal gyrus, and right transverse temporal gyrus, superior parietal lobule, and

  19. The Importance of Computational Modeling of Large Pumping Stations

    Directory of Open Access Journals (Sweden)

    S. M. Bozh'eva

    2015-01-01

    Full Text Available The article presents main design and structure principles of pumping stations. It specifies basic requirements for the favorable hydraulic operation conditions of the pumping units. The article also describes the designing cases, when computational modeling is necessary to analyse activity of pumping station and provide its reliable operation. A specific example of the large pumping station with submersible pumps describes the process of computational modeling of its operation. As the object of simulation was selected the underground pumping station with a diameter of 26 m and a depth of 13 m, divided into two independent branches, equipped with 8 submersible pumps. The objective of this work was to evaluate the effectiveness of the design solution by CFD methods, to analyze the design of the inlet chamber, to identify possible difficulties with the operation of the facility. In details are described the structure of the considered pumping station and applied computational models of physical processes. The article gives the detailed formulation of the task of simulation and the methods of its solving and presents the initial and boundary conditions. It describes the basic operation modes of the pumping station. The obtained results were presented as the flow patterns for each operation mode with detailed explanations. Data obtained as a result of CFD, prove the correctness of the general design solutions of the project. The submersible pump operation at the minimum water level was verified, was confirmed a lack of vortex formation as well as were proposed measures to improve the operating conditions of the facility. In the inlet chamber there are shown the stagnant zones, requiring separate schedule of cleaning. The measure against floating debris and foam was proposed. It justifies the use of computational modeling (CFD for the verifying and adjusting of the projects of large pumping stations as a much more precise tool that takes into account

  20. A Cortical Edge-integration Model of Object-Based Lightness Computation that Explains Effects of Spatial Context and Individual Differences

    Directory of Open Access Journals (Sweden)

    Michael E Rudd

    2014-08-01

    Full Text Available Previous work demonstrated that perceived surface reflectance (lightness can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatial integrates these steps along paths through the image to compute lightness (Rudd & Zemach, 2004, 2005, 2007. This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013 suggests that the human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010 further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer’s interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd & Zemach, 2005. Here, I show how the separate influences of grouping and attention on lightness can be together modeled by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013, and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

  1. A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences

    Science.gov (United States)

    Rudd, Michael E.

    2014-01-01

    Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4. PMID:25202253

  2. Aeroservoelastic model based active control for large civil aircraft

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A modeling and control approach for an advanced configured large civil aircraft with aeroservoelasticity via the LQG method and control allocation is presented.Mathematical models and implementation issues for the multi-input/multi-output(MIMO) aeroservoelastic system simulation developed for a flexible wing with multi control surfaces are described.A fuzzy logic based optimization approach is employed to solve the constrained control allocation problem via intelligently adjusting the components of output vector and find a proper vector in the attainable moment set(AMS) autonomously.The basic idea is to minimize the L2 norm of error between the desired moment and achievable moment using the designing freedom provided by redundantly allocated actuators and control surfaces.Considering the constraints of control surfaces,in order to obtain acceptable performance of aircraft such as stability and maneuverability,the fuzzy weights are updated by the learning algorithm,which makes the closed-loop system self-adaptation.Finally,an application example of flight control designing for the advanced civil aircraft is discussed as a demonstration.The studies we have performed showed that the advanced configured large civil aircraft has good performance with the proper designed control law designed via the proposed approach.The gust alleviation and flutter suppression are applied with the synergetic effects of elevator,ailerons,equivalent rudders and flaps.The results show good closed loop performance and meet the requirement of constraint of control surfaces.

  3. Modelling large-scale halo bias using the bispectrum

    CERN Document Server

    Pollack, Jennifer E; Porciani, Cristiano

    2011-01-01

    We study the relation between the halo and matter density fields -- commonly termed bias -- in the LCDM framework. In particular, we examine the local model of biasing at quadratic order in matter density. This model is characterized by parameters b_1 and b_2. Using an ensemble of N-body simulations, we apply several statistical methods to estimate the parameters. We measure halo and matter fluctuations smoothed on various scales and find that the parameters vary with smoothing scale. We argue that, for real-space measurements, owing to the mixing of wavemodes, no scale can be found for which the parameters are independent of smoothing. However, this is not the case in Fourier space. We measure halo power spectra and construct estimates for an effective large-scale bias. We measure the configuration dependence of the halo bispectra B_hhh and reduced bispectra Q_hhh for very large-scale k-space triangles. From this we constrain b_1 and b_2. Using the lowest-order perturbation theory, we find that for B_hhh the...

  4. Modelling large scale human activity in San Francisco

    Science.gov (United States)

    Gonzalez, Marta

    2010-03-01

    Diverse group of people with a wide variety of schedules, activities and travel needs compose our cities nowadays. This represents a big challenge for modeling travel behaviors in urban environments; those models are of crucial interest for a wide variety of applications such as traffic forecasting, spreading of viruses, or measuring human exposure to air pollutants. The traditional means to obtain knowledge about travel behavior is limited to surveys on travel journeys. The obtained information is based in questionnaires that are usually costly to implement and with intrinsic limitations to cover large number of individuals and some problems of reliability. Using mobile phone data, we explore the basic characteristics of a model of human travel: The distribution of agents is proportional to the population density of a given region, and each agent has a characteristic trajectory size contain information on frequency of visits to different locations. Additionally we use a complementary data set given by smart subway fare cards offering us information about the exact time of each passenger getting in or getting out of the subway station and the coordinates of it. This allows us to uncover the temporal aspects of the mobility. Since we have the actual time and place of individual's origin and destination we can understand the temporal patterns in each visited location with further details. Integrating two described data set we provide a dynamical model of human travels that incorporates different aspects observed empirically.

  5. Modeling Resource Utilization of a Large Data Acquisition System

    CERN Document Server

    Santos, Alejandro; The ATLAS collaboration

    2017-01-01

    The ATLAS 'Phase-II' upgrade, scheduled to start in 2024, will significantly change the requirements under which the data-acquisition system operates. The input data rate, currently fixed around 150 GB/s, is anticipated to reach 5 TB/s. In order to deal with the challenging conditions, and exploit the capabilities of newer technologies, a number of architectural changes are under consideration. Of particular interest is a new component, known as the Storage Handler, which will provide a large buffer area decoupling real-time data taking from event filtering. Dynamic operational models of the upgraded system can be used to identify the required resources and to select optimal techniques. In order to achieve a robust and dependable model, the current data-acquisition architecture has been used as a test case. This makes it possible to verify and calibrate the model against real operation data. Such a model can then be evolved toward the future ATLAS Phase-II architecture. In this paper we introduce the current ...

  6. Modelling Resource Utilization of a Large Data Acquisition System

    CERN Document Server

    Santos, Alejandro; The ATLAS collaboration

    2017-01-01

    The ATLAS 'Phase-II' upgrade, scheduled to start in 2024, will significantly change the requirements under which the data-acquisition system operates. The input data rate, currently fixed around 150 GB/s, is anticipated to reach 5 TB/s. In order to deal with the challenging conditions, and exploit the capabilities of newer technologies, a number of architectural changes are under consideration. Of particular interest is a new component, known as the Storage Handler, which will provide a large buffer area decoupling real-time data taking from event filtering. Dynamic operational models of the upgraded system can be used to identify the required resources and to select optimal techniques. In order to achieve a robust and dependable model, the current data-acquisition architecture has been used as a test case. This makes it possible to verify and calibrate the model against real operation data. Such a model can then be evolved toward the future ATLAS Phase-II architecture. In this paper we introduce the current ...

  7. Modelling large-scale evacuation of music festivals

    Directory of Open Access Journals (Sweden)

    E. Ronchi

    2016-05-01

    Full Text Available This paper explores the use of multi-agent continuous evacuation modelling for representing large-scale evacuation scenarios at music festivals. A 65,000 people capacity music festival area was simulated using the model Pathfinder. Three evacuation scenarios were developed in order to explore the capabilities of evacuation modelling during such incidents, namely (1 a preventive evacuation of a section of the festival area containing approximately 15,000 people due to a fire breaking out on a ship, (2 an escalating scenario involving the total evacuation of the entire festival area (65,000 people due to a bomb threat, and (3 a cascading scenario involving the total evacuation of the entire festival area (65,000 people due to the threat of an explosion caused by a ship engine overheating. This study suggests that the analysis of the people-evacuation time curves produced by evacuation models, coupled with a visual analysis of the simulated evacuation scenarios, allows for the identification of the main factors affecting the evacuation process (e.g., delay times, overcrowding at exits in relation to exit widths, etc. and potential measures that could improve safety.

  8. Proteomic analysis of cortical brain tissue from the BTBR mouse model of autism: Evidence for changes in STOP and myelin-related proteins.

    Science.gov (United States)

    Wei, H; Ma, Y; Liu, J; Ding, C; Hu, F; Yu, L

    2016-01-15

    Autism is a neurodevelopmental disorder characterized by abnormal reciprocal social interactions, communication deficits, and repetitive behaviors with restricted interests. However, the widely accepted biomarkers for autism are still lacking. In this study, we carried out a quantitative proteomic profiling study of cortical brain tissue from BTBR T(+)Itpr3(tf) (BTBR) mice, a mouse model that displays an autism-like phenotype. Using isobaric tag for relative and absolute quantification (iTRAQ) coupled with LC-MS/MS, a total of 3611 proteins were quantitated in mouse cortices. As compared to C57BL/6J (B6) mice, 126 differentially expressed proteins were found in the brain from BTBR mice. The functional annotation and categories of differentially expressed proteins were analyzed. Especially, the stable tubule only polypeptide (STOP) protein and myelin-related proteins down-regulated significantly in BTBR mice were confirmed by Western blotting. Furthermore, the BTBR mice displayed reduced levels of staining with ferric alum in comparison to B6 controls, indicative of myelin disruption. Finally, we propose that reduced STOP expression in the brain could be involved in the mediation of autism-like behaviors through impairments of myelination in oligodendrocytes and synaptic function in neurons. Manipulation of STOP protein could be a promising avenue for therapeutic interventions to autism.

  9. Impaired excitability of somatostatin- and parvalbumin-expressing cortical interneurons in a mouse model of Dravet syndrome.

    Science.gov (United States)

    Tai, Chao; Abe, Yasuyuki; Westenbroek, Ruth E; Scheuer, Todd; Catterall, William A

    2014-07-29

    Haploinsufficiency of the voltage-gated sodium channel NaV1.1 causes Dravet syndrome, an intractable developmental epilepsy syndrome with seizure onset in the first year of life. Specific heterozygous deletion of NaV1.1 in forebrain GABAergic-inhibitory neurons is sufficient to cause all the manifestations of Dravet syndrome in mice, but the physiological roles of specific subtypes of GABAergic interneurons in the cerebral cortex in this disease are unknown. Voltage-clamp studies of dissociated interneurons from cerebral cortex did not detect a significant effect of the Dravet syndrome mutation on sodium currents in cell bodies. However, current-clamp recordings of intact interneurons in layer V of neocortical slices from mice with haploinsufficiency in the gene encoding the NaV1.1 sodium channel, Scn1a, revealed substantial reduction of excitability in fast-spiking, parvalbumin-expressing interneurons and somatostatin-expressing interneurons. The threshold and rheobase for action potential generation were increased, the frequency of action potentials within trains was decreased, and action-potential firing within trains failed more frequently. Furthermore, the deficit in excitability of somatostatin-expressing interneurons caused significant reduction in frequency-dependent disynaptic inhibition between neighboring layer V pyramidal neurons mediated by somatostatin-expressing Martinotti cells, which would lead to substantial disinhibition of the output of cortical circuits. In contrast to these deficits in interneurons, pyramidal cells showed no differences in excitability. These results reveal that the two major subtypes of interneurons in layer V of the neocortex, parvalbumin-expressing and somatostatin-expressing, both have impaired excitability, resulting in disinhibition of the cortical network. These major functional deficits are likely to contribute synergistically to the pathophysiology of Dravet syndrome.

  10. Spared piriform cortical single-unit odor processing and odor discrimination in the Tg2576 mouse model of Alzheimer's disease.

    Science.gov (United States)

    Xu, Wenjin; Lopez-Guzman, Mirielle; Schoen, Chelsea; Fitzgerald, Shane; Lauer, Stephanie L; Nixon, Ralph A; Levy, Efrat; Wilson, Donald A

    2014-01-01

    Alzheimer's disease is a neurodegenerative disorder that is the most common cause of dementia in the elderly today. One of the earliest reported signs of Alzheimer's disease is olfactory dysfunction, which may manifest in a variety of ways. The present study sought to address this issue by investigating odor coding in the anterior piriform cortex, the primary cortical region involved in higher order olfactory function, and how it relates to performance on olfactory behavioral tasks. An olfactory habituation task was performed on cohorts of transgenic and age-matched wild-type mice at 3, 6 and 12 months of age. These animals were then anesthetized and acute, single-unit electrophysiology was performed in the anterior piriform cortex. In addition, in a separate group of animals, a longitudinal odor discrimination task was conducted from 3-12 months of age. Results showed that while odor habituation was impaired at all ages, Tg2576 performed comparably to age-matched wild-type mice on the olfactory discrimination task. The behavioral data mirrored intact anterior piriform cortex single-unit odor responses and receptive fields in Tg2576, which were comparable to wild-type at all age groups. The present results suggest that odor processing in the olfactory cortex and basic odor discrimination is especially robust in the face of amyloid β precursor protein (AβPP) over-expression and advancing amyloid β (Aβ) pathology. Odor identification deficits known to emerge early in Alzheimer's disease progression, therefore, may reflect impairments in linking the odor percept to associated labels in cortical regions upstream of the primary olfactory pathway, rather than in the basic odor processing itself.

  11. Spared piriform cortical single-unit odor processing and odor discrimination in the Tg2576 mouse model of Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Wenjin Xu

    Full Text Available Alzheimer's disease is a neurodegenerative disorder that is the most common cause of dementia in the elderly today. One of the earliest reported signs of Alzheimer's disease is olfactory dysfunction, which may manifest in a variety of ways. The present study sought to address this issue by investigating odor coding in the anterior piriform cortex, the primary cortical region involved in higher order olfactory function, and how it relates to performance on olfactory behavioral tasks. An olfactory habituation task was performed on cohorts of transgenic and age-matched wild-type mice at 3, 6 and 12 months of age. These animals were then anesthetized and acute, single-unit electrophysiology was performed in the anterior piriform cortex. In addition, in a separate group of animals, a longitudinal odor discrimination task was conducted from 3-12 months of age. Results showed that while odor habituation was impaired at all ages, Tg2576 performed comparably to age-matched wild-type mice on the olfactory discrimination task. The behavioral data mirrored intact anterior piriform cortex single-unit odor responses and receptive fields in Tg2576, which were comparable to wild-type at all age groups. The present results suggest that odor processing in the olfactory cortex and basic odor discrimination is especially robust in the face of amyloid β precursor protein (AβPP over-expression and advancing amyloid β (Aβ pathology. Odor identification deficits known to emerge early in Alzheimer's disease progression, therefore, may reflect impairments in linking the odor percept to associated labels in cortical regions upstream of the primary olfactory pathway, rather than in the basic odor processing itself.

  12. Differential changes in thalamic and cortical excitatory synapses onto striatal spiny projection neurons in a Huntington disease mouse model.

    Science.gov (United States)

    Kolodziejczyk, Karolina; Raymond, Lynn A

    2016-02-01

    Huntington disease (HD), a neurodegenerative disorder caused by CAG repeat expansion in the gene encoding huntingtin, predominantly affects the striatum, especially the spiny projection neurons (SPN). The striatum receives excitatory input from cortex and thalamus, and the role of the former has been well-studied in HD. Here, we report that mutated huntingtin alters function of thalamostriatal connections. We used a novel thalamostriatal (T-S) coculture and an established corticostriatal (C-S) coculture, generated from YAC128 HD and WT (FVB/NJ background strain) mice, to investigate excitatory neurotransmission onto striatal SPN. SPN in T-S coculture from WT mice showed similar mini-excitatory postsynaptic current (mEPSC) frequency and amplitude as in C-S coculture; however, both the frequency and amplitude were significantly reduced in YAC128 T-S coculture. Further investigation in T-S coculture showed similar excitatory synapse density in WT and YAC128 SPN dendrites by immunostaining, suggesting changes in total dendritic length or probability of release as possible explanations for mEPSC frequency changes. Synaptic N-methyl-D-aspartate receptor (NMDAR) current was similar, but extrasynaptic current, associated with cell death signaling, was enhanced in YAC128 SPN in T-S coculture. Employing optical stimulation of cortical versus thalamic afferents and recording from striatal SPN in brain slice, we found increased glutamate release probability and reduced AMPAR/NMDAR current ratios in thalamostriatal synapses, most prominently in YAC128. Enhanced extrasynaptic NMDAR current in YAC128 SPN was apparent with both cortical and thalamic stimulation. We conclude that thalamic afferents to the striatum are affected early, prior to an overt HD phenotype; however, changes in NMDAR localization in SPN are independent of the source of glutamatergic input.

  13. AUTOMATED SEGMENTATION OF CORTICAL NECROSIS USING A WAVELET BASED ABNORMALITY DETECTION SYSTEM.

    Science.gov (United States)

    Gaonkar, Bilwaj; Erus, Guray; Pohl, Kilian M; Tanwar, Manoj; Margiewicz, Stefan; Bryan, R Nick; Davatzikos, Christos

    2011-03-01

    We propose an automated method to segment cortical necrosis from brain FLAIR-MR Images. Cortical necrosis are regions of dead brain tissue in the cortex caused by cerebrovascular disease (CVD). The accurate segmentation of these regions is difficult as their intensity patterns are similar to the adjoining cerebrospinal fluid (CSF). We generate a model of normal variation using MR scans of healthy controls. The model is based on the Jacobians of warps obtained by registering scans of normal subjects to a common coordinate system. For each patient scan a Jacobian is obtained by warping it to the same coordinate system. Large deviations between the model and subject-specific Jacobians are flagged as `abnormalities'. Abnormalities are segmented as cortical necrosis if they are in the cortex and have the intensity profile of CSF. We evaluate our method by using a set of 72 healthy subjects to model cortical variation.We use this model to successfully detect and segment cortical necrosis in a set of 37 patients with CVD. A comparison of the results with segmentations from two independent human experts shows that the overlap between our approach and either of the human experts is in the range of the overlap between the two human experts themselves.

  14. An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences.

    Science.gov (United States)

    Lam, Su Datt; Das, Sayoni; Sillitoe, Ian; Orengo, Christine

    2017-08-01

    Computational modelling of proteins has been a major catalyst in structural biology. Bioinformatics groups have exploited the repositories of known structures to predict high-quality structural models with high efficiency at low cost. This article provides an overview of comparative modelling, reviews recent developments and describes resources dedicated to large-scale comparative modelling of genome sequences. The value of subclustering protein domain superfamilies to guide the template-selection process is investigated. Some recent cases in which structural modelling has aided experimental work to determine very large macromolecular complexes are also cited.

  15. Improving large-scale groundwater models by considering fossil gradients

    Science.gov (United States)

    Schulz, Stephan; Walther, Marc; Michelsen, Nils; Rausch, Randolf; Dirks, Heiko; Al-Saud, Mohammed; Merz, Ralf; Kolditz, Olaf; Schüth, Christoph

    2017-05-01

    Due to limited availability of surface water, many arid to semi-arid countries rely on their groundwater resources. Despite the quasi-absence of present day replenishment, some of these groundwater bodies contain large amounts of water, which was recharged during pluvial periods of the Late Pleistocene to Early Holocene. These mostly fossil, non-renewable resources require different management schemes compared to those which are usually applied in renewable systems. Fossil groundwater is a finite resource and its withdrawal implies mining of aquifer storage reserves. Although they receive almost no recharge, some of them show notable hydraulic gradients and a flow towards their discharge areas, even without pumping. As a result, these systems have more discharge than recharge and hence are not in steady state, which makes their modelling, in particular the calibration, very challenging. In this study, we introduce a new calibration approach, composed of four steps: (i) estimating the fossil discharge component, (ii) determining the origin of fossil discharge, (iii) fitting the hydraulic conductivity with a pseudo steady-state model, and (iv) fitting the storage capacity with a transient model by reconstructing head drawdown induced by pumping activities. Finally, we test the relevance of our approach and evaluated the effect of considering or ignoring fossil gradients on aquifer parameterization for the Upper Mega Aquifer (UMA) on the Arabian Peninsula.

  16. Dense neuron clustering explains connectivity statistics in cortical microcircuits.

    Directory of Open Access Journals (Sweden)

    Vladimir V Klinshov

    Full Text Available Local cortical circuits appear highly non-random, but the underlying connectivity rule remains elusive. Here, we analyze experimental data observed in layer 5 of rat neocortex and suggest a model for connectivity from which emerge essential observed non-random features of both wiring and weighting. These features include lognormal distributions of synaptic connection strength, anatomical clustering, and strong correlations between clustering and connection strength. Our model predicts that cortical microcircuits contain large groups of densely connected neurons which we call clusters. We show that such a cluster contains about one fifth of all excitatory neurons of a circuit which are very densely connected with stronger than average synapses. We demonstrate that such clustering plays an important role in the network dynamics, namely, it creates bistable neural spiking in small cortical circuits. Furthermore, introducing local clustering in large-scale networks leads to the emergence of various patterns of persistent local activity in an ongoing network activity. Thus, our results may bridge a gap between anatomical structure and persistent activity observed during working memory and other cognitive processes.

  17. The unified minimal supersymmetric model with large Yukawa couplings

    CERN Document Server

    Rattazzi, Riccardo

    1996-01-01

    The consequences of assuming the third-generation Yukawa couplings are all large and comparable are studied in the context of the minimal supersymmetric extension of the standard model. General aspects of the RG evolution of the parameters, theoretical constraints needed to ensure proper electroweak symmetry breaking, and experimental and cosmological bounds on low-energy parameters are presented. We also present complete and exact semi-analytic solutions to the 1-loop RG equations. Focusing on SU(5) or SO(10) unification, we analyze the relationship between the top and bottom masses and the superspectrum, and the phenomenological implications of the GUT conditions on scalar masses. Future experimental measurements of the superspectrum and of the strong coupling will distinguish between various GUT-scale scenarios. And if present experimental knowledge is to be accounted for most naturally, a particular set of predictions is singled out.

  18. Soil carbon management in large-scale Earth system modelling

    DEFF Research Database (Denmark)

    Olin, S.; Lindeskog, M.; Pugh, T. A. M.

    2015-01-01

    .5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till management and cover crops proposed in previous studies is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when......Croplands are vital ecosystems for human well-being and provide important ecosystem services such as crop yields, retention of nitrogen and carbon storage. On large (regional to global)-scale levels, assessment of how these different services will vary in space and time, especially in response...... to cropland management, are scarce. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land-use-enabled dynamic vegetation model LPJ-GUESS (Lund–Potsdam–Jena General Ecosystem Simulator). Simulated crop production, cropland carbon storage...

  19. A stochastic large deformation model for computational anatomy

    DEFF Research Database (Denmark)

    Arnaudon, Alexis; Holm, Darryl D.; Pai, Akshay Sadananda Uppinakudru

    2017-01-01

    In the study of shapes of human organs using computational anatomy, variations are found to arise from inter-subject anatomical differences, disease-specific effects, and measurement noise. This paper introduces a stochastic model for incorporating random variations into the Large Deformation...... Diffeomorphic Metric Mapping (LDDMM) framework. By accounting for randomness in a particular setup which is crafted to fit the geometrical properties of LDDMM, we formulate the template estimation problem for landmarks with noise and give two methods for efficiently estimating the parameters of the noise fields...... from a prescribed data set. One method directly approximates the time evolution of the variance of each landmark by a finite set of differential equations, and the other is based on an Expectation-Maximisation algorithm. In the second method, the evaluation of the data likelihood is achieved without...

  20. Large geospatial images discovery: metadata model and technological framework

    Directory of Open Access Journals (Sweden)

    Lukáš Brůha

    2015-12-01

    Full Text Available The advancements in geospatial web technology triggered efforts for disclosure of valuable resources of historical collections. This paper focuses on the role of spatial data infrastructures (SDI in such efforts. The work describes the interplay between SDI technologies and potential use cases in libraries such as cartographic heritage. The metadata model is introduced to link up the sources from these two distinct fields. To enhance the data search capabilities, the work focuses on the representation of the content-based metadata of raster images, which is the crucial prerequisite to target the search in a more effective way. The architecture of the prototype system for automatic raster data processing, storage, analysis and distribution is introduced. The architecture responds to the characteristics of input datasets, namely to the continuous flow of very large raster data and related metadata. Proposed solutions are illustrated on the case study of cartometric analysis of digitised early maps and related metadata encoding.

  1. Computational modeling of single particle scattering over large distances

    Science.gov (United States)

    Rapp, Rebecca; Plumley, Rajan; McCracken, Michael

    2016-09-01

    We present a Monte Carlo simulation of the propagation of a single particle through a large three-dimensional volume under the influence of individual scattering events. In such systems, short paths can be quickly and accurately simulated using random walks defined by individual scattering parameters, but the simulation time greatly increases as the size of the space grows. We present a method for reducing the overall simulation time by restricting the simulation to a cube of unit length; each `cell' is characterized by a set of parameters which dictate the distributions of allowable step lengths and polar scattering angles. We model propagation over large distances by constructing a lattice of cells with physical parameters that depend on position, such that the full set would represent a space within the entire volume available to the particle. With these, we propose the use of Markov chains to determine a probable path for the particle, thereby removing the need to simulate every step in the particle's path. For a single particle with constant velocity, we can use the step statistics to determine the travel time of the particle. We investigate the effect of scattering parameters such as average step distance and possible scattering angles on the probabilities of a cell.

  2. Large scale solar district heating. Evaluation, modelling and designing

    Energy Technology Data Exchange (ETDEWEB)

    Heller, A.

    2000-07-01

    The main objective of the research was to evaluate large-scale solar heating connected to district heating (CSDHP), to build up a simulation tool and to demonstrate the application of the tool for design studies and on a local energy planning case. The evaluation of the central solar heating technology is based on measurements on the case plant in Marstal, Denmark, and on published and unpublished data for other, mainly Danish, CSDHP plants. Evaluations on the thermal, economical and environmental performances are reported, based on the experiences from the last decade. The measurements from the Marstal case are analysed, experiences extracted and minor improvements to the plant design proposed. For the detailed designing and energy planning of CSDHPs, a computer simulation model is developed and validated on the measurements from the Marstal case. The final model is then generalised to a 'generic' model for CSDHPs in general. The meteorological reference data, Danish Reference Year, is applied to find the mean performance for the plant designs. To find the expectable variety of the thermal performance of such plants, a method is proposed where data from a year with poor solar irradiation and a year with strong solar irradiation are applied. Equipped with a simulation tool design studies are carried out spreading from parameter analysis over energy planning for a new settlement to a proposal for the combination of plane solar collectors with high performance solar collectors, exemplified by a trough solar collector. The methodology of utilising computer simulation proved to be a cheap and relevant tool in the design of future solar heating plants. The thesis also exposed the demand for developing computer models for the more advanced solar collector designs and especially for the control operation of CSHPs. In the final chapter the CSHP technology is put into perspective with respect to other possible technologies to find the relevance of the application

  3. Multistability in Large Scale Models of Brain Activity.

    Directory of Open Access Journals (Sweden)

    Mathieu Golos

    2015-12-01

    Full Text Available Noise driven exploration of a brain network's dynamic repertoire has been hypothesized to be causally involved in cognitive function, aging and neurodegeneration. The dynamic repertoire crucially depends on the network's capacity to store patterns, as well as their stability. Here we systematically explore the capacity of networks derived from human connectomes to store attractor states, as well as various network mechanisms to control the brain's dynamic repertoire. Using a deterministic graded response Hopfield model with connectome-based interactions, we reconstruct the system's attractor space through a uniform sampling of the initial conditions. Large fixed-point attractor sets are obtained in the low temperature condition, with a bigger number of attractors than ever reported so far. Different variants of the initial model, including (i a uniform activation threshold or (ii a global negative feedback, produce a similarly robust multistability in a limited parameter range. A numerical analysis of the distribution of the attractors identifies spatially-segregated components, with a centro-medial core and several well-delineated regional patches. Those different modes share similarity with the fMRI independent components observed in the "resting state" condition. We demonstrate non-stationary behavior in noise-driven generalizations of the models, with different meta-stable attractors visited along the same time course. Only the model with a global dynamic density control is found to display robust and long-lasting non-stationarity with no tendency toward either overactivity or extinction. The best fit with empirical signals is observed at the edge of multistability, a parameter region that also corresponds to the highest entropy of the attractors.

  4. Mathematical modeling of local perfusion in large distensible microvascular networks

    Science.gov (United States)

    Causin, Paola; Malgaroli, Francesca

    2017-08-01

    Microvessels -blood vessels with diameter less than 200 microns- form large, intricate networks organized into arterioles, capillaries and venules. In these networks, the distribution of flow and pressure drop is a highly interlaced function of single vessel resistances and mutual vessel interactions. In this paper we propose a mathematical and computational model to study the behavior of microcirculatory networks subjected to different conditions. The network geometry is composed of a graph of connected straight cylinders, each one representing a vessel. The blood flow and pressure drop across the single vessel, further split into smaller elements, are related through a generalized Ohm's law featuring a conductivity parameter, function of the vessel cross section area and geometry, which undergo deformations under pressure loads. The membrane theory is used to describe the deformation of vessel lumina, tailored to the structure of thick-walled arterioles and thin-walled venules. In addition, since venules can possibly experience negative transmural pressures, a buckling model is also included to represent vessel collapse. The complete model including arterioles, capillaries and venules represents a nonlinear system of PDEs, which is approached numerically by finite element discretization and linearization techniques. We use the model to simulate flow in the microcirculation of the human eye retina, a terminal system with a single inlet and outlet. After a phase of validation against experimental measurements, we simulate the network response to different interstitial pressure values. Such a study is carried out both for global and localized variations of the interstitial pressure. In both cases, significant redistributions of the blood flow in the network arise, highlighting the importance of considering the single vessel behavior along with its position and connectivity in the network.

  5. Evolution of cortical neurogenesis.

    Science.gov (United States)

    Abdel-Mannan, Omar; Cheung, Amanda F P; Molnár, Zoltán

    2008-03-18

    The neurons of the mammalian neocortex are organised into six layers. By contrast, the reptilian and avian dorsal cortices only have three layers which are thought to be equivalent to layers I, V and VI of mammals. Increased repertoire of mammalian higher cognitive functions is likely a result of an expanded cortical surface area. The majority of cortical cell proliferation in mammals occurs in the ventricular zone (VZ) and subventricular zone (SVZ), with a small number of scattered divisions outside the germinal zone. Comparative developmental studies suggest that the appearance of SVZ coincides with the laminar expansion of the cortex to six layers, as well as the tangential expansion of the cortical sheet seen within mammals. In spite of great variation and further compartmentalisation in the mitotic compartments, the number of neurons in an arbitrary cortical column appears to be remarkably constant within mammals. The current challenge is to understand how the emergence and elaboration of the SVZ has contributed to increased cortical cell diversity, tangential expansion and gyrus formation of the mammalian neocortex. This review discusses neurogenic processes that are believed to underlie these major changes in cortical dimensions in vertebrates.

  6. Multi-Resolution Modeling of Large Scale Scientific Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Baldwin, C; Abdulla, G; Critchlow, T

    2003-01-31

    This paper discusses using the wavelets modeling technique as a mechanism for querying large-scale spatio-temporal scientific simulation data. Wavelets have been used successfully in time series analysis and in answering surprise and trend queries. Our approach however is driven by the need for compression, which is necessary for viable throughput given the size of the targeted data, along with the end user requirements from the discovery process. Our users would like to run fast queries to check the validity of the simulation algorithms used. In some cases users are welling to accept approximate results if the answer comes back within a reasonable time. In other cases they might want to identify a certain phenomena and track it over time. We face a unique problem because of the data set sizes. It may take months to generate one set of the targeted data; because of its shear size, the data cannot be stored on disk for long and thus needs to be analyzed immediately before it is sent to tape. We integrated wavelets within AQSIM, a system that we are developing to support exploration and analyses of tera-scale size data sets. We will discuss the way we utilized wavelets decomposition in our domain to facilitate compression and in answering a specific class of queries that is harder to answer with any other modeling technique. We will also discuss some of the shortcomings of our implementation and how to address them.

  7. EXO-ZODI MODELING FOR THE LARGE BINOCULAR TELESCOPE INTERFEROMETER

    Energy Technology Data Exchange (ETDEWEB)

    Kennedy, Grant M.; Wyatt, Mark C.; Panić, Olja; Shannon, Andrew [Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom); Bailey, Vanessa; Defrère, Denis; Hinz, Philip M.; Rieke, George H.; Skemer, Andrew J.; Su, Katherine Y. L. [Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721 (United States); Bryden, Geoffrey; Mennesson, Bertrand; Morales, Farisa; Serabyn, Eugene [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Danchi, William C.; Roberge, Aki; Stapelfeldt, Karl R. [NASA Goddard Space Flight Center, Exoplanets and Stellar Astrophysics, Code 667, Greenbelt, MD 20771 (United States); Haniff, Chris [Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Lebreton, Jérémy [Infrared Processing and Analysis Center, MS 100-22, California Institute of Technology, 770 South Wilson Avenue, Pasadena, CA 91125 (United States); Millan-Gabet, Rafael [NASA Exoplanet Science Institute, California Institute of Technology, 770 South Wilson Avenue, Pasadena, CA 91125 (United States); and others

    2015-02-01

    Habitable zone dust levels are a key unknown that must be understood to ensure the success of future space missions to image Earth analogs around nearby stars. Current detection limits are several orders of magnitude above the level of the solar system's zodiacal cloud, so characterization of the brightness distribution of exo-zodi down to much fainter levels is needed. To this end, the Large Binocular Telescope Interferometer (LBTI) will detect thermal emission from habitable zone exo-zodi a few times brighter than solar system levels. Here we present a modeling framework for interpreting LBTI observations, which yields dust levels from detections and upper limits that are then converted into predictions and upper limits for the scattered light surface brightness. We apply this model to the HOSTS survey sample of nearby stars; assuming a null depth uncertainty of 10{sup –4} the LBTI will be sensitive to dust a few times above the solar system level around Sun-like stars, and to even lower dust levels for more massive stars.

  8. An Overview of Westinghouse Realistic Large Break LOCA Evaluation Model

    Directory of Open Access Journals (Sweden)

    Cesare Frepoli

    2008-01-01

    Full Text Available Since the 1988 amendment of the 10 CFR 50.46 rule in 1988, Westinghouse has been developing and applying realistic or best-estimate methods to perform LOCA safety analyses. A realistic analysis requires the execution of various realistic LOCA transient simulations where the effect of both model and input uncertainties are ranged and propagated throughout the transients. The outcome is typically a range of results with associated probabilities. The thermal/hydraulic code is the engine of the methodology but a procedure is developed to assess the code and determine its biases and uncertainties. In addition, inputs to the simulation are also affected by uncertainty and these uncertainties are incorporated into the process. Several approaches have been proposed and applied in the industry in the framework of best-estimate methods. Most of the implementations, including Westinghouse, follow the Code Scaling, Applicability and Uncertainty (CSAU methodology. Westinghouse methodology is based on the use of the WCOBRA/TRAC thermal-hydraulic code. The paper starts with an overview of the regulations and its interpretation in the context of realistic analysis. The CSAU roadmap is reviewed in the context of its implementation in the Westinghouse evaluation model. An overview of the code (WCOBRA/TRAC and methodology is provided. Finally, the recent evolution to nonparametric statistics in the current edition of the W methodology is discussed. Sample results of a typical large break LOCA analysis for a PWR are provided.

  9. 卡莫司汀致皮质发育障碍的模型研究%Animal models of cortical dysplasia induced by carmustine

    Institute of Scientific and Technical Information of China (English)

    龙莉莉; 肖波; 宋延民; 王康; 李国良

    2008-01-01

    Objective To establish the animal model of diffuse cortical dysplasia in Sprague-Dawley rats. Methods Pregnant rats were given intraperitoneal injections of BCNU on embryonic day 17 (E17). Cresyl-violet staining was applied to observe the histological changes in the cortex, hippocampus and neurons of the resulted pups at P60. EEG recordings were detected, and daily activities were observed. Hot water bath was used to induce seizures, the latency to seizure onset and duration of SE (epileptic status) were compared. Learning and memory abilities were estimated with Y maze at different time points. Results The mean wet brain weights in the BCNU-exposed pups were lower than those of controls on P0 (P<0.01). Cresyl-violet staining revealed disruption of cortical lamination and heterotopic cell clusters within the hippocampus. Daily activities were poor in BCNU-exposed pups. No obvious epilepsia discharges were detected. After being induced seizures, adult rats with cortical dysplasia had shorter latency to seizures(P<0.01). The frequency of attempting learning and memory of rats in model group was increased than that in normal group (P<0.05). Conclusions Intraperitoneal injections of BCNU on embryonic day 17 (E 17) can establish the animal model of diffuse cortical dysplasia, and this model has increased seizure susceptibilities and cognitive functional impairments.%目的 建立SD大鼠广泛型皮质发育障碍的动物模型.方法 在SD大鼠孕17 d腹腔注入BCNU(1,3-二氯乙烯一亚硝基脲,卡莫司汀)制作皮质发育障碍模型;病理检查P60仔鼠皮层和海马结构及神经元变化;行为学观察和脑电图检测;热水浴诱导痫性发作,观察两组大鼠的致痫潜伏期和癫痫持续时间;Y迷宫法测试不同时间点仔鼠学习记忆能力.结果 PO仔鼠脑组织湿重实验组比对照组显著减轻(P<0.01);Nissl染色显示皮质层次紊乱、海马区域异位细胞异常聚集,可出现结节状灰质团块;模型鼠

  10. Breaches of the pial basement membrane and disappearance of the glia limitans during development underlie the cortical lamination defect in the mouse model of muscle-eye-brain disease.

    Science.gov (United States)

    Hu, Huaiyu; Yang, Yuan; Eade, Amber; Xiong, Yufang; Qi, Yue

    2007-05-10

    Neuronal overmigration is the underlying cellular mechanism of cerebral cortical malformations in syndromes of congenital muscular dystrophies caused by defects in O-mannosyl glycosylation. Overmigration involves multiple developmental abnormalities in the brain surface basement membrane, Cajal-Retzius cells, and radial glia. We tested the hypothesis that breaches in basement membrane and the underlying glia limitans are the key initial events of the cellular pathomechanisms by carrying out a detailed developmental study with a mouse model of muscle-eye-brain disease, mice deficient in O-mannose beta1,2-N-acetylglucosaminyltransferase 1 (POMGnT1). The pial basement membrane was normal in the knockout mouse at E11.5. It was breached during rapid cerebral cortical expansion at E13.5. Radial glial endfeet, which comprise glia limitans, grew out of the neural boundary. Neurons moved out of the neural boundary through these breaches. The overgrown radial glia and emigrated neurons disrupted the overlying pia mater. The overmigrated neurons did not participate in cortical plate (CP) development; rather they formed a diffuse cell zone (DCZ) outside the original cortical boundary. Together, the DCZ and the CP formed the knockout cerebral cortex, with disappearance of the basement membrane and the glia limitans. These results suggest that disappearance of the basement membrane and the glia limitans at the cerebral cortical surface during development underlies cortical lamination defects in congenital muscular dystrophies and a cellular mechanism of cortical malformation distinct from that of the reeler mouse, double cortex syndrome, and periventricular heterotopia.

  11. Monitoring Stroke Progression: In Vivo Imaging of Cortical Perfusion, Blood—Brain Barrier Permeability and Cellular Damage in the Rat Photothrombosis Model

    National Research Council Canada - National Science Library

    Schoknecht, Karl; Prager, Ofer; Vazana, Udi; Kamintsky, Lyn; Harhausen, Denise; Zille, Marietta; Figge, Lena; Chassidim, Yoash; Schellenberger, Eyk; Kovács, Richard; Heinemann, Uwe; Friedman, Alon

    2014-01-01

    .... Here we describe a longitudinal in vivo fluorescence imaging approach for the evaluation of cortical perfusion, BBB dysfunction, free radical formation and cellular injury using the photothrombosis...

  12. Cortical Lewy Body Dementia

    Directory of Open Access Journals (Sweden)

    W. R. G. Gibb

    1990-01-01

    Full Text Available In cortical Lewy body dementia the distribution of Lewy bodies in the nervous system follows that of Parkinson's disease, except for their greater profusion in the cerebral cortex. The cortical tangles and plaques of Alzheimer pathology are often present, the likely explanation being that Alzheimer pathology provokes dementia in many patients. Pure cortical Lewy body dementia without Alzheimer pathology is uncommon. The age of onset reflects that of Parkinson's disease, and clinical features, though not diagnostic, include aphasias, apraxias, agnosias, paranoid delusions and visual hallucinations. Parkinsonism may present before or after the dementia, and survival duration is approximately half that seen in Parkinson's disease without dementia.

  13. Mean field methods for cortical network dynamics

    DEFF Research Database (Denmark)

    Hertz, J.; Lerchner, Alexander; Ahmadi, M.

    2004-01-01

    We review the use of mean field theory for describing the dynamics of dense, randomly connected cortical circuits. For a simple network of excitatory and inhibitory leaky integrate- and-fire neurons, we can show how the firing irregularity, as measured by the Fano factor, increases with the stren...... cortex. Finally, an extension of the model to describe an orientation hypercolumn provides understanding of how cortical interactions sharpen orientation tuning, in a way that is consistent with observed firing statistics...

  14. Prenatal ethanol exposure disrupts intraneocortical circuitry, cortical gene expression, and behavior in a mouse model of FASD.

    Science.gov (United States)

    El Shawa, Hani; Abbott, Charles W; Huffman, Kelly J

    2013-11-27

    In utero ethanol exposure from a mother's consumption of alcoholic beverages impacts brain and cognitive development, creating a range of deficits in the child (Levitt, 1998; Lebel et al., 2012). Children diagnosed with fetal alcohol spectrum disorders (FASD) are often born with facial dysmorphology and may exhibit cognitive, behavioral, and motor deficits from ethanol-related neurobiological damage in early development. Prenatal ethanol exposure (PrEE) is the number one cause of preventable mental and intellectual dysfunction globally, therefore the neurobiological underpinnings warrant systematic research. We document novel anatomical and gene expression abnormalities in the neocortex of newborn mice exposed to ethanol in utero. This is the first study to demonstrate large-scale changes in intraneocortical connections and disruption of normal patterns of neocortical gene expression in any prenatal ethanol exposure animal model. Neuroanatomical defects and abnormal neocortical RZRβ, Id2, and Cadherin8 expression patterns are observed in PrEE newborns, and abnormal behavior is present in 20-d-old PrEE mice. The vast network of neocortical connections is responsible for high-level sensory and motor processing as well as complex cognitive thought and behavior in humans. Disruptions to this network from PrEE-related changes in gene expression may underlie some of the cognitive-behavioral phenotypes observed in children with FASD.

  15. Continuous measurement of cerebral cortical blood flow by laser-Doppler flowmetry in a rat stroke model

    Energy Technology Data Exchange (ETDEWEB)

    Dirnagl, U.; Kaplan, B.; Jacewicz, M.; Pulsinelli, W. (Cornell Univ. Medical College, New York, NY (USA))

    1989-10-01

    Laser-Doppler flowmetry (LDF), a new method allowing instantaneous, continuous, and noninvasive measurements of microcirculatory blood flow in a small tissue sample, was evaluated for its accuracy in monitoring regional cerebral blood flow (rCBF) in the cortical microcirculation after focal cerebral ischemia. Wistar and spontaneously hypertensive rats (SHR, n = 19) were subjected to permanent occlusion of the middle cerebral and common carotid arteries. Absolute rCBF in a tissue sample of the ischemic hemisphere was measured autoradiographically with ({sup 14}C)iodoantipyrine as a tracer and compared to rCBF measured by LDF. Additionally, the percent change in rCBF between baseline and ischemic values was compared for both methods. Absolute rCBF values recorded with LDF correlated poorly (r = 0.54) with ({sup 14}C)iodoantipyrine measurements. In contrast LDF readings expressed as a percentage of ischemic vs. preocclusion readings (relative LDF readings) correlated very well (r = 0.91) with the percent change in (14C)iodoantipyrine measurements. We conclude that LDF does not provide accurate measurements of absolute rCBF values but this method allows accurate measurements of changes in rCBF due to induction of focal cerebral ischemia.

  16. Continuous measurement of cerebral cortical blood flow by laser-Doppler flowmetry in a rat stroke model.

    Science.gov (United States)

    Dirnagl, U; Kaplan, B; Jacewicz, M; Pulsinelli, W

    1989-10-01

    Laser-Doppler flowmetry (LDF), a new method allowing instantaneous, continuous, and noninvasive measurements of microcirculatory blood flow in a small tissue sample, was evaluated for its accuracy in monitoring regional cerebral blood flow (rCBF) in the cortical microcirculation after focal cerebral ischemia. Wistar and spontaneously hypertensive rats (SHR, n = 19) were subjected to permanent occlusion of the middle cerebral and common carotid arteries. Absolute rCBF in a tissue sample of the ischemic hemisphere was measured autoradiographically with [14C]iodoantipyrine as a tracer and compared to rCBF measured by LDF. Additionally, the percent change in rCBF between baseline and ischemic values was compared for both methods. Absolute rCBF values recorded with LDF correlated poorly (r = 0.54) with [14C]iodoantipyrine measurements. In contrast LDF readings expressed as a percentage of ischemic vs. preocclusion readings (relative LDF readings) correlated very well (r = 0.91) with the percent change in [14C]iodoantipyrine measurements. We conclude that LDF does not provide accurate measurements of absolute rCBF values but this method allows accurate measurements of changes in rCBF due to induction of focal cerebral ischemia.

  17. Multi-Resolution Modeling of Large Scale Scientific Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Baldwin, C; Abdulla, G; Critchlow, T

    2002-02-25

    Data produced by large scale scientific simulations, experiments, and observations can easily reach tera-bytes in size. The ability to examine data-sets of this magnitude, even in moderate detail, is problematic at best. Generally this scientific data consists of multivariate field quantities with complex inter-variable correlations and spatial-temporal structure. To provide scientists and engineers with the ability to explore and analyze such data sets we are using a twofold approach. First, we model the data with the objective of creating a compressed yet manageable representation. Second, with that compressed representation, we provide the user with the ability to query the resulting approximation to obtain approximate yet sufficient answers; a process called adhoc querying. This paper is concerned with a wavelet modeling technique that seeks to capture the important physical characteristics of the target scientific data. Our approach is driven by the compression, which is necessary for viable throughput, along with the end user requirements from the discovery process. Our work contrasts existing research which applies wavelets to range querying, change detection, and clustering problems by working directly with a decomposition of the data. The difference in this procedures is due primarily to the nature of the data and the requirements of the scientists and engineers. Our approach directly uses the wavelet coefficients of the data to compress as well as query. We will provide some background on the problem, describe how the wavelet decomposition is used to facilitate data compression and how queries are posed on the resulting compressed model. Results of this process will be shown for several problems of interest and we will end with some observations and conclusions about this research.

  18. Multi-Resolution Modeling of Large Scale Scientific Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Baldwin, C; Abdulla, G; Critchlow, T

    2002-02-25

    Data produced by large scale scientific simulations, experiments, and observations can easily reach tera-bytes in size. The ability to examine data-sets of this magnitude, even in moderate detail, is problematic at best. Generally this scientific data consists of multivariate field quantities with complex inter-variable correlations and spatial-temporal structure. To provide scientists and engineers with the ability to explore and analyze such data sets we are using a twofold approach. First, we model the data with the objective of creating a compressed yet manageable representation. Second, with that compressed representation, we provide the user with the ability to query the resulting approximation to obtain approximate yet sufficient answers; a process called adhoc querying. This paper is concerned with a wavelet modeling technique that seeks to capture the important physical characteristics of the target scientific data. Our approach is driven by the compression, which is necessary for viable throughput, along with the end user requirements from the discovery process. Our work contrasts existing research which applies wavelets to range querying, change detection, and clustering problems by working directly with a decomposition of the data. The difference in this procedures is due primarily to the nature of the data and the requirements of the scientists and engineers. Our approach directly uses the wavelet coefficients of the data to compress as well as query. We will provide some background on the problem, describe how the wavelet decomposition is used to facilitate data compression and how queries are posed on the resulting compressed model. Results of this process will be shown for several problems of interest and we will end with some observations and conclusions about this research.

  19. Global segregation of cortical activity and metastable dynamics.

    Science.gov (United States)

    Stratton, Peter; Wiles, Janet

    2015-01-01

    Cortical activity exhibits persistent metastable dynamics. Assemblies of neurons transiently couple (integrate) and decouple (segregate) at multiple spatiotemporal scales; both integration and segregation are required to support metastability. Integration of distant brain regions can be achieved through long range excitatory projections, but the mechanism supporting long range segregation is not clear. We argue that the thalamocortical matrix connections, which project diffusely from the thalamus to the cortex and have long been thought to support cortical gain control, play an equally-important role in cortical segregation. We present a computational model of the diffuse thalamocortical loop, called the competitive cross-coupling (CXC) spiking network. Simulations of the model show how different levels of tonic input from the brainstem to the thalamus could control dynamical complexity in the cortex, directing transitions between sleep, wakefulness and high attention or vigilance. The model also explains how mutually-exclusive activity could arise across large portions of the cortex, such as between the default-mode and task-positive networks. It is robust to noise but does not require noise to autonomously generate metastability. We conclude that the long range segregation observed in brain activity and required for global metastable dynamics could be provided by the thalamocortical matrix, and is strongly modulated by brainstem input to the thalamus.

  20. Global segregation of cortical activity and metastable dynamics

    Directory of Open Access Journals (Sweden)

    Peter eStratton

    2015-08-01

    Full Text Available Cortical activity exhibits persistent metastable dynamics. Assemblies of neurons transiently couple (integrate and decouple (segregate at multiple spatiotemporal scales; both integration and segregation are required to support metastability. Integration of distant brain regions can be achieved through long range excitatory projections, but the mechanism supporting long range segregation is not clear. We argue that the thalamocortical matrix connections, which project diffusely from the thalamus to the cortex and have long been thought to support cortical gain control, play an equally-important role in cortical segregation. We present a computational model of the diffuse thalamocortical loop, called the competitive cross-coupling (CXC spiking network. Simulations of the model show how different levels of tonic input from the brainstem to the thalamus could control dynamical complexity in the cortex, directing transitions between sleep, wakefulness and high attention or vigilance. The model also explains how mutually-exclusive activity could arise across large portions of the cortex, such as between the default-mode and task-positive networks. It is robust to noise but does not require noise to autonomously generate metastability. We conclude that the long range segregation observed in brain activity and required for global metastable dynamics could be provided by the thalamocortical matrix, and is strongly modulated by brainstem input to the thalamus.

  1. Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions

    Science.gov (United States)

    Wagatsuma, Nobuhiko; Sakai, Ko

    2017-01-01

    Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional

  2. Inhibition of the striatal specific phosphodiesterase PDE10A ameliorates striatal and cortical pathology in R6/2 mouse model of Huntington's disease.

    Directory of Open Access Journals (Sweden)

    Carmela Giampà

    Full Text Available BACKGROUND: Huntington's disease is a devastating neurodegenerative condition for which there is no therapy to slow disease progression. The particular vulnerability of striatal medium spiny neurons to Huntington's pathology is hypothesized to result from transcriptional dysregulation within the cAMP and CREB signaling cascades in these neurons. To test this hypothesis, and a potential therapeutic approach, we investigated whether inhibition of the striatal-specific cyclic nucleotide phosphodiesterase PDE10A would alleviate neurological deficits and brain pathology in a highly utilized model system, the R6/2 mouse. METHODOLOGY/PRINCIPAL FINDINGS: R6/2 mice were treated with the highly selective PDE10A inhibitor TP-10 from 4 weeks of age until euthanasia. TP-10 treatment significantly reduced and delayed the development of the hind paw clasping response during tail suspension, deficits in rotarod performance, and decrease in locomotor activity in an open field. Treatment prolonged time to loss of righting reflex. These effects of PDE10A inhibition on neurological function were reflected in a significant amelioration in brain pathology, including reduction in striatal and cortical cell loss, the formation of striatal neuronal intranuclear inclusions, and the degree of microglial activation that occurs in response to the mutant huntingtin-induced brain damage. Striatal and cortical levels of phosphorylated CREB and BDNF were significantly elevated. CONCLUSIONS/SIGNIFICANCE: Our findings provide experimental support for targeting the cAMP and CREB signaling pathways and more broadly transcriptional dysregulation as a therapeutic approach to Huntington's disease. It is noteworthy that PDE10A inhibition in the R6/2 mice reduces striatal pathology, consistent with the localization of the enzyme in medium spiny neurons, and also cortical pathology and the formation of neuronal nuclear inclusions. These latter findings suggest that striatal pathology may

  3. Focal cortical dysplasia - review.

    Science.gov (United States)

    Kabat, Joanna; Król, Przemysław

    2012-04-01

    Focal cortical dysplasia is a malformation of cortical development, which is the most common cause of medically refractory epilepsy in the pediatric population and the second/third most common etiology of medically intractable seizures in adults.Both genetic and acquired factors are involved in the pathogenesis of cortical dysplasia. Numerous classifications of the complex structural abnormalities of focal cortical dysplasia have been proposed - from Taylor et al. in 1971 to the last modification of Palmini classification made by Blumcke in 2011. In general, three types of cortical dysplasia are recognized.Type I focal cortical dysplasia with mild symptomatic expression and late onset, is more often seen in adults, with changes present in the temporal lobe.Clinical symptoms are more severe in type II of cortical dysplasia usually seen in children. In this type, more extensive changes occur outside the temporal lobe with predilection for the frontal lobes.New type III is one of the above dysplasias with associated another principal lesion as hippocampal sclerosis, tumor, vascular malformation or acquired pathology during early life.Brain MRI imaging shows abnormalities in the majority of type II dysplasias and in only some of type I cortical dysplasias.THE MOST COMMON FINDINGS ON MRI IMAGING INCLUDE: focal cortical thickening or thinning, areas of focal brain atrophy, blurring of the gray-white junction, increased signal on T2- and FLAIR-weighted images in the gray and subcortical white matter often tapering toward the ventricle. On the basis of the MRI findings, it is possible to differentiate between type I and type II cortical dysplasia. A complete resection of the epileptogenic zone is required for seizure-free life. MRI imaging is very helpful to identify those patients who are likely to benefit from surgical treatment in a group of patients with drug-resistant epilepsy.However, in type I cortical dysplasia, MR imaging is often normal, and also in both types

  4. Flexible modeling frameworks to replace small ensembles of hydrological models and move toward large ensembles?

    Science.gov (United States)

    Addor, Nans; Clark, Martyn P.; Mizukami, Naoki

    2017-04-01

    Climate change impacts on hydrological processes are typically assessed using small ensembles of hydrological models. That is, a handful of hydrological models are typically driven by a larger number of climate models. Such a setup has several limitations. Because the number of hydrological models is small, only a small proportion of the model space is sampled, likely leading to an underestimation of the uncertainties in the projections. Further, sampling is arbitrary: although hydrological models should be selected to provide a representative sample of existing models (in terms of complexity and governing hypotheses), they are instead usually selected based on legacy reasons. Furthermore, running several hydrological models currently constitutes a practical challenge because each model must be setup and calibrated individually. Finally, and probably most importantly, the differences between the projected impacts cannot be directly related to differences between hydrological models, because the models are different in almost every possible aspect. We are hence in a situation in which different hydrological models deliver different projections, but for reasons that are mostly unclear, and in which the uncertainty in the projections is probably underestimated. To overcome these limitations, we are experimenting with the flexible modeling framework FUSE (Framework for Understanding Model Errors). FUSE enables to construct conceptual models piece by piece (in a "pick and mix" approach), so it can be used to generate a large number of models that mimic existing models and/or models that differ from other models in single targeted respect (e.g. how baseflow is generated). FUSE hence allows for controlled modeling experiments, and for a more systematic and exhaustive sampling of the model space. Here we explore climate change impacts over the contiguous USA on a 12km grid using two groups of three models: the first group involves the commonly used models VIC, PRMS and HEC

  5. Postpartum cortical blindness.

    Science.gov (United States)

    Faiz, Shakeel Ahmed

    2008-09-01

    A 30-years-old third gravida with previous normal pregnancies and an unremarkable prenatal course had an emergency lower segment caesarean section at a periphery hospital for failure of labour to progress. She developed bilateral cortical blindness immediately after recovery from anesthesia due to cerebral angiopathy shown by CT and MR scan as cortical infarct cerebral angiopathy, which is a rare complication of a normal pregnancy.

  6. Progress and Current Challenges in Modeling Large RNAs.

    Science.gov (United States)

    Somarowthu, Srinivas

    2016-02-27

    Recent breakthroughs in next-generation sequencing technologies have led to the discovery of several classes of non-coding RNAs (ncRNAs). It is now apparent that RNA molecules are not only just carriers of genetic information but also key players in many cellular processes. While there has been a rapid increase in the number of ncRNA sequences deposited in various databases over the past decade, the biological functions of these ncRNAs are largely not well understood. Similar to proteins, RNA molecules carry out a function by forming specific three-dimensional structures. Understanding the function of a particular RNA therefore requires a detailed knowledge of its structure. However, determining experimental structures of RNA is extremely challenging. In fact, RNA-only structures represent just 1% of the total structures deposited in the PDB. Thus, computational methods that predict three-dimensional RNA structures are in high demand. Computational models can provide valuable insights into structure-function relationships in ncRNAs and can aid in the development of functional hypotheses and experimental designs. In recent years, a set of diverse RNA structure prediction tools have become available, which differ in computational time, input data and accuracy. This review discusses the recent progress and challenges in RNA structure prediction methods.

  7. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*

    Science.gov (United States)

    Onorante, Luca; Raftery, Adrian E.

    2015-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859

  8. SEMICONDUCTOR DEVICES MEXTRAM model based SiGe HBT large-signal modeling

    Science.gov (United States)

    Bo, Han; Shoulin, Li; Jiali, Cheng; Qiuyan, Yin; Jianjun, Gao

    2010-10-01

    An improved large-signal equivalent-circuit model for SiGe HBTs based on the MEXTRAM model (level 504.5) is proposed. The proposed model takes into account the soft knee effect. The model keeps the main features of the MEXTRAM model even though some simplifications have been made in the equivalent circuit topology. This model is validated in DC and AC analyses for SiGe HBTs fabricated with 0.35-μm BiCMOS technology, 1 × 8 μm2 emitter area. Good agreement is achieved between the measured and modeled results for DC and S-parameters (from 50 MHz to 20 GHz), which shows that the proposed model is accurate and reliable. The model has been implemented in Verilog-A using the ADS circuit simulator.

  9. Estrogen-dependent effects of 5-hydroxytryptophan on cortical spreading depression in rat: Modelling the serotonin-ovarian hormone interaction in migraine aura.

    Science.gov (United States)

    Chauvel, Virginie; Multon, Sylvie; Schoenen, Jean

    2017-01-01

    Background Cortical spreading depression (CSD) is the likely culprit of the migraine aura. Migraine is sexually dimorphic and thought to be a "low 5-HT" condition. We sought to decipher the interrelation between serotonin, ovarian hormones and cortical excitability in a model of migraine aura. Methods Occipital KCl-induced CSDs were recorded for one hour at parieto-occipital and frontal levels in adult male (n = 16) and female rats (n = 64) one hour after intraperitoneal (i.p.) injection of 5-hydroxytryptophan (5-HTP) or NaCl. Sixty-five oophorectomized females were treated with estradiol- (E2) or cholesterol- (Chol) filled capsules. Two weeks later we recorded CSDs after 5-HTP/NaCl injections before or 20 hours after capsule removal. Results 5-HTP had no effect in males, but decreased CSD frequency in cycling females, significantly so during estrus, at parieto-occipital (-3.5CSD/h, p HTP was significant only in E2-treated rats (-3.4CSD/h, p = 0.006 and -1.8CSD/h, p = 0.029). Neither the estrous cycle phase, nor E2 or 5-HTP treatments significantly modified CSD propagation velocity. Conclusion 5-HTP decreases CSD occurrence in the presence of ovarian hormones, suggesting its potential efficacy in migraine with aura prophylaxis in females. Elevated E2 levels increase CSD susceptibility, while estrogen withdrawal decreases CSD. In a translational perspective, these findings may explain why migraine auras can appear during pregnancy and why menstrual-related migraine attacks are rarely associated with an aura.

  10. A novel underuse model shows that inactivity but not ovariectomy determines the deteriorated material properties and geometry of cortical bone in the tibia of adult rats.

    Science.gov (United States)

    Miyagawa, Kazuaki; Kozai, Yusuke; Ito, Yumi; Furuhama, Takami; Naruse, Kouji; Nonaka, Kiichi; Nagai, Yumiko; Yamato, Hideyuki; Kashima, Isamu; Ohya, Keiichi; Aoki, Kazuhiro; Mikuni-Takagaki, Yuko

    2011-07-01

    Our goal in this study was to determine to what extent the physiologic consequences of ovariectomy (OVX) in bones are exacerbated by a lack of daily activity such as walking. We forced 14-week-old female rats to be inactive for 15 weeks with a unique experimental system that prevents standing and walking while allowing other movements. Tibiae, femora, and 4th lumbar vertebrae were analyzed by peripheral quantitative computed tomography (pQCT), microfocused X-ray computed tomography (micro-CT), histology, histomorphometry, Raman spectroscopy, and the three-point bending test. Contrary to our expectation, the exacerbation was very much limited to the cancellous bone parameters. Parameters of femur and tibia cortical bone were affected by the forced inactivity but not by OVX: (1) cross-sectional moment of inertia was significantly smaller in Sham-Inactive rat bones than that of their walking counterparts; (2) the number of sclerostin-positive osteocytes per unit cross-sectional area was larger in Sham-Inactive rat bones than in Sham-Walking rat bones; and (3) material properties such as ultimate stress of inactive rat tibia was lower than that of their walking counterparts. Of note, the additive effect of inactivity and OVX was seen only in a few parameters, such as the cancellous bone mineral density of the lumbar vertebrae and the structural parameters of cancellous bone in the lumbar vertebrae/tibiae. It is concluded that the lack of daily activity is detrimental to the strength and quality of cortical bone in the femur and tibia of rats, while lack of estrogen is not. Our inactive rat model, with the older rats, will aid the study of postmenopausal osteoporosis, the etiology of which may be both hormonal and mechanical.

  11. Neuroprotective effects of a novel single compound 1-methoxyoctadecan-1-ol isolated from Uncaria sinensis in primary cortical neurons and a photothrombotic ischemia model.

    Directory of Open Access Journals (Sweden)

    Ji Yeon Jang

    Full Text Available We identified a novel neuroprotective compound, 1-methoxyoctadecan-1-ol, from Uncaria sinensis (Oliv. Havil and investigated its effects and mechanisms in primary cortical neurons and in a photothrombotic ischemic model. In primary rat cortical neurons against glutamate-induced neurotoxicity, pretreatment with 1-methoxyoctadecan-1-ol resulted in significantly reduced neuronal death in a dose-dependent manner. In addition, treatment with 1-methoxyoctadecan-1-ol resulted in decreased neuronal apoptotic death, as assessed by nuclear morphological approaches. To clarify the neuroprotective mechanism of 1-methoxyoctadecan-1-ol, we explored the downstream signaling pathways of N-methyl-D-aspartate receptor (NMDAR with calpain activation. Treatment with glutamate leads to early activation of NMDAR, which in turn leads to calpain-mediated cleavage of striatal-enriched protein tyrosine phosphatase (STEP and subsequent activation of p38 mitogen activated protein kinase (MAPK. However, pretreatment with 1-methoxyoctadecan-1-ol resulted in significantly attenuated activation of GluN2B-NMDAR and a decrease in calpain-mediated STEP cleavage, leading to subsequent attenuation of p38 MAPK activation. We confirmed the critical role of p38 MAPK in neuroprotective effects of 1-methoxyoctadecan-1-ol using specific inhibitor SB203580. In the photothrombotic ischemic injury in mice, treatment with 1-methoxyoctadecan-1-ol resulted in significantly reduced infarct volume, edema size, and improved neurological function. 1-methoxyoctadecan-1-ol effectively prevents cerebral ischemic damage through down-regulation of calpain-mediated STEP cleavage and activation of p38 MAPK. These results suggest that 1-methoxyoctadecan-1-ol showed neuroprotective effects through down-regulation of calpain-mediated STEP cleavage with activation of GluN2B-NMDAR, and subsequent alleviation of p38 MAPK activation. In addition, 1-methoxyoctadecan-1-ol might be a useful therapeutic agent for

  12. Repeated mild lateral fluid percussion brain injury in the rat causes cumulative long-term behavioral impairments, neuroinflammation, and cortical loss in an animal model of repeated concussion.

    Science.gov (United States)

    Shultz, Sandy R; Bao, Feng; Omana, Vanessa; Chiu, Charlotte; Brown, Arthur; Cain, Donald Peter

    2012-01-20

    There is growing evidence that repeated brain concussion can result in cumulative and long-term behavioral symptoms, neuropathological changes, and neurodegeneration. Little is known about the factors and mechanisms that contribute to these effects. The current study addresses the need to investigate and better understand the effects of repeated concussion through the development of an animal model. Male Long-Evans rats received 1, 3, or 5 mild lateral fluid percussion injuries or sham injuries spaced 5 days apart. After the final injury, rats received either a short (24 h) or long (8 weeks) post-injury recovery period, followed by a detailed behavioral analysis consisting of tests for rodent anxiety-like behavior, cognition, social behavior, sensorimotor function, and depression-like behavior. Brains were examined immunohistochemically to assess neuroinflammation and cortical damage. Rats given 1, 3, or 5 mild percussion injuries displayed significant short-term cognitive impairments. Rats given repeated mild percussion injuries displayed significantly worse short- and long-term cognitive impairments. Rats given 5 mild percussion injuries also displayed increased anxiety- and depression-like behaviors. Neuropathological analysis revealed short-term neuroinflammation in 3-injury rats, and both short- and long-term neuroinflammation in 5-injury rats. There was also evidence that repeated injuries induced short- and long-term cortical damage. These cumulative and long-term changes are consistent with findings in human patients suffering repeated brain concussion, provide support for the use of repeated mild lateral fluid percussion injuries to study repeated concussion in the rat, and suggest that neuroinflammation may be important for understanding the cumulative and chronic effects of repeated concussion.

  13. Multiobjective adaptive surrogate modeling-based optimization for parameter estimation of large, complex geophysical models

    Science.gov (United States)

    Gong, Wei; Duan, Qingyun; Li, Jianduo; Wang, Chen; Di, Zhenhua; Ye, Aizhong; Miao, Chiyuan; Dai, Yongjiu

    2016-03-01

    Parameter specification is an important source of uncertainty in large, complex geophysical models. These models generally have multiple model outputs that require multiobjective optimization algorithms. Although such algorithms have long been available, they usually require a large number of model runs and are therefore computationally expensive for large, complex dynamic models. In this paper, a multiobjective adaptive surrogate modeling-based optimization (MO-ASMO) algorithm is introduced that aims to reduce computational cost while maintaining optimization effectiveness. Geophysical dynamic models usually have a prior parameterization scheme derived from the physical processes involved, and our goal is to improve all of the objectives by parameter calibration. In this study, we developed a method for directing the search processes toward the region that can improve all of the objectives simultaneously. We tested the MO-ASMO algorithm against NSGA-II and SUMO with 13 test functions and a land surface model - the Common Land Model (CoLM). The results demonstrated the effectiveness and efficiency of MO-ASMO.

  14. Cortical Neural Computation by Discrete Results Hypothesis

    Science.gov (United States)

    Castejon, Carlos; Nuñez, Angel

    2016-01-01

    One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called “Discrete Results” (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of “Discrete Results” is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel “Discrete Results” concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast

  15. Effects of acupoint versus non-acupoint electroacupuncture on cerebral cortical neuronal Bcl-2,Bax and caspase-3 expression in a rat model of focal cerebral ischemia

    Institute of Scientific and Technical Information of China (English)

    Jun Wang; Junming Fan; Yongshu Dong; Xia Huang; Hongxia Zhang

    2008-01-01

    BACKGROUND: Several studies have demonstrated that electroacupuncture by acupoint selection can inhibit cerebral cortical neuronal apoptosis following cerebral ischemia/reperfusion.OBJECTIVE: To validate the effects of electroacupuncture by acupoint selection on the expression level of cortical neuronal anti-apoptotic Bcl-2 protein and the apoptotic executive protein, caspase-3, in rat models of focal cerebral ischemia/reperfusion.DESIGN, TIME AND SETTING: This randomized grouping, neural cell and molecular biology animal experiment was performed at the Laboratory of Pharmacology of Traditional Chinese Medicine and the Laboratory Animal Center of Henan Institute of Traditional Chinese Medicine between November 2006 and May 2007.MATERIALS: Atotal of 40 healthy male adult Sprague-Dawley rats were randomly and evenly divided into four groups: sham-operated, model, electroacupuncture and non-acupoint control. G6895 electro-acupuncture instruments were purchased from Shanghai Huayi Instrument Factory, China. Caspase-3, Bcl-2 and Bax kits were provided by Wuhan Boster Bioengineering Co., Ltd., China.METHODS: Middle cerebral artery occlusion was induced in the model, electroacupuncture and non-acupoint groups. In the electroacupuncture group, the acupoints Jianyu (LI15), Waiguan (SJ5), Biguan (ST31), and Zusanli (ST36) were given electroacupuncture. In the non-acupoint control group, at each time point (immediately after ischemia and after reperfusion, or 2 hours after reperfusion), electroacupuncture was performed at the midpoints of Tianquan (PC2)-Quze (PC 3) line, Quze (PC 3)-Ximen (PC4) line, Zuwuli (LRlO)-Yinbao (LRg) line, and Xiguan (LR7)-Zhongdu (LR6) line. Electroacupuncture parameters were set with a continuous wave with a frequency of 10 Hz, wave width 0.6 ms, voltage 1.5-3.0 V, and a duration of 10 minutes. The sham-operated and model groups received only animal fixation without electroacupuncture procedure.MAIN OUTCOME MEASURES: Five rats were selected from

  16. IBAR: Interacting boson model calculations for large system sizes

    Science.gov (United States)

    Casperson, R. J.

    2012-04-01

    Scaling the system size of the interacting boson model-1 (IBM-1) into the realm of hundreds of bosons has many interesting applications in the field of nuclear structure, most notably quantum phase transitions in nuclei. We introduce IBAR, a new software package for calculating the eigenvalues and eigenvectors of the IBM-1 Hamiltonian, for large numbers of bosons. Energies and wavefunctions of the nuclear states, as well as transition strengths between them, are calculated using these values. Numerical errors in the recursive calculation of reduced matrix elements of the d-boson creation operator are reduced by using an arbitrary precision mathematical library. This software has been tested for up to 1000 bosons using comparisons to analytic expressions. Comparisons have also been made to the code PHINT for smaller system sizes. Catalogue identifier: AELI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELI_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 3 No. of lines in distributed program, including test data, etc.: 28 734 No. of bytes in distributed program, including test data, etc.: 4 104 467 Distribution format: tar.gz Programming language: C++ Computer: Any computer system with a C++ compiler Operating system: Tested under Linux RAM: 150 MB for 1000 boson calculations with angular momenta of up to L=4 Classification: 17.18, 17.20 External routines: ARPACK (http://www.caam.rice.edu/software/ARPACK/) Nature of problem: Construction and diagonalization of large Hamiltonian matrices, using reduced matrix elements of the d-boson creation operator. Solution method: Reduced matrix elements of the d-boson creation operator have been stored in data files at machine precision, after being recursively calculated with higher than machine precision. The Hamiltonian matrix is calculated and diagonalized, and the requested transition strengths are calculated

  17. Quantification of alterations in cortical bone geometry using Site Specificity Software in mouse models of aging and the responses to ovariectomy and altered loading

    Directory of Open Access Journals (Sweden)

    Gabriel L Galea

    2015-04-01

    Full Text Available Investigations into the effect of (remodelling stimuli on cortical bone in rodents normally rely on analysis of changes in bone mass and architecture at a narrow cross-sectional site. However, it is well established that the effects of axial loading produce site-specific changes throughout bones’ structure. Non-mechanical influences (e.g. hormones can be additional to or oppose locally-controlled adaptive responses and may have more generalized effects. Tools currently available to study site-specific cortical bone adaptation are limited. Here we applied novel Site-Specificity software to measure bone mass and architecture at each 1% site along the length of the mouse tibia from standard micro-computed tomography (μCT images. Resulting measures are directly comparable to those obtained through μCT analysis (R2 > 0.96. Site-Specificity Analysis was used to compare a number of parameters in tibiae from young adult (19-week-old versus aged (19-month-old mice; ovariectomized and entire mice; limbs subjected to short periods of axial loading or disuse induced by sciatic neurectomy. Age was associated with uniformly reduced cortical thickness and site-specific decreases in cortical area most apparent in the proximal tibia. Mechanical loading site-specifically increased cortical area and thickness in the proximal tibia. Disuse uniformly decreased cortical thickness and decreased cortical area in the proximal tibia. Ovariectomy uniformly reduced cortical area without altering cortical thickness. Differences in polar moment of inertia between experimental groups were only observed in the proximal tibia. Ageing and ovariectomy also altered eccentricity in the distal tibia. In summary, Site-Specificity Analysis provides a valuable tool for measuring changes in cortical bone mass and architecture along the entire length of a bone. Changes in the (remodelling response determined at a single site may not reflect the response at different locations within

  18. Heterotopic neurogenesis in a rat with cortical heterotopia.

    Science.gov (United States)

    Lee, K S; Collins, J L; Anzivino, M J; Frankel, E A; Schottler, F

    1998-11-15

    Early cellular development was studied in the neocortex of the tish rat. This neurological mutant is seizure-prone and displays cortical heterotopia similar to those observed in certain epileptic patients. The present study demonstrates that a single cortical preplate is formed in a typical superficial position of the developing tish neocortex. In contrast, two cortical plates are formed: one in a normotopic position and a second in a heterotopic position in the intermediate zone. As the normotopic cortical plate is formed, it characteristically separates the subplate cells from the superficial Cajal-Retzius cells. In contrast, the heterotopic cortical plate is not intercalated between the preplate cells because of its deeper position in the developing cortex. Cellular proliferation occurs in two zones of the developing tish cortex. One proliferative zone is located in a typical position in the ventricular/subventricular zone. A second proliferative zone is located in a heterotopic position in the superficial intermediate zone, i.e., between the two cortical plates. This misplaced proliferative zone may contribute cells to both the normotopic and heterotopic cortical plates. Taken together, these findings indicate that misplaced cortical plate cells, but not preplate cells, comprise the heterotopia of the tish cortex. Heterotopic neurogenesis is an early developmental event that is initiated before the migration of most cortical plate cells. It is concluded that misplaced cellular proliferation, in addition to disturbed neuronal migration, can play a key role in the formation of large cortical heterotopia.

  19. Reduction of large-scale numerical ground water flow models

    NARCIS (Netherlands)

    Vermeulen, P.T.M.; Heemink, A.W.; Testroet, C.B.M.

    2002-01-01

    Numerical models are often used for simulating ground water flow. Written in state space form, the dimension of these models is of the order of the number of model cells and can be very high (> million). As a result, these models are computationally very demanding, especially if many different scena

  20. Parallel runs of a large air pollution model on a grid of Sun computers

    DEFF Research Database (Denmark)

    Alexandrov, V.N.; Owczarz, W.; Thomsen, Per Grove

    2004-01-01

    Large -scale air pollution models can successfully be used in different environmental studies. These models are described mathematically by systems of partial differential equations. Splitting procedures followed by discretization of the spatial derivatives leads to several large systems of ordin...

  1. Validating the Runoff from the PRECIS Model Using a Large-Scale Routing Model

    Institute of Scientific and Technical Information of China (English)

    CAO Lijuan; DONG Wenjie; XU Yinlong; ZHANG Yong; Michael SPARROW

    2007-01-01

    The streamflow over the Yellow River basin is simulated using the PRECIS (Providing REgional Climates for Impacts Studies) regional climate model driven by 15-year (1979-1993) ECMWF reanalysis data as the initial and lateral boundary conditions and an off-line large-scale routing model (LRM). The LRM uses physical catchment and river channel information and allows streamflow to be predicted for large continental rivers with a 1°× 1° spatial resolution. The results show that the PRECIS model can reproduce the general southeast to northwest gradient distribution of the precipitation over the Yellow River basin. The PRECISLRM model combination has the capability to simulate the seasonal and annual streamflow over the Yellow River basin. The simulated streamflow is generally coincident with the naturalized streamflow both in timing and in magnitude.

  2. The effects of glucocorticoid on microarchitecture, collagen, mineral and mechanical properties of sheep femur cortical bone

    DEFF Research Database (Denmark)

    Ding, Ming; Danielsen, Carl C; Overgaard, Søren

    2010-01-01

    The effects of glucocorticoid on microarchitecture, collagen, mineral and mechanical properties of sheep femur cortical bone – Validation of large animal model for tissue engineering and biomaterial research Ming Ding,1* Carl Christian Danielsen,2 Søren Overgaard1 1Orthopaedic Research Laboratory...... treatment. Group 3 was left untreated and served as the controls. All sheep received restricted diet with low calcium and phosphorus. At sacrifice, cortical bone samples from the femur midshaft of sheep were harvested, micro-CT scanned and tested in 3 point bending and in tensile. Bone collagen and mineral...... mechanical properties in the glucocorticoid-2. In conclusion, 7 months glucocorticoid treatment with malnutrition had significant impact on cortical microarchitecture of sheep femur midshaft. These changes occurred particularly 3 months after the glucocorticoid cessation suggesting a delayed effect...

  3. CLADA: cortical longitudinal atrophy detection algorithm.

    Science.gov (United States)

    Nakamura, Kunio; Fox, Robert; Fisher, Elizabeth

    2011-01-01

    Measurement of changes in brain cortical thickness is useful for the assessment of regional gray matter atrophy in neurodegenerative conditions. A new longitudinal method, called CLADA (cortical longitudinal atrophy detection algorithm), has been developed for the measurement of changes in cortical thickness in magnetic resonance images (MRI) acquired over time. CLADA creates a subject-specific cortical model which is longitudinally deformed to match images from individual time points. The algorithm was designed to work reliably for lower resolution images, such as the MRIs with 1×1×5 mm(3) voxels previously acquired for many clinical trials in multiple sclerosis (MS). CLADA was evaluated to determine reproducibility, accuracy, and sensitivity. Scan-rescan variability was 0.45% for images with 1mm(3) isotropic voxels and 0.77% for images with 1×1×5 mm(3) voxels. The mean absolute accuracy error was 0.43 mm, as determined by comparison of CLADA measurements to cortical thickness measured directly in post-mortem tissue. CLADA's sensitivity for correctly detecting at least 0.1mm change was 86% in a simulation study. A comparison to FreeSurfer showed good agreement (Pearson correlation=0.73 for global mean thickness). CLADA was also applied to MRIs acquired over 18 months in secondary progressive MS patients who were imaged at two different resolutions. Cortical thinning was detected in this group in both the lower and higher resolution images. CLADA detected a higher rate of cortical thinning in MS patients compared to healthy controls over 2 years. These results show that CLADA can be used for reliable measurement of cortical atrophy in longitudinal studies, even in lower resolution images.

  4. Advances and visions in large-scale hydrological modelling: findings from the 11th workshop on large-scale hydrological modelling

    NARCIS (Netherlands)

    Döll, P.; Berkhoff, K.; Bormann, H.; Fohrer, N.; Gerten, D.; Hagemann, S.; Krol, Martinus S.

    2008-01-01

    Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area.

  5. Computational Study of the Effect of Cortical Porosity on Ultrasound Wave Propagation in Healthy and Osteoporotic Long Bones

    Directory of Open Access Journals (Sweden)

    Vassiliki T. Potsika

    2016-03-01

    Full Text Available Computational studies on the evaluation of bone status in cases of pathologies have gained significant interest in recent years. This work presents a parametric and systematic numerical study on ultrasound propagation in cortical bone models to investigate the effect of changes in cortical porosity and the occurrence of large basic multicellular units, simply called non-refilled resorption lacunae (RL, on the velocity of the first arriving signal (FAS. Two-dimensional geometries of cortical bone are established for various microstructural models mimicking normal and pathological tissue states. Emphasis is given on the detection of RL formation which may provoke the thinning of the cortical cortex and the increase of porosity at a later stage of the disease. The central excitation frequencies 0.5 and 1 MHz are examined. The proposed configuration consists of one point source and multiple successive receivers in order to calculate the FAS velocity in small propagation paths (local velocity and derive a variation profile along the cortical surface. It was shown that: (a the local FAS velocity can capture porosity changes including the occurrence of RL with different number, size and depth of formation; and (b the excitation frequency 0.5 MHz is more sensitive for the assessment of cortical microstructure.

  6. Large animal models of rare genetic disorders: sheep as phenotypically relevant models of human genetic disease.

    Science.gov (United States)

    Pinnapureddy, Ashish R; Stayner, Cherie; McEwan, John; Baddeley, Olivia; Forman, John; Eccles, Michael R

    2015-09-02

    Animals that accurately model human disease are invaluable in medical research, allowing a critical understanding of disease mechanisms, and the opportunity to evaluate the effect of therapeutic compounds in pre-clinical studies. Many types of animal models are used world-wide, with the most common being small laboratory animals, such as mice. However, rodents often do not faithfully replicate human disease, despite their predominant use in research. This discordancy is due in part to physiological differences, such as body size and longevity. In contrast, large animal models, including sheep, provide an alternative to mice for biomedical research due to their greater physiological parallels with humans. Completion of the full genome sequences of many species, and the advent of Next Generation Sequencing (NGS) technologies, means it is now feasible to screen large populations of domesticated animals for genetic variants that resemble human genetic diseases, and generate models that more accurately model rare human pathologies. In this review, we discuss the notion of using sheep as large animal models, and their advantages in modelling human genetic disease. We exemplify several existing naturally occurring ovine variants in genes that are orthologous to human disease genes, such as the Cln6 sheep model for Batten disease. These, and other sheep models, have contributed significantly to our understanding of the relevant human disease process, in addition to providing opportunities to trial new therapies in animals with similar body and organ size to humans. Therefore sheep are a significant species with respect to the modelling of rare genetic human disease, which we summarize in this review.

  7. Modeling a Dry Etch Process for Large-Area Devices

    Energy Technology Data Exchange (ETDEWEB)

    Buss, R.J.; Hebner, G.A.; Ruby, D.S.; Yang, P.

    1999-07-28

    There has been considerable interest in developing dry processes which can effectively replace wet processing in the manufacture of large area photovoltaic devices. Environmental and health issues are a driver for this activity because wet processes generally increase worker exposure to toxic and hazardous chemicals and generate large volumes of liquid hazardous waste. Our work has been directed toward improving the performance of screen-printed solar cells while using plasma processing to reduce hazardous chemical usage.

  8. Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

    NARCIS (Netherlands)

    Loon, van A.F.; Huijgevoort, van M.H.J.; Lanen, van H.A.J.

    2012-01-01

    Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological

  9. Ketogenic diet restores aberrant cortical motor maps and excitation-to-inhibition imbalance in the BTBR mouse model of autism spectrum disorder.

    Science.gov (United States)

    Smith, Jacklyn; Rho, Jong M; Teskey, G Campbell

    2016-05-01

    Autism spectrum disorder (ASD) is an increasingly prevalent neurodevelopmental disorder characterized by deficits in sociability and communication, and restricted and/or repetitive motor behaviors. Amongst the diverse hypotheses regarding the pathophysiology of ASD, one possibility is that there is increased neuronal excitation, leading to alterations in sensory processing, functional integration and behavior. Meanwhile, the high-fat, low-carbohydrate ketogenic diet (KD), traditionally used in the treatment of medically intractable epilepsy, has already been shown to reduce autistic behaviors in both humans and in rodent models of ASD. While the mechanisms underlying these effects remain unclear, we hypothesized that this dietary approach might shift the balance of excitation and inhibition towards more normal levels of inhibition. Using high-resolution intracortical microstimulation, we investigated basal sensorimotor excitation/inhibition in the BTBR T+Itpr(tf)/J (BTBR) mouse model of ASD and tested whether the KD restores the balance of excitation/inhibition. We found that BTBR mice had lower movement thresholds and larger motor maps indicative of higher excitation/inhibition compared to C57BL/6J (B6) controls, and that the KD reversed both these abnormalities. Collectively, our results afford a greater understanding of cortical excitation/inhibition balance in ASD and may help expedite the development of therapeutic approaches aimed at improving functional outcomes in this disorder.

  10. Glutamate-bound NMDARs arising from in vivo-like network activity extend spatio-temporal integration in a L5 cortical pyramidal cell model.

    Directory of Open Access Journals (Sweden)

    Matteo Farinella

    2014-04-01

    Full Text Available In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such 'background' synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5 pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a 'balanced' background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales.

  11. Long-Run Properties of Large-Scale Macroeconometric Models

    OpenAIRE

    Kenneth F. WALLIS-; John D. WHITLEY

    1987-01-01

    We consider alternative approaches to the evaluation of the long-run properties of dynamic nonlinear macroeconometric models, namely dynamic simulation over an extended database, or the construction and direct solution of the steady-state version of the model. An application to a small model of the UK economy is presented. The model is found to be unstable, but a stable form can be produced by simple alterations to the structure.

  12. A SUSY SO(10) model with large tan$\\beta$

    CERN Document Server

    Lazarides, G

    1994-01-01

    We construct a supersymmetric SO(10) model with the asymptotic relation tan\\beta \\simeq m_t/m_b automatically arising from its structure. The model retains the significant Minimal Supersymmetric Standard Model predictions for sin^2 \\theta_w and \\alpha_s and contains an automatic Z_2 matter parity. Proton decay through d=5 operators is sufficiently suppressed. It is remarkable that no global symmetries need to be imposed on the model.

  13. Large scale modelling of catastrophic floods in Italy

    Science.gov (United States)

    Azemar, Frédéric; Nicótina, Ludovico; Sassi, Maximiliano; Savina, Maurizio; Hilberts, Arno

    2017-04-01

    The RMS European Flood HD model® is a suite of country scale flood catastrophe models covering 13 countries throughout continental Europe and the UK. The models are developed with the goal of supporting risk assessment analyses for the insurance industry. Within this framework RMS is developing a hydrologic and inundation model for Italy. The model aims at reproducing the hydrologic and hydraulic properties across the domain through a modeling chain. A semi-distributed hydrologic model that allows capturing the spatial variability of the runoff formation processes is coupled with a one-dimensional river routing algorithm and a two-dimensional (depth averaged) inundation model. This model setup allows capturing the flood risk from both pluvial (overland flow) and fluvial flooding. Here we describe the calibration and validation methodologies for this modelling suite applied to the Italian river basins. The variability that characterizes the domain (in terms of meteorology, topography and hydrologic regimes) requires a modeling approach able to represent a broad range of meteo-hydrologic regimes. The calibration of the rainfall-runoff and river routing models is performed by means of a genetic algorithm that identifies the set of best performing parameters within the search space over the last 50 years. We first establish the quality of the calibration parameters on the full hydrologic balance and on individual discharge peaks by comparing extreme statistics to observations over the calibration period on several stations. The model is then used to analyze the major floods in the country; we discuss the different meteorological setup leading to the historical events and the physical mechanisms that induced these floods. We can thus assess the performance of RMS' hydrological model in view of the physical mechanisms leading to flood and highlight the main controls on flood risk modelling throughout the country. The model's ability to accurately simulate antecedent

  14. Neurodynamics of somatosensory cortices studied by magnetoencephelography.

    Science.gov (United States)

    Kishida, Kuniharu

    2013-09-01

    From the viewpoint of statistical inverse problems, identification of transfer functions in feedback models is applied for neurodynamics of somatosensory cortices, and brain communication among active regions can be expressed in terms of transfer functions. However, brain activities have been investigated mainly by averaged waveforms in the conventional magnetoencephalography analysis, and thus brain communication among active regions has not yet been identified. It is shown that brain communication among two more than three brain regions is determined, when fluctuations related to concatenate averaged waveforms can be obtained by using a suitable blind source separation method. In blind identification of feedback model, some transfer functions or their impulse responses between output variables of current dipoles corresponding to active regions are identified from reconstructed time series data of fluctuations by the method of inverse problem. Neurodynamics of somatosensory cortices in 5 Hz median nerve stimuli can be shown by cerebral communication among active regions of somatosensory cortices in terms of impulse responses of feedback model.

  15. Lattice Boltzmann modeling of multiphase flows at large density ratio with an improved pseudopotential model

    CERN Document Server

    Li, Q; Li, X J

    2012-01-01

    Owing to its conceptual simplicity and computational efficiency, the pseudopotential multiphase lattice Boltzmann (LB) model has attracted significant attention since its emergence. In this work, we aim to extend the pseudopotential LB model to the simulations of multiphase flows at large density ratio and relatively high Reynolds number. First, based on our recent work [Li et al., Phys. Rev. E. 86, 016709 (2012)], an improved forcing scheme is proposed for the multiple-relaxation-time (MRT) pseudopotential LB model in order to achieve thermodynamic consistency and large density ratio in the model. Next, through investigating the effects of the parameter a in the Carnahan-Starling equation of state, we find that, as compared with a = 1, a = 0.25 is capable of greatly reducing the magnitude of the spurious currents at large density ratio. Furthermore, it is found that a lower liquid viscosity can be gained in the pseudopotential LB model by increasing the kinematic viscosity ratio between the vapor and liquid ...

  16. Broadband cortical desynchronization underlies the human psychedelic state.

    Science.gov (United States)

    Muthukumaraswamy, Suresh D; Carhart-Harris, Robin L; Moran, Rosalyn J; Brookes, Matthew J; Williams, Tim M; Errtizoe, David; Sessa, Ben; Papadopoulos, Andreas; Bolstridge, Mark; Singh, Krish D; Feilding, Amanda; Friston, Karl J; Nutt, David J

    2013-09-18

    Psychedelic drugs produce profound changes in consciousness, but the underlying neurobiological mechanisms for this remain unclear. Spontaneous and induced oscillatory activity was recorded in healthy human participants with magnetoencephalography after intravenous infusion of psilocybin--prodrug of the nonselective serotonin 2A receptor agonist and classic psychedelic psilocin. Psilocybin reduced spontaneous cortical oscillatory power from 1 to 50 Hz in posterior association cortices, and from 8 to 100 Hz in frontal association cortices. Large decreases in oscillatory power were seen in areas of the default-mode network. Independent component analysis was used to identify a number of resting-state networks, and activity in these was similarly decreased after psilocybin. Psilocybin had no effect on low-level visually induced and motor-induced gamma-band oscillations, suggesting that some basic elements of oscillatory brain activity are relatively preserved during the psychedelic experience. Dynamic causal modeling revealed that posterior cingulate cortex desynchronization can be explained by increased excitability of deep-layer pyramidal neurons, which are known to be rich in 5-HT2A receptors. These findings suggest that the subjective effects of psychedelics result from a desynchronization of ongoing oscillatory rhythms in the cortex, likely triggered by 5-HT2A receptor-mediated excitation of deep pyramidal cells.

  17. Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling

    Directory of Open Access Journals (Sweden)

    P. Döll

    2008-10-01

    Full Text Available Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future.

  18. Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

    Energy Technology Data Exchange (ETDEWEB)

    Rossi, R; Gallagher, B; Neville, J; Henderson, K

    2011-11-11

    Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied our model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.

  19. Light dilaton in the large N tricritical O (N ) model

    Science.gov (United States)

    Omid, Hamid; Semenoff, Gordon W.; Wijewardhana, L. C. R.

    2016-12-01

    The leading order of the large N limit of the O (N ) symmetric phi-six theory in three dimensions has a phase which exhibits spontaneous breaking of scale symmetry accompanied by a massless dilaton which is a Goldstone boson. At the next-to-leading order in large N , the phi-six coupling has a beta function of order 1 /N and it is expected that the dilaton acquires a small mass, proportional to the beta function and the condensate. In this article, we show that this "light dilaton" is actually a tachyon. This indicates an instability of the phase of the theory with spontaneously broken approximate scale invariance.

  20. The standard model Higgs search at the large hadron collider

    Indian Academy of Sciences (India)

    Satyaki Bhattacharya; on behalf of the CMS and the ATLAS Collaborations

    2007-11-01

    The experiments at the large hadron collider (LHC) will probe for Higgs boson in the mass range between the lower bound on the Higgs mass set by the experiments at the large electron positron collider (LEP) and the unitarity bound (∼ 1 TeV). Strategies are being developed to look for signatures of Higgs boson and measure its properties. In this paper results from full detector simulation-based studies on Higgs discovery from both ATLAS and CMS experiments at the LHC will be presented. Results of simulation studies on Higgs coupling measurement at LHC will be discussed.

  1. Modelling the spreading of large-scale wildland fires

    CERN Document Server

    Drissi, Mohamed

    2014-01-01

    The objective of the present study is twofold. First, the last developments and validation results of a hybrid model designed to simulate fire patterns in heterogeneous landscapes are presented. The model combines the features of a stochastic small-world network model with those of a deterministic semi-physical model of the interaction between burning and non-burning cells that strongly depends on local conditions of wind, topography, and vegetation. Radiation and convection from the flaming zone, and radiative heat loss to the ambient are considered in the preheating process of unburned cells. Second, the model is applied to an Australian grassland fire experiment as well as to a real fire that took place in Corsica in 2009. Predictions compare favorably to experiments in terms of rate of spread, area and shape of the burn. Finally, the sensitivity of the model outcomes (here the rate of spread) to six input parameters is studied using a two-level full factorial design.

  2. Experimental Investigation of Very Large Model Wind Turbine Arrays

    Science.gov (United States)

    Charmanski, Kyle; Wosnik, Martin

    2013-11-01

    The decrease in energy yield in large wind farms (array losses) and associated revenue losses can be significant. When arrays are sufficiently large they can reach what is known as a fully developed wind turbine array boundary layer, or fully developed wind farm condition. This occurs when the turbulence statistics and the structure of the turbulence, within and above a wind farm, as well as the performance of the turbines remain the same from one row to the next. The study of this condition and how it is affected by parameters such as turbine spacing, power extraction, tip speed ratio, etc. is important for the optimization of large wind farms. An experimental investigation of the fully developed wind farm condition was conducted using a large array of porous disks (upstream) and realistically scaled 3-bladed wind turbines with a diameter of 0.25m. The turbines and porous disks were placed inside a naturally grown turbulent boundary layer in the 6m × 2.5m × 72m test section of the UNH Flow Physics Facility which can achieve test section velocities of up to 14 m/s and Reynolds numbers δ+ = δuτ / ν ~ 20 , 000 . Power, rate of rotation and rotor thrust were measured for select turbines, and hot-wire anemometry was used for flow measurements.

  3. Cortical region-specific engraftment of embryonic stem cell-derived neural progenitor cells restores axonal sprouting to a subcortical target and achieves motor functional recovery in a mouse model of neonatal hypoxic-ischemic brain injury

    Directory of Open Access Journals (Sweden)

    Mizuya eShinoyama

    2013-08-01

    Full Text Available Hypoxic–ischemic encephalopathy (HIE at birth could cause cerebral palsy, mental retardation, and epilepsy, which last throughout the individual’s lifetime. However, few restorative treatments for ischemic tissue are currently available. Cell replacement therapy offers the potential to rescue brain damage caused by HI and to restore motor function. In the present study, we evaluated the ability of embryonic stem cell-derived neural progenitor cells (ES-NPCs to become cortical deep layer neurons, to restore the neural network, and to repair brain damage in an HIE mouse model. ES cells stably expressing the reporter gene GFP are induced to a neural precursor state by stromal cell co-culture. Forty-hours after the induction of HIE, animals were grafted with ES-NPCs targeting the deep layer of the motor cortex in the ischemic brain. Motor function was evaluated 3 weeks after transplantation. Immunohistochemistry and neuroanatomical tracing with GFP were used to analyze neuronal differentiation and axonal sprouting. ES-NPCs could differentiate to cortical neurons with pyramidal morphology and expressed the deep layer-specific marker, Ctip2. The graft showed good survival and an appropriate innervation pattern via axonal sprouting from engrafted cells in the ischemic brain. The motor functions of the transplanted HIE mice also improved significantly compared to the sham-transplanted group. These findings suggest that cortical region specific engraftment of preconditioned cortical precursor cells could support motor functional recovery in the HIE model. It is not clear whether this is a direct effect of the engrafted cells or due to neurotrophic factors produced by these cells. These results suggest that cortical region-specific NPC engraftment is a promising therapeutic approach for brain repair.

  4. Cortical region-specific engraftment of embryonic stem cell-derived neural progenitor cells restores axonal sprouting to a subcortical target and achieves motor functional recovery in a mouse model of neonatal hypoxic-ischemic brain injury.

    Science.gov (United States)

    Shinoyama, Mizuya; Ideguchi, Makoto; Kida, Hiroyuki; Kajiwara, Koji; Kagawa, Yoshiteru; Maeda, Yoshihiko; Nomura, Sadahiro; Suzuki, Michiyasu

    2013-01-01

    Hypoxic-ischemic encephalopathy (HIE) at birth could cause cerebral palsy (CP), mental retardation, and epilepsy, which last throughout the individual's lifetime. However, few restorative treatments for ischemic tissue are currently available. Cell replacement therapy offers the potential to rescue brain damage caused by HI and to restore motor function. In the present study, we evaluated the ability of embryonic stem cell-derived neural progenitor cells (ES-NPCs) to become cortical deep layer neurons, to restore the neural network, and to repair brain damage in an HIE mouse model. ES cells stably expressing the reporter gene GFP are induced to a neural precursor state by stromal cell co-culture. Forty-hours after the induction of HIE, animals were grafted with ES-NPCs targeting the deep layer of the motor cortex in the ischemic brain. Motor function was evaluated 3 weeks after transplantation. Immunohistochemistry and neuroanatomical tracing with GFP were used to analyze neuronal differentiation and axonal sprouting. ES-NPCs could differentiate to cortical neurons with pyramidal morphology and expressed the deep layer-specific marker, Ctip2. The graft showed good survival and an appropriate innervation pattern via axonal sprouting from engrafted cells in the ischemic brain. The motor functions of the transplanted HIE mice also improved significantly compared to the sham-transplanted group. These findings suggest that cortical region specific engraftment of preconditioned cortical precursor cells could support motor functional recovery in the HIE model. It is not clear whether this is a direct effect of the engrafted cells or due to neurotrophic factors produced by these cells. These results suggest that cortical region-specific NPC engraftment is a promising therapeutic approach for brain repair.

  5. Expression of metabotropic glutamate receptor 1a in a rat cortical neuronal model of in vitro mechanical injury and the effects of its competitive antagonist (RS)-1-aminoindan-1, 5-dicarboxylic acid

    Institute of Scientific and Technical Information of China (English)

    Fei Cao; Mantao Chen; Xiujue Zheng; Gu Li; Liang Wen; Xiaofeng Yang

    2011-01-01

    The present study established a rat cortical neuronal model of in vitro mechanical injury. At 30 min-utes after injury, the survival rate of the injured cortical neurons was decreased compared with normal neurons, and was gradually decreased with aggravated degree of injury. Reverse transcrip-tion-polymerase chain reaction results showed that at 1 hour after injury, there was increased ex-pression of metabotropic glutamate receptor 1a in cortical neurons. Immunohistochemical staining results showed that at 30 minutes after injury, the number of metabotropic glutamate receptor 1a-positive cells increased compared with normal neurons. At 12 hours after injury, lactate dehy-drogenase activity in the (RS)-1-aminoindan-1, 5-dicarboxylic acid (AIDA)-treated injury neurons was significantly decreased than that in the pure injury group. At 1 hour after injury, intracellular free Ca2+ concentration was markedly decreased in the AIDA-treated injury neurons than that in the pure injury neurons. These findings suggest that after mechanical injury to cortical neurons, metabotropic glutamate receptor 1a expression increased. The resulting increase in intracellular free Ca2+ con-centration was blocked by AIDA, indicating that AIDA exhibits neuroprotective effects after me-chanical injury.

  6. Comparing large-scale computational approaches to epidemic modeling: Agent-based versus structured metapopulation models

    Directory of Open Access Journals (Sweden)

    Merler Stefano

    2010-06-01

    Full Text Available Abstract Background In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used. Methods We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels. Results The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, R0, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age

  7. Running Large-Scale Air Pollution Models on Parallel Computers

    DEFF Research Database (Denmark)

    Georgiev, K.; Zlatev, Z.

    2000-01-01

    Proceedings of the 23rd NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application, held 28 September - 2 October 1998, in Varna, Bulgaria.......Proceedings of the 23rd NATO/CCMS International Technical Meeting on Air Pollution Modeling and Its Application, held 28 September - 2 October 1998, in Varna, Bulgaria....

  8. A Large Scale, High Resolution Agent-Based Insurgency Model

    Science.gov (United States)

    2013-09-30

    2007). HSCB Models can be employed for simulating mission scenarios, determining optimal strategies for disrupting terrorist networks, or training and...High Resolution Agent-Based Insurgency Model ∑ = ⎜ ⎜ ⎝ ⎛ − −− = desired 1 move,desired, desired,,desired, desired,, N j ij jmoveij moveiD rp prp

  9. Misspecified poisson regression models for large-scale registry data

    DEFF Research Database (Denmark)

    Grøn, Randi; Gerds, Thomas A.; Andersen, Per K.

    2016-01-01

    working models that are then likely misspecified. To support and improve conclusions drawn from such models, we discuss methods for sensitivity analysis, for estimation of average exposure effects using aggregated data, and a semi-parametric bootstrap method to obtain robust standard errors. The methods...

  10. Modelling expected train passenger delays on large scale railway networks

    DEFF Research Database (Denmark)

    Landex, Alex; Nielsen, Otto Anker

    2006-01-01

    Forecasts of regularity for railway systems have traditionally – if at all – been computed for trains, not for passengers. Relatively recently it has become possible to model and evaluate the actual passenger delays by a passenger regularity model for the operation already carried out. First...

  11. Monitoring stroke progression: in vivo imaging of cortical perfusion, blood-brain barrier permeability and cellular damage in the rat photothrombosis model.

    Science.gov (United States)

    Schoknecht, Karl; Prager, Ofer; Vazana, Udi; Kamintsky, Lyn; Harhausen, Denise; Zille, Marietta; Figge, Lena; Chassidim, Yoash; Schellenberger, Eyk; Kovács, Richard; Heinemann, Uwe; Friedman, Alon

    2014-11-01

    Focal cerebral ischemia is among the main causes of death and disability worldwide. The ischemic core often progresses, invading the peri-ischemic brain; however, assessing the propensity of the peri-ischemic brain to undergo secondary damage, understanding the underlying mechanisms, and adjusting treatment accordingly remain clinically unmet challenges. A significant hallmark of the peri-ischemic brain is dysfunction of the blood-brain barrier (BBB), yet the role of disturbed vascular permeability in stroke progression is unclear. Here we describe a longitudinal in vivo fluorescence imaging approach for the evaluation of cortical perfusion, BBB dysfunction, free radical formation and cellular injury using the photothrombosis vascular occlusion model in male Sprague Dawley rats. Blood-brain barrier dysfunction propagated within the peri-ischemic brain in the first hours after photothrombosis and was associated with free radical formation and cellular injury. Inhibiting free radical signaling significantly reduced progressive cellular damage after photothrombosis, with no significant effect on blood flow and BBB permeability. Our approach allows a dynamic follow-up of cellular events and their response to therapeutics in the acutely injured cerebral cortex.

  12. Quetiapine attenuates cognitive impairment and decreases seizure susceptibility possibly through promoting myelin development in a rat model of malformations of cortical development.

    Science.gov (United States)

    Ma, Lei; Yang, Feng; Zhao, Rui; Li, Li; Kang, Xiaogang; Xiao, Lan; Jiang, Wen

    2015-10-05

    Developmental delay, cognitive impairment, and refractory epilepsy are the most frequent consequences found in patients suffering from malformations of cortical development (MCD). However, therapeutic options for these psychiatric and neurological comorbidities are currently limited. The development of white matter undergoes dramatic changes during postnatal brain maturation, thus myelination deficits resulting from MCD contribute to its comorbid diseases. Consequently, drugs specifically targeting white matter are a promising therapeutic option for the treatment of MCD. We have used an in utero irradiation rat model of MCD to investigate the effects of postnatal quetiapine treatment on brain myelination as well as neuropsychological and cognitive performances and seizure susceptibility. Fatally irradiated rats were treated with quetiapine (10mg/kg, i.p.) or saline once daily from postnatal day 0 (P0) to P30. We found that postnatal administration of quetiapine attenuated object recognition memory impairment and improved long-term spatial memory in the irradiated rats. Quetiapine treatment also reduced the susceptibility and severity of pentylenetetrazol-induced seizures. Importantly, quetiapine treatment resulted in an inhibition of irradiation-induced myelin breakdown in the cerebral cortex and corpus callosum. These findings suggest that quetiapine may have beneficial, postnatal effects in the irradiated rats, strongly suggesting that improving MCD-derived white matter pathology is a possible underlying mechanism. Collectively, these results indicate that brain myelination represents an encouraging pharmacological target to improve the prognosis of patients with MCD. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Targeting RPTPσ with lentiviral shRNA promotes neurites outgrowth of cortical neurons and improves functional recovery in a rat spinal cord contusion model.

    Science.gov (United States)

    Zhou, Heng-Xing; Li, Xue-Ying; Li, Fu-Yuan; Liu, Chang; Liang, Zhi-Pin; Liu, Shen; Zhang, Bin; Wang, Tian-Yi; Chu, Tian-Ci; Lu, Lu; Ning, Guang-Zhi; Kong, Xiao-Hong; Feng, Shi-Qing

    2014-10-24

    After spinal cord injury (SCI), the rapidly upregulated chondroitin sulfate proteoglycans (CSPGs), the prominent chemical constituents and main repulsive factors of the glial scar, play an important role in the extremely limited ability to regenerate in adult mammals. Although many methods to overcome the inhibition have been tested, no successful method with clinical feasibility has been devised to date. It was recently discovered that receptor protein tyrosine phosphatase sigma (RPTPσ) is a functional receptor for CSPGs-mediated inhibition. In view of the potential clinical application of RNA interference (RNAi), here we investigated whether silencing RPTPσ via lentivirus-mediated RNA interference can promote axon regeneration and functional recovery after SCI. Neurites of primary rat cerebral cortical neurons with depleted RPTPσ exhibited a significant enhancement in elongation and crossing ability when they encountered CSPGs in vitro. A contusion model of spinal cord injury in Wistar rats (the New York University (NYU) impactor) was used for in vivo experiments. Local injection of lentivirus encoding RPTPσ shRNA at the lesion site promoted axon regeneration and synapse formation, but did not affect the scar formation. Meanwhile, in vivo functional recovery (motor and sensory) was also enhanced after RPTPσ depletion. Therefore, strategies directed at silencing RPTPσ by RNAi may prove to be a beneficial, efficient and valuable approach for the treatment of SCI. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Traffic assignment models in large-scale applications

    DEFF Research Database (Denmark)

    Rasmussen, Thomas Kjær

    on individual behaviour in the model specification, (ii) proposing a method to use disaggregate Revealed Preference (RP) data to estimate utility functions and provide evidence on the value of congestion and the value of reliability, (iii) providing a method to account for individual mis...... of observations of actual behaviour to obtain estimates of the (monetary) value of different travel time components, thereby increasing the behavioural realism of largescale models. vii The generation of choice sets is a vital component in route choice models. This is, however, not a straight-forward task in real...... non-universal choice sets and (ii) flow distribution according to random utility maximisation theory. One model allows distinction between used and unused routes based on the distribution of the random error terms, while the other model allows this distinction by posing restrictions on the costs...

  15. Cortical myoclonus and cerebellar pathology

    NARCIS (Netherlands)

    Tijssen, MAJ; Thom, M; Ellison, DW; Wilkins, P; Barnes, D; Thompson, PD; Brown, P

    2000-01-01

    Objective To study the electrophysiologic and pathologic findings in three patients with cortical myoclonus. In two patients the myoclonic ataxic syndrome was associated with proven celiac disease. Background: The pathologic findings in conditions associated with cortical myoclonus commonly involve

  16. Cortical Abnormalities in ADHD

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2003-12-01

    Full Text Available Grey-matter abnormalities at the cortical surface and regional brain size were mapped by high-resolution MRI and surface-based, computational image analytical techniques in a group of 27 children and adolescents with attention deficit hyperactivity disorder (ADHD and 46 controls, matched by age and sex, at the University of California at Los Angeles.

  17. Determinants of Multiple Semantic Priming: A Meta-Analysis and Spike Frequency Adaptive Model of a Cortical Network

    Science.gov (United States)

    Lavigne, Frederic; Dumercy, Laurent; Darmon, Nelly

    2011-01-01

    Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current…

  18. The Physics of Decision Making:. Stochastic Differential Equations as Models for Neural Dynamics and Evidence Accumulation in Cortical Circuits

    Science.gov (United States)

    Holmes, Philip; Eckhoff, Philip; Wong-Lin, K. F.; Bogacz, Rafal; Zacksenhouse, Miriam; Cohen, Jonathan D.

    2010-03-01

    We describe how drift-diffusion (DD) processes - systems familiar in physics - can be used to model evidence accumulation and decision-making in two-alternative, forced choice tasks. We sketch the derivation of these stochastic differential equations from biophysically-detailed models of spiking neurons. DD processes are also continuum limits of the sequential probability ratio test and are therefore optimal in the sense that they deliver decisions of specified accuracy in the shortest possible time. This leaves open the critical balance of accuracy and speed. Using the DD model, we derive a speed-accuracy tradeoff that optimizes reward rate for a simple perceptual decision task, compare human performance with this benchmark, and discuss possible reasons for prevalent sub-optimality, focussing on the question of uncertain estimates of key parameters. We present an alternative theory of robust decisions that allows for uncertainty, and show that its predictions provide better fits to experimental data than a more prevalent account that emphasises a commitment to accuracy. The article illustrates how mathematical models can illuminate the neural basis of cognitive processes.

  19. Determinants of Multiple Semantic Priming: A Meta-Analysis and Spike Frequency Adaptive Model of a Cortical Network

    Science.gov (United States)

    Lavigne, Frederic; Dumercy, Laurent; Darmon, Nelly

    2011-01-01

    Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current…

  20. Multilevel method for modeling large-scale networks.

    Energy Technology Data Exchange (ETDEWEB)

    Safro, I. M. (Mathematics and Computer Science)

    2012-02-24

    Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from

  1. Prediction of brain maturity based on cortical thickness at different spatial resolutions.

    Science.gov (United States)

    Khundrakpam, Budhachandra S; Tohka, Jussi; Evans, Alan C

    2015-05-01

    Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity.

  2. A model for recovery kinetics of aluminum after large strain

    DEFF Research Database (Denmark)

    Yu, Tianbo; Hansen, Niels

    2012-01-01

    A model is suggested to analyze recovery kinetics of heavily deformed aluminum. The model is based on the hardness of isothermal annealed samples before recrystallization takes place, and it can be extrapolated to longer annealing times to factor out the recrystallization component of the hardness...... for conditions where recovery and recrystallization overlap. The model is applied to the isothermal recovery at temperatures between 140 and 220°C of commercial purity aluminum deformed to true strain 5.5. EBSD measurements have been carried out to detect the onset of discontinuous recrystallization. Furthermore...

  3. Alterations to dendritic spine morphology, but not dendrite patterning, of cortical projection neurons in Tc1 and Ts1Rhr mouse models of Down syndrome.

    Directory of Open Access Journals (Sweden)

    Matilda A Haas

    Full Text Available Down Syndrome (DS is a highly prevalent developmental disorder, affecting 1/700 births. Intellectual disability, which affects learning and memory, is present in all cases and is reflected by below average IQ. We sought to determine whether defective morphology and connectivity in neurons of the cerebral cortex may underlie the cognitive deficits that have been described in two mouse models of DS, the Tc1 and Ts1Rhr mouse lines. We utilised in utero electroporation to label a cohort of future upper layer projection neurons in the cerebral cortex of developing mouse embryos with GFP, and then examined neuronal positioning and morphology in early adulthood, which revealed no alterations in cortical layer position or morphology in either Tc1 or Ts1Rhr mouse cortex. The number of dendrites, as well as dendrite length and branching was normal in both DS models, compared with wildtype controls. The sites of projection neuron synaptic inputs, dendritic spines, were analysed in Tc1 and Ts1Rhr cortex at three weeks and three months after birth, and significant changes in spine morphology were observed in both mouse lines. Ts1Rhr mice had significantly fewer thin spines at three weeks of age. At three months of age Tc1 mice had significantly fewer mushroom spines--the morphology associated with established synaptic inputs and learning and memory. The decrease in mushroom spines was accompanied by a significant increase in the number of stubby spines. This data suggests that dendritic spine abnormalities may be a more important contributor to cognitive deficits in DS models, rather than overall neuronal architecture defects.

  4. Neuronal deletion of caspase 8 protects against brain injury in mouse models of controlled cortical impact and kainic acid-induced excitotoxicity.

    Directory of Open Access Journals (Sweden)

    Maryla Krajewska

    Full Text Available Acute brain injury is an important health problem. Given the critical position of caspase 8 at the crossroads of cell death pathways, we generated a new viable mouse line (Ncasp8(-/-, in which the gene encoding caspase 8 was selectively deleted in neurons by cre-lox system.Caspase 8 deletion reduced rates of neuronal cell death in primary neuronal cultures and in whole brain organotypic coronal slice cultures prepared from 4 and 8 month old mice and cultivated up to 14 days in vitro. Treatments of cultures with recombinant murine TNFα (100 ng/ml or TRAIL (250 ng/mL plus cyclohexamide significantly protected neurons against cell death induced by these apoptosis-inducing ligands. A protective role of caspase 8 deletion in vivo was also demonstrated using a controlled cortical impact (CCI model of traumatic brain injury (TBI and seizure-induced brain injury caused by kainic acid (KA. Morphometric analyses were performed using digital imaging in conjunction with image analysis algorithms. By employing virtual images of hundreds of brain sections, we were able to perform quantitative morphometry of histological and immunohistochemical staining data in an unbiased manner. In the TBI model, homozygous deletion of caspase 8 resulted in reduced lesion volumes, improved post-injury motor performance, superior learning and memory retention, decreased apoptosis, diminished proteolytic processing of caspases and caspase substrates, and less neuronal degeneration, compared to wild type, homozygous cre, and caspase 8-floxed control mice. In the KA model, Ncasp8(-/- mice demonstrated superior survival, reduced seizure severity, less apoptosis, and reduced caspase 3 processing. Uninjured aged knockout mice showed improved learning and memory, implicating a possible role for caspase 8 in cognitive decline with aging.Neuron-specific deletion of caspase 8 reduces brain damage and improves post-traumatic functional outcomes, suggesting an important role for this

  5. Cortical Polarity of the RING Protein PAR-2 Is Maintained by Exchange Rate Kinetics at the Cortical-Cytoplasmic Boundary

    Directory of Open Access Journals (Sweden)

    Yukinobu Arata

    2016-08-01

    Full Text Available Cell polarity arises through the spatial segregation of polarity regulators. PAR proteins are polarity regulators that localize asymmetrically to two opposing cortical domains. However, it is unclear how the spatially segregated PAR proteins interact to maintain their mutually exclusive partitioning. Here, single-molecule detection analysis in Caenorhabditis elegans embryos reveals that cortical PAR-2 diffuses only short distances, and, as a result, most PAR-2 molecules associate and dissociate from the cortex without crossing into the opposing domain. Our results show that cortical PAR-2 asymmetry is maintained by the local exchange reactions that occur at the cortical-cytoplasmic boundary. Additionally, we demonstrate that local exchange reactions are sufficient to maintain cortical asymmetry in a parameter-free mathematical model. These findings suggest that anterior and posterior PAR proteins primarily interact through the cytoplasmic pool and not via cortical diffusion.

  6. Cortical Polarity of the RING Protein PAR-2 Is Maintained by Exchange Rate Kinetics at the Cortical-Cytoplasmic Boundary.

    Science.gov (United States)

    Arata, Yukinobu; Hiroshima, Michio; Pack, Chan-Gi; Ramanujam, Ravikrishna; Motegi, Fumio; Nakazato, Kenichi; Shindo, Yuki; Wiseman, Paul W; Sawa, Hitoshi; Kobayashi, Tetsuya J; Brandão, Hugo B; Shibata, Tatsuo; Sako, Yasushi

    2016-08-23

    Cell polarity arises through the spatial segregation of polarity regulators. PAR proteins are polarity regulators that localize asymmetrically to two opposing cortical domains. However, it is unclear how the spatially segregated PAR proteins interact to maintain their mutually exclusive partitioning. Here, single-molecule detection analysis in Caenorhabditis elegans embryos reveals that cortical PAR-2 diffuses only short distances, and, as a result, most PAR-2 molecules associate and dissociate from the cortex without crossing into the opposing domain. Our results show that cortical PAR-2 asymmetry is maintained by the local exchange reactions that occur at the cortical-cytoplasmic boundary. Additionally, we demonstrate that local exchange reactions are sufficient to maintain cortical asymmetry in a parameter-free mathematical model. These findings suggest that anterior and posterior PAR proteins primarily interact through the cytoplasmic pool and not via cortical diffusion.

  7. Layer-specific modulation of entorhinal cortical excitability by presubiculum in a rat model of temporal lobe epilepsy

    OpenAIRE

    Abbasi, Saad; Sanjay S Kumar

    2015-01-01

    Temporal lobe epilepsy (TLE) is the most common form of epilepsy in adults and is often refractory to antiepileptic medications. The medial entorhinal area (MEA) is affected in TLE but mechanisms underlying hyperexcitability of MEA neurons require further elucidation. Previous studies suggest that inputs from the presubiculum (PrS) contribute to MEA pathophysiology. We assessed electrophysiologically how PrS influences MEA excitability using the rat pilocarpine model of TLE. PrS-MEA connectiv...

  8. Effect of ovariectomy on BMD, micro-architecture and biomechanics of cortical and cancellous bones in a sheep model.

    Science.gov (United States)

    Wu, Zi-xiang; Lei, Wei; Hu, Yun-yu; Wang, Hai-qiang; Wan, Shi-yong; Ma, Zhen-sheng; Sang, Hong-xun; Fu, Suo-chao; Han, Yi-sheng

    2008-11-01

    Osteoporotic/osteopenia fractures occur most frequently in trabeculae-rich skeletal sites. The purpose of this study was to use a high-resolution micro-computed tomography (micro-CT) and dual energy X-ray absorptionmeter (DEXA) to investigate the changes in micro-architecture and bone mineral density (BMD) in a sheep model resulted from ovariectomy (OVX). Biomechanical tests were performed to evaluate the strength of the trabecular bone. Twenty adult sheeps were randomly divided into three groups: sham group (n=8), group 1 (n=4) and group 2 (n=8). In groups 1 and 2, all sheep were ovariectomized (OVX); in the sham group, the ovaries were located and the oviducts were ligated. In all animals, BMD for lumbar spine was obtained during the surgical procedure. BMD at the spine, femoral neck and femoral condyle was determined 6 months (group 1) and 12 months (group 2) post-OVX. Lumbar spines and femora were obtained and underwent BMD scan, micro-CT analysis. Compressive mechanical properties were determined from biopsies of vertebral bodies and femoral condyles. BMD, micro-architectural parameters and mechanical properties of cancellous bone did not decrease significantly at 6 months post-OVX. Twelve months after OVX, BMD, micro-architectural parameters and mechanical properties decreased significantly. The results of linear regression analyses showed that trabecular thickness (Tb.Th) (r=0.945, R2=0.886) and bone volume fraction (BV/TV) (r=0.783, R2=0.586) had strong (R2>0.5) correlation to compression stress. In OVX sheep, changes in the structural parameters of trabecular bone are comparable to the human situation during osteoporosis was induced. The sheep model presented seems to meet the criteria for an osteopenia model for fracture treatment with respect to morphometric and mechanical properties. But the duration of OVX must be longer than 12 months to ensure the animal model can be established successfully.

  9. A Large Deformation Model for the Elastic Moduli of Two-dimensional Cellular Materials

    Institute of Scientific and Technical Information of China (English)

    HU Guoming; WAN Hui; ZHANG Youlin; BAO Wujun

    2006-01-01

    We developed a large deformation model for predicting the elastic moduli of two-dimensional cellular materials. This large deformation model was based on the large deflection of the inclined members of the cells of cellular materials. The deflection of the inclined member, the strain of the representative structure and the elastic moduli of two-dimensional cellular materials were expressed using incomplete elliptic integrals. The experimental results show that these elastic moduli are no longer constant at large deformation, but vary significantly with the strain. A comparison was made between this large deformation model and the small deformation model proposed by Gibson and Ashby.

  10. Exploring model based engineering for large telescopes: getting started with descriptive models

    Science.gov (United States)

    Karban, R.; Zamparelli, M.; Bauvir, B.; Koehler, B.; Noethe, L.; Balestra, A.

    2008-07-01

    Large telescopes pose a continuous challenge to systems engineering due to their complexity in terms of requirements, operational modes, long duty lifetime, interfaces and number of components. A multitude of decisions must be taken throughout the life cycle of a new system, and a prime means of coping with complexity and uncertainty is using models as one decision aid. The potential of descriptive models based on the OMG Systems Modeling Language (OMG SysMLTM) is examined in different areas: building a comprehensive model serves as the basis for subsequent activities of soliciting and review for requirements, analysis and design alike. Furthermore a model is an effective communication instrument against misinterpretation pitfalls which are typical of cross disciplinary activities when using natural language only or free-format diagrams. Modeling the essential characteristics of the system, like interfaces, system structure and its behavior, are important system level issues which are addressed. Also shown is how to use a model as an analysis tool to describe the relationships among disturbances, opto-mechanical effects and control decisions and to refine the control use cases. Considerations on the scalability of the model structure and organization, its impact on the development process, the relation to document-centric structures, style and usage guidelines and the required tool chain are presented.

  11. Use of models in large-area forest surveys: comparing model-assisted, model-based and hybrid estimation

    Directory of Open Access Journals (Sweden)

    Göran Ståhl

    2016-02-01

    Full Text Available This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where models play a core role: model-assisted, model-based, and hybrid estimation. The first two are well known, whereas the third has only recently been introduced in forest surveys. Hybrid inference mixes designbased and model-based inference, since it relies on a probability sample of auxiliary data and a model predicting the target variable from the auxiliary data..We review studies on large-area forest surveys based on model-assisted, modelbased, and hybrid estimation, and discuss advantages and disadvantages of the approaches. We conclude that no general recommendations can be made about whether model-assisted, model-based, or hybrid estimation should be preferred. The choice depends on the objective of the survey and the possibilities to acquire appropriate field and remotely sensed data. We also conclude that modelling approaches can only be successfully applied for estimating target variables such as growing stock volume or biomass, which are adequately related to commonly available remotely sensed data, and thus purely field based surveys remain important for several important forest parameters. Keywords: Design-based inference, Model-assisted estimation, Model-based inference, Hybrid inference, National forest inventory, Remote sensing, Sampling

  12. Gyrification from constrained cortical expansion

    CERN Document Server

    Tallinen, Tuomas; Biggins, John S; Mahadevan, L

    2015-01-01

    The exterior of the mammalian brain - the cerebral cortex - has a conserved layered structure whose thickness varies little across species. However, selection pressures over evolutionary time scales have led to cortices that have a large surface area to volume ratio in some organisms, with the result that the brain is strongly convoluted into sulci and gyri. Here we show that the gyrification can arise as a nonlinear consequence of a simple mechanical instability driven by tangential expansion of the gray matter constrained by the white matter. A physical mimic of the process using a layered swelling gel captures the essence of the mechanism, and numerical simulations of the brain treated as a soft solid lead to the formation of cusped sulci and smooth gyri similar to those in the brain. The resulting gyrification patterns are a function of relative cortical expansion and relative thickness (compared with brain size), and are consistent with observations of a wide range of brains, ranging from smooth to highl...

  13. Geometric modeling and analysis of large latticed surfaces

    Science.gov (United States)

    Nayfeh, A. H.; Hefzy, M. S.

    1980-01-01

    The application of geometrical schemes, similar to geodesic domes, to large spherical antenna reflectors was investigated. The shape and size of flat segmented latticed surfaces which approximate general shells of revolution, and in particular spherical and paraboloidal reflective surfaces, were determined. The extensive mathematical and computational geometric analyses of the reflector resulted in the development of a general purpose computer program capable of generating the complete design parameters of the dish. The program also includes a graphical self contained subroutine for graphic display of the required design.

  14. Large dimension forecasting models and random singular value spectra

    CERN Document Server

    Bouchaud, J P; Miceli, M A; Potters, M; Bouchaud, Jean-Philippe; Laloux, Laurent; Potters, Marc

    2005-01-01

    We present a general method to detect and extract from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality. Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval where singular values are expected in the absence of any true correlations between the variables under study. Our result can be seen as the natural generalization of the Marcenko-Pastur distribution for the case of rectangular correlation matrices. We illustrate the interest of our method on a set of macroeconomic time series.

  15. Adaptive optics sky coverage modeling for extremely large telescopes.

    Science.gov (United States)

    Clare, Richard M; Ellerbroek, Brent L; Herriot, Glen; Véran, Jean-Pierre

    2006-12-10

    A Monte Carlo sky coverage model for laser guide star adaptive optics systems was proposed by Clare and Ellerbroek [J. Opt. Soc. Am. A 23, 418 (2006)]. We refine the model to include (i) natural guide star (NGS) statistics using published star count models, (ii) noise on the NGS measurements, (iii) the effect of telescope wind shake, (iv) a model for how the Strehl and hence NGS wavefront sensor measurement noise varies across the field, (v) the focus error due to imperfectly tracking the range to the sodium layer, (vi) the mechanical bandwidths of the tip-tilt (TT) stage and deformable mirror actuators, and (vii) temporal filtering of the NGS measurements to balance errors due to noise and servo lag. From this model, we are able to generate a TT error budget for the Thirty Meter Telescope facility narrow-field infrared adaptive optics system (NFIRAOS) and perform several design trade studies. With the current NFIRAOS design, the median TT error at the galactic pole with median seeing is calculated to be 65 nm or 1.8 mas rms.

  16. Stochastic analysis and modeling of abnormally large waves

    Science.gov (United States)

    Kuznetsov, Konstantin; Shamin, Roman; Yudin, Aleksandr

    2016-04-01

    In this work stochastics of amplitude characteristics of waves during the freak waves formation was estimated. Also amplitude characteristics of freak wave was modeling with the help of the developed Markov model on the basis of in-situ and numerical experiments. Simulation using the Markov model showed a great similarity of results of in-situ wave measurements[1], results of directly calculating the Euler equations[2] and stochastic modeling data. This work is supported by grant of Russian Foundation for Basic Research (RFBR) n°16-35-00526. 1. K. I. Kuznetsov, A. A. Kurkin, E. N. Pelinovsky and P. D. Kovalev Features of Wind Waves at the Southeastern Coast of Sakhalin according to Bottom Pressure Measurements //Izvestiya, Atmospheric and Oceanic Physics, 2014, Vol. 50, No. 2, pp. 213-220. DOI: 10.1134/S0001433814020066. 2. R.V. Shamin, V.E. Zakharov, A.I. Dyachenko. How probability for freak wave formation can be found // THE EUROPEAN PHYSICAL JOURNAL - SPECIAL TOPICS Volume 185, Number 1, 113-124, DOI: 10.1140/epjst/e2010-01242-y 3.E. N. Pelinovsky, K. I. Kuznetsov, J. Touboul, A. A. Kurkin Bottom pressure caused by passage of a solitary wave within the strongly nonlinear Green-Naghdi model //Doklady Physics, April 2015, Volume 60, Issue 4, pp 171-174. DOI: 10.1134/S1028335815040035

  17. Quantitative radiology: radiogrammetry of cortical bone.

    Science.gov (United States)

    Dequeker, J

    1976-11-01

    Based on personal experience and data in the literature, an overview is given of radiogrammetry of cortical bone of the second metacarpal. There is a within- and between-observer error which amounts respectively to 1.2 and 1.5% for the outer diameter and 4.8 and 6.4% for the inner diameter. The systematic + or-- trend between observers indicates that one observer working according to certain defined rules obtains the most reliable results. There is a large variability in amount of bone within one age and sex group which is partly due to skeletal size differences, are insufficient since skeletal size differences still exist. The variability is reduced when the data are divided into strata of skeletal size. Since cortical area shows the best correlation with outer diameter within each age group and since cortical area represents best the ash content of the bones the values of this index are most suited to be grouped according to outer diameter. In differentiating pathological from physiological bone loss this procedure is an improvement on the previously published indices of amount of bone. When comparing different populations this method has advantages since skeletal size differences are eliminated. Comparing seven populations it was found that populations living in the United States of America have more bone for a given skeletal size than populations in Europe or Nigeria. Bone loss with age is a general phenomenon but differences in rate of loss are observed between the sexes and between ethnic different populations. The decrease of bone mass is faster after the age of 50 years in woman than in men. Blacks living in the United States loose less bone with age than whites. Radiogrammetry of cortical bone in groups gives useful information on bond remodelling during ageing and in pathological conditions. At an individual level, however, it is difficult to evaluate changes on a short term basis with radiogrammetry. Radiogrammetry of cortical bone is a simple and

  18. Renal cortical scarring and renal length measurement as assessed by {sup 99m}Tc-DMSA and ultrasound examination - pathological correlation using the pig model.

    Energy Technology Data Exchange (ETDEWEB)

    Rossleigh, M.A.; Farnsworth, R.H.; Leighton, D.M.; Young, J.; Rose, M.; Christian, C. [Prince of Wales Hospital, Randwick, NSW, (Australia). Department of Nuclear Medicine

    1997-09-01

    Full text; The aims of this study were to validate DMSA appearances with histopathological features of scarring, to evaluate the sensitivity and specificity of DMSA and ultrasound (US) for the detection of renal scarring, to compare planar, pinhole and SPECT when performing DMSA and to compare DMSA and US renal length measurement. Reflux nephropathy was induced in large white pigs, using established methods. To ensure that the abnormalities detected were scars and not inflammatory changes, the pigs were not studied until three months following the treated episode of acute pyelonephritis confirmed by DMSA. Twenty-four pigs were enrolled in the study of which 11 reached the end-point. However, only nine pigs (18 kidneys) were available for analysis. Thirty-four scars were identified pathologically; 24 were present macroscopically and a further 10 were seen on microscopy only. DMSA abnormalities correlated with scars histopathologically with an accuracy of 92 per cent versus that of ultrasound, 25 per cent (p<0.001). DMSA more accurately identified scarring with a higher sensitivity (76% v 29%) and specificity (98% v 92%) than US. On the DMSA study, pinhole imaging had the highest accuracy (92%) when compared with planar (90%) and SPECT (87%) data. Renal lengths as measured on DMSA were more closely correlated with length measurement at pathological examination than US. DMSA measurement was on average 6 per cent higher than pathology and US was on average 22 per cent lower. In conclusion, DMSA appears to be the preferred method for the detection of renal cortical scarring accurate renal length measurement when compared with ultrasound examination.

  19. Sediment Yield Modeling in a Large Scale Drainage Basin

    Science.gov (United States)

    Ali, K.; de Boer, D. H.

    2009-05-01

    This paper presents the findings of spatially distributed sediment yield modeling in the upper Indus River basin. Spatial erosion rates calculated by using the Thornes model at 1-kilometre spatial resolution and monthly time scale indicate that 87 % of the annual gross erosion takes place in the three summer months. The model predicts a total annual erosion rate of 868 million tons, which is approximately 4.5 times the long- term observed annual sediment yield of the basin. Sediment delivery ratios (SDR) are hypothesized to be a function of the travel time of surface runoff from catchment cells to the nearest downstream channel. Model results indicate that higher delivery ratios (SDR > 0.6) are found in 18 % of the basin area, mostly located in the high-relief sub-basins and in the areas around the Nanga Parbat Massif. The sediment delivery ratio is lower than 0.2 in 70 % of the basin area, predominantly in the low-relief sub-basins like the Shyok on the Tibetan Plateau. The predicted annual basin sediment yield is 244 million tons which compares reasonably to the measured value of 192.5 million tons. The average annual specific sediment yield in the basin is predicted as 1110 tons per square kilometre. Model evaluation based on accuracy statistics shows very good to satisfactory performance ratings for predicted monthly basin sediment yields and for mean annual sediment yields of 17 sub-basins. This modeling framework mainly requires global datasets, and hence can be used to predict erosion and sediment yield in other ungauged drainage basins.

  20. The effect of the large cerebral cortical tubers on seizure outcomes in tuber sclerosis com-plex patients%颅内皮层大结节对结节性硬化症患者癫癎预后的影响

    Institute of Scientific and Technical Information of China (English)

    李花; 潘速跃; 胡湘蜀; 费凌霞; 郭强; 张玮; 张佩琪; 钟水生; 沈鼎烈; 周锦华

    2015-01-01

    目的:明确颅内皮层大结节对结节性硬化症(T SC )患者癫�发作及其预后的影响。方法:通过对颅内皮层结节的测量寻找颅内皮层大结节,定义为在皮层结节长宽高3个平面中,至少有2个平面的直径≥3 cm。观察颅内皮层大结节对T SC患者癫�发作及其预后的影响。结果:本研究共入组89例伴有癫�发作的T SC患者,其中男性53例,女性36例,癫�发病年龄最小为出生后1个月,最大为28岁。通过测量皮层结节发现36例(40%)患者符合本研究定义的皮层大结节。经统计学分析发现皮层大结节与痉挛发作史( P=0.022)、多种发作类型( P=0.014)、智力低下( P=0.024)及难治性癫�( P=0.041)等方面差异有统计学意义。结论:颅内皮层大结节的患者容易出现痉挛发作及多种发作类型,患者更易出现智力低下和难治性癫�,因此对于存在皮层大结节的患者需考虑早期手术治疗。%Objective:To study the effect of the large cerebral cortical tubers on seizure outcomes in patients with tuber sclerosis complex(TSC) .Methods:The diameters of at least two planes of the tuber dimention on MR were found to be ≥3 cm through the measurement of the large cerebral cortical tubers in patients with TSC .The study was aimed at observing the effect of the large cerebral cortical tubers on seizure outcomes .Results:89 patients with definite epileptic TSC were inrolved in the study ,53 male and 36 female .The onset age of seizure ranged from 1 month to 28 years .36 patients (40% ) had large cere‐bral cortical tubers according to the examination .There were statistically significant relation between the large cortical tubers and a history of infantile spasms(P=0 .022) ,multiple seizure types(P=0 .014) ,cog‐nitive impairment (P=0 .024) and refractory epilepsy(P= 0 .041) .Conclusion:The patients with large cortical tubers are found to

  1. Dynamic Modeling, Optimization, and Advanced Control for Large Scale Biorefineries

    DEFF Research Database (Denmark)

    Prunescu, Remus Mihail

    with building a plantwide model-based optimization layer, which searches for optimal values regarding the pretreatment temperature, enzyme dosage in liquefaction, and yeast seed in fermentation such that profit is maximized [7]. When biomass is pretreated, by-products are also created that affect the downstream...... processes acting as inhibitors in enzymatic hydrolysis and fermentation. Therefore, the biorefinery is treated in an integrated manner capturing the trade-offs between the conversion steps. Sensitivity and uncertainty analysis is also performed in order to identify the modeling bottlenecks and which...

  2. INTEGRATED STRATEGIES FOR THE MODELING VERY LARGE AND COMPLEX ARCHITECTURES

    Directory of Open Access Journals (Sweden)

    F. Fassi

    2012-09-01

    Full Text Available The paper would like to present a research job conducted in cooperation with the Veneranda Fabbrica of Milan Cathedral to survey and model the main cathedral spire. The job aims to find methods and a typological way to operate to produce an accurate 3D model to support forthcoming restoration works. The paper will concentrate on the description and analysis of problems and difficulties found during the survey processes and solutions chosen to overcome these problems, both in the measuring phase but in particular in the processing one. Future research is also proposed.

  3. REPORT ON THE MODELING OF THE LARGE MIS CANS

    Energy Technology Data Exchange (ETDEWEB)

    E. MOODY; J. LYMAN; K. VEIRS

    2000-12-01

    Changes in gas composition and gas pressure for closed systems containing plutonium dioxide and water are studied using a model that incorporates both radiolysis and chemical reactions. The model is used to investigate the behavior of material stored in storage containers conforming to DOE-STD-3013-99 storage standard. Scaling of the container to allow use of smaller amounts of nuclear material in experiments designed to bound the behavior of all material destined for long-term storage is studied. It is found that the container volume must be scaled along with the amount of material to achieve applicable results.

  4. Modeling and analysis of a large deployable antenna structure

    Science.gov (United States)

    Chu, Zhengrong; Deng, Zongquan; Qi, Xiaozhi; Li, Bing

    2014-02-01

    One kind of large deployable antenna (LDA) structure is proposed by combining a number of basic deployable units in this paper. In order to avoid vibration caused by fast deployment speed of the mechanism, a braking system is used to control the spring-actuated system. Comparisons between the LDA structure and a similar structure used by the large deployable reflector (LDR) indicate that the former has potential for use in antennas with up to 30 m aperture due to its lighter weight. The LDA structure is designed to form a spherical surface found by the least square fitting method so that it can be symmetrical. In this case, the positions of the terminal points in the structure are determined by two principles. A method to calculate the cable network stretched on the LDA structure is developed, which combines the original force density method and the parabolic surface constraint. Genetic algorithm is applied to ensure that each cable reaches a desired tension, which avoids the non-convergence issue effectively. We find that the pattern for the front and rear cable net must be the same when finding the shape of the rear cable net, otherwise anticlastic surface would generate.

  5. Quantifying noise-induced stability of a cortical fast-spiking cell model with Kv3-channel-like current.

    Science.gov (United States)

    Tateno, T; Robinson, H P C

    2007-01-01

    Population oscillations in neural activity in the gamma (>30 Hz) and higher frequency ranges are found over wide areas of the mammalian cortex. Recently, in the somatosensory cortex, the details of neural connections formed by several types of GABAergic interneurons have become apparent, and they are believed to play a significant role in generating these oscillations through synaptic and gap-junctional interactions. However, little is known about the mechanism of how such oscillations are maintained stably by particular interneurons and by their local networks, in a noisy environment with abundant synaptic inputs. To obtain more insight into this, we studied a fast-spiking (FS)-cell model including Kv3-channel-like current, which is a distinctive feature of these cells, from the viewpoint of nonlinear dynamical systems. To examine the specific role of the Kv3-channel in determining oscillation properties, we analyzed basic properties of the FS-cell model, such as the bifurcation structure and phase resetting curves (PRCs). Furthermore, to quantitatively characterize the oscillation stability under noisy fluctuations mimicking small fast synaptic inputs, we applied a recently developed method from random dynamical system theory to estimate Lyapunov exponents, both for the original four-dimensional dynamics and for a reduced one-dimensional phase-equation on the circle. The results indicated that the presence of the Kv3-channel-like current helps to regulate the stability of noisy neural oscillations and a transient-period length to stochastic attractors.

  6. Model-Based Analysis and Optimization of the Mapping of Cortical Sources in the Spontaneous Scalp EEG

    Directory of Open Access Journals (Sweden)

    Andrei V. Sazonov

    2007-01-01

    Full Text Available The mapping of brain sources into the scalp electroencephalogram (EEG depends on volume conduction properties of the head and on an electrode montage involving a reference. Mathematically, this source mapping (SM is fully determined by an observation function (OF matrix. This paper analyses the OF-matrix for a generation model for the desynchronized spontaneous EEG. The model involves a four-shell spherical volume conductor containing dipolar sources that are mutually uncorrelated so as to reflect the desynchronized EEG. The reference is optimized in order to minimize the impact in the SM of the sources located distant from the electrodes. The resulting reference is called the localized reference (LR. The OF-matrix is analyzed in terms of the relative power contribution of the sources and the cross-channel correlation coefficient for five existing references as well as for the LR. It is found that the Hjorth Laplacian reference is a fair approximation of the LR, and thus is close to optimum for practical intents and purposes. The other references have a significantly poorer performance. Furthermore, the OF-matrix is analyzed for limits to the spatial resolution for the EEG. These are estimated to be around 2 cm.

  7. Automatic Tuning of a Retina Model for a Cortical Visual Neuroprosthesis Using a Multi-Objective Optimization Genetic Algorithm.

    Science.gov (United States)

    Martínez-Álvarez, Antonio; Crespo-Cano, Rubén; Díaz-Tahoces, Ariadna; Cuenca-Asensi, Sergio; Ferrández Vicente, José Manuel; Fernández, Eduardo

    2016-11-01

    The retina is a very complex neural structure, which contains many different types of neurons interconnected with great precision, enabling sophisticated conditioning and coding of the visual information before it is passed via the optic nerve to higher visual centers. The encoding of visual information is one of the basic questions in visual and computational neuroscience and is also of seminal importance in the field of visual prostheses. In this framework, it is essential to have artificial retina systems to be able to function in a way as similar as possible to the biological retinas. This paper proposes an automatic evolutionary multi-objective strategy based on the NSGA-II algorithm for tuning retina models. Four metrics were adopted for guiding the algorithm in the search of those parameters that best approximate a synthetic retinal model output with real electrophysiological recordings. Results show that this procedure exhibits a high flexibility when different trade-offs has to be considered during the design of customized neuro prostheses.

  8. A New Method of Color Image Enhancement Using Spiking Cortical Model%一种采用SCM模型的彩色图像增强方法

    Institute of Scientific and Technical Information of China (English)

    马义德; 滕飞; 绽琨; 张红娟

    2012-01-01

    经研究脉冲发放皮层模型(SCM)动态阈值衰减特性和神经元点火周期,发现该模型的赋时矩阵对图像灰度处理过程恰好符合韦伯费赫涅尔定律.对于较亮部分,灰度差值处理比较粗糙,而对于较暗区域,灰度差值处理更加精细.基于此,提出了一种利用SCM的彩色图像增强算法.选择符合人眼视觉特性的HSI色彩空间,保持色调不变,对饱和度分量进行幂次拉伸,对亮度分量利用SCM进行增强处理.仿真实验结果证明,该算法可行,图像增强效果明显.%Dynamic threshold attenuation characteristics and firing periodicity of spiking cortical model (SCM) are analyzed. It is concluded that the negative time matrix of this model conforms to Weber-Fech-ner-law. It processes lighter areas coarsely and darker areas accurately. And then a new image enhancement algorithm based on SCM is presented. The hue saturation intensity (HSI) color space that satisfies with human visual system is chosen. Hue component is kept unchanged; but saturation component is changed by power stretch while luminance component is processed by SCM. Experiment shows that this algorithm is feasible, and the enhancement effect is obvious.

  9. A model for presenting accelerometer paradata in large studies: ISCOLE

    OpenAIRE

    Tudor-Locke, Catrine; Mire, Emily F; Dentro, Kara N; Barreira, Tiago V.; Schuna, John M.; Zhao, Pei; Tremblay, Mark S; Standage, Martyn; Sarmiento, Olga L.; Onywera, Vincent; Olds, Tim; Matsudo, Victor; Maia, José; Maher, Carol; Estelle V. Lambert

    2015-01-01

    Abstract Background We present a model for reporting accelerometer paradata (process-related data produced from survey administration) collected in the International Study of Childhood Obesity Lifestyle and the Environment (ISCOLE), a multi-national investigation of >7000 children (averaging 10.5 years of age) sampled from 12 different developed and developing countries and five continents. ...

  10. Modeling Fermi Large Area Telescope and Multiwavelength Data from Blazars

    CERN Document Server

    Finke, Justin

    2016-01-01

    Blazars are active galactic nuclei with relativistic jets pointed at the Earth, making them extremely bright at essentially all wavelengths, from radio to gamma rays. I review the modeling of this broadband spectral energy distributions of these objects, and what we have learned, with a focus on gamma rays.

  11. Predictability of the large relaxations in a cellular automaton model

    Energy Technology Data Exchange (ETDEWEB)

    Tejedor, Alejandro; Ambroj, Samuel; Gomez, Javier B; Pacheco, Amalio F [Faculty of Sciences, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza (Spain)

    2008-09-19

    A simple one-dimensional cellular automaton model with threshold dynamics is introduced. It is loaded at a uniform rate and unloaded by abrupt relaxations. The cumulative distribution of the size of the relaxations is analytically computed and behaves as a power law with an exponent equal to -1. This coincides with the phenomenological Gutenberg-Richter behavior observed in seismology for the cumulative statistics of earthquakes at the regional or global scale. The key point of the model is the zero-load state of the system after the occurrence of any relaxation, no matter what its size. This leads to an equipartition of probability between all possible load configurations in the system during the successive loading cycles. Each cycle ends with the occurrence of the greatest-or characteristic-relaxation in the system. The duration of the cycles in the model is statistically distributed with a coefficient of variation ranging from 0.5 to 1. The predictability of the characteristic relaxations is evaluated by means of error diagrams. This model illustrates the value taking into account the refractory periods to obtain a considerable gain in the quality of the predictions.

  12. Large BR(h -> tau mu) in Supersymmetric Models

    CERN Document Server

    Hammad, Ahmed; Un, Cem Salih

    2016-01-01

    We analyze the Lepton Flavor Violating (LFV) Higgs decay h -> tau mu in three supersymmetric models: Minimal Supersymmetric Standard Model (MSSM), Supersymmetric Seesaw Model (SSM), and Supersymmetric B-L model with Inverse Seesaw (BLSSM-IS). We show that in generic MSSM, with non-universal slepton masses and/or trilinear couplings, it is not possible to enhance BR(h -> tau mu) without violating the experimental bound on the BR(tau -> mu gamma). In SSM, where flavor mixing is radiatively generated, the LFV process mu -> e gamma strictly constrains the parameter space and the maximum value of BR(h -> tau mu) is of order 10^-10, which is extremely smaller than the recent results reported by the CMS and ATLAS experiments. In BLSSM-IS, with universal soft SUSY breaking terms at the grand unified scale, we emphasize that the measured values of BR(h -> tau mu) can be accommodated in a wide region of parameter space without violating LFV constraints. Thus, confirming the LFV Higgs decay results will be a clear signa...

  13. Optimisation of a large WWTP thanks to mathematical modelling.

    Science.gov (United States)

    Printemps, C; Baudin, A; Dormoy, T; Zug, M; Vanrolleghem, P A

    2004-01-01

    Better controlling and optimising the plant's processes has become a priority for WWTP (Wastewater Treatment Plant) managers. The main objective of this project is to develop a simplified mathematical tool able to reproduce and anticipate the behaviour of the Tougas WWTP (Nantes, France). This tool is aimed to be used directly by the managers of the site. The mathematical WWTP model was created using the software WEST. This paper describes the studied site and the modelling results obtained during the stage of the model calibration and validation. The good simulation results have allowed to show that despite a first very simple description of the WWTP, the model was able to correctly predict the nitrogen composition (ammonia and nitrate) of the effluent and the daily sludge extraction. Then, a second more detailed configuration of the WWTP was implemented. It has allowed to independently study the behaviour of each of four biological trains. Once this first stage will be completely achieved, the remainder of the study will focus on the operational use of a simplified simulator with the purpose of optimising the Tougas WWTP operation.

  14. Models of 'obesity' in large animals and birds.

    Science.gov (United States)

    Clarke, Iain J

    2008-01-01

    Most laboratory-based research on obesity is carried out in rodents, but there are a number of other interesting models in the animal kingdom that are instructive. This includes domesticated animal species such as pigs and sheep, as well as wild, migrating and hibernating species. Larger animals allow particular experimental manipulations that are not possible in smaller animals and especially useful models have been developed to address issues such as manipulation of fetal development. Although some of the most well-studied models are ruminants, with metabolic control that differs from monogastrics, the general principles of metabolic regulation still pertain. It is possible to obtain much more accurate endocrine profiles in larger animals and this has provided important data in relation to leptin and ghrelin physiology. Genetic models have been created in domesticated animals through selection and these complement those of the laboratory rodent. This short review highlights particular areas of research in domesticated and wild species that expand our knowledge of systems that are important for our understanding of obesity and metabolism.

  15. Rich-Club Organization in Effective Connectivity among Cortical Neurons

    Science.gov (United States)

    Shimono, Masanori; Ito, Shinya; Yeh, Fang-Chin; Timme, Nicholas; Myroshnychenko, Maxym; Lapish, Christopher C.; Tosi, Zachary; Hottowy, Pawel; Smith, Wesley C.; Masmanidis, Sotiris C.; Litke, Alan M.; Sporns, Olaf; Beggs, John M.

    2016-01-01

    The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a “rich club.” We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. SIGNIFICANCE STATEMENT Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several

  16. Chiral mercaptoacetamides display enantioselective inhibition of histone deacetylase 6 and exhibit neuroprotection in cortical neuron models of oxidative stress.

    Science.gov (United States)

    Kalin, Jay H; Zhang, Hankun; Gaudrel-Grosay, Sophie; Vistoli, Giulio; Kozikowski, Alan P

    2012-03-05

    Mercaptoacetamide-based ligands have been designed as a new class of histone deacetylase (HDAC) inhibitors for possible use in the treatment of neurodegenerative diseases. The thiol group of these compounds provides a key binding element for interaction with the catalytic zinc ion, and thus differs from the more typically employed hydroxamic acid based zinc binding groups. Herein we disclose the chemistry and biology of some substituted mercaptoacetamides with the intention of increasing HDAC6 isoform selectivity while maintaining potency similar to their hydroxamic acid analogues. The introduction of a stereocenter α to the thiol group was found to have a considerable impact on HDAC inhibitor potency. These new compounds were also profiled for their therapeutic potential in an in vitro model of stress-induced neuronal injury and were found to act as nontoxic neuroprotective agents. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Regional cortical thinning predicts worsening apathy and hallucinations across the Alzheimer disease spectrum.

    Science.gov (United States)

    Donovan, Nancy J; Wadsworth, Lauren P; Lorius, Natacha; Locascio, Joseph J; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Marshall, Gad A

    2014-11-01

    To examine regions of cortical thinning and cerebrospinal fluid (CSF) Alzheimer disease (AD) biomarkers associated with apathy and hallucinations in a continuum of individuals including clinically normal elderly, mild cognitive impairment, and mild AD dementia. Cross-sectional and longitudinal studies. Fifty-seven research sites across North America. Eight-hundred twelve community-dwelling volunteers; 413 participants in the CSF sub-study. Structural magnetic resonance imaging data and CSF concentrations of amyloid-β 1-42, total tau, and phosphorylated tau derived from the Alzheimer Disease Neuroimaging Initiative database were analyzed. Apathy and hallucinations were measured at baseline and over 3 years using the Neuropsychiatric Inventory-Questionnaire. General linear models and mixed effects models were used to evaluate the relationships among baseline cortical thickness in seven regions, and baseline CSF biomarkers, apathy, and hallucinations at baseline and longitudinally. Covariates included diagnosis, sex, age, apolipoprotein E genotype, premorbid intelligence, memory performance, processing speed, antidepressant use, and AD duration. Reduced baseline inferior temporal cortical thickness was predictive of increasing apathy over time, and reduced supramarginal cortical thickness was predictive of increasing hallucinations over time. There was no association with cortical thickness at baseline. CSF biomarkers were not related to severity of apathy or hallucinations in cross-sectional or longitudinal analyses. These results suggest that greater baseline temporal and parietal atrophy is associated with worsening apathy and hallucinations in a large AD spectrum cohort, while adjusting for multiple disease-related variables. Localized cortical neurodegeneration may contribute to the pathophysiology of apathy and hallucinations and their adverse consequences in AD. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All

  18. Regional cortical thinning predicts worsening apathy and hallucinations across the Alzheimer’s disease spectrum

    Science.gov (United States)

    Donovan, Nancy J.; Wadsworth, Lauren P.; Lorius, Natacha; Locascio, Joseph J.; Rentz, Dorene M.; Johnson, Keith A.; Sperling, Reisa A.; Marshall, Gad A.

    2013-01-01

    Objectives To examine regions of cortical thinning and cerebrospinal fluid (CSF) Alzheimer’s disease (AD) biomarkers associated with apathy and hallucinations in a continuum of individuals including clinically normal elderly, mild cognitive impairment and mild AD dementia. Design Cross-sectional and longitudinal studies. Setting 57 research sites across North America. Participants 812 community dwelling volunteers; 413 participants in the CSF sub-study. Measurements Structural magnetic resonance imaging data and CSF concentrations of amyloid-β 1-42, total tau and phosphorylated tau derived from the Alzheimer’s Disease Neuroimaging Initiative database were analyzed. Apathy and hallucinations were measured at baseline and over 3 years using the Neuropsychiatric Inventory-Questionnaire. General linear models and mixed effects models were used to evaluate the relationships among baseline cortical thickness in 7 regions, baseline CSF biomarkers and apathy and hallucinations at baseline and longitudinally. Covariates included diagnosis, gender, age, Apolipoprotein E genotype, premorbid intelligence, memory performance, processing speed, antidepressant use, and AD duration. Results Reduced baseline inferior temporal cortical thickness was predictive of increasing apathy over time, while reduced supramarginal cortical thickness was predictive of increasing hallucinations over time. There was no association with cortical thickness at baseline. CSF biomarkers were not related to severity of apathy or hallucinations in cross-sectional or longitudinal analyses. Conclusions These results suggest that greater baseline temporal and parietal atrophy is associated with worsening apathy and hallucinations in a large AD spectrum cohort, while adjusting for multiple disease-related variables. Localized cortical neurodegeneration may contribute to the pathophysiology of apathy and hallucinations and their adverse consequences in AD. PMID:23890751

  19. Efficiently parallelized modeling of tightly focused, large bandwidth laser pulses

    CERN Document Server

    Dumont, Joey; Lefebvre, Catherine; Gagnon, Denis; MacLean, Steve

    2016-01-01

    The Stratton-Chu integral representation of electromagnetic fields is used to study the spatio-temporal properties of large bandwidth laser pulses focused by high numerical aperture mirrors. We review the formal aspects of the derivation of diffraction integrals from the Stratton-Chu representation and discuss the use of the Hadamard finite part in the derivation of the physical optics approximation. By analyzing the formulation we show that, for the specific case of a parabolic mirror, the integrands involved in the description of the reflected field near the focal spot do not possess the strong oscillations characteristic of diffraction integrals. Consequently, the integrals can be evaluated with simple and efficient quadrature methods rather than with specialized, more costly approaches. We report on the development of an efficiently parallelized algorithm that evaluates the Stratton-Chu diffraction integrals for incident fields of arbitrary temporal and spatial dependence. We use our method to show that t...

  20. Large Deviation Results for Generalized Compound Negative Binomial Risk Models

    Institute of Scientific and Technical Information of China (English)

    Fan-chao Kong; Chen Shen

    2009-01-01

    In this paper we extend and improve some results of the large deviation for random sums of random variables.Let {Xn;n≥1} be a sequence of non-negative,independent and identically distributed random variables with common heavy-tailed distribution function F and finite mean μ∈R+,{N(n);n≥0} be a sequence of negative binomial distributed random variables with a parameter p ∈(0,1),n≥0,let {M(n);n≥0} be a Poisson process with intensity λ0.Suppose {N(n);n≥0},{Xn;n≥1} and {M(n);n≥0} are mutually results.These results can be applied to certain problems in insurance and finance.

  1. Pathogenetic mechanisms of focal cortical dysplasia.

    Science.gov (United States)

    Marin-Valencia, Isaac; Guerrini, Renzo; Gleeson, Joseph G

    2014-07-01

    Focal cortical dysplasias (FCDs) constitute a prevalent cause of intractable epilepsy in children, and is one of the leading conditions requiring epilepsy surgery. Despite recent advances in the cellular and molecular biology of these conditions, the pathogenetic mechanisms of FCDs remain largely unknown. The purpose if this work is to review the molecular underpinnings of FCDs and to highlight potential therapeutic targets. A systematic review of the literature regarding the histologic, molecular, and electrophysiologic aspects of FCDs was conducted. Disruption of the mammalian target of rapamycin (mTOR) signaling comprises a common pathway underlying the structural and electrical disturbances of some FCDs. Other mechanisms such as viral infections, prematurity, head trauma, and brain tumors are also posited. mTOR inhibitors (i.e., rapamycin) have shown positive results on seizure management in animal models and in a small cohort of patients with FCD. Encouraging progress has been achieved on