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Sample records for model large cortical

  1. Modeling cortical circuits.

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    Science.gov (United States)

    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.

  3. 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

    2017-11-01

    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).

  4. Large Scale Biologically Realistic Models of Cortical Microcircuit Dynamics with Application to Novel Statistical Classifiers (Pilot Investigation)

    National Research Council Canada - National Science Library

    Goodman, Philip

    2000-01-01

    The purpose of this project was to better understand brain-like network dynamics by incorporated biological parameters into large-scale computer simulations using parallel distributed "Beowulf" clustering...

  5. A Turing Reaction-Diffusion Model for Human Cortical Folding Patterns and Cortical Pattern Malformations

    Science.gov (United States)

    Hurdal, Monica K.; Striegel, Deborah A.

    2011-11-01

    Modeling and understanding cortical folding pattern formation is important for quantifying cortical development. We present a biomathematical model for cortical folding pattern formation in the human brain and apply this model to study diseases involving cortical pattern malformations associated with neural migration disorders. Polymicrogyria is a cortical malformation disease resulting in an excessive number of small gyri. Our mathematical model uses a Turing reaction-diffusion system to model cortical folding. The lateral ventricle (LV) and ventricular zone (VZ) of the brain are critical components in the formation of cortical patterning. In early cortical development the shape of the LV can be modeled with a prolate spheroid and the VZ with a prolate spheroid surface. We use our model to study how global cortex characteristics, such as size and shape of the LV, affect cortical pattern formation. We demonstrate increasing domain scale can increase the number of gyri and sulci formed. Changes in LV shape can account for sulcus directionality. By incorporating LV size and shape, our model is able to elucidate which parameters can lead to excessive cortical folding.

  6. Critical fluctuations in cortical models near instability

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    Matthew J. Aburn

    2012-08-01

    Full Text Available Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human EEG, however, have shown significant autocorrelation at time lags on the scale of minutes, indicating the need to consider regimes where nonlinearities influence the dynamics. Statistical properties such as increased autocorrelation length, increased variance, power-law scaling and bistable switching have been suggested as generic indicators of the approach to bifurcation in nonlinear dynamical systems. We study temporal fluctuations in a widely-employed computational model (the Jansen-Rit model of cortical activity, examining the statistical signatures that accompany bifurcations. Approaching supercritical Hopf bifurcations through tuning of the background excitatory input, we find a dramatic increase in the autocorrelation length that depends sensitively on the direction in phase space of the input fluctuations and hence on which neuronal subpopulation is stochastically perturbed. Similar dependence on the input direction is found in the distribution of fluctuation size and duration, which show power law scaling that extends over four orders of magnitude at the Hopf bifurcation. We conjecture that the alignment in phase space between the input noise vector and the center manifold of the Hopf bifurcation is directly linked to these changes. These results are consistent with the possibility of statistical indicators of linear instability being detectable in real EEG time series. However, even in a simple cortical model, we find that these indicators may not necessarily be visible even when bifurcations are present because their expression can depend sensitively on the neuronal pathway of incoming fluctuations.

  7. Modeling the effects of transcranial magnetic stimulation on cortical circuits.

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    Esser, Steve K; Hill, Sean L; Tononi, Giulio

    2005-07-01

    Transcranial magnetic stimulation (TMS) is commonly used to activate or inactivate specific cortical areas in a noninvasive manner. Because of technical constraints, the precise effects of TMS on cortical circuits are difficult to assess experimentally. Here, this issue is investigated by constructing a detailed model of a portion of the thalamocortical system and examining the effects of the simulated delivery of a TMS pulse. The model, which incorporates a large number of physiological and anatomical constraints, includes 33,000 spiking neurons arranged in a 3-layered motor cortex and over 5 million intra- and interlayer synaptic connections. The model was validated by reproducing several results from the experimental literature. These include the frequency, timing, dose response, and pharmacological modulation of epidurally recorded responses to TMS (the so-called I-waves), as well as paired-pulse response curves consistent with data from several experimental studies. The modeled responses to simulated TMS pulses in different experimental paradigms provide a detailed, self-consistent account of the neural and synaptic activities evoked by TMS within prototypical cortical circuits.

  8. 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.

  9. Dynamic Causal Modeling of the Cortical Responses to Wrist Perturbations

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    Yuan Yang

    2017-09-01

    Full Text Available Mechanical perturbations applied to the wrist joint typically evoke a stereotypical sequence of cortical and muscle responses. The early cortical responses (<100 ms are thought be involved in the “rapid” transcortical reaction to the perturbation while the late cortical responses (>100 ms are related to the “slow” transcortical reaction. Although previous studies indicated that both responses involve the primary motor cortex, it remains unclear if both responses are engaged by the same effective connectivity in the cortical network. To answer this question, we investigated the effective connectivity cortical network after a “ramp-and-hold” mechanical perturbation, in both the early (<100 ms and late (>100 ms periods, using dynamic causal modeling. Ramp-and-hold perturbations were applied to the wrist joint while the subject maintained an isometric wrist flexion. Cortical activity was recorded using a 128-channel electroencephalogram (EEG. We investigated how the perturbation modulated the effective connectivity for the early and late periods. Bayesian model comparisons suggested that different effective connectivity networks are engaged in these two periods. For the early period, we found that only a few cortico-cortical connections were modulated, while more complicated connectivity was identified in the cortical network during the late period with multiple modulated cortico-cortical connections. The limited early cortical network likely allows for a rapid muscle response without involving high-level cognitive processes, while the complexity of the late network may facilitate coordinated responses.

  10. Learning in AN Oscillatory Cortical Model

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    Scarpetta, Silvia; Li, Zhaoping; Hertz, John

    We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. The learning rule is based on the synaptic plasticity observed experimentally, in particular long-term potentiation and long-term depression of the synaptic efficacies depending on the relative timing of the pre- and postsynaptic activities during learning. The learned memory or representational states can be encoded by both the amplitude and the phase patterns of the oscillating neural populations, enabling more efficient and robust information coding than in conventional models of associative memory or input representation. Depending on the class of nonlinearity of the activation function, the model can function as an associative memory for oscillatory patterns (nonlinearity of class II) or can generalize from or interpolate between the learned states, appropriate for the function of input representation (nonlinearity of class I). In the former case, simulations of the model exhibits a first order transition between the "disordered state" and the "ordered" memory state.

  11. The Computational Properties of a Simplified Cortical Column Model.

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    Cain, Nicholas; Iyer, Ramakrishnan; Koch, Christof; Mihalas, Stefan

    2016-09-01

    The mammalian neocortex has a repetitious, laminar structure and performs functions integral to higher cognitive processes, including sensory perception, memory, and coordinated motor output. What computations does this circuitry subserve that link these unique structural elements to their function? Potjans and Diesmann (2014) parameterized a four-layer, two cell type (i.e. excitatory and inhibitory) model of a cortical column with homogeneous populations and cell type dependent connection probabilities. We implement a version of their model using a displacement integro-partial differential equation (DiPDE) population density model. This approach, exact in the limit of large homogeneous populations, provides a fast numerical method to solve equations describing the full probability density distribution of neuronal membrane potentials. It lends itself to quickly analyzing the mean response properties of population-scale firing rate dynamics. We use this strategy to examine the input-output relationship of the Potjans and Diesmann cortical column model to understand its computational properties. When inputs are constrained to jointly and equally target excitatory and inhibitory neurons, we find a large linear regime where the effect of a multi-layer input signal can be reduced to a linear combination of component signals. One of these, a simple subtractive operation, can act as an error signal passed between hierarchical processing stages.

  12. Critical fluctuations in cortical models near instability

    NARCIS (Netherlands)

    Aburn, M.J.; Holmes, C.A.; Roberts, J.A.; Boonstra, T.W.; Breakspear, M.

    2012-01-01

    Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human electroencephalography (EEG), however, have shown significant autocorrelation at time lags on the scale

  13. 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. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

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

    2014-01-01

    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

  15. Dual extradural cortical stimulation in chronic stroke patients with large infarcts: technical case report.

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    Shin, Yong-Il; Kim, Hyoungihl; Moon, Seong-Keun; Kim, Hyojoon; Yun, Yong-Soon; Chung, Gyung-Ho

    2010-06-01

    Recent works on extradural cortical stimulation have been successful in improving neurological recovery in chronic stroke patients. On the other hand, single perirolandic stimulations are often associated with disappointing results. We report two cases of chronic stroke in which the magnitude of infarct was too large to be improved with single perirolandic stimulation. Patient 1 had severe hemiplegia associated with large cortical infarct in the right frontoparietal area. The patient could neither stand independently or walk. Patient 2 had hemiplegia and aphasia due to cortical infarct in the left middle cerebral artery territory. Both patients had intensive rehabilitative training for more than 6 months with no beneficial results. Two paddle electrodes covering frontal and parietal area were implanted, followed by dual cortical stimulation with concurrent rehabilitative training in patient 1. After 6 months of stimulation, the patient could walk with a good posture. Two paddle electrodes were implanted to cover pre-motor and motor cortex in patient 2. After similar treatment, the motor function was markedly improved. Dual cortex stimulation, which acts on more diffuse areas or functionally related areas, is beneficial to promote the motor recovery in chronic stroke patients with large infarcts.

  16. Crossmodal Connections of Primary Sensory Cortices Largely Vanish During Normal Aging

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    Henschke, Julia U.; Ohl, Frank W.; Budinger, Eike

    2018-01-01

    During aging, human response times (RTs) to unisensory and crossmodal stimuli decrease. However, the elderly benefit more from crossmodal stimulus representations than younger people. The underlying short-latency multisensory integration process is mediated by direct crossmodal connections at the level of primary sensory cortices. We investigate the age-related changes of these connections using a rodent model (Mongolian gerbil), retrograde tracer injections into the primary auditory (A1), somatosensory (S1), and visual cortex (V1), and immunohistochemistry for markers of apoptosis (Caspase-3), axonal plasticity (Growth associated protein 43, GAP 43), and a calcium-binding protein (Parvalbumin, PV). In adult animals, primary sensory cortices receive a substantial number of direct thalamic inputs from nuclei of their matched, but also from nuclei of non-matched sensory modalities. There are also direct intracortical connections among primary sensory cortices and connections with secondary sensory cortices of other modalities. In very old animals, the crossmodal connections strongly decrease in number or vanish entirely. This is likely due to a retraction of the projection neuron axonal branches rather than ongoing programmed cell death. The loss of crossmodal connections is also accompanied by changes in anatomical correlates of inhibition and excitation in the sensory thalamus and cortex. Together, the loss and restructuring of crossmodal connections during aging suggest a shift of multisensory processing from primary cortices towards other sensory brain areas in elderly individuals. PMID:29551970

  17. Crossmodal Connections of Primary Sensory Cortices Largely Vanish During Normal Aging

    Directory of Open Access Journals (Sweden)

    Julia U. Henschke

    2018-03-01

    Full Text Available During aging, human response times (RTs to unisensory and crossmodal stimuli decrease. However, the elderly benefit more from crossmodal stimulus representations than younger people. The underlying short-latency multisensory integration process is mediated by direct crossmodal connections at the level of primary sensory cortices. We investigate the age-related changes of these connections using a rodent model (Mongolian gerbil, retrograde tracer injections into the primary auditory (A1, somatosensory (S1, and visual cortex (V1, and immunohistochemistry for markers of apoptosis (Caspase-3, axonal plasticity (Growth associated protein 43, GAP 43, and a calcium-binding protein (Parvalbumin, PV. In adult animals, primary sensory cortices receive a substantial number of direct thalamic inputs from nuclei of their matched, but also from nuclei of non-matched sensory modalities. There are also direct intracortical connections among primary sensory cortices and connections with secondary sensory cortices of other modalities. In very old animals, the crossmodal connections strongly decrease in number or vanish entirely. This is likely due to a retraction of the projection neuron axonal branches rather than ongoing programmed cell death. The loss of crossmodal connections is also accompanied by changes in anatomical correlates of inhibition and excitation in the sensory thalamus and cortex. Together, the loss and restructuring of crossmodal connections during aging suggest a shift of multisensory processing from primary cortices towards other sensory brain areas in elderly individuals.

  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. Modeling a space-variant cortical representation for apparent motion.

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    Wurbs, Jeremy; Mingolla, Ennio; Yazdanbakhsh, Arash

    2013-08-06

    Receptive field sizes of neurons in early primate visual areas increase with eccentricity, as does temporal processing speed. The fovea is evidently specialized for slow, fine movements while the periphery is suited for fast, coarse movements. In either the fovea or periphery discrete flashes can produce motion percepts. Grossberg and Rudd (1989) used traveling Gaussian activity profiles to model long-range apparent motion percepts. We propose a neural model constrained by physiological data to explain how signals from retinal ganglion cells to V1 affect the perception of motion as a function of eccentricity. Our model incorporates cortical magnification, receptive field overlap and scatter, and spatial and temporal response characteristics of retinal ganglion cells for cortical processing of motion. Consistent with the finding of Baker and Braddick (1985), in our model the maximum flash distance that is perceived as an apparent motion (Dmax) increases linearly as a function of eccentricity. Baker and Braddick (1985) made qualitative predictions about the functional significance of both stimulus and visual system parameters that constrain motion perception, such as an increase in the range of detectable motions as a function of eccentricity and the likely role of higher visual processes in determining Dmax. We generate corresponding quantitative predictions for those functional dependencies for individual aspects of motion processing. Simulation results indicate that the early visual pathway can explain the qualitative linear increase of Dmax data without reliance on extrastriate areas, but that those higher visual areas may serve as a modulatory influence on the exact Dmax increase.

  20. 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.

  1. Large scale model testing

    International Nuclear Information System (INIS)

    Brumovsky, M.; Filip, R.; Polachova, H.; Stepanek, S.

    1989-01-01

    Fracture mechanics and fatigue calculations for WWER reactor pressure vessels were checked by large scale model testing performed using large testing machine ZZ 8000 (with a maximum load of 80 MN) at the SKODA WORKS. The results are described from testing the material resistance to fracture (non-ductile). The testing included the base materials and welded joints. The rated specimen thickness was 150 mm with defects of a depth between 15 and 100 mm. The results are also presented of nozzles of 850 mm inner diameter in a scale of 1:3; static, cyclic, and dynamic tests were performed without and with surface defects (15, 30 and 45 mm deep). During cyclic tests the crack growth rate in the elastic-plastic region was also determined. (author). 6 figs., 2 tabs., 5 refs

  2. Cortical functional hyperconnectivity in a mouse model of depression and selective network effects of ketamine.

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    McGirr, Alexander; LeDue, Jeffrey; Chan, Allen W; Xie, Yicheng; Murphy, Timothy H

    2017-08-01

    See Huang and Liston (doi:10.1093/awx166) for a scientific commentary on this article.Human depression is associated with glutamatergic dysfunction and alterations in resting state network activity. However, the indirect nature of human in vivo glutamate and activity assessments obscures mechanistic details. Using the chronic social defeat mouse model of depression, we determine how mesoscale glutamatergic networks are altered after chronic stress, and in response to the rapid acting antidepressant, ketamine. Transgenic mice (Ai85) expressing iGluSnFR (a recombinant protein sensor) permitted real-time in vivo selective characterization of extracellular glutamate and longitudinal imaging of mesoscale cortical glutamatergic functional circuits. Mice underwent chronic social defeat or a control condition, while spontaneous cortical activity was longitudinally sampled. After chronic social defeat, we observed network-wide glutamate functional hyperconnectivity in defeated animals, which was confirmed with voltage sensitive dye imaging in an independent cohort. Subanaesthetic ketamine has unique effects in defeated animals. Acutely, subanaesthetic ketamine induces large global cortical glutamate transients in defeated animals, and an elevated subanaesthetic dose resulted in sustained global increase in cortical glutamate. Local cortical inhibition of glutamate transporters in naïve mice given ketamine produced a similar extracellular glutamate phenotype, with both glutamate transients and a dose-dependent accumulation of glutamate. Twenty-four hours after ketamine, normalization of depressive-like behaviour in defeated animals was accompanied by reduced glutamate functional connectivity strength. Altered glutamate functional connectivity in this animal model confirms the central role of glutamate dynamics as well as network-wide changes after chronic stress and in response to ketamine. © The Author (2017). Published by Oxford University Press on behalf of the

  3. 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

  4. Comparing Intrinsic Connectivity Models for the Primary Auditory Cortices

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    Hamid, Khairiah Abdul; Yusoff, Ahmad Nazlim; Mohamad, Mazlyfarina; Hamid, Aini Ismafairus Abd; Manan, Hanani Abd

    2010-07-01

    This fMRI study is about modeling the intrinsic connectivity between Heschl' gyrus (HG) and superior temporal gyrus (STG) in human primary auditory cortices. Ten healthy male subjects participated and required to listen to white noise stimulus during the fMRI scans. Two intrinsic connectivity models comprising bilateral HG and STG were constructed using statistical parametric mapping (SPM) and dynamic causal modeling (DCM). Group Bayes factor (GBF), positive evidence ratio (PER) and Bayesian model selection (BMS) for group studies were used in model comparison. Group results indicated significant bilateral asymmetrical activation (puncorr < 0.001) in HG and STG. Comparison results showed strong evidence of Model 2 as the preferred model (STG as the input center) with GBF value of 5.77 × 1073 The model is preferred by 6 out of 10 subjects. The results were supported by BMS results for group studies. One-sample t-test on connection values obtained from Model 2 indicates unidirectional parallel connections from STG to bilateral HG (p<0.05). Model 2 was determined to be the most probable intrinsic connectivity model between bilateral HG and STG when listening to white noise.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.)

  6. Large scale composting model

    OpenAIRE

    Henon , Florent; Debenest , Gérald; Tremier , Anne; Quintard , Michel; Martel , Jean-Luc; Duchalais , Guy

    2012-01-01

    International audience; One way to treat the organic wastes accordingly to the environmental policies is to develop biological treatment like composting. Nevertheless, this development largely relies on the quality of the final product and as a consequence on the quality of the biological activity during the treatment. Favourable conditions (oxygen concentration, temperature and moisture content) in the waste bed largely contribute to the establishment of a good aerobic biological activity an...

  7. 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

  8. 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.

  9. Linear distributed source modeling of local field potentials recorded with intra-cortical electrode arrays.

    Directory of Open Access Journals (Sweden)

    Rikkert Hindriks

    Full Text Available Planar intra-cortical electrode (Utah arrays provide a unique window into the spatial organization of cortical activity. Reconstruction of the current source density (CSD underlying such recordings, however, requires "inverting" Poisson's equation. For inter-laminar recordings, this is commonly done by the CSD method, which consists in taking the second-order spatial derivative of the recorded local field potentials (LFPs. Although the CSD method has been tremendously successful in mapping the current generators underlying inter-laminar LFPs, its application to planar recordings is more challenging. While for inter-laminar recordings the CSD method seems reasonably robust against violations of its assumptions, is it unclear as to what extent this holds for planar recordings. One of the objectives of this study is to characterize the conditions under which the CSD method can be successfully applied to Utah array data. Using forward modeling, we find that for spatially coherent CSDs, the CSD method yields inaccurate reconstructions due to volume-conducted contamination from currents in deeper cortical layers. An alternative approach is to "invert" a constructed forward model. The advantage of this approach is that any a priori knowledge about the geometrical and electrical properties of the tissue can be taken into account. Although several inverse methods have been proposed for LFP data, the applicability of existing electroencephalographic (EEG and magnetoencephalographic (MEG inverse methods to LFP data is largely unexplored. Another objective of our study therefore, is to assess the applicability of the most commonly used EEG/MEG inverse methods to Utah array data. Our main conclusion is that these inverse methods provide more accurate CSD reconstructions than the CSD method. We illustrate the inverse methods using event-related potentials recorded from primary visual cortex of a macaque monkey during a motion discrimination task.

  10. Resveratrol attenuates cortical neuron activity: roles of large conductance calcium-activated potassium channels and voltage-gated sodium channels.

    Science.gov (United States)

    Wang, Ya-Jean; Chan, Ming-Huan; Chen, Linyi; Wu, Sheng-Nan; Chen, Hwei-Hisen

    2016-05-21

    Resveratrol, a phytoalexin found in grapes and red wine, exhibits diverse pharmacological activities. However, relatively little is known about whether resveratrol modulates the ion channels in cortical neurons. The large-conductance calcium-activated potassium channels (BKCa) and voltage-gated sodium channels were expressed in cortical neurons and play important roles in regulation of neuronal excitability. The present study aimed to determine the effects of resveratrol on BKCa currents and voltage-gated sodium currents in cortical neurons. Resveratrol concentration-dependently increased the current amplitude and the opening activity of BKCa channels, but suppressed the amplitude of voltage-gated sodium currents. Similar to the BKCa channel opener NS1619, resveratrol decreased the firing rate of action potentials. In addition, the enhancing effects of BKCa channel blockers tetraethylammonium (TEA) and paxilline on action potential firing were sensitive to resveratrol. Our results indicated that the attenuation of action potential firing rate by resveratrol might be mediated through opening the BKCa channels and closing the voltage-gated sodium channels. As BKCa channels and sodium channels are critical molecular determinants for seizure generation, our findings suggest that regulation of these two channels in cortical neurons probably makes a considerable contribution to the antiseizure activity of resveratrol.

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

    CERN Document Server

    Lerchner, A; Hertz, J

    2004-01-01

    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 due to the tendency of spikes being clustered into bursts. We show that this behavior emerges naturally in a balanced 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 of cortical neurons in their natural environment, and variable non-Poissonian spike statistics with Fano factors greater than 1.

  12. Is There a Canonical Cortical Circuit for the Cholinergic System? Anatomical Differences Across Common Model Systems.

    Science.gov (United States)

    Coppola, Jennifer J; Disney, Anita A

    2018-01-01

    Acetylcholine (ACh) is believed to act as a neuromodulator in cortical circuits that support cognition, specifically in processes including learning, memory consolidation, vigilance, arousal and attention. The cholinergic modulation of cortical processes is studied in many model systems including rodents, cats and primates. Further, these studies are performed in cortical areas ranging from the primary visual cortex to the prefrontal cortex and using diverse methodologies. The results of these studies have been combined into singular models of function-a practice based on an implicit assumption that the various model systems are equivalent and interchangeable. However, comparative anatomy both within and across species reveals important differences in the structure of the cholinergic system. Here, we will review anatomical data including innervation patterns, receptor expression, synthesis and release compared across species and cortical area with a focus on rodents and primates. We argue that these data suggest no canonical cortical model system exists for the cholinergic system. Further, we will argue that as a result, care must be taken both in combining data from studies across cortical areas and species, and in choosing the best model systems to improve our understanding and support of human health.

  13. Is There a Canonical Cortical Circuit for the Cholinergic System? Anatomical Differences Across Common Model Systems

    Directory of Open Access Journals (Sweden)

    Jennifer J. Coppola

    2018-01-01

    Full Text Available Acetylcholine (ACh is believed to act as a neuromodulator in cortical circuits that support cognition, specifically in processes including learning, memory consolidation, vigilance, arousal and attention. The cholinergic modulation of cortical processes is studied in many model systems including rodents, cats and primates. Further, these studies are performed in cortical areas ranging from the primary visual cortex to the prefrontal cortex and using diverse methodologies. The results of these studies have been combined into singular models of function—a practice based on an implicit assumption that the various model systems are equivalent and interchangeable. However, comparative anatomy both within and across species reveals important differences in the structure of the cholinergic system. Here, we will review anatomical data including innervation patterns, receptor expression, synthesis and release compared across species and cortical area with a focus on rodents and primates. We argue that these data suggest no canonical cortical model system exists for the cholinergic system. Further, we will argue that as a result, care must be taken both in combining data from studies across cortical areas and species, and in choosing the best model systems to improve our understanding and support of human health.

  14. Repair of Neocortex in a Model of Cortical Dysplasia

    Science.gov (United States)

    2007-03-27

    postnatally. MAM treatment on E24 leads to disorganized cortical laminae, abnormal radial morphology, precocious differentiation of radial glia, and dispersal...of Cajal Retzius cells. MAM treatment on E33 leads to less severe effects including diminished layer 4, widespread termination of thalamocortical...as dyslexia , intractable epilepsy, and schizophrenia which has been linked to abnormal reelin expression (Grayson et al., 2005; Brigman et al., 2006

  15. Hybrid MEG (Magnetoencephalography) source characterization by cortical remapping and imaging of parametric source models

    Energy Technology Data Exchange (ETDEWEB)

    Baillet, S. (Sylvain); Mosher, J. C. (John C.); Jerbi, K. (Karim); Leahy, R. M. (Richard M.)

    2001-01-01

    Reliable estimation of the local spatial extent of neural activity is a key to the quantitative analysis of MEG sources across subjects and conditions. In association with an understanding of the temporal dynamics among multiple areas, this would represent a major advance in electrophysiological source imaging. Parametric current dipole approaches to MEG (and EEG) source localization can rapidly generate a physical model of neural current generators using a limited number of parameters. However, physiological interpretation of these models is often difficult, especially in terms of the spatial extent of the true cortical activity. In new approaches using multipolar source models [3, 5], similar problems remain in the analysis of the higher-order source moments as parameters of cortical extent. Image-based approaches to the inverse problem provide a direct estimate of cortical current generators, but computationally expensive nonlinear methods are required to produce focal sources [1,4]. Recent efforts describe how a cortical patch can be grown until a best fit to the data is reached in the least-squares sense [6], but computational considerations necessitate that the growth be seeded in predefined regions of interest. In a previous study [2], a source obtained using a parametric model was remapped onto the cortex by growing a patch of cortical dipoles in the vicinity of the parametric source until the forward MEG or EEG fields of the parametric and cortical sources matched. The source models were dipoles and first-order multipoles. We propose to combine the parametric and imaging methods for MEG source characterization to take advantage of (i) the parsimonious and computationally efficient nature of parametric source localization methods and (ii) the anatomical and physiological consistency of imaging techniques that use relevant a priori information. By performing the cortical remapping imaging step by matching the multipole expansions of the original parametric

  16. 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; Shen, Dinggang

    2012-10-01

    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.

  17. Cortical Maps.

    Science.gov (United States)

    Bednar, James A; Wilson, Stuart P

    2016-12-01

    In this article, we review functional organization in sensory cortical regions-how the cortex represents the world. We consider four interrelated aspects of cortical organization: (1) the set of receptive fields of individual cortical sensory neurons, (2) how lateral interaction between cortical neurons reflects the similarity of their receptive fields, (3) the spatial distribution of receptive-field properties across the horizontal extent of the cortical tissue, and (4) how the spatial distributions of different receptive-field properties interact with one another. We show how these data are generally well explained by the theory of input-driven self-organization, with a family of computational models of cortical maps offering a parsimonious account for a wide range of map-related phenomena. We then discuss important challenges to this explanation, with respect to the maps present at birth, maps present under activity blockade, the limits of adult plasticity, and the lack of some maps in rodents. Because there is not at present another credible general theory for cortical map development, we conclude by proposing key experiments to help uncover other mechanisms that might also be operating during map development. © The Author(s) 2015.

  18. 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.

  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

    estimates. Volume-based smoothing resulted in large bias and intersubject variance because it smears signal across tissue types. In some cases, PVC with volume smoothing paradoxically caused the estimated BPND to be less than when no PVC was used at all. When applied in the absence of PVC, cortical surface...

  20. Model cortical responses for the detection of perceptual onsets and beat tracking in singing

    NARCIS (Netherlands)

    Coath, M.; Denham, S.L.; Smith, L.M.; Honing, H.; Hazan, A.; Holonowicz, P.; Purwins, H.

    2009-01-01

    We describe a biophysically motivated model of auditory salience based on a model of cortical responses and present results that show that the derived measure of salience can be used to identify the position of perceptual onsets in a musical stimulus successfully. The salience measure is also shown

  1. Evoked potentials in large-scale cortical networks elicited by TMS of the visual cortex

    Science.gov (United States)

    Grossman, Emily D.; Srinivasan, Ramesh

    2011-01-01

    Single pulses of transcranial magnetic stimulation (TMS) result in distal and long-lasting oscillations, a finding directly challenging the virtual lesion hypothesis. Previous research supporting this finding has primarily come from stimulation of the motor cortex. We have used single-pulse TMS with simultaneous EEG to target seven brain regions, six of which belong to the visual system [left and right primary visual area V1, motion-sensitive human middle temporal cortex, and a ventral temporal region], as determined with functional MRI-guided neuronavigation, and a vertex “control” site to measure the network effects of the TMS pulse. We found the TMS-evoked potential (TMS-EP) over visual cortex consists mostly of site-dependent theta- and alphaband oscillations. These site-dependent oscillations extended beyond the stimulation site to functionally connected cortical regions and correspond to time windows where the EEG responses maximally diverge (40, 200, and 385 ms). Correlations revealed two site-independent oscillations ∼350 ms after the TMS pulse: a theta-band oscillation carried by the frontal cortex, and an alpha-band oscillation over parietal and frontal cortical regions. A manipulation of stimulation intensity at one stimulation site (right hemisphere V1-V3) revealed sensitivity to the stimulation intensity at different regions of cortex, evidence of intensity tuning in regions distal to the site of stimulation. Together these results suggest that a TMS pulse applied to the visual cortex has a complex effect on brain function, engaging multiple brain networks functionally connected to the visual system with both invariant and site-specific spatiotemporal dynamics. With this characterization of TMS, we propose an alternative to the virtual lesion hypothesis. Rather than a technique that simulates lesions, we propose TMS generates natural brain signals and engages functional networks. PMID:21715670

  2. Semantic integration by pattern priming: experiment and cortical network model.

    Science.gov (United States)

    Lavigne, Frédéric; Longrée, Dominique; Mayaffre, Damon; Mellet, Sylvie

    2016-12-01

    Neural network models describe semantic priming effects by way of mechanisms of activation of neurons coding for words that rely strongly on synaptic efficacies between pairs of neurons. Biologically inspired Hebbian learning defines efficacy values as a function of the activity of pre- and post-synaptic neurons only. It generates only pair associations between words in the semantic network. However, the statistical analysis of large text databases points to the frequent occurrence not only of pairs of words (e.g., "the way") but also of patterns of more than two words (e.g., "by the way"). The learning of these frequent patterns of words is not reducible to associations between pairs of words but must take into account the higher level of coding of three-word patterns. The processing and learning of pattern of words challenges classical Hebbian learning algorithms used in biologically inspired models of priming. The aim of the present study was to test the effects of patterns on the semantic processing of words and to investigate how an inter-synaptic learning algorithm succeeds at reproducing the experimental data. The experiment manipulates the frequency of occurrence of patterns of three words in a multiple-paradigm protocol. Results show for the first time that target words benefit more priming when embedded in a pattern with the two primes than when only associated with each prime in pairs. A biologically inspired inter-synaptic learning algorithm is tested that potentiates synapses as a function of the activation of more than two pre- and post-synaptic neurons. Simulations show that the network can learn patterns of three words to reproduce the experimental results.

  3. Model of large pool fires

    International Nuclear Information System (INIS)

    Fay, J.A.

    2006-01-01

    A two zone entrainment model of pool fires is proposed to depict the fluid flow and flame properties of the fire. Consisting of combustion and plume zones, it provides a consistent scheme for developing non-dimensional scaling parameters for correlating and extrapolating pool fire visible flame length, flame tilt, surface emissive power, and fuel evaporation rate. The model is extended to include grey gas thermal radiation from soot particles in the flame zone, accounting for emission and absorption in both optically thin and thick regions. A model of convective heat transfer from the combustion zone to the liquid fuel pool, and from a water substrate to cryogenic fuel pools spreading on water, provides evaporation rates for both adiabatic and non-adiabatic fires. The model is tested against field measurements of large scale pool fires, principally of LNG, and is generally in agreement with experimental values of all variables

  4. A new approach to detect the coding rule of the cortical spiking model in the information transmission.

    Science.gov (United States)

    Nazari, Soheila; Faez, Karim; Janahmadi, Mahyar

    2018-03-01

    Investigation of the role of the local field potential (LFP) fluctuations in encoding the received sensory information by the nervous system remains largely unknown. On the other hand, transmission of these translation rules in information transmission between the structure of sensory stimuli and the cortical oscillations to the bio-inspired artificial neural networks operating at the efficiency of the nervous system is still a vague puzzle. In order to move towards this important goal, computational neuroscience tools can be useful so, we simulated a large-scale network of excitatory and inhibitory spiking neurons with synaptic connections consisting of AMPA and GABA currents as a model of cortical populations. Spiking network was equipped with spike-based unsupervised weight optimization based on the dynamical behavior of the excitatory (AMPA) and inhibitory (GABA) synapses using Spike Timing Dependent Plasticity (STDP) on the MNIST benchmark and we specified how the generated LFP by the network contained information about input patterns. The main result of this article is that the calculated coefficients of Prolate spheroidal wave functions (PSWF) from the input pattern with mean square error (MSE) criterion and power spectrum of LFP with maximum correntropy criterion (MCC) are equal. The more important result is that 82.3% of PSWF coefficients are the same as the connecting weights of the cortical neurons to the classifying neurons after the completion of the training process. Higher compliance percentage of coefficients with synaptic weights (82.3%) gives the expectance us that this coding rule will be able to extend to biological systems. Eventually, we introduced the cortical spiking network as an information channel, which transmits the information of the input pattern in the form of PSWF coefficients to the power spectrum of the output generated LFP. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. 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.

  6. 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 ...

  7. Model-driven harmonic parameterization of the cortical surface: HIP-HOP.

    Science.gov (United States)

    Auzias, G; Lefèvre, J; Le Troter, A; Fischer, C; Perrot, M; Régis, J; Coulon, O

    2013-05-01

    In the context of inter subject brain surface matching, we present a parameterization of the cortical surface constrained by a model of cortical organization. The parameterization is defined via an harmonic mapping of each hemisphere surface to a rectangular planar domain that integrates a representation of the model. As opposed to previous landmark-based registration methods we do not match folds between individuals but instead optimize the fit between cortical sulci and specific iso-coordinate axis in the model. This strategy overcomes some limitation to sulcus-based registration techniques such as topological variability in sulcal landmarks across subjects. Experiments on 62 subjects with manually traced sulci are presented and compared with the result of the Freesurfer software. The evaluation involves a measure of dispersion of sulci with both angular and area distortions. We show that the model-based strategy can lead to a natural, efficient and very fast (less than 5 min per hemisphere) method for defining inter subjects correspondences. We discuss how this approach also reduces the problems inherent to anatomically defined landmarks and open the way to the investigation of cortical organization through the notion of orientation and alignment of structures across the cortex.

  8. Simulation study of axial ultrasound transmission in heterogeneous cortical bone model

    Science.gov (United States)

    Takano, Koki; Nagatani, Yoshiki; Matsukawa, Mami

    2017-07-01

    Ultrasound propagation in a heterogeneous cortical bone was studied. Using a bovine radius, the longitudinal wave velocity distribution in the axial direction was experimentally measured in the MHz range. The bilinear interpolation and piecewise cubic Hermite interpolation methods were applied to create a three-dimensional (3D) precise velocity model of the bone using experimental data. By assuming the uniaxial anisotropy of the bone, the distributions of all elastic moduli of a 3D heterogeneous model were estimated. The elastic finite-difference time-domain method was used to simulate axial ultrasonic wave propagation. The wave propagation in the initial model was compared with that in the thinner model, where the inner part of the cortical bone model was removed. The wave front of the first arriving signal (FAS) slightly depended on the heterogeneity in each model. Owing to the decrease in bone thickness, the propagation behavior also changed and the FAS velocity clearly decreased.

  9. Three-Dimensional Visualization with Large Data Sets: A Simulation of Spreading Cortical Depression in Human Brain

    Directory of Open Access Journals (Sweden)

    Korhan Levent Ertürk

    2012-01-01

    Full Text Available We developed 3D simulation software of human organs/tissues; we developed a database to store the related data, a data management system to manage the created data, and a metadata system for the management of data. This approach provides two benefits: first of all the developed system does not require to keep the patient's/subject's medical images on the system, providing less memory usage. Besides the system also provides 3D simulation and modification options, which will help clinicians to use necessary tools for visualization and modification operations. The developed system is tested in a case study, in which a 3D human brain model is created and simulated from 2D MRI images of a human brain, and we extended the 3D model to include the spreading cortical depression (SCD wave front, which is an electrical phoneme that is believed to cause the migraine.

  10. Three-Dimensional Visualization with Large Data Sets: A Simulation of Spreading Cortical Depression in Human Brain

    Science.gov (United States)

    Ertürk, Korhan Levent; Şengül, Gökhan

    2012-01-01

    We developed 3D simulation software of human organs/tissues; we developed a database to store the related data, a data management system to manage the created data, and a metadata system for the management of data. This approach provides two benefits: first of all the developed system does not require to keep the patient's/subject's medical images on the system, providing less memory usage. Besides the system also provides 3D simulation and modification options, which will help clinicians to use necessary tools for visualization and modification operations. The developed system is tested in a case study, in which a 3D human brain model is created and simulated from 2D MRI images of a human brain, and we extended the 3D model to include the spreading cortical depression (SCD) wave front, which is an electrical phoneme that is believed to cause the migraine. PMID:23258956

  11. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. 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.

  13. A multidomain model for ionic electrodiffusion and osmosis with an application to cortical spreading depression

    Science.gov (United States)

    Mori, Yoichiro

    2015-07-01

    Ionic electrodiffusion and osmotic water flow are central processes in many physiological systems. We formulate a system of partial differential equations that governs ion movement and water flow in biological tissue. A salient feature of this model is that it satisfies a free energy identity, ensuring the thermodynamic consistency of the model. A numerical scheme is developed for the model in one spatial dimension and is applied to a model of cortical spreading depression, a propagating breakdown of ionic and cell volume homeostasis in the brain.

  14. 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.

  15. Precise MRI-based stereotaxic surgery in large animal models

    DEFF Research Database (Denmark)

    Glud, A. N.; Bech, J.; Tvilling, L.

    and subcortical anatomical differences. NEW METHOD: We present a convenient method to make an MRI-visible skull fiducial for 3D MRI-based stereotaxic procedures in larger experimental animals. Plastic screws were filled with either copper-sulphate solution or MRI-visible paste from a commercially available......BACKGROUND: Stereotaxic neurosurgery in large animals is used widely in different sophisticated models, where precision is becoming more crucial as desired anatomical target regions are becoming smaller. Individually calculated coordinates are necessary in large animal models with cortical...... cranial head marker. The screw fiducials were inserted in the animal skulls and T1 weighted MRI was performed allowing identification of the inserted skull marker. RESULTS: Both types of fiducial markers were clearly visible on the MRÍs. This allows high precision in the stereotaxic space. COMPARISON...

  16. 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.

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

    NARCIS (Netherlands)

    Adams, Hugo J A; de Klerk, John M H; Fijnheer, Rob; Heggelman, Ben G F; Dubois, Stefan V.; Nievelstein, Rutger A J; Kwee, Thomas C.

    2015-01-01

    Purpose: To determine the prognostic value of tumor-induced cortical bone destruction at computed tomography (CT) in newly diagnosed diffuse large B-cell lymphoma (DLBCL). Materials and methods: This retrospective study included 105 patients with newly diagnosed DLBCL who had undergone CT and bone

  18. SEP-induced activity and its thermographic cortical representation in a murine model.

    Science.gov (United States)

    Hoffmann, Klaus-Peter; Ruff, Roman; Kirsch, Matthias

    2013-06-01

    This article is a methodical report on the generation of reproducible changes in brain activity in a murine model. Somatosensory evoked potentials (SEP) are used to generate synchronized cortical activity. After electrical stimulation of mice forelimbs, the potentials were recorded with a flexible thin-film polyimide electrode structure directly from the cortex. Every registration included a simultaneous recording from both hemispheres that repeated four times to reproduce and compare the results. The SEPs in the murine model were shown to generate a very stable signal. The latency of the second positive wave (P2 wave) ranged between 16 and 19 ms, and the N1-P2 amplitude ranged between 39 and 48 µV. In addition, the temperature distribution of the cortex was acquired using infrared thermography. Surface cortical temperature changed during electrical stimulation without a clear hemispheric correlation. These initial results could be a step toward a better understanding of the different synchronized cortical activities and basic methods of evaluation of various mathematical algorithms to detect them.

  19. Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

    Science.gov (United States)

    Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

    2013-01-01

    Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes

  20. Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells.

    Science.gov (United States)

    Martínez-Cañada, Pablo; Mobarhan, Milad Hobbi; Halnes, Geir; Fyhn, Marianne; Morillas, Christian; Pelayo, Francisco; Einevoll, Gaute T

    2018-01-01

    Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN) in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs) and interneurons (INs) not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed ('push-pull') and phase-matched ('push-push'), as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli when feedback

  1. Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells.

    Directory of Open Access Journals (Sweden)

    Pablo Martínez-Cañada

    2018-01-01

    Full Text Available Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs and interneurons (INs not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY. We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed ('push-pull' and phase-matched ('push-push', as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli

  2. Biophysical network modeling of the dLGN circuit: Effects of cortical feedback on spatial response properties of relay cells

    Science.gov (United States)

    Martínez-Cañada, Pablo; Halnes, Geir; Fyhn, Marianne

    2018-01-01

    Despite half-a-century of research since the seminal work of Hubel and Wiesel, the role of the dorsal lateral geniculate nucleus (dLGN) in shaping the visual signals is not properly understood. Placed on route from retina to primary visual cortex in the early visual pathway, a striking feature of the dLGN circuit is that both the relay cells (RCs) and interneurons (INs) not only receive feedforward input from retinal ganglion cells, but also a prominent feedback from cells in layer 6 of visual cortex. This feedback has been proposed to affect synchronicity and other temporal properties of the RC firing. It has also been seen to affect spatial properties such as the center-surround antagonism of thalamic receptive fields, i.e., the suppression of the response to very large stimuli compared to smaller, more optimal stimuli. Here we explore the spatial effects of cortical feedback on the RC response by means of a a comprehensive network model with biophysically detailed, single-compartment and multicompartment neuron models of RCs, INs and a population of orientation-selective layer 6 simple cells, consisting of pyramidal cells (PY). We have considered two different arrangements of synaptic feedback from the ON and OFF zones in the visual cortex to the dLGN: phase-reversed (‘push-pull’) and phase-matched (‘push-push’), as well as different spatial extents of the corticothalamic projection pattern. Our simulation results support that a phase-reversed arrangement provides a more effective way for cortical feedback to provide the increased center-surround antagonism seen in experiments both for flashing spots and, even more prominently, for patch gratings. This implies that ON-center RCs receive direct excitation from OFF-dominated cortical cells and indirect inhibitory feedback from ON-dominated cortical cells. The increased center-surround antagonism in the model is accompanied by spatial focusing, i.e., the maximum RC response occurs for smaller stimuli when

  3. 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.

  4. Emergent spatial patterns of excitatory and inhibitory synaptic strengths drive somatotopic representational discontinuities and their plasticity in a computational model of primary sensory cortical area 3b

    Directory of Open Access Journals (Sweden)

    Kamil A. Grajski

    2016-07-01

    Full Text Available Mechanisms underlying the emergence and plasticity of representational discontinuities in the mammalian primary somatosensory cortical representation of the hand are investigated in a computational model. The model consists of an input lattice organized as a three-digit hand forward-connected to a lattice of cortical columns each of which contains a paired excitatory and inhibitory cell. Excitatory and inhibitory synaptic plasticity of feedforward and lateral connection weights is implemented as a simple covariance rule and competitive normalization. Receptive field properties are computed independently for excitatory and inhibitory cells and compared within and across columns. Within digit representational zones intracolumnar excitatory and inhibitory receptive field extents are concentric, single-digit, small, and unimodal. Exclusively in representational boundary-adjacent zones, intracolumnar excitatory and inhibitory receptive field properties diverge: excitatory cell receptive fields are single-digit, small, and unimodal; and the paired inhibitory cell receptive fields are bimodal, double-digit, and large. In simulated syndactyly (webbed fingers, boundary-adjacent intracolumnar receptive field properties reorganize to within-representation type; divergent properties are reacquired following syndactyly release. This study generates testable hypotheses for assessment of cortical laminar-dependent receptive field properties and plasticity within and between cortical representational zones. For computational studies, present results suggest that concurrent excitatory and inhibitory plasticity may underlie novel emergent properties.

  5. Modeling Neurodegenerative Microenvironment Using Cortical Organoids Derived from Human Stem Cells.

    Science.gov (United States)

    Yan, Yuanwei; Song, Liqing; Bejoy, Julie; Zhao, Jing; Kanekiyo, Takahisa; Bu, Guojun; Zhou, Yi; Li, Yan

    2018-02-27

    Alzheimer's disease (AD) is one of the most common neurodegenerative disorders and causes cognitive impairment and memory deficits of the patients. The mechanism of AD is not well known, due to lack of human brain models. Recently, mini-brain tissues called organoids have been derived from human induced pluripotent stem cells (hiPSCs) for modeling human brain development and neurological diseases. Thus, the objective of this research is to model and characterize neural degeneration microenvironment using three-dimensional (3D) forebrain cortical organoids derived from hiPSCs and study the response to the drug treatment. It is hypothesized that the 3D forebrain organoids derived from hiPSCs with AD-associated genetic background may partially recapitulate the extracellular microenvironment in neural degeneration. To test this hypothesis, AD-patient derived hiPSCs with presenilin-1 mutation were used for cortical organoid generation. AD-related inflammatory responses, matrix remodeling and the responses to DAPT, heparin (completes with heparan sulfate proteoglycans [HSPGs] to bind Aβ42), and heparinase (digests HSPGs) treatments were investigated. The results indicate that the cortical organoids derived from AD-associated hiPSCs exhibit a high level of Aβ42 comparing with healthy control. In addition, the AD-derived organoids result in an elevated gene expression of proinflammatory cytokines interleukin-6 and tumor necrosis factor-α, upregulate syndecan-3, and alter matrix remodeling protein expression. Our study demonstrates the capacity of hiPSC-derived organoids for modeling the changes of extracellular microenvironment and provides a potential approach for AD-related drug screening.

  6. Frontal cortical synaptic communication is abnormal in Disc1 genetic mouse models of schizophrenia.

    Science.gov (United States)

    Holley, Sandra M; Wang, Elizabeth A; Cepeda, Carlos; Jentsch, J David; Ross, Christopher A; Pletnikov, Mikhail V; Levine, Michael S

    2013-05-01

    Mouse models carrying Disc1 mutations may provide insights into how Disc1 genetic variations contribute to schizophrenia (SZ) susceptibility. Disc1 mutant mice show behavioral and cognitive disturbances reminiscent of SZ. To dissect the synaptic mechanisms underlying these phenotypes, we examined electrophysiological properties of cortical neurons from two mouse models, the first expressing a truncated mouse Disc1 (mDisc1) protein throughout the entire brain, and the second expressing a truncated human Disc1 (hDisc1) protein in forebrain regions. We obtained whole-cell patch clamp recordings to examine how altered expression of Disc1 protein changes excitatory and inhibitory synaptic transmissions onto cortical pyramidal neurons in the medial prefrontal cortex in 4-7 month-old mDisc1 and hDisc1 mice. In both mDisc1 and hDisc1 mice, the frequency of spontaneous EPSCs was greater than in wild-type littermate controls. Male mice from both lines were more affected by the Disc1 mutation than were females, exhibiting increases in the ratio of excitatory to inhibitory events. Changes in spontaneous IPSCs were only observed in the mDisc1 model and were sex-specific, with diminished cortical GABAergic neurotransmission, a well-documented characteristic of SZ, occurring only in male mDisc1 mice. In contrast, female mDisc1 mice showed an increase in the frequency of small-amplitude sIPSCs. These findings indicate that truncations of Disc1 alter glutamatergic and GABAergic neurotransmission both commonly and differently in the models and some of the effects are sex-specific, revealing how altered Disc1 expression may contribute to behavioral disruptions and cognitive deficits of SZ. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. The Controlled Cortical Impact Model: Applications, Considerations for Researchers, & Future Directions

    Directory of Open Access Journals (Sweden)

    Nicole D. Osier

    2016-08-01

    Full Text Available The cControlled cortical impact model (CCI is a mechanical model of traumatic brain injury (TBI that was developed nearly 30 years ago with the goal of creating a testing platform to determine the biomechanical properties of brain tissue exposed to direct mechanical deformation. Initially used to model TBIs produced by automotive crashes, the CCI model rapidly transformed into a standardized technique to study TBI mechanisms and evaluate therapies. CCI is most commonly produced using a device that rapidly accelerates a rod to impact the surgically exposed cortical dural surface. The tip of the rod can be varied in size and geometry to accommodate scalability to difference species. Typically, the rod is actuated by a pneumatic piston or electro-mechanic actuator. With some limits, CCI devices can control the velocity, depth, duration, and site of impact. The CCI model produces morphologic and cerebrovascular injury responses that resemble certain aspects of human TBI. Commonly observed are graded histologic and axonal derangements, disruption of the blood-brain barrier, subdural and intra-parenchymal hematoma, edema, inflammation, and alterations in cerebral blood flow. The CCI model also produces neurobehavioral and cognitive impairments similar to those observed clinically. In contrast to other TBI models, the CCI device induces a significantly pronounced cortical contusion, but is limited in the extent to which it models the diffuse effects of TBI; a related limitation is that not all clinical TBI cases are characterized by a contusion. Another perceived limitation is that a non-clinically relevant craniotomy is performed. Biomechanically, this is irrelevant at the tissue level. However, craniotomies are not atraumatic and the effects of surgery should be controlled by including surgical sham control groups. CCI devices have also been successfully used to impact closed skulls to study mild and repetitive TBI. Future directions for CCI research

  8. A New Rat Model of Epileptic Spasms Based on Methylazoxymethanol-Induced Malformations of Cortical Development

    Directory of Open Access Journals (Sweden)

    Eun-Hee Kim

    2017-06-01

    Full Text Available Malformations of cortical development (MCDs can cause medically intractable epilepsies and cognitive disabilities in children. We developed a new model of MCD-associated epileptic spasms by treating rats prenatally with methylazoxymethanol acetate (MAM to induce cortical malformations and postnatally with N-methyl-d-aspartate (NMDA to induce spasms. To produce cortical malformations to infant rats, two dosages of MAM (15 mg/kg, intraperitoneally were injected to pregnant rats at gestational day 15. In prenatally MAM-exposed rats and the controls, spasms were triggered by single (6 mg/kg on postnatal day 12 (P12 or 10 mg/kg on P13 or 15 mg/kg on P15 or multiple doses (P12, P13, and P15 of NMDA. In prenatally MAM-exposed rats with single NMDA-provoked spasms at P15, we obtain the intracranial electroencephalography and examine the pretreatment response to adrenocorticotropic hormone (ACTH or vigabatrin. Rat pups prenatally exposed to MAM exhibited a significantly greater number of spasms in response to single and multiple postnatal NMDA doses than vehicle-exposed controls. Vigabatrin treatment prior to a single NMDA dose on P15 significantly suppressed spasms in MAM group rats (p < 0.05, while ACTH did not. The MAM group also showed significantly higher fast oscillation (25–100 Hz power during NMDA-induced spasms than controls (p = 0.047. This new model of MCD-based epileptic spasms with corresponding features of human spasms will be valuable for future research of the developmental epilepsy.

  9. A cortical sparse distributed coding model linking mini- and macrocolumn-scale functionality

    Directory of Open Access Journals (Sweden)

    Gerard J Rinkus

    2010-06-01

    Full Text Available No generic function for the minicolumn—i.e., one that would apply equally well to all cortical areas and species—has yet been proposed. I propose that the minicolumn does have a generic functionality, which only becomes clear when seen in the context of the function of the higher-level, subsuming unit, the macrocolumn. I propose that: a a macrocolumn’s function is to store sparse distributed representations of its inputs and to be a recognizer of those inputs; and b the generic function of the minicolumn is to enforce macrocolumnar code sparseness. The minicolumn, defined here as a physically localized pool of ~20 L2/3 pyramidals, does this by acting as a winner-take-all (WTA competitive module, implying that macrocolumnar codes consist of ~70 active L2/3 cells, assuming ~70 minicolumns per macrocolumn. I describe an algorithm for activating these codes during both learning and retrievals, which causes more similar inputs to map to more highly intersecting codes, a property which yields ultra-fast (immediate, first-shot storage and retrieval. The algorithm achieves this by adding an amount of randomness (noise into the code selection process, which is inversely proportional to an input’s familiarity. I propose a possible mapping of the algorithm onto cortical circuitry, and adduce evidence for a neuromodulatory implementation of this familiarity-contingent noise mechanism. The model is distinguished from other recent columnar cortical circuit models in proposing a generic minicolumnar function in which a group of cells within the minicolumn, the L2/3 pyramidals, compete (WTA to be part of the macrocolumnar code.

  10. 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.

  11. Turing-like structures in a functional model of cortical spreading depression

    Science.gov (United States)

    Verisokin, A. Yu.; Verveyko, D. V.; Postnov, D. E.

    2017-12-01

    Cortical spreading depression (CSD) along with migraine waves and spreading depolarization events with stroke or injures are the front-line examples of extreme physiological behaviors of the brain cortex which manifest themselves via the onset and spreading of localized areas of neuronal hyperactivity followed by their depression. While much is known about the physiological pathways involved, the dynamical mechanisms of the formation and evolution of complex spatiotemporal patterns during CSD are still poorly understood, in spite of the number of modeling studies that have been already performed. Recently we have proposed a relatively simple mathematical model of cortical spreading depression which counts the effects of neurovascular coupling and cerebral blood flow redistribution during CSD. In the present study, we address the main dynamical consequences of newly included pathways, namely, the changes in the formation and propagation speed of the CSD front and the pattern formation features in two dimensions. Our most notable finding is that the combination of vascular-mediated spatial coupling with local regulatory mechanisms results in the formation of stationary Turing-like patterns during a CSD event.

  12. 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.

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

    Science.gov (United States)

    Colciaghi, Francesca; Finardi, Adele; Nobili, Paola; Locatelli, Denise; Spigolon, Giada; Battaglia, Giorgio Stefano

    2014-01-01

    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.

  14. 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

  15. 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...

  16. 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 α 1A subunit of voltage-gated Ca V 2.1 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.

  17. Effects of mechanical loading on cortical defect repair using a novel mechanobiological model of bone healing.

    Science.gov (United States)

    Liu, Chao; Carrera, Robert; Flamini, Vittoria; Kenny, Lena; Cabahug-Zuckerman, Pamela; George, Benson M; Hunter, Daniel; Liu, Bo; Singh, Gurpreet; Leucht, Philipp; Mann, Kenneth A; Helms, Jill A; Castillo, Alesha B

    2018-03-01

    Mechanical loading is an important aspect of post-surgical fracture care. The timing of load application relative to the injury event may differentially regulate repair depending on the stage of healing. Here, we used a novel mechanobiological model of cortical defect repair that offers several advantages including its technical simplicity and spatially confined repair program, making effects of both physical and biological interventions more easily assessed. Using this model, we showed that daily loading (5N peak load, 2Hz, 60 cycles, 4 consecutive days) during hematoma consolidation and inflammation disrupted the injury site and activated cartilage formation on the periosteal surface adjacent to the defect. We also showed that daily loading during the matrix deposition phase enhanced both bone and cartilage formation at the defect site, while loading during the remodeling phase resulted in an enlarged woven bone regenerate. All loading regimens resulted in abundant cellular proliferation throughout the regenerate and fibrous tissue formation directly above the defect demonstrating that all phases of cortical defect healing are sensitive to physical stimulation. Stress was concentrated at the edges of the defect during exogenous loading, and finite element (FE)-modeled longitudinal strain (ε zz ) values along the anterior and posterior borders of the defect (~2200με) was an order of magnitude larger than strain values on the proximal and distal borders (~50-100με). It is concluded that loading during the early stages of repair may impede stabilization of the injury site important for early bone matrix deposition, whereas loading while matrix deposition and remodeling are ongoing may enhance stabilization through the formation of additional cartilage and bone. Published by Elsevier Inc.

  18. 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.

  19. 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

    underlie this dysfunction. Here, we studied the GABAergic system in cortex using patch-clamp recordings in the wobbler mouse, a model of ALS. In layer 5 pyramidal neurons of motor cortex, the frequency of GABA(A) receptor-mediated spontaneous inhibitory postsynaptic currents was reduced by 72% in wobbler......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...... interneurons and reduced vesicular GABA transporter immunoreactivity in the neuropil. Finally, we observed an increased input resistance and excitability of wobbler excitatory neurons, which could be explained by lack of GABA(A) receptor-mediated influences. In conclusion, we demonstrate decreases in GABAergic...

  20. Modelling of Cortical Bone Tissue as a Fluid Saturated Double-Porous Material - Parametric Study

    Directory of Open Access Journals (Sweden)

    Jana TURJANICOVÁ

    2013-06-01

    Full Text Available In this paper, the cortical bone tissue is considered as a poroelastic material with periodic structure represented at microscopic and mesoscopic levels. The pores of microscopic scale are connected with the pores of mesoscopic scale creating one system of connected network filled with compressible fluid. The method of asymptotic homogenization is applied to upscale the microscopic model of the fluid-solid interaction under a static loading. Obtained homogenized coefficients describe material properties of the poroelastic matrix fractured by fluid-filled pores whose geometry is described at the mesoscopic level. The second-level upscaling provides homogenized poroelastic coefficients relevant on the macroscopic scale. Furthermore, we study the dependence of these coefficients on geometrical parameters on related microscopic and macroscopic scales.

  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. 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.

  3. Biomechanics of single cortical neurons.

    Science.gov (United States)

    Bernick, Kristin B; Prevost, Thibault P; Suresh, Subra; Socrate, Simona

    2011-03-01

    This study presents experimental results and computational analysis of the large strain dynamic behavior of single neurons in vitro with the objective of formulating a novel quantitative framework for the biomechanics of cortical neurons. Relying on the atomic force microscopy (AFM) technique, novel testing protocols are developed to enable the characterization of neural soma deformability over a range of indentation rates spanning three orders of magnitude, 10, 1, and 0.1 μm s(-1). Modified spherical AFM probes were utilized to compress the cell bodies of neonatal rat cortical neurons in load, unload, reload and relaxation conditions. The cell response showed marked hysteretic features, strong non-linearities, and substantial time/rate dependencies. The rheological data were complemented with geometrical measurements of cell body morphology, i.e. cross-diameter and height estimates. A constitutive model, validated by the present experiments, is proposed to quantify the mechanical behavior of cortical neurons. The model aimed to correlate empirical findings with measurable degrees of (hyper)elastic resilience and viscosity at the cell level. The proposed formulation, predicated upon previous constitutive model developments undertaken at the cortical tissue level, was implemented in a three-dimensional finite element framework. The simulated cell response was calibrated to the experimental measurements under the selected test conditions, providing a novel single cell model that could form the basis for further refinements. Copyright © 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  4. A viscoelastic, viscoplastic model of cortical bone valid at low and high strain rates.

    Science.gov (United States)

    Johnson, T P M; Socrate, S; Boyce, M C

    2010-10-01

    The stress-strain behavior of cortical bone is well known to be strain-rate dependent, exhibiting both viscoelastic and viscoplastic behavior. Viscoelasticity has been demonstrated in literature data with initial modulus increasing by more than a factor of 2 as applied strain rate is increased from 0.001 to 1500 s(-1). A strong dependence of yield on strain rate has also been reported in the literature, with the yield stress at 250 s(-1) having been observed to be more than twice that at 0.001 s(-1), demonstrating the material viscoplasticity. Constitutive models which capture this rate-dependent behavior from very low to very high strain rates are required in order to model and simulate the full range of loading conditions which may be experienced in vivo; particularly those involving impact, ballistic and blast events. This paper proposes a new viscoelastic, viscoplastic constitutive model which has been developed to meet these requirements. The model is fitted to three sets of stress-strain measurements from the literature and shown to be valid at strain rates ranging over seven orders of magnitude. 2010 Acta Materialia Inc. All rights reserved.

  5. 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 sugge...... 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.......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...

  6. Regularization modeling for large-eddy simulation

    NARCIS (Netherlands)

    Geurts, Bernardus J.; Holm, D.D.

    2003-01-01

    A new modeling approach for large-eddy simulation (LES) is obtained by combining a "regularization principle" with an explicit filter and its inversion. This regularization approach allows a systematic derivation of the implied subgrid model, which resolves the closure problem. The central role of

  7. Models for large superconducting toroidal magnet systems

    International Nuclear Information System (INIS)

    Arendt, F.; Brechna, H.; Erb, J.; Komarek, P.; Krauth, H.; Maurer, W.

    1976-01-01

    Prior to the design of large GJ toroidal magnet systems it is appropriate to procure small scale models, which can simulate their pertinent properties and allow to investigate their relevant phenomena. The important feature of the model is to show under which circumstances the system performance can be extrapolated to large magnets. Based on parameters such as the maximum magnetic field and the current density, the maximum tolerable magneto-mechanical stresses, a simple method of designing model magnets is presented. It is shown how pertinent design parameters are changed when the toroidal dimensions are altered. In addition some conductor cost estimations are given based on reactor power output and wall loading

  8. 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

    2012-01-01

    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 1H 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. PMID:22044866

  9. Constituent models and large transverse momentum reactions

    International Nuclear Information System (INIS)

    Brodsky, S.J.

    1975-01-01

    The discussion of constituent models and large transverse momentum reactions includes the structure of hard scattering models, dimensional counting rules for large transverse momentum reactions, dimensional counting and exclusive processes, the deuteron form factor, applications to inclusive reactions, predictions for meson and photon beams, the charge-cubed test for the e/sup +-/p → e/sup +-/γX asymmetry, the quasi-elastic peak in inclusive hadronic reactions, correlations, and the multiplicity bump at large transverse momentum. Also covered are the partition method for bound state calculations, proofs of dimensional counting, minimal neutralization and quark--quark scattering, the development of the constituent interchange model, and the A dependence of high transverse momentum reactions

  10. 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.

  11. Dynamics of the semantic priming shift: behavioral experiments and cortical network model.

    Science.gov (United States)

    Lavigne, Frédéric; Dumercy, Laurent; Chanquoy, Lucile; Mercier, Brunissende; Vitu-Thibault, Françoise

    2012-12-01

    Multiple semantic priming processes between several related and/or unrelated words are at work during the processing of sequences of words. Multiple priming generates rich dynamics of effects depending on the relationship between the target word and the first and/or second prime previously presented. The experimental literature suggests that during the on-line processing of the primes, the activation can shift from associates to the first prime to associates to the second prime. Though the semantic priming shift is central to the on-line and rapid updating of word meanings in the working memory, its precise dynamics are still poorly understood and it is still a challenge to model how it functions in the cerebral cortex. Four multiple priming experiments are proposed that cross-manipulate delays and association strength between the primes and the target. Results show for the first time that association strength determines complex dynamics of the semantic priming shift, ranging from an absence of a shift to a complete shift. A cortical network model of spike frequency adaptive neuron populations is proposed to account for the non-continuous evolution of the priming shift over time. It allows linking the dynamics of the priming shift assessed at the behavioral level to the non-linear dynamics of the firing rates of neurons populations.

  12. 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.

  13. 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

  14. [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. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  15. Computer modelling of RF ablation in cortical osteoid osteoma: Assessment of the insulating effect of the reactive zone.

    Science.gov (United States)

    Irastorza, Ramiro M; Trujillo, Macarena; Martel Villagrán, Jose; Berjano, Enrique

    2016-05-01

    The aim was to study by computer simulations the insulating role of the reactive zone surrounding a cortical osteoid osteoma (OO) in terms of electrical and thermal performance during radiofrequency ablation (RFA). We modelled a cortical OO consisting of a nidus (10 mm diameter) enclosed by a reactive zone. The OO was near a layer of cortical bone 1.5 mm thick. Trabecular bone partially surrounds the OO and there was muscle around the cortical bone layer. We modelled RF ablations with a non-cooled-tip 17-gauge needle electrode (300 s duration and 90 °C target temperature). Sensitivity analyses were conducted assuming a reactive zone electrical conductivity value (σrz) within the limits of the cortical and trabecular bone, i.e. 0.02 S/m and 0.087 S/m, respectively. In this way we were really modelling the different degrees of osteosclerosis associated with the reactive zone. The presence of the reactive zone drastically reduced the maximum temperature reached outside it. The temperature drop was proportional to the thickness of the reactive zone: from 68 °C when it was absent to 44 °C when it is 7.5 mm thick. Higher nidus conductivity values (σn) implied higher temperatures, while lower temperatures meant higher σrz values. Changing σrz from 0.02 S/m to 0.087 S/m reduced lesion diameters from 2.4 cm to 1.8 cm. The computer results suggest that the reactive zone plays the role of insulator in terms of reducing the temperature in the surrounding area.

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

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Ahmadi, Mandana; Hertz, John

    2004-01-01

    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....

  17. Large Mammalian Animal Models of Heart Disease

    Directory of Open Access Journals (Sweden)

    Paula Camacho

    2016-10-01

    Full Text Available Due to the biological complexity of the cardiovascular system, the animal model is an urgent pre-clinical need to advance our knowledge of cardiovascular disease and to explore new drugs to repair the damaged heart. Ideally, a model system should be inexpensive, easily manipulated, reproducible, a biological representative of human disease, and ethically sound. Although a larger animal model is more expensive and difficult to manipulate, its genetic, structural, functional, and even disease similarities to humans make it an ideal model to first consider. This review presents the commonly-used large animals—dog, sheep, pig, and non-human primates—while the less-used other large animals—cows, horses—are excluded. The review attempts to introduce unique points for each species regarding its biological property, degrees of susceptibility to develop certain types of heart diseases, and methodology of induced conditions. For example, dogs barely develop myocardial infarction, while dilated cardiomyopathy is developed quite often. Based on the similarities of each species to the human, the model selection may first consider non-human primates—pig, sheep, then dog—but it also depends on other factors, for example, purposes, funding, ethics, and policy. We hope this review can serve as a basic outline of large animal models for cardiovascular researchers and clinicians.

  18. Managing large-scale models: DBS

    International Nuclear Information System (INIS)

    1981-05-01

    A set of fundamental management tools for developing and operating a large scale model and data base system is presented. Based on experience in operating and developing a large scale computerized system, the only reasonable way to gain strong management control of such a system is to implement appropriate controls and procedures. Chapter I discusses the purpose of the book. Chapter II classifies a broad range of generic management problems into three groups: documentation, operations, and maintenance. First, system problems are identified then solutions for gaining management control are disucssed. Chapters III, IV, and V present practical methods for dealing with these problems. These methods were developed for managing SEAS but have general application for large scale models and data bases

  19. 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

  20. 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…

  1. Generation and analysis of large reliability models

    Science.gov (United States)

    Palumbo, Daniel L.; Nicol, David M.

    1990-01-01

    An effort has been underway for several years at NASA's Langley Research Center to extend the capability of Markov modeling techniques for reliability analysis to the designers of highly reliable avionic systems. This effort has been focused in the areas of increased model abstraction and increased computational capability. The reliability model generator (RMG), a software tool which uses as input a graphical, object-oriented block diagram of the system, is discussed. RMG uses an automated failure modes-effects analysis algorithm to produce the reliability model from the graphical description. Also considered is the ASSURE software tool, a parallel processing program which uses the ASSIST modeling language and SURE semi-Markov solution technique. An executable failure modes-effects analysis is used by ASSURE. The successful combination of the power of graphical representation, automated model generation, and parallel computation leads to the conclusion that large system architectures can now be analyzed.

  2. 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.

  3. Effect of trabecular bone loss on cortical strain rate during impact in an in vitro model of avian femur

    Directory of Open Access Journals (Sweden)

    Gefen Amit

    2006-07-01

    Full Text Available Abstract Background Osteoporotic hip fractures occur due to loss of cortical and trabecular bone mass and consequent degradation in whole bone strength. The direct cause of most fractures is a fall, and hence, characterizing the mechanical behavior of a whole osteopenic bone under impact is important. However, very little is known about the mechanical interactions between cortical and trabecular bone during impact, and it is specifically unclear to what extent epiphyseal trabecular bone contributes to impact resistance of whole bones. We hypothesized that trabecular bone serves as a structural support to the cortex during impact, and hence, loss of a critical mass of trabecular bone reduces internal constraining of the cortex, and, thereby, decreases the impact tolerance of the whole bone. Methods To test this hypothesis, we conducted cortical strain rate measurements in adult chicken's proximal femora subjected to a Charpy impact test, after removing different trabecular bone core masses to simulate different osteopenic severities. Results We found that removal of core trabecular bone decreased by ~10-fold the cortical strain rate at the side opposite to impact (p Conclusion We conclude that in our in vitro avian model, loss of over 10% of core trabecular bone substantially altered the deformation response of whole bone to impact, which supports the above hypothesis and indicates that integrity of trabecular bone is critical for resisting impact loads.

  4. 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).

  5. Dark radiation in LARGE volume models

    Science.gov (United States)

    Cicoli, Michele; Conlon, Joseph P.; Quevedo, Fernando

    2013-02-01

    We consider reheating driven by volume modulus decays in the LARGE volume scenario. Such reheating always generates nonzero dark radiation through the decays to the axion partner, while the only competitive visible sector decays are Higgs pairs via the Giudice-Masiero term. In the framework of sequestered models where the cosmological moduli problem is absent, the simplest model with a shift-symmetric Higgs sector generates 1.56≤ΔNeff≤1.74. For more general cases, the known experimental bounds on ΔNeff strongly constrain the parameters and matter content of the models.

  6. Modeling a model: Mouse genetics, 22q11.2 Deletion Syndrome, and disorders of cortical circuit development

    Science.gov (United States)

    Meechan, Daniel W.; Maynard, Thomas M.; Fernandez, Alejandra; Karpinski, Beverly A.; Rothblat, Lawrence A.; LaMantia, Anthony S.

    2015-01-01

    Understanding the developmental etiology of autistic spectrum disorders, attention deficit/hyperactivity disorder and schizophrenia remains a major challenge for establishing new diagnostic and therapeutic approaches to these common, difficult-to-treat diseases that compromise neural circuits in the cerebral cortex. One aspect of this challenge is the breadth and overlap of ASD, ADHD, and SCZ deficits; another is the complexity of mutations associated with each, and a third is the difficulty of analyzing disrupted development in at-risk or affected human fetuses. The identification of distinct genetic syndromes that include behavioral deficits similar to those in ASD, ADHC and SCZ provides a critical starting point for meeting this challenge. We summarize clinical and behavioral impairments in children and adults with one such genetic syndrome, the 22q11.2 Deletion Syndrome, routinely called 22q11DS, caused by micro-deletions of between 1.5 and 3.0 MB on human chromosome 22. Among many syndromic features, including cardiovascular and craniofacial anomalies, 22q11DS patients have a high incidence of brain structural, functional, and behavioral deficits that reflect cerebral cortical dysfunction and fall within the spectrum that defines ASD, ADHD, and SCZ. We show that developmental pathogenesis underlying this apparent genetic “model” syndrome in patients can be defined and analyzed mechanistically using genomically accurate mouse models of the deletion that causes 22q11DS. We conclude that “modeling a model”, in this case 22q11DS as a model for idiopathic ASD, ADHD and SCZ, as well as other behavioral disorders like anxiety frequently seen in 22q11DS patients, in genetically engineered mice provides a foundation for understanding the causes and improving diagnosis and therapy for these disorders of cortical circuit development. PMID:25866365

  7. Modelling and control of large cryogenic refrigerator

    International Nuclear Information System (INIS)

    Bonne, Francois

    2014-01-01

    This manuscript is concern with both the modeling and the derivation of control schemes for large cryogenic refrigerators. The particular case of those which are submitted to highly variable pulsed heat load is studied. A model of each object that normally compose a large cryo-refrigerator is proposed. The methodology to gather objects model into the model of a subsystem is presented. The manuscript also shows how to obtain a linear equivalent model of the subsystem. Based on the derived models, advances control scheme are proposed. Precisely, a linear quadratic controller for warm compression station working with both two and three pressures state is derived, and a predictive constrained one for the cold-box is obtained. The particularity of those control schemes is that they fit the computing and data storage capabilities of Programmable Logic Controllers (PLC) with are well used in industry. The open loop model prediction capability is assessed using experimental data. Developed control schemes are validated in simulation and experimentally on the 400W1.8K SBT's cryogenic test facility and on the CERN's LHC warm compression station. (author) [fr

  8. 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).

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

    Science.gov (United States)

    Bornstein, Aaron M; Daw, Nathaniel D

    2013-01-01

    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 be recalled during

  10. 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

  11. Effect of large doses of 131I-19-iodocholesterol on metapyralone-induced adrenal cortical hyperplasia in dogs

    International Nuclear Information System (INIS)

    Anderson, B.G.; Beierwaltes, W.H.; Nishiyama, R.H.; Ice, R.D.

    1975-01-01

    The potential use of 131 I-19-iodocholesterol to treat ACTH excess Cushing's disease was evaluated in the dog. Three normal female dogs were given LD 50 radiation doses of 131 I-19-iodocholesterol without producing gross or histopathologically demonstrable change of the adrenals at autopsy 3 months later. The adrenal cortices of three dogs were made hyperplastic (to simulate the adrenal cortex in Cushing's disease) with ACTH and three with Metapyralone. In addition these six dogs were given LD 50 doses of 131 I-19-iodocholesterol. Three months after treatment, the adrenal glands of the ACTH-treated dogs were not enlarged, the cortex was thicker than normal, and there were no changes attributable to irradiation. At 3 months, the Metapyralone-treated dogs had enlarged adrenals, widening of the adrenal cortex, and no necrosis or other changes attributable to irradiation. It is concluded that a therapeutic trial of 131 I-19-iodocholesterol in the treatment of Cushing's disease is not indicated. (auth)

  12. Neonatal L-glutamine modulates anxiety-like behavior, cortical spreading depression, and microglial immunoreactivity: analysis in developing rats suckled on normal size- and large size litters.

    Science.gov (United States)

    de Lima, Denise Sandrelly Cavalcanti; Francisco, Elian da Silva; Lima, Cássia Borges; Guedes, Rubem Carlos Araújo

    2017-02-01

    In mammals, L-glutamine (Gln) can alter the glutamate-Gln cycle and consequently brain excitability. Here, we investigated in developing rats the effect of treatment with different doses of Gln on anxiety-like behavior, cortical spreading depression (CSD), and microglial activation expressed as Iba1-immunoreactivity. Wistar rats were suckled in litters with 9 and 15 pups (groups L 9 and L 15 ; respectively, normal size- and large size litters). From postnatal days (P) 7-27, the animals received Gln per gavage (250, 500 or 750 mg/kg/day), or vehicle (water), or no treatment (naive). At P28 and P30, we tested the animals, respectively, in the elevated plus maze and open field. At P30-35, we measured CSD parameters (velocity of propagation, amplitude, and duration). Fixative-perfused brains were processed for microglial immunolabeling with anti-IBA-1 antibodies to analyze cortical microglia. Rats treated with Gln presented an anxiolytic behavior and accelerated CSD propagation when compared to the water- and naive control groups. Furthermore, CSD velocity was higher (p litter sizes, and for microglial activation in the L 15 groups. Besides confirming previous electrophysiological findings (CSD acceleration after Gln), our data demonstrate for the first time a behavioral and microglial activation that is associated with early Gln treatment in developing animals, and that is possibly operated via changes in brain excitability.

  13. 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.

  14. 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.

  15. The effect of commitment on relative left frontal cortical activity: tests of the action-based model of dissonance.

    Science.gov (United States)

    Harmon-Jones, Eddie; Harmon-Jones, Cindy; Serra, Raymond; Gable, Philip A

    2011-03-01

    The action-based model of dissonance and recent advances in neuroscience suggest that commitment to action should cause greater relative left frontal cortical activity. Two experiments were conducted in which electroencephalographic activity was recorded following commitment to action, operationalized with a perceived choice manipulation. Perceived high as compared to low choice to engage in the action, regardless of whether it was counterattitudinal or proattitudinal, caused greater relative left frontal cortical activity. Moreover, perceived high as compared to low choice caused attitudes to be more consistent with the action. These results broaden the theoretical reach of the action-based model by suggesting that similar neural and motivational processes are involved in attitudinal responses to counterattitudinal and proattitudinal commitments.

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

    Science.gov (United States)

    Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C

    2013-04-01

    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.

  17. 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.

  18. Periosteal PTHrP regulates cortical bone modeling during linear growth in mice.

    Science.gov (United States)

    Wang, Meina; VanHouten, Joshua N; Nasiri, Ali R; Tommasini, Steven M; Broadus, Arthur E

    2014-07-01

    The modeling of long bone surfaces during linear growth is a key developmental process, but its regulation is poorly understood. We report here that parathyroid hormone-related peptide (PTHrP) expressed in the fibrous layer of the periosteum (PO) drives the osteoclastic (OC) resorption that models the metaphyseal-diaphyseal junction (MDJ) in the proximal tibia and fibula during linear growth. PTHrP was conditionally deleted (cKO) in the PO via Scleraxis gene targeting (Scx-Cre). In the lateral tibia, cKO of PTHrP led to a failure of modeling, such that the normal concave MDJ was replaced by a mound-like deformity. This was accompanied by a failure to induce receptor activator of NF-kB ligand (RANKL) and a 75% reduction in OC number (P ≤ 0.001) on the cortical surface. The MDJ also displayed a curious threefold increase in endocortical osteoblast mineral apposition rate (P ≤ 0.001) and a thickened cortex, suggesting some form of coupling of endocortical bone formation to events on the PO surface. Because it fuses distally, the fibula is modeled only proximally and does so at an extraordinary rate, with an anteromedial cortex in CD-1 mice that was so moth-eaten that a clear PO surface could not be identified. The cKO fibula displayed a remarkable phenotype, with a misshapen club-like metaphysis and an enlargement in the 3D size of the entire bone, manifest as a 40-45% increase in the PO circumference at the MDJ (P ≤ 0.001) as well as the mid-diaphysis (P ≤ 0.001). These tibial and fibular phenotypes were reproduced in a Scx-Cre-driven RANKL cKO mouse. We conclude that PTHrP in the fibrous PO mediates the modeling of the MDJ of long bones during linear growth, and that in a highly susceptible system such as the fibula this surface modeling defines the size and shape of the entire bone. © 2014 Anatomical Society.

  19. Large-scale multimedia modeling applications

    International Nuclear Information System (INIS)

    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

  20. On spinfoam models in large spin regime

    International Nuclear Information System (INIS)

    Han, Muxin

    2014-01-01

    We study the semiclassical behavior of Lorentzian Engle–Pereira–Rovelli–Livine (EPRL) spinfoam model, by taking into account the sum over spins in the large spin regime. We also employ the method of stationary phase analysis with parameters and the so-called, almost analytic machinery, in order to find the asymptotic behavior of the contributions from all possible large spin configurations in the spinfoam model. The spins contributing the sum are written as J f = λj f , where λ is a large parameter resulting in an asymptotic expansion via stationary phase approximation. The analysis shows that at least for the simplicial Lorentzian geometries (as spinfoam critical configurations), they contribute the leading order approximation of spinfoam amplitude only when their deficit angles satisfy γ Θ-ring f ≤λ −1/2 mod 4πZ. Our analysis results in a curvature expansion of the semiclassical low energy effective action from the spinfoam model, where the UV modifications of Einstein gravity appear as subleading high-curvature corrections. (paper)

  1. AAV-mediated targeting of gene expression to the peri-infarct region in rat cortical stroke model.

    Science.gov (United States)

    Mätlik, Kert; Abo-Ramadan, Usama; Harvey, Brandon K; Arumäe, Urmas; Airavaara, Mikko

    2014-10-30

    For stroke patients the recovery of cognitive and behavioral functions is often incomplete. Functional recovery is thought to be mediated largely by connectivity rearrangements in the peri-infarct region. A method for manipulating gene expression in this region would be useful for identifying new recovery-enhancing treatments. We have characterized a way of targeting adeno-associated virus (AAV) vectors to the peri-infarct region of cortical ischemic lesion in rats 2days after middle cerebral artery occlusion (MCAo). We used magnetic resonance imaging (MRI) to show that the altered properties of post-ischemic brain tissue facilitate the spreading of intrastriatally injected nanoparticles toward the infarct. We show that subcortical injection of green fluorescent protein-encoding dsAAV7-GFP resulted in transduction of cells in and around the white matter tract underlying the lesion, and in the cortex proximal to the lesion. A similar result was achieved with dsAAV7 vector encoding the cerebral dopamine neurotrophic factor (CDNF), a protein with therapeutic potential. Viral vector-mediated intracerebral gene delivery has been used before in rodent models of ischemic injury. However, the method of targeting gene expression to the peri-infarct region, after the initial phase of ischemic cell death, has not been described before. We demonstrate a straightforward and robust way to target AAV vector-mediated over-expression of genes to the peri-infarct region in a rat stroke model. This method will be useful for studying the action of specific proteins in peri-infarct region during the recovery process. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Inter-synaptic learning of combination rules in a cortical network model

    Directory of Open Access Journals (Sweden)

    Frédéric eLavigne

    2014-08-01

    Full Text Available Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons.Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network.

  3. Modelling large-scale hydrogen infrastructure development

    International Nuclear Information System (INIS)

    De Groot, A.; Smit, R.; Weeda, M.

    2005-08-01

    In modelling a possible H2 infrastructure development the following questions are answered in this presentation: How could the future demand for H2 develop in the Netherlands?; and In which year and where would it be economically viable to construct a H2 infrastructure in the Netherlands? Conclusions are that: A model for describing a possible future H2 infrastructure is successfully developed; The model is strongly regional and time dependent; Decrease of fuel cell cost appears to be a sensitive parameter for development of H2 demand; Cost-margin between large-scale and small-scale H2 production is a main driver for development of a H2 infrastructure; A H2 infrastructure seems economically viable in the Netherlands starting from the year 2022

  4. Left frontal cortical activation and spreading of alternatives: tests of the action-based model of dissonance.

    Science.gov (United States)

    Harmon-Jones, Eddie; Harmon-Jones, Cindy; Fearn, Meghan; Sigelman, Jonathan D; Johnson, Peter

    2008-01-01

    The action-based model of dissonance predicts that following decisional commitment, approach-oriented motivational processes occur to assist in translating the decision into effective and unconflicted behavior. Therefore, the modulation of these approach-oriented processes should affect the degree to which individuals change their attitudes to be more consistent with the decisional commitment (spreading of alternatives). Experiment 1 demonstrated that a neurofeedback-induced decrease in relative left frontal cortical activation, which has been implicated in approach motivational processes, caused a reduction in spreading of alternatives. Experiment 2 manipulated an action-oriented mindset following a decision and demonstrated that the action-oriented mindset caused increased activation in the left frontal cortical region as well as increased spreading of alternatives. Discussion focuses on how this integration of neuroscience and dissonance theory benefits both parent literatures. Copyright 2008 APA, all rights reserved.

  5. Cortical Thought Theory: A Working Model of the Human Gestalt Mechanism.

    Science.gov (United States)

    1985-07-01

    2. The Artificial Inteligence Perspective • -° 2.1 Introduction: Chapter Overview This chapter addresses the development of a...6 . . 2. The Artificial Intelligence Perspective ... .......... 9 2.1 Introduction: Chapter Overview .... ........... 9 2.2 The Problem 9...new unified theory of human brain function called Cortical Thought Theory (CTT). The analysis integrates the disciplines of Artificial Intelligence

  6. 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

  7. Chronic immobilization stress occludes in vivo cortical activation in an animal model of panic induced by carbon dioxide inhalation

    Directory of Open Access Journals (Sweden)

    Mohammed Mostafizur eRahman

    2014-09-01

    Full Text Available Breathing high concentrations of carbon dioxide (CO2 can trigger panic and anxiety in humans. CO2 inhalation has been hypothesized to activate neural systems similar to those underlying fear learning, especially those involving the amygdala. Amygdala activity is also upregulated by stress. Recently, however, a separate pathway has been proposed for interoceptive panic and anxiety signals, as patients exhibited CO2-inhalation induced panic responses despite bilateral lesions of the amygdala. This paradoxical observation has raised the possibility that cortical circuits may underlie these responses. We sought to examine these divergent models by comparing in vivo brain activation in unstressed and chronically-stressed rats breathing CO2. Regional cerebral blood flow measurements using functional Magnetic Resonance Imaging (fMRI in lightly-anaesthetized rats showed especially strong activation of the somatosensory cortex by CO2 inhalation in the unstressed group. Strikingly, prior exposure to chronic stress occluded this effect on cortical activity. This lends support to recent clinical observations and highlights the importance of looking beyond the traditional focus on limbic structures, such as the hippocampus and amygdala, to investigate a role for cortical areas in panic and anxiety in humans.

  8. Using a virtual cortical module implementing a neural field model to modulate brain rhythms in Parkinson's disease

    Directory of Open Access Journals (Sweden)

    Julien Modolo

    2010-06-01

    Full Text Available We propose a new method for selective modulation of cortical rhythms based on neural field theory, in which the activity of a cortical area is extensively monitored using a two-dimensional microelectrode array. The example of Parkinson's disease illustrates the proposed method, in which a neural field model is assumed to accurately describe experimentally recorded activity. In addition, we propose a new closed-loop stimulation signal that is both space- and time- dependent. This method is especially designed to specifically modulate a targeted brain rhythm, without interfering with other rhythms. A new class of neuroprosthetic devices is also proposed, in which the multielectrode array is seen as an artificial neural network interacting with biological tissue. Such a bio-inspired approach may provide a solution to optimize interactions between the stimulation device and the cortex aiming to attenuate or augment specific cortical rhythms. The next step will be to validate this new approach experimentally in patients with Parkinson's disease.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. Modeling chronic brain exposure to amphetamines using primary rat neuronal cortical cultures.

    Science.gov (United States)

    Nogueira, T B; da Costa Araújo, S; Carvalho, F; Pereira, F C; Fernandes, E; Bastos, M L; Costa, V M; Capela, J P

    2014-09-26

    Amphetamine-type psychostimulants (ATS) are used worldwide by millions of patients for several psychiatric disorders. Amphetamine (AMPH) and "ecstasy" (3,4-methylenedioxymethamphetamine or MDMA) are common drugs of abuse. The impact of chronic ATS exposure to neurons and brain aging is still undisclosed. Current neuronal culture paradigms are designed to access acute ATS toxicity. We report for the first time a model of chronic exposure to AMPH and MDMA using long-term rat cortical cultures. In two paradigms, ATS were applied to neurons at day 1 in vitro (DIV) (0, 1, 10 and 100 μM of each drug) up to 28 days (200 μM was applied to cultures up to 14 DIV). Our reincubation protocol assured no decrease in the neuronal media's drug concentration. Chronic exposure of neurons to concentrations equal to or above 100 μM of ATS up to 28 DIV promoted significant mitochondrial dysfunction and elicited neuronal death, which was not prevented by glutamate receptor antagonists at 14 DIV. ATS failed to promote accelerated senescence as no increase in β-galactosidase activity at 21 DIV was found. In younger cultures (4 or 8 DIV), AMPH promoted mitochondrial dysfunction and neuronal death earlier than MDMA. Overall, AMPH proved more toxic and was the only drug that decreased intraneuronal glutathione levels. Meanwhile, caspase 3 activity increased for either drug at 200 μM in younger cultures at 8 DIV, but not at 14 DIV. At 8 DIV, ATS promoted a significant change in the percentage of neurons and astroglia present in culture, promoting a global decrease in the number of both cells. Importantly, concentrations equal to or below 10 μM of either drug did not promote neuronal death or oxidative stress. Our paradigm of neuronal cultures long-term exposure to low micromolar concentrations of ATS closely reproduces the in vivo scenario, being valuable to study the chronic impact of ATS. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  13. 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

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

    Science.gov (United States)

    Khaligh-Razavi, Seyed-Mahdi; Kriegeskorte, Nikolaus

    2014-11-01

    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

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

    Directory of Open Access Journals (Sweden)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Abnormal Development of the Earliest Cortical Circuits in a Mouse Model of Autism Spectrum Disorder

    Directory of Open Access Journals (Sweden)

    Daniel A. Nagode

    2017-01-01

    Full Text Available Autism spectrum disorder (ASD involves deficits in speech and sound processing. Cortical circuit changes during early development likely contribute to such deficits. Subplate neurons (SPNs form the earliest cortical microcircuits and are required for normal development of thalamocortical and intracortical circuits. Prenatal valproic acid (VPA increases ASD risk, especially when present during a critical time window coinciding with SPN genesis. Using optical circuit mapping in mouse auditory cortex, we find that VPA exposure on E12 altered the functional excitatory and inhibitory connectivity of SPNs. Circuit changes manifested as “patches” of mostly increased connection probability or strength in the first postnatal week and as general hyper-connectivity after P10, shortly after ear opening. These results suggest that prenatal VPA exposure severely affects the developmental trajectory of cortical circuits and that sensory-driven activity may exacerbate earlier, subtle connectivity deficits. Our findings identify the subplate as a possible common pathophysiological substrate of deficits in ASD.

  18. Black holes from large N singlet models

    Science.gov (United States)

    Amado, Irene; Sundborg, Bo; Thorlacius, Larus; Wintergerst, Nico

    2018-03-01

    The emergent nature of spacetime geometry and black holes can be directly probed in simple holographic duals of higher spin gravity and tensionless string theory. To this end, we study time dependent thermal correlation functions of gauge invariant observables in suitably chosen free large N gauge theories. At low temperature and on short time scales the correlation functions encode propagation through an approximate AdS spacetime while interesting departures emerge at high temperature and on longer time scales. This includes the existence of evanescent modes and the exponential decay of time dependent boundary correlations, both of which are well known indicators of bulk black holes in AdS/CFT. In addition, a new time scale emerges after which the correlation functions return to a bulk thermal AdS form up to an overall temperature dependent normalization. A corresponding length scale was seen in equal time correlation functions in the same models in our earlier work.

  19. Cortical herniation through compressive subdural membrane in an infant with a history of a large bihemispheric subdural hematoma and subdural-peritoneal shunt: case report.

    Science.gov (United States)

    Scoco, Aleka; Emily Bennett, E; Recinos, Violette

    2017-02-01

    Cortical herniation through subdural membrane formation is a rare complication of chronic subdural fluid collections and may occur following subdural shunting. The authors present a unique case of progressive cortical herniation through a compressive subdural membrane that occurred concomitant with a functioning subdural-peritoneal shunt.

  20. 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

  1. 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.

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

    Science.gov (United States)

    2013-02-01

    other aspect of this collection of information, including suggestions for reducing the burden, to the Department of Defense, Executive Services and...Firstly, they are more capable than regular recurrent networks (RNNs), such as the Elman network, in capturing temporal information. Secondly, CSRNs

  3. 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

  4. How the Cortex Gets Its Folds: An Inside-Out, Connectivity-Driven Model for the Scaling of Mammalian Cortical Folding

    Science.gov (United States)

    Mota, Bruno; Herculano-Houzel, Suzana

    2012-01-01

    Larger mammalian cerebral cortices tend to have increasingly folded surfaces, often considered to result from the lateral expansion of the gray 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 inward. As an important necessary simplifying hypothesis, we assume that axons leaving or entering the WM do so approximately perpendicularly to the WM–GM interface. 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 average 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

  5. 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

  6. 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. © The Author(s) 2015.

  7. 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

  8. Random Coefficient Logit Model for Large Datasets

    NARCIS (Netherlands)

    C. Hernández-Mireles (Carlos); D. Fok (Dennis)

    2010-01-01

    textabstractWe present an approach for analyzing market shares and products price elasticities based on large datasets containing aggregate sales data for many products, several markets and for relatively long time periods. We consider the recently proposed Bayesian approach of Jiang et al [Jiang,

  9. 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.

  10. A fuzzy logic model for hand posture control using human cortical activity recorded by micro-ECog electrodes.

    Science.gov (United States)

    Vinjamuri, R; Weber, D J; Degenhart, A D; Collinger, J L; Sudre, G P; Adelson, P D; Holder, D L; Boninger, M L; Schwartz, A B; Crammond, D J; Tyler-Kabara, E C; Wang, W

    2009-01-01

    This paper presents a fuzzy logic model to decode the hand posture from electro-cortico graphic (ECoG) activity of the motor cortical areas. One subject was implanted with a micro-ECoG electrode array on the surface of the motor cortex. Neural signals were recorded from 14 electrodes on this array while Subject participated in three reach and grasp sessions. In each session, Subject reached and grasped a wooden toy hammer for five times. Optimal channels/electrodes which were active during the task were selected. Power spectral densities of optimal channels averaged over a time period of 1/2 second before the onset of the movement and 1 second after the onset of the movement were fed into a fuzzy logic model. This model decoded whether the posture of the hand is open or closed with 80% accuracy. Hand postures along the task time were decoded by using the output from the fuzzy logic model by two methods (i) velocity based decoding (ii) acceleration based decoding. The latter performed better when hand postures predicted by the model were compared to postures recorded by a data glove during the experiment. This fuzzy logic model was imported to MATLABSIMULINK to control a virtual hand.

  11. Rehabilitative training promotes rapid motor recovery but delayed motor map reorganization in a rat cortical ischemic infarct model.

    Science.gov (United States)

    Nishibe, Mariko; Urban, Edward T R; Barbay, Scott; Nudo, Randolph J

    2015-06-01

    In preclinical stroke models, improvement in motor performance is associated with reorganization of cortical motor maps. However, the temporal relationship between performance gains and map plasticity is not clear. This study was designed to assess the effects of rehabilitative training on the temporal dynamics of behavioral and neurophysiological endpoints in a rat model of focal cortical infarct. Eight days after an ischemic infarct in primary motor cortex, adult rats received either rehabilitative training or were allowed to recover spontaneously. Motor performance and movement quality of the paretic forelimb was assessed on a skilled reach task. Intracortical microstimulation mapping procedures were conducted to assess the topography of spared forelimb representations either at the end of training (post-lesion day 18) or at the end of a 3-week follow-up period (post-lesion day 38). Rats receiving rehabilitative training demonstrated more rapid improvement in motor performance and movement quality during the training period that persisted through the follow-up period. Motor maps in both groups were unusually small on post-lesion day 18. On post-lesion day 38, forelimb motor maps in the rehabilitative training group were significantly enlarged compared with the no-rehab group, and within the range of normal maps. Postinfarct rehabilitative training rapidly improves motor performance and movement quality after an ischemic infarct in motor cortex. However, training-induced motor improvements are not reflected in spared motor maps until substantially later, suggesting that early motor training after stroke can help shape the evolving poststroke neural network. © The Author(s) 2014.

  12. 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.

  13. Holonic Modelling of Large Scale Geographic Environments

    Science.gov (United States)

    Mekni, Mehdi; Moulin, Bernard

    In this paper, we propose a novel approach to model Virtual Geographic Environments (VGE) which uses the holonic approach as a computational geographic methodology and holarchy as organizational principle. Our approach allows to automatically build VGE using data provided by Geographic Information Systems (GIS) and enables an explicit representation of the geographic environment for Situated Multi-Agent Systems (SMAS) in which agents are situated and with which they interact. In order to take into account geometric, topologic, and semantic characteristics of the geographic environment, we propose the use of the holonic approach to build the environment holarchy. We illustrate our holonic model using two different environments: an urban environment and a natural environment.

  14. Enhanced Burst-Suppression and Disruption of Local Field Potential Synchrony in a Mouse Model of Focal Cortical Dysplasia Exhibiting Spike-Wave Seizures

    Directory of Open Access Journals (Sweden)

    Anthony J. Williams

    2016-11-01

    Full Text Available Focal cortical dysplasias (FCDs are a common cause of brain seizures and are often associated with intractable epilepsy. Here we evaluated aberrant brain neurophysiology in an in vivo mouse model of FCD induced by neonatal freeze lesions (FLs to the right cortical hemisphere (near S1. Linear multi-electrode arrays were used to record extracellular potentials from cortical and subcortical brain regions near the FL in anesthetized mice (5-13 months old followed by 24 h cortical EEG recordings. Results indicated that FL animals exhibit a high prevalence of spontaneous spike-wave discharges (SWDs, predominately during sleep (EEG, and an increase in the incidence of hyper-excitable burst/suppression activity under general anesthesia (extracellular recordings, 0.5-3.0% isoflurane. Brief periods of burst activity in the local field potential (LFP typically presented as an arrhythmic pattern of increased theta-alpha spectral peaks (4-12 Hz on a background of low-amplitude delta activity (1-4 Hz, were associated with an increase in spontaneous spiking of cortical neurons, and were highly synchronized in control animals across recording sites in both cortical and subcortical layers (average cross-correlation values ranging from +0.73 to +1.0 with minimal phase shift between electrodes. However, in FL animals, cortical vs. subcortical burst activity was strongly out of phase with significantly lower cross-correlation values compared to controls (average values of -0.1 to +0.5, P<0.05 between groups. In particular, a marked reduction in the level of synchronous burst activity was observed the closer the recording electrodes were to the malformation (Pearson’s Correlation = 0.525, P<0.05. In a subset of FL animals (3/9, burst activity also included a spike or spike-wave pattern similar to the SWDs observed in unanesthetized animals. In summary, neonatal FLs increased the hyperexcitable pattern of burst activity induced by anesthesia and disrupted field

  15. 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 ...

  16. Stress Analysis of Osteoporotic Lumbar Vertebra Using Finite Element Model with Microscaled Beam-Shell Trabecular-Cortical Structure

    Directory of Open Access Journals (Sweden)

    Yoon Hyuk Kim

    2013-01-01

    Full Text Available Osteoporosis is a disease in which low bone mass and microarchitectural deterioration of bone tissue lead to enhanced bone fragility and susceptibility to fracture. Due to the complex anatomy of the vertebral body, the difficulties associated with obtaining bones for in vitro experiments, and the limitations on the control of the experimental parameters, finite element models have been developed to analyze the biomechanical properties of the vertebral body. We developed finite element models of the L2 vertebra, which consisted of the endplates, the trabecular lattice, and the cortical shell, for three age-related grades (young, middle, and old of osteoporosis. The compressive strength and stiffness results revealed that we had developed a valid model that was consistent with the results of previous experimental and computational studies. The von-Mises stress, which was assumed to predict the risk of a burst fracture, was also determined for the three age groups. The results showed that the von-Mises stress was substantially higher under relatively high levels of compressive loading, which suggests that patients with osteoporosis should be cautious of fracture risk even during daily activities.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. Long-Term Calculations with Large Air Pollution Models

    DEFF Research Database (Denmark)

    Ambelas Skjøth, C.; Bastrup-Birk, A.; Brandt, J.

    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...

  2. Constituent rearrangement model and large transverse momentum reactions

    International Nuclear Information System (INIS)

    Igarashi, Yuji; Imachi, Masahiro; Matsuoka, Takeo; Otsuki, Shoichiro; Sawada, Shoji.

    1978-01-01

    In this chapter, two models based on the constituent rearrangement picture for large p sub( t) phenomena are summarized. One is the quark-junction model, and the other is the correlating quark rearrangement model. Counting rules of the models apply to both two-body reactions and hadron productions. (author)

  3. 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...... compartment. A global optimum was found from a wide range of parameter permutations using cluster computing. We also present simulations of cell swelling and changes of exchange rate and intracellular diffusion as possible cellular mechanisms in ischemia. RESULTS: Our model estimates an extracellular volume...... fraction of 0.19 in accordance with the accepted value from histology. The absolute apparent diffusion coefficient obtained from the model was similar to that of experiments. The model and the experimental results indicate significant differences in diffusion and transverse relaxation between the tissue...

  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. Metrics for cortical map organization and lateralization.

    Science.gov (United States)

    Alvarez, S A; Levitan, S; Reggia, J A

    1998-01-01

    Cerebral lateralization refers to the poorly understood fact that some functions are better controlled by one side of the brain than the other (e.g. handedness, language). Of particular concern here are the asymmetries apparent in cortical topographic maps that can be demonstrated electrophysiologically in mirror-image locations of the cerebral cortex. In spite of great interest in issues surrounding cerebral lateralization, methods for measuring the degree of organization and asymmetry in cortical maps are currently quite limited. In this paper, several measures are developed and used to assess the degree of organization, lateralization, and mirror symmetry in topographic map formation. These measures correct for large constant displacements as well as curving of maps. The behavior of the measures is tested on several topographic maps obtained by self-organization of an initially random artificial neural network model of a bihemispheric brain, and the results are compared with subjective assessments made by humans.

  6. 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...... by glucocorticoid treatment and the changes in properties of cancellous bone were comparable with those observed in humans after long-term glucocorticoid treatment. However, the influence on cortical bone has not been thoroughly elucidated. This study aimed to investigate the influence of glucocorticoid on sheep...... cortical bone after long-term treatment. Specifically, we quantify the microarchitecture, mechanical properties, collagen and mineral quality of sheep cortical bone. We hypothesized that glucocorticoid treatment also had significant influences on cortical bone that might increase risk of fracture...

  7. Recapitulating cortical development with organoid culture in vitro and modeling abnormal spindle-like (ASPM related primary microcephaly disease

    Directory of Open Access Journals (Sweden)

    Rui Li

    2017-10-01

    Full Text Available Abstract The development of a cerebral organoid culture in vitro offers an opportunity to generate human brain-like organs to investigate mechanisms of human disease that are specific to the neurogenesis of radial glial (RG and outer radial glial (oRG cells in the ventricular zone (VZ and subventricular zone (SVZ of the developing neocortex. Modeling neuronal progenitors and the organization that produces mature subcortical neuron subtypes during early stages of development is essential for studying human brain developmental diseases. Several previous efforts have shown to grow neural organoid in culture dishes successfully, however we demonstrate a new paradigm that recapitulates neocortical development process with VZ, OSVZ formation and the lamination organization of cortical layer structure. In addition, using patient-specific induced pluripotent stem cells (iPSCs with dysfunction of the Aspm gene from a primary microcephaly patient, we demonstrate neurogenesis defects result in defective neuronal activity in patient organoids, suggesting a new strategy to study human developmental diseases in central nerve system.

  8. Assessing cortical and subcortical changes in a western diet mouse model using spectral/Fourier domain OCT (Conference Presentation)

    Science.gov (United States)

    Bernucci, Marcel T.; Norman, Jennifer E.; Merkle, Conrad W.; Aung, Hnin H.; Rutkowsky, Jennifer; Rutledge, John C.; Srinivasan, Vivek J.

    2017-02-01

    The Western diet, causative in the development of atherosclerotic cardiovascular disease, has recently been associated with the development of diffuse white matter disease (WMD) and other subcortical changes. Yet, little is known about the pathophysiological mechanisms by which a high-fat diet can cause WMD. Mechanistic studies of deep brain regions in mice have been challenging due to a lack of non-invasive, high-resolution, and deep imaging technologies. Here we used Optical Coherence Tomography to study mouse cortical/subcortical structures noninvasively and in vivo. To better understand the role of Western Diet in the development of WMD, intensity and Doppler flow OCT images, obtained using a 1300 nm spectral / Fourier domain OCT system, were used to observe the structural and functional alterations in the cortex and corpus callosum of Western Diet and control diet mouse models. Specifically, we applied segmentation to the OCT images to identify the boundaries of the cortex/corpus callosum, and further quantify the layer thicknesses across animals between the two diet groups. Furthermore, microvasculature alterations such as changes in spatiotemporal flow profiles within diving arterioles, arteriole diameter, and collateral tortuosity were analyzed. In the current study, while the arteriole vessel diameters between the two diet groups was comparable, we show that collateral tortuosity was significantly higher in the Western diet group, compared to control diet group, possibly indicating remodeling of brain vasculature due to dietary changes. Moreover, there is evidence showing that the corpus callosum is thinner in Western diet mice, indicative of tissue atrophy.

  9. A neural network model for the self-organization of cortical grating cells.

    Science.gov (United States)

    Bauer, C; Burger, T; Stetter, M; Lang, E W

    2000-01-01

    A neural network model with incremental Hebbian learning of afferent and lateral synaptic couplings is proposed,which simulates the activity-dependent self-organization of grating cells in upper layers of striate cortex. These cells, found in areas V1 and V2 of the visual cortex of monkeys, respond vigorously and exclusively to bar gratings of a preferred orientation and periodicity. Response behavior to varying contrast and to an increasing number of bars in the grating show threshold and saturation effects. Their location with respect to the underlying orientation map and their nonlinear response behavior are investigated. The number of emerging grating cells is controlled in the model by the range and strength of the lateral coupling structure.

  10. Cortical visual impairment

    OpenAIRE

    Koželj, Urša

    2013-01-01

    In this thesis we discuss cortical visual impairment, diagnosis that is in the developed world in first place, since 20 percent of children with blindness or low vision are diagnosed with it. The objectives of the thesis are to define cortical visual impairment and the definition of characters suggestive of the cortical visual impairment as well as to search for causes that affect the growing diagnosis of cortical visual impairment. There are a lot of signs of cortical visual impairment. ...

  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. 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...

  13. 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.

  14. Synaptic augmentation in a cortical circuit model reproduces serial dependence in visual working memory.

    Directory of Open Access Journals (Sweden)

    Daniel P Bliss

    Full Text Available Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic "activity-silent" synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior.

  15. Increased homocysteine levels impair reference memory and reduce cortical levels of acetylcholine in a mouse model of vascular cognitive impairment.

    Science.gov (United States)

    Dam, Kevin; Füchtemeier, Martina; Farr, Tracy D; Boehm-Sturm, Philipp; Foddis, Marco; Dirnagl, Ulrich; Malysheva, Olga; Caudill, Marie A; Jadavji, Nafisa M

    2017-03-15

    Folates are B-vitamins that are vital for normal brain function. Deficiencies in folates either genetic (methylenetetrahydrofolate reductase, MTHFR) or dietary intake of folic acid result in elevated levels of homocysteine. Clinical studies have shown that elevated levels of homocysteine (Hcy) may be associated with the development of dementia, however this link remains unclear. The purpose of this study was to evaluate the impact of increased Hcy levels on a mouse model of vascular cognitive impairment (VCI) produced by chronic hypoperfusion. Male and female Mthfr +/+ and Mthfr +/- mice were placed on either control (CD) or folic acid deficient (FADD) diets after which all animals underwent microcoil implantation around each common carotid artery or a sham procedure. Post-operatively animals were tested on the Morris water maze (MWM), y-maze, and rotarod. Animals had no motor impairments on the rotarod, y-maze, and could learn the location of the platform on the MWM. However, on day 8 of testing of MWM testing during the probe trial, Mthfr +/- FADD microcoil mice spent significantly less time in the target quadrant when compared to Mthfr +/- CD sham mice, suggesting impaired reference memory. All FADD mice had elevated levels of plasma homocysteine. MRI analysis revealed arterial remodeling was present in Mthfr +/- microcoil mice not Mthfr +/+ mice. Acetylcholine and related metabolites were reduced in cortical tissue because of microcoil implantation and elevated levels of homocysteine. Deficiencies in folate metabolism resulting in increased Hcy levels yield a metabolic profile that increases susceptibility to neurodegeneration in a mouse model of VCI. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. 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.

  17. Regularization modeling for large-eddy simulation of diffusion flames

    NARCIS (Netherlands)

    Geurts, Bernardus J.; Wesseling, P.; Oñate, E.; Périaux, J.

    We analyze the evolution of a diffusion flame in a turbulent mixing layer using large-eddy simulation. The large-eddy simulation includes Leray regularization of the convective transport and approximate inverse filtering to represent the chemical source terms. The Leray model is compared to the more

  18. Advances in Modelling of Large Scale Coastal Evolution

    NARCIS (Netherlands)

    Stive, M.J.F.; De Vriend, H.J.

    1995-01-01

    The attention for climate change impact on the world's coastlines has established large scale coastal evolution as a topic of wide interest. Some more recent advances in this field, focusing on the potential of mathematical models for the prediction of large scale coastal evolution, are discussed.

  19. Nuclear spectroscopy in large shell model spaces: recent advances

    International Nuclear Information System (INIS)

    Kota, V.K.B.

    1995-01-01

    Three different approaches are now available for carrying out nuclear spectroscopy studies in large shell model spaces and they are: (i) the conventional shell model diagonalization approach but taking into account new advances in computer technology; (ii) the recently introduced Monte Carlo method for the shell model; (iii) the spectral averaging theory, based on central limit theorems, in indefinitely large shell model spaces. The various principles, recent applications and possibilities of these three methods are described and the similarity between the Monte Carlo method and the spectral averaging theory is emphasized. (author). 28 refs., 1 fig., 5 tabs

  20. 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

  1. 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

  2. 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

  3. 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...

  4. Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice

    NARCIS (Netherlands)

    Callot, Laurent A.F.; Kock, Anders B.; Medeiros, Marcelo C.

    2017-01-01

    We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso-type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast

  5. 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.

  6. Synaptic Changes in AMPA Receptor Subunit Expression in Cortical Parvalbumin Interneurons in the Stargazer Model of Absence Epilepsy

    Directory of Open Access Journals (Sweden)

    Nadia K. Adotevi

    2017-12-01

    Full Text Available Feedforward inhibition is essential to prevent run away excitation within the brain. Recent evidence suggests that a loss of feed-forward inhibition in the corticothalamocortical circuitry may underlie some absence seizures. However, it is unclear if this aberration is specifically linked to loss of synaptic excitation onto local fast-spiking parvalbumin-containing (PV+ inhibitory interneurons, which are responsible for mediating feedforward inhibition within cortical networks. We recently reported a global tissue loss of AMPA receptors (AMPARs, and a specific mistrafficking of these AMPARs in PV+ interneurons in the stargazer somatosensory cortex. The current study was aimed at investigating if cellular changes in AMPAR expression were translated into deficits in receptors at specific synapses in the feedforward inhibitory microcircuit. Using western blot immunolabeling on biochemically isolated synaptic fractions, we demonstrate a loss of AMPAR GluA1–4 subunits in the somatosensory cortex of stargazers compared to non-epileptic control mice. Furthermore, using double post-embedding immunogold-cytochemistry, we show a loss of GluA1–4-AMPARs at excitatory synapses onto cortical PV+ interneurons. Altogether, these data indicate a loss of synaptic AMPAR-mediated excitation of cortical PV+ inhibitory neurons. As the cortex is considered the site of initiation of spike wave discharges (SWDs within the corticothalamocortical circuitry, loss of AMPARs at cortical PV+ interneurons likely impairs feed-forward inhibitory output, and contributes to the generation of SWDs and absence seizures in stargazers.

  7. Cognitive reserve and cortical thickness in preclinical Alzheimer's disease.

    Science.gov (United States)

    Pettigrew, Corinne; Soldan, Anja; Zhu, Yuxin; Wang, Mei-Cheng; Brown, Timothy; Miller, Michael; Albert, Marilyn

    2017-04-01

    This study examined whether cognitive reserve (CR) alters the relationship between magnetic resonance imaging (MRI) measures of cortical thickness and risk of progression from normal cognition to the onset of clinical symptoms associated with mild cognitive impairment (MCI). The analyses included 232 participants from the BIOCARD study. Participants were cognitively normal and largely middle aged (M age = 56.5) at their baseline MRI scan. After an average of 11.8 years of longitudinal follow-up, 48 have developed clinical symptoms of MCI or dementia (M time from baseline to clinical symptom onset = 7.0 years). Mean thickness was measured over eight 'AD vulnerable' cortical regions, and cognitive reserve was indexed by a composite score consisting of years of education, reading, and vocabulary measures. Using Cox regression models, CR and cortical thickness were each independently associated with risk of clinical symptom onset within 7 years of baseline, suggesting that the neuronal injury occurring proximal to symptom onset has a direct association with clinical outcomes, regardless of CR. In contrast, there was a significant interaction between CR and mean cortical thickness for risk of progression more than 7 years from baseline, suggesting that individuals with high CR are better able to compensate for cortical thinning that is beginning to occur at the very earliest phase of AD.

  8. 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...... 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...

  9. 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....

  10. Active Exploration of Large 3D Model Repositories.

    Science.gov (United States)

    Gao, Lin; Cao, Yan-Pei; Lai, Yu-Kun; Huang, Hao-Zhi; Kobbelt, Leif; Hu, Shi-Min

    2015-12-01

    With broader availability of large-scale 3D model repositories, the need for efficient and effective exploration becomes more and more urgent. Existing model retrieval techniques do not scale well with the size of the database since often a large number of very similar objects are returned for a query, and the possibilities to refine the search are quite limited. We propose an interactive approach where the user feeds an active learning procedure by labeling either entire models or parts of them as "like" or "dislike" such that the system can automatically update an active set of recommended models. To provide an intuitive user interface, candidate models are presented based on their estimated relevance for the current query. From the methodological point of view, our main contribution is to exploit not only the similarity between a query and the database models but also the similarities among the database models themselves. We achieve this by an offline pre-processing stage, where global and local shape descriptors are computed for each model and a sparse distance metric is derived that can be evaluated efficiently even for very large databases. We demonstrate the effectiveness of our method by interactively exploring a repository containing over 100 K models.

  11. Modeling and Simulation Techniques for Large-Scale Communications Modeling

    National Research Council Canada - National Science Library

    Webb, Steve

    1997-01-01

    .... Tests of random number generators were also developed and applied to CECOM models. It was found that synchronization of random number strings in simulations is easy to implement and can provide significant savings for making comparative studies. If synchronization is in place, then statistical experiment design can be used to provide information on the sensitivity of the output to input parameters. The report concludes with recommendations and an implementation plan.

  12. Estimation and Inference for Very Large Linear Mixed Effects Models

    OpenAIRE

    Gao, K.; Owen, A. B.

    2016-01-01

    Linear mixed models with large imbalanced crossed random effects structures pose severe computational problems for maximum likelihood estimation and for Bayesian analysis. The costs can grow as fast as $N^{3/2}$ when there are N observations. Such problems arise in any setting where the underlying factors satisfy a many to many relationship (instead of a nested one) and in electronic commerce applications, the N can be quite large. Methods that do not account for the correlation structure can...

  13. Spectra of operators in large N tensor models

    Science.gov (United States)

    Bulycheva, Ksenia; Klebanov, Igor R.; Milekhin, Alexey; Tarnopolsky, Grigory

    2018-01-01

    We study the operators in the large N tensor models, focusing mostly on the fermionic quantum mechanics with O (N )3 symmetry which may be either global or gauged. In the model with global symmetry, we study the spectra of bilinear operators, which are in either the symmetric traceless or the antisymmetric representation of one of the O (N ) groups. In the symmetric traceless case, the spectrum of scaling dimensions is the same as in the Sachdev-Ye-Kitaev (SYK) model with real fermions; it includes the h =2 zero mode. For the operators antisymmetric in the two indices, the scaling dimensions are the same as in the additional sector found in the complex tensor and SYK models; the lowest h =0 eigenvalue corresponds to the conserved O (N ) charges. A class of singlet operators may be constructed from contracted combinations of m symmetric traceless or antisymmetric two-particle operators. Their two-point functions receive contributions from m melonic ladders. Such multiple ladders are a new phenomenon in the tensor model, which does not seem to be present in the SYK model. The more typical 2 k -particle operators do not receive any ladder corrections and have quantized large N scaling dimensions k /2 . We construct pictorial representations of various singlet operators with low k . For larger k , we use available techniques to count the operators and show that their number grows as 2kk !. As a consequence, the theory has a Hagedorn phase transition at the temperature which approaches zero in the large N limit. We also study the large N spectrum of low-lying operators in the Gurau-Witten model, which has O (N )6 symmetry. We argue that it corresponds to one of the generalized SYK models constructed by Gross and Rosenhaus. Our paper also includes studies of the invariants in large N tensor integrals with various symmetries.

  14. Modelling and transient stability of large wind farms

    DEFF Research Database (Denmark)

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

    2003-01-01

    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...... technology. This subject is treated as a parameter study with respect to the windmill electrical and mechanical parameters and with use of control strategies within the conventional generator technology. Stability improvements on the wind farm side of the connection point lead to significant reduction......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...

  15. "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. Copyright © 2015 The Authors. Published by

  16. 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

  17. Disinformative data in large-scale hydrological modelling

    Directory of Open Access Journals (Sweden)

    A. Kauffeldt

    2013-07-01

    Full Text Available Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i basin areas for different hydrographic datasets, and (ii between climate data (precipitation and potential evaporation and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering sub-grid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent

  18. Coupled SWAT-MODFLOW Model Development for Large Basins

    Science.gov (United States)

    Aliyari, F.; Bailey, R. T.; Tasdighi, A.

    2017-12-01

    Water management in semi-arid river basins requires allocating water resources between urban, industrial, energy, and agricultural sectors, with the latter competing for necessary irrigation water to sustain crop yield. Competition between these sectors will intensify due to changes in climate and population growth. In this study, the recently developed SWAT-MODFLOW coupled hydrologic model is modified for application in a large managed river basin that provides both surface water and groundwater resources for urban and agricultural areas. Specific modifications include the linkage of groundwater pumping and irrigation practices and code changes to allow for the large number of SWAT hydrologic response units (HRU) required for a large river basin. The model is applied to the South Platte River Basin (SPRB), a 56,980 km2 basin in northeastern Colorado dominated by large urban areas along the front range of the Rocky Mountains and agriculture regions to the east. Irregular seasonal and annual precipitation and 150 years of urban and agricultural water management history in the basin provide an ideal test case for the SWAT-MODFLOW model. SWAT handles land surface and soil zone processes whereas MODFLOW handles groundwater flow and all sources and sinks (pumping, injection, bedrock inflow, canal seepage, recharge areas, groundwater/surface water interaction), with recharge and stream stage provided by SWAT. The model is tested against groundwater levels, deep percolation estimates, and stream discharge. The model will be used to quantify spatial groundwater vulnerability in the basin under scenarios of climate change and population growth.

  19. Modeling neurodevelopment and cortical dysfunction in SPG11-linked hereditary spastic paraplegia using human induced pluripotent stem cells

    OpenAIRE

    Mishra, Himanshu Kumar

    2016-01-01

    Hereditary spastic paraplegias (HSPs) are a heterogeneous group of inherited motor neuron diseases characterized by progressive spasticity and weakness of the lower limbs. Mutations in the Spastic Paraplegia Gene11 (SPG11), encoding spatacsin, cause the most frequent form of autosomal recessive HSP. SPG11 patients are clinically distinguishable from most other HSPs, by severe cortical atrophy and presence of a thin corpus callosum (TCC), associated with cognitive deficits. Partly due to l...

  20. Large N scalars: From glueballs to dynamical Higgs models

    Science.gov (United States)

    Sannino, Francesco

    2016-05-01

    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 a 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 realizations we determine the leading N corrections to the electroweak precision parameters. The results nicely elucidate the underlying large N dynamics and can be used to confront first principle lattice results featuring composite scalars with a systematic effective approach.

  1. Solving large linear systems in an implicit thermohaline ocean model

    NARCIS (Netherlands)

    de Niet, Arie Christiaan

    2007-01-01

    The climate on earth is largely determined by the global ocean circulation. Hence it is important to predict how the flow will react to perturbation by for example melting icecaps. To answer questions about the stability of the global ocean flow, a computer model has been developed that is able to

  2. 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…

  3. Searches for phenomena beyond the Standard Model at the Large ...

    Indian Academy of Sciences (India)

    metry searches at the LHC is thus the channel with large missing transverse momentum and jets of high transverse momentum. No excess above the expected SM background is observed and limits are set on supersymmetric models. Figures 1 and 2 show the limits from ATLAS [11] and CMS [12]. In addition to setting limits ...

  4. 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...

  5. Adaptive Gaussian Predictive Process Models for Large Spatial Datasets

    Science.gov (United States)

    Guhaniyogi, Rajarshi; Finley, Andrew O.; Banerjee, Sudipto; Gelfand, Alan E.

    2011-01-01

    Large point referenced datasets occur frequently in the environmental and natural sciences. Use of Bayesian hierarchical spatial models for analyzing these datasets is undermined by onerous computational burdens associated with parameter estimation. Low-rank spatial process models attempt to resolve this problem by projecting spatial effects to a lower-dimensional subspace. This subspace is determined by a judicious choice of “knots” or locations that are fixed a priori. One such representation yields a class of predictive process models (e.g., Banerjee et al., 2008) for spatial and spatial-temporal data. Our contribution here expands upon predictive process models with fixed knots to models that accommodate stochastic modeling of the knots. We view the knots as emerging from a point pattern and investigate how such adaptive specifications can yield more flexible hierarchical frameworks that lead to automated knot selection and substantial computational benefits. PMID:22298952

  6. Particle production at large transverse momentum and hard collision models

    International Nuclear Information System (INIS)

    Ranft, G.; Ranft, J.

    1977-04-01

    The majority of the presently available experimental data is consistent with hard scattering models. Therefore the hard scattering model seems to be well established. There is good evidence for jets in large transverse momentum reactions as predicted by these models. The overall picture is however not yet well enough understood. We mention only the empirical hard scattering cross section introduced in most of the models, the lack of a deep theoretical understanding of the interplay between quark confinement and jet production, and the fact that we are not yet able to discriminate conclusively between the many proposed hard scattering models. The status of different hard collision models discussed in this paper is summarized. (author)

  7. 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...

  8. Large deflection of viscoelastic beams using fractional derivative model

    International Nuclear Information System (INIS)

    Bahranini, Seyed Masoud Sotoodeh; Eghtesad, Mohammad; Ghavanloo, Esmaeal; Farid, Mehrdad

    2013-01-01

    This paper deals with large deflection of viscoelastic beams using a fractional derivative model. For this purpose, a nonlinear finite element formulation of viscoelastic beams in conjunction with the fractional derivative constitutive equations has been developed. The four-parameter fractional derivative model has been used to describe the constitutive equations. The deflected configuration for a uniform beam with different boundary conditions and loads is presented. The effect of the order of fractional derivative on the large deflection of the cantilever viscoelastic beam, is investigated after 10, 100, and 1000 hours. The main contribution of this paper is finite element implementation for nonlinear analysis of viscoelastic fractional model using the storage of both strain and stress histories. The validity of the present analysis is confirmed by comparing the results with those found in the literature.

  9. Engineering Large Animal Species to Model Human Diseases.

    Science.gov (United States)

    Rogers, Christopher S

    2016-07-01

    Animal models are an important resource for studying human diseases. Genetically engineered mice are the most commonly used species and have made significant contributions to our understanding of basic biology, disease mechanisms, and drug development. However, they often fail to recreate important aspects of human diseases and thus can have limited utility as translational research tools. Developing disease models in species more similar to humans may provide a better setting in which to study disease pathogenesis and test new treatments. This unit provides an overview of the history of genetically engineered large animals and the techniques that have made their development possible. Factors to consider when planning a large animal model, including choice of species, type of modification and methodology, characterization, production methods, and regulatory compliance, are also covered. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

  10. 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.

  11. Dynamics of large-scale cortical interactions at high gamma frequencies during word production: event related causality (ERC) analysis of human electrocorticography (ECoG).

    Science.gov (United States)

    Korzeniewska, Anna; Franaszczuk, Piotr J; Crainiceanu, Ciprian M; Kuś, Rafał; Crone, Nathan E

    2011-06-15

    Intracranial EEG studies in humans have shown that functional brain activation in a variety of functional-anatomic domains of human cortex is associated with an increase in power at a broad range of high gamma (>60Hz) frequencies. Although these electrophysiological responses are highly specific for the location and timing of cortical processing and in animal recordings are highly correlated with increased population firing rates, there has been little direct empirical evidence for causal interactions between different recording sites at high gamma frequencies. Such causal interactions are hypothesized to occur during cognitive tasks that activate multiple brain regions. To determine whether such causal interactions occur at high gamma frequencies and to investigate their functional significance, we used event-related causality (ERC) analysis to estimate the dynamics, directionality, and magnitude of event-related causal interactions using subdural electrocorticography (ECoG) recorded during two word production tasks: picture naming and auditory word repetition. A clinical subject who had normal hearing but was skilled in American Signed Language (ASL) provided a unique opportunity to test our hypothesis with reference to a predictable pattern of causal interactions, i.e. that language cortex interacts with different areas of sensorimotor cortex during spoken vs. signed responses. Our ERC analyses confirmed this prediction. During word production with spoken responses, perisylvian language sites had prominent causal interactions with mouth/tongue areas of motor cortex, and when responses were gestured in sign language, the most prominent interactions involved hand and arm areas of motor cortex. Furthermore, we found that the sites from which the most numerous and prominent causal interactions originated, i.e. sites with a pattern of ERC "divergence", were also sites where high gamma power increases were most prominent and where electrocortical stimulation mapping

  12. Ecohydrological modeling for large-scale environmental impact assessment.

    Science.gov (United States)

    Woznicki, Sean A; Nejadhashemi, A Pouyan; Abouali, Mohammad; Herman, Matthew R; Esfahanian, Elaheh; Hamaamin, Yaseen A; Zhang, Zhen

    2016-02-01

    Ecohydrological models are frequently used to assess the biological integrity of unsampled streams. These models vary in complexity and scale, and their utility depends on their final application. Tradeoffs are usually made in model scale, where large-scale models are useful for determining broad impacts of human activities on biological conditions, and regional-scale (e.g. watershed or ecoregion) models provide stakeholders greater detail at the individual stream reach level. Given these tradeoffs, the objective of this study was to develop large-scale stream health models with reach level accuracy similar to regional-scale models thereby allowing for impacts assessments and improved decision-making capabilities. To accomplish this, four measures of biological integrity (Ephemeroptera, Plecoptera, and Trichoptera taxa (EPT), Family Index of Biotic Integrity (FIBI), Hilsenhoff Biotic Index (HBI), and fish Index of Biotic Integrity (IBI)) were modeled based on four thermal classes (cold, cold-transitional, cool, and warm) of streams that broadly dictate the distribution of aquatic biota in Michigan. The Soil and Water Assessment Tool (SWAT) was used to simulate streamflow and water quality in seven watersheds and the Hydrologic Index Tool was used to calculate 171 ecologically relevant flow regime variables. Unique variables were selected for each thermal class using a Bayesian variable selection method. The variables were then used in development of adaptive neuro-fuzzy inference systems (ANFIS) models of EPT, FIBI, HBI, and IBI. ANFIS model accuracy improved when accounting for stream thermal class rather than developing a global model. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Large time periodic solutions to coupled chemotaxis-fluid models

    Science.gov (United States)

    Jin, Chunhua

    2017-12-01

    In this paper, we deal with the time periodic problem to coupled chemotaxis-fluid models. We prove the existence of large time periodic strong solutions for the full chemotaxis-Navier-Stokes system in spatial dimension N=2, and the existence of large time periodic strong solutions for the chemotaxis-Stokes system in spatial dimension N=3. On the basis of these, the regularity of the solutions can be further improved. More precisely speaking, if the time periodic source g and the potential force \

  14. 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.

  15. Global Bedload Flux Modeling and Analysis in Large Rivers

    Science.gov (United States)

    Islam, M. T.; Cohen, S.; Syvitski, J. P.

    2017-12-01

    Proper sediment transport quantification has long been an area of interest for both scientists and engineers in the fields of geomorphology, and management of rivers and coastal waters. Bedload flux is important for monitoring water quality and for sustainable development of coastal and marine bioservices. Bedload measurements, especially for large rivers, is extremely scarce across time, and many rivers have never been monitored. Bedload measurements in rivers, is particularly acute in developing countries where changes in sediment yields is high. The paucity of bedload measurements is the result of 1) the nature of the problem (large spatial and temporal uncertainties), and 2) field costs including the time-consuming nature of the measurement procedures (repeated bedform migration tracking, bedload samplers). Here we present a first of its kind methodology for calculating bedload in large global rivers (basins are >1,000 km. Evaluation of model skill is based on 113 bedload measurements. The model predictions are compared with an empirical model developed from the observational dataset in an attempt to evaluate the differences between a physically-based numerical model and a lumped relationship between bedload flux and fluvial and basin parameters (e.g., discharge, drainage area, lithology). The initial study success opens up various applications to global fluvial geomorphology (e.g. including the relationship between suspended sediment (wash load) and bedload). Simulated results with known uncertainties offers a new research product as a valuable resource for the whole scientific community.

  16. 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

  17. Neuroprotective effects of hydrated fullerene C60: cortical and hippocampal EEG interplay in an amyloid-infused rat model of Alzheimer's disease.

    Science.gov (United States)

    Vorobyov, Vasily; Kaptsov, Vladimir; Gordon, Rita; Makarova, Ekaterina; Podolski, Igor; Sengpiel, Frank

    2015-01-01

    We studied the effects of fullerene C60 nanoparticles, namely hydrated fullerene C60 (C60HyFn), on interrelations between EEG frequency spectra from the frontal cortex and the dorsal hippocampus (CA1) on an amyloid-β (Aβ) rat model of Alzheimer's disease (AD). Infusion of Aβ1-42 protein (1.5 μl) into the CA1 region two weeks before EEG testing diminished hippocampal theta (3.8-8.4 Hz) predominance and eliminated cortical beta (12.9-26.2 Hz) predominance observed in baseline EEG of rats infused with saline (control) or with C60HyFn alone. In contrast, these Aβ1-42 effects were abolished in rats pretreated with C60HyFn, 30 min apart. Dopaminergic mediation in AD has been shown to be involved in neuronal plasticity and Aβ transformation in different ways. To clarify its role in the cortex-hippocampus interplay in the Aβ model of AD, we used peripheral injection of a dopamine agonist, apomorphine (APO), at a low dose (0.1 mg/kg). In rats infused with C60HyFn or Aβ1-42 alone, APO attenuated the cortical beta predominance, with immediate and delayed phases evident in the Aβ1-42-rats. Pretreatment with C60HyFn diminished the APO effect in the Aβ1-42-treated rats. Thus, we show that intrahippocampal injection of Aβ1-42 dramatically disrupts cortical versus hippocampal EEG interrelations and that pretreatment with the fullerene eliminates this abnormality. We suggest that some effects of C60HyFn may be mediated through presynaptic dopamine receptors and that water-soluble C60 fullerenes have a neuroprotective potential.

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

    OpenAIRE

    Bruno eMota; Bruno eMota; Suzana eHerculano-Houzel; Suzana eHerculano-Houzel

    2012-01-01

    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 ...

  19. Penalized Estimation in Large-Scale Generalized Linear Array Models

    DEFF Research Database (Denmark)

    Lund, Adam; Vincent, Martin; Hansen, Niels Richard

    2017-01-01

    Large-scale generalized linear array models (GLAMs) can be challenging to fit. Computation and storage of its tensor product design matrix can be impossible due to time and memory constraints, and previously considered design matrix free algorithms do not scale well with the dimension of the para......Large-scale generalized linear array models (GLAMs) can be challenging to fit. Computation and storage of its tensor product design matrix can be impossible due to time and memory constraints, and previously considered design matrix free algorithms do not scale well with the dimension...... of the parameter vector. A new design matrix free algorithm is proposed for computing the penalized maximum likelihood estimate for GLAMs, which, in particular, handles nondifferentiable penalty functions. The proposed algorithm is implemented and available via the R package glamlasso. It combines several ideas...

  20. Model for large scale circulation of nuclides in nature, 1

    Energy Technology Data Exchange (ETDEWEB)

    Ohnishi, Teruaki

    1988-12-01

    A model for large scale circulation of nuclides was developed, and a computer code named COCAIN was made which simulates this circulation system-dynamically. The natural environment considered in the present paper consists of 2 atmospheres, 8 geospheres and 2 lithospheres. The biosphere is composed of 4 types of edible plants, 5 cattles and their products, 4 water biota and 16 human organs. The biosphere is assumed to be given nuclides from the natural environment mentioned above. With the use of COCAIN, two numerical case studies were carried out; the one is the study on nuclear pollution in nature by the radioactive nuclides originating from the past nuclear bomb tests, and the other is the study on the response of environment and biota to the pulse injection of nuclides into one compartment. From the former case study it was verified that this model can well explain the observation and properly simulate the large scale circulation of nuclides in nature.

  1. 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.

  2. Large animal models and new therapies for glycogen storage disease.

    Science.gov (United States)

    Brooks, Elizabeth D; Koeberl, Dwight D

    2015-05-01

    Glycogen storage diseases (GSD), a unique category of inherited metabolic disorders, were first described early in the twentieth century. Since then, the biochemical and genetic bases of these disorders have been determined, and an increasing number of animal models for GSD have become available. At least seven large mammalian models have been developed for laboratory research on GSDs. These models have facilitated the development of new therapies, including gene therapy, which are undergoing clinical translation. For example, gene therapy prolonged survival and prevented hypoglycemia during fasting for greater than one year in dogs with GSD type Ia, and the need for periodic re-administration to maintain efficacy was demonstrated in that dog model. The further development of gene therapy could provide curative therapy for patients with GSD and other inherited metabolic disorders.

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

    Science.gov (United States)

    Dura-Bernal, Salvador; Wennekers, Thomas; Denham, Susan L

    2012-01-01

    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-up interactions, for

  4. 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

  5. Top-Down Feedback in an HMAX-Like Cortical Model of Object Perception Based on Hierarchical Bayesian Networks and Belief Propagation

    Science.gov (United States)

    Dura-Bernal, Salvador; Wennekers, Thomas; Denham, Susan L.

    2012-01-01

    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-up interactions, for

  6. ARMA modelling of neutron stochastic processes with large measurement noise

    International Nuclear Information System (INIS)

    Zavaljevski, N.; Kostic, Lj.; Pesic, M.

    1994-01-01

    An autoregressive moving average (ARMA) model of the neutron fluctuations with large measurement noise is derived from langevin stochastic equations and validated using time series data obtained during prompt neutron decay constant measurements at the zero power reactor RB in Vinca. Model parameters are estimated using the maximum likelihood (ML) off-line algorithm and an adaptive pole estimation algorithm based on the recursive prediction error method (RPE). The results show that subcriticality can be determined from real data with high measurement noise using much shorter statistical sample than in standard methods. (author)

  7. Modeling large underground experimental halls for the superconducting super collider

    International Nuclear Information System (INIS)

    Duan, F.; Mrugala, M.

    1993-01-01

    Geomechanical aspects of the excavation design, and analysis of two large underground experimental halls for the Superconducting Super Collider (SSC), being built in Texas, have been extensively investigated using computer modeling. Each chamber, measuring approximately 350 ft long, 110 ft wide, and 190 ft high, is to be excavated mainly through soft marl and overlying competent limestone. Wall stability is essential not only for ensuring excavation safety but also for meeting strict requirements for chamber stability over the 30-yr design life of the facility. Extensive numerical modeling has played a significant role in the selection of excavation methods, excavation sequence, and rock reinforcement systems. (Author)

  8. A Modeling & Simulation Implementation Framework for Large-Scale Simulation

    Directory of Open Access Journals (Sweden)

    Song Xiao

    2012-10-01

    Full Text Available Classical High Level Architecture (HLA systems are facing development problems for lack of supporting fine-grained component integration and interoperation in large-scale complex simulation applications. To provide efficient methods of this issue, an extensible, reusable and composable simulation framework is proposed. To promote the reusability from coarse-grained federate to fine-grained components, this paper proposes a modelling & simulation framework which consists of component-based architecture, modelling methods, and simulation services to support and simplify the process of complex simulation application construction. Moreover, a standard process and simulation tools are developed to ensure the rapid and effective development of simulation application.

  9. Simulating large cosmology surveys with calibrated halo models

    OpenAIRE

    Lynn, Stuart

    2011-01-01

    In this thesis I present a novel method for constructing large scale mock galaxy and halo catalogues and apply this model to a number of important topics in modern cosmology. Traditionally such mocks are created through first evolving a high resolution particle simulation from a set of initial conditions to the present epoch, identifying bound structures and their evolution, and finally applying a semi-analytic prescription for galaxy formation. In contrast to this computatio...

  10. Shear viscosity from a large-Nc NJL model

    Energy Technology Data Exchange (ETDEWEB)

    Lang, Robert; Kaiser, Norbert [TUM Physik Department, Garching (Germany); Weise, Wolfram [ECT, Villa Tambosi, Villazzano (Italy); TUM Physik Department, Garching (Germany)

    2015-07-01

    We calculate the ratio of shear viscosity to entropy density within a large-N{sub c} Nambu-Jona-Lasinio model. A consistent treatment of the Kubo formalism incorporating the full Dirac structure of the quark self-energy from mesonic fluctuations is presented. We compare our results to common approximation schemes applied to the Kubo formalism and to the quark self-energy.

  11. Protein homology model refinement by large-scale energy optimization.

    Science.gov (United States)

    Park, Hahnbeom; Ovchinnikov, Sergey; Kim, David E; DiMaio, Frank; Baker, David

    2018-03-20

    Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

  12. Discrimination of cortical laminae using MEG.

    Science.gov (United States)

    Troebinger, Luzia; López, José David; Lutti, Antoine; Bestmann, Sven; Barnes, Gareth

    2014-11-15

    Typically MEG source reconstruction is used to estimate the distribution of current flow on a single anatomically derived cortical surface model. In this study we use two such models representing superficial and deep cortical laminae. We establish how well we can discriminate between these two different cortical layer models based on the same MEG data in the presence of different levels of co-registration noise, Signal-to-Noise Ratio (SNR) and cortical patch size. We demonstrate that it is possible to make a distinction between superficial and deep cortical laminae for levels of co-registration noise of less than 2mm translation and 2° rotation at SNR > 11 dB. We also show that an incorrect estimate of cortical patch size will tend to bias layer estimates. We then use a 3D printed head-cast (Troebinger et al., 2014) to achieve comparable levels of co-registration noise, in an auditory evoked response paradigm, and show that it is possible to discriminate between these cortical layer models in real data. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Cortical columns for quick brains

    OpenAIRE

    Stoop, Ralph L.; Saase, Victor; Wagner, Clemens; Stoop, Britta; Stoop, Ruedi

    2012-01-01

    It is widely believed that the particular wiring observed within cortical columns boosts neural computation. We use rewiring of neural networks performing real-world cognitive tasks to study the validity of this argument. In a vast survey of wirings within the column we detect, however, no traces of the proposed effect. It is on the mesoscopic inter-columnar scale that the existence of columns - largely irrespective of their inner organization - enhances the speed of information transfer and ...

  14. 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 .

  15. Validating modeled turbulent heat fluxes across large freshwater surfaces

    Science.gov (United States)

    Lofgren, B. M.; Fujisaki-Manome, A.; Gronewold, A.; Anderson, E. J.; Fitzpatrick, L.; Blanken, P.; Spence, C.; Lenters, J. D.; Xiao, C.; Charusambot, U.

    2017-12-01

    Turbulent fluxes of latent and sensible heat are important physical processes that influence the energy and water budgets of the Great Lakes. Validation and improvement of bulk flux algorithms to simulate these turbulent heat fluxes are critical for accurate prediction of hydrodynamics, water levels, weather, and climate over the region. Here we consider five heat flux algorithms from several model systems; the Finite-Volume Community Ocean Model, the Weather Research and Forecasting model, and the Large Lake Thermodynamics Model, which are used in research and operational environments and concentrate on different aspects of the Great Lakes' physical system, but interface at the lake surface. The heat flux algorithms were isolated from each model and driven by meteorological data from over-lake stations in the Great Lakes Evaporation Network. The simulation results were compared with eddy covariance flux measurements at the same stations. All models show the capacity to the seasonal cycle of the turbulent heat fluxes. Overall, the Coupled Ocean Atmosphere Response Experiment algorithm in FVCOM has the best agreement with eddy covariance measurements. Simulations with the other four algorithms are overall improved by updating the parameterization of roughness length scales of temperature and humidity. Agreement between modelled and observed fluxes notably varied with geographical locations of the stations. For example, at the Long Point station in Lake Erie, observed fluxes are likely influenced by the upwind land surface while the simulations do not take account of the land surface influence, and therefore the agreement is worse in general.

  16. Architectural Large Constructed Environment. Modeling and Interaction Using Dynamic Simulations

    Science.gov (United States)

    Fiamma, P.

    2011-09-01

    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.

  17. 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.

  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. Hydrogen combustion modelling in large-scale geometries

    International Nuclear Information System (INIS)

    Studer, E.; Beccantini, A.; Kudriakov, S.; Velikorodny, A.

    2014-01-01

    Hydrogen risk mitigation issues based on catalytic recombiners cannot exclude flammable clouds to be formed during the course of a severe accident in a Nuclear Power Plant. Consequences of combustion processes have to be assessed based on existing knowledge and state of the art in CFD combustion modelling. The Fukushima accidents have also revealed the need for taking into account the hydrogen explosion phenomena in risk management. Thus combustion modelling in a large-scale geometry is one of the remaining severe accident safety issues. At present day there doesn't exist a combustion model which can accurately describe a combustion process inside a geometrical configuration typical of the Nuclear Power Plant (NPP) environment. Therefore the major attention in model development has to be paid on the adoption of existing approaches or creation of the new ones capable of reliably predicting the possibility of the flame acceleration in the geometries of that type. A set of experiments performed previously in RUT facility and Heiss Dampf Reactor (HDR) facility is used as a validation database for development of three-dimensional gas dynamic model for the simulation of hydrogen-air-steam combustion in large-scale geometries. The combustion regimes include slow deflagration, fast deflagration, and detonation. Modelling is based on Reactive Discrete Equation Method (RDEM) where flame is represented as an interface separating reactants and combustion products. The transport of the progress variable is governed by different flame surface wrinkling factors. The results of numerical simulation are presented together with the comparisons, critical discussions and conclusions. (authors)

  20. Effective models of new physics at the Large Hadron Collider

    International Nuclear Information System (INIS)

    Llodra-Perez, J.

    2011-07-01

    With the start of the Large Hadron Collider runs, in 2010, particle physicists will be soon able to have a better understanding of the electroweak symmetry breaking. They might also answer to many experimental and theoretical open questions raised by the Standard Model. Surfing on this really favorable situation, we will first present in this thesis a highly model-independent parametrization in order to characterize the new physics effects on mechanisms of production and decay of the Higgs boson. This original tool will be easily and directly usable in data analysis of CMS and ATLAS, the huge generalist experiments of LHC. It will help indeed to exclude or validate significantly some new theories beyond the Standard Model. In another approach, based on model-building, we considered a scenario of new physics, where the Standard Model fields can propagate in a flat six-dimensional space. The new spatial extra-dimensions will be compactified on a Real Projective Plane. This orbifold is the unique six-dimensional geometry which possesses chiral fermions and a natural Dark Matter candidate. The scalar photon, which is the lightest particle of the first Kaluza-Klein tier, is stabilized by a symmetry relic of the six dimension Lorentz invariance. Using the current constraints from cosmological observations and our first analytical calculation, we derived a characteristic mass range around few hundred GeV for the Kaluza-Klein scalar photon. Therefore the new states of our Universal Extra-Dimension model are light enough to be produced through clear signatures at the Large Hadron Collider. So we used a more sophisticated analysis of particle mass spectrum and couplings, including radiative corrections at one-loop, in order to establish our first predictions and constraints on the expected LHC phenomenology. (author)

  1. Interactive modeling, design and analysis of large spacecraft

    Science.gov (United States)

    Garrett, L. B.

    1982-01-01

    An efficient computer aided design and analysis capability applicable to large space structures was developed to relieve the engineer of much of the effort required in the past. The automated capabilities can be used to rapidly synthesize, evaluate, and determine performance characteristics and costs for future large spacecraft concepts. The interactive design and evaluation of advanced spacecraft program (IDEAS) is used to illustrate the power, efficiency, and versatility of the approach. The coupling of space environment modeling algorithms with simplified analysis and design modules in the IDEAS program permits rapid evaluation of completing spacecraft and mission designs. The approach is particularly useful in the conceptual design phase of advanced space missions when a multiplicity of concepts must be considered before a limited set can be selected or more detailed analysis. Integrated spacecraft systems level data and data files are generated or subsystems and mission reexamination and/or refinement and for more rigorous analyses.

  2. 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.

  3. 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.

  4. 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

  5. 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

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

    Science.gov (United States)

    Zielinski, Brandon A; 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

    2014-06-01

    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

  7. 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.

  8. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Modeling fall propensity in Parkinson's disease: deficits in the attentional control of complex movements in rats with cortical-cholinergic and striatal-dopaminergic deafferentation.

    Science.gov (United States)

    Kucinski, Aaron; Paolone, Giovanna; Bradshaw, Marc; Albin, Roger L; Sarter, Martin

    2013-10-16

    Cognitive symptoms, complex movement deficits, and increased propensity for falls are interrelated and levodopa-unresponsive symptoms in patients with Parkinson's disease (PD). We developed a test system for the assessment of fall propensity in rats and tested the hypothesis that interactions between loss of cortical cholinergic and striatal dopaminergic afferents increase fall propensity. Rats were trained to traverse stationary and rotating rods, placed horizontally or at inclines, and while exposed to distractors. Rats also performed an operant Sustained Attention Task (SAT). Partial cortical cholinergic and/or caudate dopaminergic deafferentation were produced by bilateral infusions of 192 IgG-saporin (SAP) into the basal forebrain and/or 6-hydroxydopamine (6-OHDA) into the caudate nucleus, respectively, modeling the lesions seen in early PD. Rats with dual cholinergic-dopaminergic lesions (DL) fell more frequently than SAP or 6-OHDA rats. Falls in DL rats were associated with incomplete rebalancing after slips and low traversal speed. Ladder rung walking and pasta handling performance did not indicate sensorimotor deficits. SAT performance was impaired in DL and SAP rats; however, SAT performance and falls were correlated only in DL rats. Furthermore, in DL rats, but not in rats with only dopaminergic lesions, the placement and size of dopaminergic lesion correlated significantly with fall rates. The results support the hypothesis that after dual cholinergic-dopaminergic lesions, attentional resources can no longer be recruited to compensate for diminished striatal control of complex movement, thereby "unmasking" impaired striatal control of complex movements and yielding falls.

  10. Wireless cortical implantable systems

    CERN Document Server

    Majidzadeh Bafar, Vahid

    2013-01-01

    Wireless Cortical Implantable Systems examines the design for data acquisition and transmission in cortical implants. The first part of the book covers existing system-level cortical implants, as well as future devices. The authors discuss the major constraints in terms of microelectronic integration. The second part of the book focuses on system-level as well as circuit and system level solutions to the development of ultra low-power and low-noise microelectronics for cortical implants. Existing solutions are presented and novel methods and solutions proposed. The third part of the book focuses on the usage of digital impulse radio ultra wide-band transmission as an efficient method to transmit cortically neural recorded data at high data-rate to the outside world. Original architectural and circuit and system solutions are discussed.

  11. 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...

  12. 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......, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land-use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. Our model experiments allow us...... modelling C–N interactions in agricultural ecosystems under future environmental change and the effects these have on terrestrial biogeochemical cycles....

  13. 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.

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

    DEFF Research Database (Denmark)

    Larsen, Ulrik

    recovery (WHR) systems. Studies of alternative WHR systems in other applications suggests that the Kalina cycle and the organic Rankine cycle (ORC) can provide significant advantages over the steam Rankine cycle, which is currently used for marine WHR. This thesis aims at creating a better understanding...... consisting of a two-zone combustion and NOx emission model, a double Wiebe heat release model, the Redlich-Kwong equation of state and the Woschni heat loss correlation. A novel methodology is presented and used to determine the optimum organic Rankine cycle process layout, working fluid and process...... of the Kalina cycle and the ORC in the application on board large ships; the thermodynamic performances of the mentioned power cycles are compared. Recommendations of suitable system layouts and working fluids for the marine applications are provided along with methodologies useful for the design...

  15. Brief anesthesia, but not voluntary locomotion, significantly alters cortical temperature

    Science.gov (United States)

    Shirey, Michael J.; Kudlik, D'Anne E.; Huo, Bing-Xing; Greene, Stephanie E.; Drew, Patrick J.

    2015-01-01

    Changes in brain temperature can alter electrical properties of neurons and cause changes in behavior. However, it is not well understood how behaviors, like locomotion, or experimental manipulations, like anesthesia, alter brain temperature. We implanted thermocouples in sensorimotor cortex of mice to understand how cortical temperature was affected by locomotion, as well as by brief and prolonged anesthesia. Voluntary locomotion induced small (∼0.1°C) but reliable increases in cortical temperature that could be described using a linear convolution model. In contrast, brief (90-s) exposure to isoflurane anesthesia depressed cortical temperature by ∼2°C, which lasted for up to 30 min after the cessation of anesthesia. Cortical temperature decreases were not accompanied by a concomitant decrease in the γ-band local field potential power, multiunit firing rate, or locomotion behavior, which all returned to baseline within a few minutes after the cessation of anesthesia. In anesthetized animals where core body temperature was kept constant, cortical temperature was still >1°C lower than in the awake animal. Thermocouples implanted in the subcortex showed similar temperature changes under anesthesia, suggesting these responses occur throughout the brain. Two-photon microscopy of individual blood vessel dynamics following brief isoflurane exposure revealed a large increase in vessel diameter that ceased before the brain temperature significantly decreased, indicating cerebral heat loss was not due to increased cerebral blood vessel dilation. These data should be considered in experimental designs recording in anesthetized preparations, computational models relating temperature and neural activity, and awake-behaving methods that require brief anesthesia before experimental procedures. PMID:25972579

  16. Photorealistic large-scale urban city model reconstruction.

    Science.gov (United States)

    Poullis, Charalambos; You, Suya

    2009-01-01

    The rapid and efficient creation of virtual environments has become a crucial part of virtual reality applications. In particular, civil and defense applications often require and employ detailed models of operations areas for training, simulations of different scenarios, planning for natural or man-made events, monitoring, surveillance, games, and films. A realistic representation of the large-scale environments is therefore imperative for the success of such applications since it increases the immersive experience of its users and helps reduce the difference between physical and virtual reality. However, the task of creating such large-scale virtual environments still remains a time-consuming and manual work. In this work, we propose a novel method for the rapid reconstruction of photorealistic large-scale virtual environments. First, a novel, extendible, parameterized geometric primitive is presented for the automatic building identification and reconstruction of building structures. In addition, buildings with complex roofs containing complex linear and nonlinear surfaces are reconstructed interactively using a linear polygonal and a nonlinear primitive, respectively. Second, we present a rendering pipeline for the composition of photorealistic textures, which unlike existing techniques, can recover missing or occluded texture information by integrating multiple information captured from different optical sensors (ground, aerial, and satellite).

  17. Geometric algorithms for electromagnetic modeling of large scale structures

    Science.gov (United States)

    Pingenot, James

    With the rapid increase in the speed and complexity of integrated circuit designs, 3D full wave and time domain simulation of chip, package, and board systems becomes more and more important for the engineering of modern designs. Much effort has been applied to the problem of electromagnetic (EM) simulation of such systems in recent years. Major advances in boundary element EM simulations have led to O(n log n) simulations using iterative methods and advanced Fast. Fourier Transform (FFT), Multi-Level Fast Multi-pole Methods (MLFMM), and low-rank matrix compression techniques. These advances have been augmented with an explosion of multi-core and distributed computing technologies, however, realization of the full scale of these capabilities has been hindered by cumbersome and inefficient geometric processing. Anecdotal evidence from industry suggests that users may spend around 80% of turn-around time manipulating the geometric model and mesh. This dissertation addresses this problem by developing fast and efficient data structures and algorithms for 3D modeling of chips, packages, and boards. The methods proposed here harness the regular, layered 2D nature of the models (often referred to as "2.5D") to optimize these systems for large geometries. First, an architecture is developed for efficient storage and manipulation of 2.5D models. The architecture gives special attention to native representation of structures across various input models and special issues particular to 3D modeling. The 2.5D structure is then used to optimize the mesh systems First, circuit/EM co-simulation techniques are extended to provide electrical connectivity between objects. This concept is used to connect independently meshed layers, allowing simple and efficient 2D mesh algorithms to be used in creating a 3D mesh. Here, adaptive meshing is used to ensure that the mesh accurately models the physical unknowns (current and charge). Utilizing the regularized nature of 2.5D objects and

  18. 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.

  19. Modeling Resource Utilization of a Large Data Acquisition System

    CERN Document Server

    AUTHOR|(SzGeCERN)756497; The ATLAS collaboration; Garcia Garcia, Pedro Javier; Vandelli, Wainer; Froening, Holger

    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 ...

  20. 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 ...

  1. 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.

  2. How do parcellation size and short-range connectivity affect dynamics in large-scale brain network models?

    Science.gov (United States)

    Proix, Timothée; Spiegler, Andreas; Schirner, Michael; Rothmeier, Simon; Ritter, Petra; Jirsa, Viktor K

    2016-11-15

    Recent efforts to model human brain activity on the scale of the whole brain rest on connectivity estimates of large-scale networks derived from diffusion magnetic resonance imaging (dMRI). This type of connectivity describes white matter fiber tracts. The number of short-range cortico-cortical white-matter connections is, however, underrepresented in such large-scale brain models. It is still unclear on the one hand, which scale of representation of white matter fibers is optimal to describe brain activity on a large-scale such as recorded with magneto- or electroencephalography (M/EEG) or functional magnetic resonance imaging (fMRI), and on the other hand, to which extent short-range connections that are typically local should be taken into account. In this article we quantified the effect of connectivity upon large-scale brain network dynamics by (i) systematically varying the number of brain regions before computing the connectivity matrix, and by (ii) adding generic short-range connections. We used dMRI data from the Human Connectome Project. We developed a suite of preprocessing modules called SCRIPTS to prepare these imaging data for The Virtual Brain, a neuroinformatics platform for large-scale brain modeling and simulations. We performed simulations under different connectivity conditions and quantified the spatiotemporal dynamics in terms of Shannon Entropy, dwell time and Principal Component Analysis. For the reconstructed connectivity, our results show that the major white matter fiber bundles play an important role in shaping slow dynamics in large-scale brain networks (e.g. in fMRI). Faster dynamics such as gamma oscillations (around 40 Hz) are sensitive to the short-range connectivity if transmission delays are considered. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Modeling containment of large wildfires using generalized linear mixed-model analysis

    Science.gov (United States)

    Mark Finney; Isaac C. Grenfell; Charles W. McHugh

    2009-01-01

    Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...

  4. Dynamics of a large extra dimension inspired hybrid inflation model

    International Nuclear Information System (INIS)

    Green, Anne M.; Mazumdar, Anupam

    2002-01-01

    In low scale quantum gravity scenarios the fundamental scale of nature can be as low as 1 TeV, in order to address the naturalness of the electroweak scale. A number of difficulties arise in constructing specific models: stabilization of the radius of the extra dimensions, avoidance of overproduction of Kaluza-Klein modes, achieving successful baryogenesis and production of a close to scale-invariant spectrum of density perturbations with the correct amplitude. We examine in detail the dynamics, including radion stabilization, of a hybrid inflation model that has been proposed in order to address these difficulties, where the inflaton is a gauge singlet residing in the bulk. We find that for a low fundamental scale the phase transition, which in standard four dimensional hybrid models usually ends inflation, is slow and there is a second phase of inflation lasting for a large number of e-foldings. The density perturbations on cosmologically interesting scales exit the Hubble radius during this second phase of inflation, and we find that their amplitude is far smaller than is required. We find that the duration of the second phase of inflation can be short, so that cosmologically interesting scales exit the Hubble radius prior to the phase transition, and the density perturbations have the correct amplitude, only if the fundamental scale takes an intermediate value. Finally we comment briefly on the implications of an intermediate fundamental scale for the production of primordial black holes and baryogenesis

  5. 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.

  6. 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.

  7. A large animal model for boron neutron capture therapy

    International Nuclear Information System (INIS)

    Gavin, P.R.; Kraft, S.L.; DeHaan, C.E.; Moore, M.P.; Griebenow, M.L.

    1992-01-01

    An epithermal neutron beam is needed to treat relatively deep seated tumors. The scattering characteristics of neutrons in this energy range dictate that in vivo experiments be conducted in a large animal to prevent unacceptable total body irradiation. The canine species has proven an excellent model to evaluate the various problems of boron neutron capture utilizing an epithermal neutron beam. This paper discusses three major components of the authors study: (1) the pharmacokinetics of borocaptate sodium (NA 2 B 12 H 11 SH or BSH) in dogs with spontaneously occurring brain tumors, (2) the radiation tolerance of normal tissues in the dog using an epithermal beam alone and in combination with borocaptate sodium, and (3) initial treatment of dogs with spontaneously occurring brain tumors utilizing borocaptate sodium and an epithermal neutron beam

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

    DEFF Research Database (Denmark)

    Yin, Chungen

    2012-01-01

    Quite some studies have been conducted in order to implement oxy-fuel combustion with flue gas recycle in conventional utility boilers as an effective effort of carbon capture and storage. However, combustion under oxy-fuel conditions is significantly different from conventional air-fuel firing......, 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...... calculation of the oxy-fuel WSGGM remarkably over-predicts the radiative heat transfer to the furnace walls and under-predicts the gas temperature at the furnace exit plane, which also result in a higher incomplete combustion in the gray calculation. Moreover, the gray and non-gray calculations of the same...

  9. Parameterization of Fire Injection Height in Large Scale Transport Model

    Science.gov (United States)

    Paugam, R.; Wooster, M.; Atherton, J.; Val Martin, M.; Freitas, S.; Kaiser, J. W.; Schultz, M. G.

    2012-12-01

    The parameterization of fire injection height in global chemistry transport model is currently a subject of debate in the atmospheric community. The approach usually proposed in the literature is based on relationships linking injection height and remote sensing products like the Fire Radiative Power (FRP) which can measure active fire properties. In this work we present an approach based on the Plume Rise Model (PRM) developed by Freitas et al (2007, 2010). This plume model is already used in different host models (e.g. WRF, BRAMS). In its original version, the fire is modeled by: a convective heat flux (CHF; pre-defined by the land cover and evaluated as a fixed part of the total heat released) and a plume radius (derived from the GOES Wildfire-ABBA product) which defines the fire extension where the CHF is homogeneously distributed. Here in our approach the Freitas model is modified, in particular we added (i) an equation for mass conservation, (ii) a scheme to parameterize horizontal entrainment/detrainment, and (iii) a new initialization module which estimates the sensible heat released by the fire on the basis of measured FRP rather than fuel cover type. FRP and Active Fire (AF) area necessary for the initialization of the model are directly derived from a modified version of the Dozier algorithm applied to the MOD14 product. An optimization (using the simulating annealing method) of this new version of the PRM is then proposed based on fire plume characteristics derived from the official MISR plume height project and atmospheric profiles extracted from the ECMWF analysis. The data set covers the main fire region (Africa, Siberia, Indonesia, and North and South America) and is set up to (i) retain fires where plume height and FRP can be easily linked (i.e. avoid large fire cluster where individual plume might interact), (ii) keep fire which show decrease of FRP and AF area after MISR overpass (i.e. to minimize effect of the time period needed for the plume to

  10. 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

  11. 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.

  12. GIS for large-scale watershed observational data model

    Science.gov (United States)

    Patino-Gomez, Carlos

    Because integrated management of a river basin requires the development of models that are used for many purposes, e.g., to assess risks and possible mitigation of droughts and floods, manage water rights, assess water quality, and simply to understand the hydrology of the basin, the development of a relational database from which models can access the various data needed to describe the systems being modeled is fundamental. In order for this concept to be useful and widely applicable, however, it must have a standard design. The recently developed ArcHydro data model facilitates the organization of data according to the "basin" principle and allows access to hydrologic information by models. The development of a basin-scale relational database for the Rio Grande/Bravo basin implemented in a Geographic Information System is one of the contributions of this research. This geodatabase represents the first major attempt to establish a more complete understanding of the basin as a whole, including spatial and temporal information obtained from the United States of America and Mexico. Difficulties in processing raster datasets over large regions are studied in this research. One of the most important contributions is the application of a Raster-Network Regionalization technique, which utilizes raster-based analysis at the subregional scale in an efficient manner and combines the resulting subregional vector datasets into a regional database. Another important contribution of this research is focused on implementing a robust structure for handling huge temporal data sets related to monitoring points such as hydrometric and climatic stations, reservoir inlets and outlets, water rights, etc. For the Rio Grande study area, the ArcHydro format is applied to the historical information collected in order to include and relate these time series to the monitoring points in the geodatabase. Its standard time series format is changed to include a relationship to the agency from

  13. 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

    2010-10-01

    Full Text Available 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.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.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 be a primary driver of these secondary pathological events. More

  14. SCIMAP: Modelling Diffuse Pollution in Large River Basins

    Science.gov (United States)

    Milledge, D.; Heathwaite, L.; Lane, S. N.; Reaney, S. M.

    2009-12-01

    Polluted rivers are a problem for the plants and animals that require clean water to survive. Watershed scale processes can influence instream aquatic ecosystems by delivering fine sediment, solutes and organic matter from diffuse sources. To improve our rivers we need to identify the pollution sources. Models can help us to do this but these rarely address the extent to which risky land uses are hydrologically-connected, and hence able to deliver, to the drainage network. Those that do tend to apply a full hydrological scheme, which is unfeasible for large watersheds. Here we develop a risk-based modelling framework, SCIMAP, for diffuse pollution from agriculture (Nitrate, Phosphate and Fine Sediment). In each case the basis of the analysis is the joint consideration of the probability of a unit of land (25 m2 cell) producing a particular environmental risk and then of that risk reaching the river. The components share a common treatment of hydrological connectivity but differ in their treatment of each pollution type. We test and apply SCIMAP using spatially-distributed instream water quality data for some of the UK’s largest catchments to infer the processes and the associated process parameters that matter in defining their concentrations. We use these to identify a series of risky field locations, where this land use is readily connected to the river system by overland flow.

  15. On the homogeneity and heterogeneity of cortical thickness profiles in Homo sapiens sapiens.

    Science.gov (United States)

    Koten, Jan Willem; Schüppen, André; Morozova, Maria; Lehofer, Agnes; Koschutnig, Karl; Wood, Guilherme

    2017-12-20

    Cortical thickness has been investigated since the beginning of the 20th century, but we do not know how similar the cortical thickness profiles among humans are. In this study, the local similarity of cortical thickness profiles was investigated using sliding window methods. Here, we show that approximately 5% of the cortical thickness profiles are similarly expressed among humans while 45% of the cortical thickness profiles show a high level of heterogeneity. Therefore, heterogeneity is the rule, not the exception. Cortical thickness profiles of somatosensory homunculi and the anterior insula are consistent among humans, while the cortical thickness profiles of the motor homunculus are more variable. Cortical thickness profiles of homunculi that code for muscle position and skin stimulation are highly similar among humans despite large differences in sex, education, and age. This finding suggests that the structure of these cortices remains well preserved over a lifetime. Our observations possibly relativize opinions on cortical plasticity.

  16. Modelling of heat transfer during torrefaction of large lignocellulosic biomass

    Science.gov (United States)

    Regmi, Bharat; Arku, Precious; Tasnim, Syeda Humaira; Mahmud, Shohel; Dutta, Animesh

    2018-02-01

    Preparation of feedstock is a major energy intensive process for the thermochemical conversion of biomass into fuel. By eliminating the need to grind biomass prior to the torrefaction process, there would be a potential gain in the energy requirements as the entire step would be eliminated. In regards to a commercialization of torrefaction technology, this study has examined heat transfer inside large cylindrical biomass both numerically and experimentally during torrefaction. A numerical axis-symmetrical 2-D model for heat transfer during torrefaction at 270°C for 1 h was created in COMSOL Multiphysics 5.1 considering heat generation evaluated from the experiment. The model analyzed the temperature distribution within the core and on the surface of biomass during torrefaction for various sizes. The model results showed similarities with experimental results. The effect of L/D ratio on temperature distribution within biomass was observed by varying length and diameter and compared with experiments in literature to find out an optimal range of cylindrical biomass size suitable for torrefaction. The research demonstrated that a cylindrical biomass sample of 50 mm length with L/D ratio of 2 can be torrefied with a core-surface temperature difference of less than 30 °C. The research also demonstrated that sample length has a negligible effect on core-surface temperature difference during torrefaction when the diameter is fixed at 25 mm. This information will help to design a torrefaction processing system and develop a value chain for biomass supply without using an energy-intensive grinding process.

  17. Environmental Impacts of Large Scale Biochar Application Through Spatial Modeling

    Science.gov (United States)

    Huber, I.; Archontoulis, S.

    2017-12-01

    In an effort to study the environmental (emissions, soil quality) and production (yield) impacts of biochar application at regional scales we coupled the APSIM-Biochar model with the pSIMS parallel platform. So far the majority of biochar research has been concentrated on lab to field studies to advance scientific knowledge. Regional scale assessments are highly needed to assist decision making. The overall objective of this simulation study was to identify areas in the USA that have the most gain environmentally from biochar's application, as well as areas which our model predicts a notable yield increase due to the addition of biochar. We present the modifications in both APSIM biochar and pSIMS components that were necessary to facilitate these large scale model runs across several regions in the United States at a resolution of 5 arcminutes. This study uses the AgMERRA global climate data set (1980-2010) and the Global Soil Dataset for Earth Systems modeling as a basis for creating its simulations, as well as local management operations for maize and soybean cropping systems and different biochar application rates. The regional scale simulation analysis is in progress. Preliminary results showed that the model predicts that high quality soils (particularly those common to Iowa cropping systems) do not receive much, if any, production benefit from biochar. However, soils with low soil organic matter ( 0.5%) do get a noteworthy yield increase of around 5-10% in the best cases. We also found N2O emissions to be spatial and temporal specific; increase in some areas and decrease in some other areas due to biochar application. In contrast, we found increases in soil organic carbon and plant available water in all soils (top 30 cm) due to biochar application. The magnitude of these increases (% change from the control) were larger in soil with low organic matter (below 1.5%) and smaller in soils with high organic matter (above 3%) and also dependent on biochar

  18. Mnemonic Encoding and Cortical Organization in Parietal and Prefrontal Cortices.

    Science.gov (United States)

    Masse, Nicolas Y; Hodnefield, Jonathan M; Freedman, David J

    2017-06-21

    Persistent activity within the frontoparietal network is consistently observed during tasks that require working memory. However, the neural circuit mechanisms underlying persistent neuronal encoding within this network remain unresolved. Here, we ask how neural circuits support persistent activity by examining population recordings from posterior parietal (PPC) and prefrontal (PFC) cortices in two male monkeys that performed spatial and motion direction-based tasks that required working memory. While spatially selective persistent activity was observed in both areas, robust selective persistent activity for motion direction was only observed in PFC. Crucially, we find that this difference between mnemonic encoding in PPC and PFC is associated with the presence of functional clustering: PPC and PFC neurons up to ∼700 μm apart preferred similar spatial locations, and PFC neurons up to ∼700 μm apart preferred similar motion directions. In contrast, motion-direction tuning similarity between nearby PPC neurons was much weaker and decayed rapidly beyond ∼200 μm. We also observed a similar association between persistent activity and functional clustering in trained recurrent neural network models embedded with a columnar topology. These results suggest that functional clustering facilitates mnemonic encoding of sensory information. SIGNIFICANCE STATEMENT Working memory refers to our ability to temporarily store and manipulate information. Numerous studies have observed that, during working memory, neurons in higher cortical areas, such as the parietal and prefrontal cortices, mnemonically encode the remembered stimulus. However, several recent studies have failed to observe mnemonic encoding during working memory, raising the question as to why mnemonic encoding is observed during some, but not all, conditions. In this study, we show that mnemonic encoding occurs when a cortical area is organized such that nearby neurons preferentially respond to the same

  19. 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

    2018-03-01

    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.

  20. 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

  1. Cortical high-density counterstream architectures.

    Science.gov (United States)

    Markov, Nikola T; Ercsey-Ravasz, Mária; Van Essen, David C; Knoblauch, Kenneth; Toroczkai, Zoltán; Kennedy, Henry

    2013-11-01

    Small-world networks provide an appealing description of cortical architecture owing to their capacity for integration and segregation combined with an economy of connectivity. Previous reports of low-density interareal graphs and apparent small-world properties are challenged by data that reveal high-density cortical graphs in which economy of connections is achieved by weight heterogeneity and distance-weight correlations. These properties define a model that predicts many binary and weighted features of the cortical network including a core-periphery, a typical feature of self-organizing information processing systems. Feedback and feedforward pathways between areas exhibit a dual counterstream organization, and their integration into local circuits constrains cortical computation. Here, we propose a bow-tie representation of interareal architecture derived from the hierarchical laminar weights of pathways between the high-efficiency dense core and periphery.

  2. Computation of Large Molecules with the Hartree-Fock Model

    Science.gov (United States)

    Clementi, Enrico

    1972-01-01

    The usual way to compute Hartree-Fock type functions for molecules is by an expansion of the one-electron functions (molecular orbitals) in a linear combination of analytical functions (LCAO-MO-SCF, linear combination of atomic orbitals—Molecular Orbital—Self Consistent field). The expansion coefficients are obtained variationally. This technique requires the computation of several multicenter two-electron integrals (representing the electron-electron interaction) proportional to the fourth power of the basis set size. There are several types of basis sets; the Gaussian type introduced by S. F. Boys is used herein. Since it requires from a minimum of 10 (or 15) Gaussian-type functions to about 25 (or 30) Gaussian functions to describe a second-row atom in a molecule, the fourth power dependency of the basis set has been the de facto bottleneck of quantum chemical computations in the last decade. In this paper, the concept is introduced of a “dynamical” basis set, which allows for drastic computational simplifications while retaining full numerical accuracy. Examples are given that show that computational saving in computer time of more than a factor of one hundred is achieved and that large basis sets (up to the order of several hundred Gaussian functions per molecule) can be used routinely. It is noted that the limitation in the Hartree-Fock energy (correlation energy error) can be easily computed by use of a statistical model introduced by Wigner for solid-state systems in 1934. Thus, large molecules can now be simulated by computational techniques without reverting to semi-empirical parameterization and without requiring enormous computational time and storage. PMID:16592020

  3. Hue opponency: chromatic valence functions, individual differences, cortical winner-take-all opponent modeling, and the relationship between spikes and sensitivity.

    Science.gov (United States)

    Billock, Vincent A

    2018-04-01

    Neural spike rate data are more restricted in range than related psychophysical data. For example, several studies suggest a compressive (roughly cube root) nonlinear relationship between wavelength-opponent spike rates in primate midbrain and color appearance in humans, two rather widely separated domains. This presents an opportunity to partially bridge a chasm between these two domains and to probe the putative nonlinearity with other psychophysical data. Here neural wavelength-opponent data are used to create cortical competition models for hue opponency. This effort led to creation of useful models of spiking neuron winner-take-all (WTA) competition and MAX selection. When fed with actual primate data, the spiking WTA models generate reasonable wavelength-opponent spike rate behaviors. An average psychophysical observer for red-green and blue-yellow opponency is curated from eight applicable studies in the refereed and dissertation literatures, with cancellation data roughly every 10 nm in 18 subjects for yellow-blue opponency and 15 subjects for red-green opponency. A direct mapping between spiking neurons with broadband wavelength sensitivity and human psychophysical luminance yields a power law exponent of 0.27, similar to the cube root nonlinearity. Similarly, direct mapping between the WTA model opponent spike rates and psychophysical opponent data suggests power law relationships with exponents between 0.24 and 0.41.

  4. 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-spiking (FS

  5. Traumatic brain injury and hemorrhagic shock: evaluation of different resuscitation strategies in a large animal model of combined insults.

    Science.gov (United States)

    Jin, Guang; DeMoya, Marc A; Duggan, Michael; Knightly, Thomas; Mejaddam, Ali Y; Hwabejire, John; Lu, Jennifer; Smith, William Michael; Kasotakis, Georgios; Velmahos, George C; Socrate, Simona; Alam, Hasan B

    2012-07-01

    Traumatic brain injury (TBI) and hemorrhagic shock (HS) are the leading causes of trauma-related mortality and morbidity. Combination of TBI and HS (TBI + HS) is highly lethal, and the optimal resuscitation strategy for this combined insult remains unclear. A critical limitation is the lack of suitable large animal models to test different treatment strategies. We have developed a clinically relevant large animal model of TBI + HS, which was used to evaluate the impact of different treatments on brain lesion size and associated edema. Yorkshire swine (42-50 kg) were instrumented to measure hemodynamic parameters and intracranial pressure. A computer-controlled cortical impact device was used to create a TBI through a 20-mm craniotomy: 15-mm cylindrical tip impactor at 4 m/s velocity, 100-ms dwell time, and 12-mm penetration depth. Volume-controlled hemorrhage was started (40% blood volume) concurrent with the TBI. After 2 h of shock, animals were randomized to one of three resuscitation groups (n = 5/group): (a) normal saline (NS); (b) 6% hetastarch, Hextend (Hex); and (c) fresh frozen plasma (FFP). Volumes of Hex and FFP matched the shed blood, whereas NS was three times the volume. After 6 h of postresuscitation monitoring, brains were sectioned into 5-mm slices and stained with TTC (2,3,5-triphenyltetrazolium chloride) to quantify the lesion size and brain swelling. Combination of 40% blood loss with cortical impact and a period of shock (2 h) resulted in a highly reproducible brain injury. Total fluid requirements were lower in the Hex and FFP groups. Lesion size and brain swelling in the FFP group (2,160 ± 202.63 mm and 22% ± 1.0%, respectively) were significantly smaller than those in the NS group (3,285 ± 130.8 mm3 and 37% ± 1.6%, respectively) (P < 0.05). Hex treatment decreased the swelling (29% ± 1.6%) without reducing the lesion size. Early administration of FFP reduces the size of brain lesion and associated swelling in a large animal model of TBI

  6. Empirical Models of Social Learning in a Large, Evolving Network.

    Directory of Open Access Journals (Sweden)

    Ayşe Başar Bener

    Full Text Available This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals' access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1 attraction homophily causes individuals to form ties on the basis of attribute similarity, 2 aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3 social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends.

  7. Empirical Models of Social Learning in a Large, Evolving Network.

    Science.gov (United States)

    Bener, Ayşe Başar; Çağlayan, Bora; Henry, Adam Douglas; Prałat, Paweł

    2016-01-01

    This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals' access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1) attraction homophily causes individuals to form ties on the basis of attribute similarity, 2) aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3) social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends.

  8. Large Animal Stroke Models vs. Rodent Stroke Models, Pros and Cons, and Combination?

    Science.gov (United States)

    Cai, Bin; Wang, Ning

    2016-01-01

    Stroke is a leading cause of serious long-term disability worldwide and the second leading cause of death in many countries. Long-time attempts to salvage dying neurons via various neuroprotective agents have failed in stroke translational research, owing in part to the huge gap between animal stroke models and stroke patients, which also suggests that rodent models have limited predictive value and that alternate large animal models are likely to become important in future translational research. The genetic background, physiological characteristics, behavioral characteristics, and brain structure of large animals, especially nonhuman primates, are analogous to humans, and resemble humans in stroke. Moreover, relatively new regional imaging techniques, measurements of regional cerebral blood flow, and sophisticated physiological monitoring can be more easily performed on the same animal at multiple time points. As a result, we can use large animal stroke models to decrease the gap and promote translation of basic science stroke research. At the same time, we should not neglect the disadvantages of the large animal stroke model such as the significant expense and ethical considerations, which can be overcome by rodent models. Rodents should be selected as stroke models for initial testing and primates or cats are desirable as a second species, which was recommended by the Stroke Therapy Academic Industry Roundtable (STAIR) group in 2009.

  9. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.

    Science.gov (United States)

    Onorante, Luca; Raftery, Adrian E

    2016-01-01

    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.

  10. 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

  11. Modeling the contributions of Ca2+ flows to spontaneous Ca2+ oscillations and cortical spreading depression-triggered Ca2+ waves in astrocyte networks.

    Directory of Open Access Journals (Sweden)

    Bing Li

    Full Text Available Astrocytes participate in brain functions through Ca(2+ signals, including Ca(2+ waves and Ca(2+ oscillations. Currently the mechanisms of Ca(2+ signals in astrocytes are not fully clear. Here, we present a computational model to specify the relative contributions of different Ca(2+ flows between the extracellular space, the cytoplasm and the endoplasmic reticulum of astrocytes to the generation of spontaneous Ca(2+ oscillations (CASs and cortical spreading depression (CSD-triggered Ca(2+ waves (CSDCWs in a one-dimensional astrocyte network. This model shows that CASs depend primarily on Ca(2+ released from internal stores of astrocytes, and CSDCWs depend mainly on voltage-gated Ca(2+ influx. It predicts that voltage-gated Ca(2+ influx is able to generate Ca(2+ waves during the process of CSD even after depleting internal Ca(2+ stores. Furthermore, the model investigates the interactions between CASs and CSDCWs and shows that the pass of CSDCWs suppresses CASs, whereas CASs do not prevent the generation of CSDCWs. This work quantitatively analyzes the generation of astrocytic Ca(2+ signals and indicates different mechanisms underlying CSDCWs and non-CSDCWs. Research on the different types of Ca(2+ signals might help to understand the ways by which astrocytes participate in information processing in brain functions.

  12. State-dependent intrinsic predictability of cortical network dynamics.

    Directory of Open Access Journals (Sweden)

    Leila Fakhraei

    Full Text Available The information encoded in cortical circuit dynamics is fleeting, changing from moment to moment as new input arrives and ongoing intracortical interactions progress. A combination of deterministic and stochastic biophysical mechanisms governs how cortical dynamics at one moment evolve from cortical dynamics in recently preceding moments. Such temporal continuity of cortical dynamics is fundamental to many aspects of cortex function but is not well understood. Here we study temporal continuity by attempting to predict cortical population dynamics (multisite local field potential based on its own recent history in somatosensory cortex of anesthetized rats and in a computational network-level model. We found that the intrinsic predictability of cortical dynamics was dependent on multiple factors including cortical state, synaptic inhibition, and how far into the future the prediction extends. By pharmacologically tuning synaptic inhibition, we obtained a continuum of cortical states with asynchronous population activity at one extreme and stronger, spatially extended synchrony at the other extreme. Intermediate between these extremes we observed evidence for a special regime of population dynamics called criticality. Predictability of the near future (10-100 ms increased as the cortical state was tuned from asynchronous to synchronous. Predictability of the more distant future (>1 s was generally poor, but, surprisingly, was higher for asynchronous states compared to synchronous states. These experimental results were confirmed in a computational network model of spiking excitatory and inhibitory neurons. Our findings demonstrate that determinism and predictability of network dynamics depend on cortical state and the time-scale of the dynamics.

  13. Astrocyte membrane properties are altered in a rat model of developmental cortical malformation but single-cell astrocytic glutamate uptake is robust.

    Science.gov (United States)

    Hanson, Elizabeth; Danbolt, Niels Christian; Dulla, Chris G

    2016-05-01

    Developmental cortical malformations (DCMs) are linked with severe epilepsy and are caused by both genetic and environmental insults. DCMs include several neurological diseases, such as focal cortical dysplasia, polymicrogyria, schizencephaly, and others. Human studies have implicated astrocyte reactivity and dysfunction in the pathophysiology of DCMs, but their specific role is unknown. As astrocytes powerfully regulate glutamate neurotransmission, and glutamate levels are known to be increased in human epileptic foci, understanding the role of astrocytes in the pathological sequelae of DCMs is extremely important. Additionally, recent studies examining astrocyte glutamate uptake in DCMs have reported conflicting results, adding confusion to the field. In this study we utilized the freeze lesion (FL) model of DCM, which is known to induce reactive astrocytosis and cause significant changes in astrocyte morphology, proliferation, and distribution. Using whole-cell patch clamp recording from astrocytes, we recorded both UV-uncaging and synaptically evoked glutamate transporter currents (TCs), widely accepted assays of functional glutamate transport by astrocytes. With this approach, we set out to test the hypothesis that astrocyte membrane properties and glutamate transport were disrupted in this model of DCM. Though we found that the developmental maturation of astrocyte membrane resistance was disrupted by FL, glutamate uptake by individual astrocytes was robust throughout FL development. Interestingly, using an immunolabeling approach, we observed spatial and developmental differences in excitatory amino acid transporter (EAAT) expression in FL cortex. Spatially specific differences in EAAT2 (GLT-1) and EAAT1 (GLAST) expression suggest that the relative contribution of each EAAT to astrocytic glutamate uptake may be altered in FL cortex. Lastly, we carefully analyzed the amplitudes and onset times of both synaptically- and UV uncaging-evoked TCs. We found that in

  14. Modeling the spreading of large-scale wildland fires

    Science.gov (United States)

    Mohamed Drissi

    2015-01-01

    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...

  15. Modeling Large Time Series for Efficient Approximate Query Processing

    DEFF Research Database (Denmark)

    Perera, Kasun S; Hahmann, Martin; Lehner, Wolfgang

    2015-01-01

    -wise aggregation to derive the models. These models are initially created from the original data and are kept in the database along with it. Subsequent queries are answered using the stored models rather than scanning and processing the original datasets. In order to support model query processing, we maintain...

  16. Trajectories of cortical surface area and cortical volume maturation in normal brain development

    Directory of Open Access Journals (Sweden)

    Simon Ducharme

    2015-12-01

    Full Text Available This is a report of developmental trajectories of cortical surface area and cortical volume in the NIH MRI Study of Normal Brain Development. The quality-controlled sample included 384 individual typically-developing subjects with repeated scanning (1–3 per subject, total scans n=753 from 4.9 to 22.3 years of age. The best-fit model (cubic, quadratic, or first-order linear was identified at each vertex using mixed-effects models, with statistical correction for multiple comparisons using random field theory. Analyses were performed with and without controlling for total brain volume. These data are provided for reference and comparison with other databases. Further discussion and interpretation on cortical developmental trajectories can be found in the associated Ducharme et al.׳s article “Trajectories of cortical thickness maturation in normal brain development – the importance of quality control procedures” (Ducharme et al., 2015 [1].

  17. Stress Analysis of Osteoporotic Lumbar Vertebra Using Finite Element Model with Microscaled Beam-Shell Trabecular-Cortical Structure

    OpenAIRE

    Kim, Yoon Hyuk; Wu, Mengying; Kim, Kyungsoo

    2013-01-01

    Osteoporosis is a disease in which low bone mass and microarchitectural deterioration of bone tissue lead to enhanced bone fragility and susceptibility to fracture. Due to the complex anatomy of the vertebral body, the difficulties associated with obtaining bones for in vitro experiments, and the limitations on the control of the experimental parameters, finite element models have been developed to analyze the biomechanical properties of the vertebral body. We developed finite element models ...

  18. The anterior cerebral artery: II. A computer model of its cortical branches estereotaxically obtained from anatomical specimens

    Directory of Open Access Journals (Sweden)

    Raul Marino Jr

    1979-12-01

    Full Text Available This article is a corrollary of a previously published anatomical study of the anterior cerebral artery. The authors propose a method to obtain a computer model of the anterior cerebral artery, based on a combined system of stereotaxic coordinates and a specially developed computer program. The graphic analysis, thus obtained, is projected on a model atlas brain and an ideal diagram of this anatomical structure is obtained. Forty anatomical specimens were used for this study.

  19. 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...

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. Cortical myoclonus and cerebellar pathology

    NARCIS (Netherlands)

    Tijssen, M. A.; Thom, M.; Ellison, D. W.; Wilkins, P.; Barnes, D.; Thompson, P. D.; 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

  5. The Cortical Organization of Speech Processing: Feedback Control and Predictive Coding the Context of a Dual-Stream Model

    Science.gov (United States)

    Hickok, Gregory

    2012-01-01

    Speech recognition is an active process that involves some form of predictive coding. This statement is relatively uncontroversial. What is less clear is the source of the prediction. The dual-stream model of speech processing suggests that there are two possible sources of predictive coding in speech perception: the motor speech system and the…

  6. 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…

  7. Integrated modeling of the Canadian Very Large Optical Telescope

    Science.gov (United States)

    Roberts, Scott C.; Pazder, John S.; Fitzsimmons, Joeleff T.; Herriot, Glen; Loewen, Nathan; Smith, Malcolm J.; Dunn, Jennifer; Saddlemyer, Leslie K.

    2004-07-01

    We describe the VLOT integrated model, which simulates the telescope optical performance under the influence of external disturbances including wind. Details of the implementation in the MATLAB/SIMULINK environment are given, and the data structures are described. The structural to optical interface is detailed, including a discussion of coordinate transformations. The optical model includes both an interface with ZEMAX to perform raytracing analysis and an efficient Linear Optics Model for producing telescope optical path differences from within MATLAB. An extensive set of optical analysis routines has been developed for use with the integrated model. The telescope finite element model, state-space formulation and the high fidelity 1500 mode modal state-space structural dynamics model are presented. Control systems and wind models are described. We present preliminary results, showing the delivered image quality under the influence of wind on the primary mirror, with and without primary mirror control.

  8. 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.

  9. 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.

  10. 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

  11. A hierarchical causal modeling for large industrial plants supervision

    International Nuclear Information System (INIS)

    Dziopa, P.; Leyval, L.

    1994-01-01

    A supervision system has to analyse the process current state and the way it will evolve after a modification of the inputs or disturbance. It is proposed to base this analysis on a hierarchy of models, witch differ by the number of involved variables and the abstraction level used to describe their temporal evolution. In a first step, special attention is paid to causal models building, from the most abstract one. Once the hierarchy of models has been build, the most detailed model parameters are estimated. Several models of different abstraction levels can be used for on line prediction. These methods have been applied to a nuclear reprocessing plant. The abstraction level could be chosen on line by the operator. Moreover when an abnormal process behaviour is detected a more detailed model is automatically triggered in order to focus the operator attention on the suspected subsystem. (authors). 11 refs., 11 figs

  12. Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets

    OpenAIRE

    Purushotham, Sanjay; Meng, Chuizheng; Che, Zhengping; Liu, Yan

    2017-01-01

    Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist which have benchmarked the performance of the deep learning models with respect to the state-of-the-art machine learning models and prognostic scoring systems on publicly available healthcare datasets. In this paper, we present the benchmarking res...

  13. VLSI (Very Large Scale Integrated Circuits) Device Reliability Models.

    Science.gov (United States)

    1984-12-01

    components have been particularly effective on phased array radars, including Cobra Dane, Pave Paws, Cobra Judy and AN/TPS-59. In spite of the large number...Quincy, MA 55. California Devices Promised Data San Jose, CA 56. Micro-Pac Industries Promised Data Garland TX 57. Teleydyne Philbrick No Data Available

  14. Truck Route Choice Modeling using Large Streams of GPS Data

    Science.gov (United States)

    2017-07-31

    The primary goal of this research was to use large streams of truck-GPS data to analyze travel routes (or paths) chosen by freight trucks to travel between different origin and destination (OD) location pairs in metropolitan regions of Florida. Two s...

  15. Symmetry in stochasticity: Random walk models of large-scale ...

    Indian Academy of Sciences (India)

    This paper describes the insights gained from the excursion set approach, in which various questions about the phenomenology of large-scale structure formation can be mapped to problems associated with the first crossing distribution of appropriately defined barriers by random walks. Much of this is summarized in R K ...

  16. 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...

  17. 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...

  18. 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

  19. Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

    Science.gov (United States)

    Ajelli, Marco; Gonçalves, Bruno; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José J; Merler, Stefano; Vespignani, Alessandro

    2010-06-29

    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. 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. 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 breakdown analysis shows that similar attack rates are

  20. The Role of Inhibition in a Computational Model of an Auditory Cortical Neuron during the Encoding of Temporal Information

    Science.gov (United States)

    Bendor, Daniel

    2015-01-01

    In auditory cortex, temporal information within a sound is represented by two complementary neural codes: a temporal representation based on stimulus-locked firing and a rate representation, where discharge rate co-varies with the timing between acoustic events but lacks a stimulus-synchronized response. Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition. In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition. Using single-unit recordings from awake marmosets (Callithrix jacchus), we validate several model predictions, including differences in the temporal fidelity, discharge rates and temporal dynamics of stimulus-evoked responses between neurons with rate and temporal representations. Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex. PMID:25879843

  1. 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

  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. Large Scale Community Detection Using a Small World Model

    Directory of Open Access Journals (Sweden)

    Ranjan Kumar Behera

    2017-11-01

    Full Text Available In a social network, small or large communities within the network play a major role in deciding the functionalities of the network. Despite of diverse definitions, communities in the network may be defined as the group of nodes that are more densely connected as compared to nodes outside the group. Revealing such hidden communities is one of the challenging research problems. A real world social network follows small world phenomena, which indicates that any two social entities can be reachable in a small number of steps. In this paper, nodes are mapped into communities based on the random walk in the network. However, uncovering communities in large-scale networks is a challenging task due to its unprecedented growth in the size of social networks. A good number of community detection algorithms based on random walk exist in literature. In addition, when large-scale social networks are being considered, these algorithms are observed to take considerably longer time. In this work, with an objective to improve the efficiency of algorithms, parallel programming framework like Map-Reduce has been considered for uncovering the hidden communities in social network. The proposed approach has been compared with some standard existing community detection algorithms for both synthetic and real-world datasets in order to examine its performance, and it is observed that the proposed algorithm is more efficient than the existing ones.

  4. Traffic assignment models in large-scale applications

    DEFF Research Database (Denmark)

    Rasmussen, Thomas Kjær

    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......-perceptions. It is the commonly adopted assumption that the distributed elements follow unbounded distributions which induces the need to enumerate all paths in the SUE, no matter how unattractive they might be. The Deterministic User Equilibrium (DUE), on the other hand, has a built-in criterion distinguishing definitely unused...... 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...

  5. Large scale Bayesian nuclear data evaluation with consistent model defects

    International Nuclear Information System (INIS)

    Schnabel, G

    2015-01-01

    The aim of nuclear data evaluation is the reliable determination of cross sections and related quantities of the atomic nuclei. To this end, evaluation methods are applied which combine the information of experiments with the results of model calculations. The evaluated observables with their associated uncertainties and correlations are assembled into data sets, which are required for the development of novel nuclear facilities, such as fusion reactors for energy supply, and accelerator driven systems for nuclear waste incineration. The efficiency and safety of such future facilities is dependent on the quality of these data sets and thus also on the reliability of the applied evaluation methods. This work investigated the performance of the majority of available evaluation methods in two scenarios. The study indicated the importance of an essential component in these methods, which is the frequently ignored deficiency of nuclear models. Usually, nuclear models are based on approximations and thus their predictions may deviate from reliable experimental data. As demonstrated in this thesis, the neglect of this possibility in evaluation methods can lead to estimates of observables which are inconsistent with experimental data. Due to this finding, an extension of Bayesian evaluation methods is proposed to take into account the deficiency of the nuclear models. The deficiency is modeled as a random function in terms of a Gaussian process and combined with the model prediction. This novel formulation conserves sum rules and allows to explicitly estimate the magnitude of model deficiency. Both features are missing in available evaluation methods so far. Furthermore, two improvements of existing methods have been developed in the course of this thesis. The first improvement concerns methods relying on Monte Carlo sampling. A Metropolis-Hastings scheme with a specific proposal distribution is suggested, which proved to be more efficient in the studied scenarios than the

  6. Nonlinear Synapses for Large-Scale Models: An Efficient Representation Enables Complex Synapse Dynamics Modeling in Large-Scale Simulations

    Directory of Open Access Journals (Sweden)

    Eric eHu

    2015-09-01

    Full Text Available Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

  7. Topological σ Models and Large N Matrix Integral

    Science.gov (United States)

    Eguchi, Tohru; Hori, Kentaro; Yang, Sung-Kil

    In this paper we describe in some detail the representation of the topological CP1 model in terms of a matrix integral which we have introduced in a previous article. We first discuss the integrable structure of the CP1 model and show that it is governed by an extension of the one-dimensional Toda hierarchy. We then introduce a matrix model which reproduces the sum over holomorphic maps from arbitrary Riemann surfaces onto CP1. We compute intersection numbers on the moduli space of curves using a geometrical method and show that the results agree with those predicted by the matrix model. We also develop a Landau-Ginzburg (LG) description of the CP1 model using a superpotential eX + et0,Q e-X given by the Lax operator of the Toda hierarchy (X is the LG field and t0,Q is the coupling constant of the Kähler class). The form of the superpotential indicates the close connection between CP1 and N=2 supersymmetric sine-Gordon theory which was noted sometime ago by several authors. We also discuss possible generalizations of our construction to other manifolds and present an LG formulation of the topological CP2 model.

  8. Computational modelling of the cerebral cortical microvasculature: effect of x-ray microbeams versus broad beam irradiation

    Science.gov (United States)

    Merrem, A.; Bartzsch, S.; Laissue, J.; Oelfke, U.

    2017-05-01

    Microbeam Radiation Therapy is an innovative pre-clinical strategy which uses arrays of parallel, tens of micrometres wide kilo-voltage photon beams to treat tumours. These x-ray beams are typically generated on a synchrotron source. It was shown that these beam geometries allow exceptional normal tissue sparing from radiation damage while still being effective in tumour ablation. A final biological explanation for this enhanced therapeutic ratio has still not been found, some experimental data support an important role of the vasculature. In this work, the effect of microbeams on a normal microvascular network of the cerebral cortex was assessed in computer simulations and compared to the effect of homogeneous, seamless exposures at equal energy absorption. The anatomy of a cerebral microvascular network and the inflicted radiation damage were simulated to closely mimic experimental data using a novel probabilistic model of radiation damage to blood vessels. It was found that the spatial dose fractionation by microbeam arrays significantly decreased the vascular damage. The higher the peak-to-valley dose ratio, the more pronounced the sparing effect. Simulations of the radiation damage as a function of morphological parameters of the vascular network demonstrated that the distribution of blood vessel radii is a key parameter determining both the overall radiation damage of the vasculature and the dose-dependent differential effect of microbeam irradiation.

  9. 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

  10. 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 the molecular and electrophysiologic basis of constitutive cells in the dysplastic tissue. Despite the promising results of mTOR inhibitors, large-scale randomized trials are in need to evaluate their efficacy and side effects, along with additional mechanistic studies for the development of novel, molecular-based diagnostic and therapeutic approaches. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

  11. N-methyl-D-aspartate receptor antagonist effects on prefrontal cortical connectivity better model early than chronic schizophrenia.

    Science.gov (United States)

    Anticevic, Alan; Corlett, Philip R; Cole, Michael W; Savic, Aleksandar; Gancsos, Mark; Tang, Yanqing; Repovs, Grega; Murray, John D; Driesen, Naomi R; Morgan, Peter T; Xu, Ke; Wang, Fei; Krystal, John H

    2015-03-15

    Prefrontal cortex (PFC) function contributes to schizophrenia onset and progression. However, little is known about neural mechanisms behind PFC functional alterations along illness stages. Recent pharmacologic studies indicate that glutamate dysfunction may produce increased functional connectivity. However, pharmacologic models of schizophrenia overlook effects of illness progression on PFC function. This study compared N-methyl-D-aspartate glutamate receptor (NMDAR) antagonist effects in healthy volunteers with stages of schizophrenia with respect to PFC functional connectivity. First, we tested ketamine effects on PFC functional connectivity in healthy volunteers in a data-driven way (n = 19). Next, we compared healthy subjects (n = 96) with three clinical groups: individuals at high risk for schizophrenia (n = 21), people early in their course of schizophrenia (EC-SCZ) (n = 28), and patients with chronic illness (n = 20). Across independent analyses, we used data-driven global brain connectivity techniques restricted to PFC to identify functional dysconnectivity. Results revealed robust PFC hyperconnectivity in healthy volunteers administered ketamine (Cohen's d = 1.46), resembling individuals at high risk for schizophrenia and EC-SCZ. Hyperconnectivity was not found in patients with chronic illness relative to EC-SCZ patients. Results provide the first evidence that ketamine effects on PFC functional connectivity resemble early course but not chronic schizophrenia. Results suggest an illness phase-specific relevance of NMDAR antagonist administration for prefrontal dysconnectivity associated with schizophrenia. This finding has implications for the neurobiology of illness progression and for the widespread use of NMDAR antagonists in the development of therapeutics for schizophrenia. Copyright © 2015. Published by Elsevier Inc.

  12. Large Scale Computing for the Modelling of Whole Brain Connectivity

    DEFF Research Database (Denmark)

    Albers, Kristoffer Jon

    , which allows us to couple and explore different models and sampling procedures in runtime, still being applied to full-sized data. Using the implemented tools, we demonstrate that the models successfully can be applied for clustering whole-brain connectivity networks. Without being informed of spatial......The human brain constitutes an impressive network formed by the structural and functional connectivity patterns between billions of neurons. Modern functional and diffusion magnetic resonance imaging (fMRI and dMRI) provides unprecedented opportunities for exploring the functional and structural...... organization of the brain in continuously increasing resolution. From these images, networks of structural and functional connectivity can be constructed. Bayesian stochastic block modelling provides a prominent data-driven approach for uncovering the latent organization, by clustering the networks into groups...

  13. Modeling and simulation of large scale stirred tank

    Science.gov (United States)

    Neuville, John R.

    The purpose of this dissertation is to provide a written record of the evaluation performed on the DWPF mixing process by the construction of numerical models that resemble the geometry of this process. There were seven numerical models constructed to evaluate the DWPF mixing process and four pilot plants. The models were developed with Fluent software and the results from these models were used to evaluate the structure of the flow field and the power demand of the agitator. The results from the numerical models were compared with empirical data collected from these pilot plants that had been operated at an earlier date. Mixing is commonly used in a variety ways throughout industry to blend miscible liquids, disperse gas through liquid, form emulsions, promote heat transfer and, suspend solid particles. The DOE Sites at Hanford in Richland Washington, West Valley in New York, and Savannah River Site in Aiken South Carolina have developed a process that immobilizes highly radioactive liquid waste. The radioactive liquid waste at DWPF is an opaque sludge that is mixed in a stirred tank with glass frit particles and water to form slurry of specified proportions. The DWPF mixing process is composed of a flat bottom cylindrical mixing vessel with a centrally located helical coil, and agitator. The helical coil is used to heat and cool the contents of the tank and can improve flow circulation. The agitator shaft has two impellers; a radial blade and a hydrofoil blade. The hydrofoil is used to circulate the mixture between the top region and bottom region of the tank. The radial blade sweeps the bottom of the tank and pushes the fluid in the outward radial direction. The full scale vessel contains about 9500 gallons of slurry with flow behavior characterized as a Bingham Plastic. Particles in the mixture have an abrasive characteristic that cause excessive erosion to internal vessel components at higher impeller speeds. The desire for this mixing process is to ensure the

  14. The pig as a large preclinical model for therapeutic human anti-cancer vaccine development

    DEFF Research Database (Denmark)

    Overgaard, Nana Haahr; Frøsig, Thomas Mørch; Welner, Simon

    2016-01-01

    Development of therapeutic cancer vaccines has largely been based on rodent models and the majority failed to establish therapeutic responses in clinical trials. We therefore used pigs as a large animal model for human cancer vaccine development due to the large similarity between the porcine...

  15. Renal cortical scintigraphy

    International Nuclear Information System (INIS)

    Locher, J.Th.

    2002-01-01

    In this report the renal cortical scintigraphy with 99m Tc-DMSA (Dimercaptosuccinic acid) like a 'gold standard' for the diagnosis of pyelonephritis in children is presented. The role of the vesicoureteral reflux, the level of C-reactive protein and other urinary tract anomaly to the pyelonephritis development is considered. The administrated doses for children and adults, procedure of the study and the SPECT possibilities are given. A four-grade scale describing the grade of parenchymal damage is shown. The correlation between the radiopharmaceutical accumulation in the functioning renal cortex and the intrarenal blood flow and proximal tubular cell membrane transport function is discussed. Because of the slow transfer of activity from blood to kidney, imaging should be delayed for 3 hours after injection. The renal cortical scintigraphy with 99m Tc-DMSA is a primary method for an early diagnosis of acute pyelonephritis because animal experiences have demonstrated a high sensitivity and specificity for DMSA scanning when correlated with histopathology. The results from several multiple-center study for the specificity and sensitivity of the method are discussed. The necessity for the renal cortical scintigraphy standardization is outlined

  16. Dynamic Modeling, Optimization, and Advanced Control for Large Scale Biorefineries

    DEFF Research Database (Denmark)

    Prunescu, Remus Mihail

    Second generation biorefineries transform agricultural wastes into biochemicals with higher added value, e.g. bioethanol, which is thought to become a primary component in liquid fuels [1]. Extensive endeavors have been conducted to make the production process feasible on a large scale, and recen......Second generation biorefineries transform agricultural wastes into biochemicals with higher added value, e.g. bioethanol, which is thought to become a primary component in liquid fuels [1]. Extensive endeavors have been conducted to make the production process feasible on a large scale......-time monitoring. The Inbicon biorefinery converts wheat straw into bioethanol utilizing steam, enzymes, and genetically modified yeast. The biomass is first pretreated in a steam pressurized and continuous thermal reactor where lignin is relocated, and hemicellulose partially hydrolyzed such that cellulose...... becomes more accessible to enzymes. The biorefinery is integrated with a nearby power plant following the Integrated Biomass Utilization System (IBUS) principle for reducing steam costs [4]. During the pretreatment, by-products are also created such as organic acids, furfural, and pseudo-lignin, which act...

  17. Large-area dry bean yield prediction modeling in Mexico

    Science.gov (United States)

    Given the importance of dry bean in Mexico, crop yield predictions before harvest are valuable for authorities of the agricultural sector, in order to define support for producers. The aim of this study was to develop an empirical model to estimate the yield of dry bean at the regional level prior t...

  18. 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.

  19. Searches for phenomena beyond the Standard Model at the Large ...

    Indian Academy of Sciences (India)

    Keywords. LHC; ATLAS; CMS; BSM; supersymmetry; exotic. Abstract. The LHC has delivered several fb-1 of data in spring and summer 2011, opening new windows of opportunity for discovering phenomena beyond the Standard Model. A summary of the searches conducted by the ATLAS and CMS experiments based on ...

  20. 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.

  1. Energy-aware semantic modeling in large scale infrastructures

    NARCIS (Netherlands)

    Zhu, H.; van der Veldt, K.; Grosso, P.; Zhao, Z.; Liao, X.; de Laat, C.

    2012-01-01

    Including the energy profile of the computing infrastructure in the decision process for scheduling computing tasks and allocating resources is essential to improve the system energy efficiency. However, the lack of an effective model of the infrastructure energy information makes it difficult for

  2. Searches for phenomena beyond the Standard Model at the Large

    Indian Academy of Sciences (India)

    The LHC has delivered several fb-1 of data in spring and summer 2011, opening new windows of opportunity for discovering phenomena beyond the Standard Model. A summary of the searches conducted by the ATLAS and CMS experiments based on about 1 fb-1 of data is presented.

  3. Symmetry-guided large-scale shell-model theory

    Czech Academy of Sciences Publication Activity Database

    Launey, K. D.; Dytrych, Tomáš; Draayer, J. P.

    2016-01-01

    Roč. 89, JUL (2016), s. 101-136 ISSN 0146-6410 R&D Projects: GA ČR GA16-16772S Institutional support: RVO:61389005 Keywords : Ab intio shell-model theory * Symplectic symmetry * Collectivity * Clusters * Hoyle state * Orderly patterns in nuclei from first principles Subject RIV: BE - Theoretical Physics Impact factor: 11.229, year: 2016

  4. Misspecified poisson regression models for large-scale registry data: inference for 'large n and small p'.

    Science.gov (United States)

    Grøn, Randi; Gerds, Thomas A; Andersen, Per K

    2016-03-30

    Poisson regression is an important tool in register-based epidemiology where it is used to study the association between exposure variables and event rates. In this paper, we will discuss the situation with 'large n and small p', where n is the sample size and p is the number of available covariates. Specifically, we are concerned with modeling options when there are time-varying covariates that can have time-varying effects. One problem is that tests of the proportional hazards assumption, of no interactions between exposure and other observed variables, or of other modeling assumptions have large power due to the large sample size and will often indicate statistical significance even for numerically small deviations that are unimportant for the subject matter. Another problem is that information on important confounders may be unavailable. In practice, this situation may lead to simple 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 are illustrated using data from the Danish national registries investigating the diabetes incidence for individuals treated with antipsychotics compared with the general unexposed population. Copyright © 2015 John Wiley & Sons, Ltd.

  5. Airflow and radon transport modeling in four large buildings

    International Nuclear Information System (INIS)

    Fan, J.B.; Persily, A.K.

    1995-01-01

    Computer simulations of multizone airflow and contaminant transport were performed in four large buildings using the program CONTAM88. This paper describes the physical characteristics of the buildings and their idealizations as multizone building airflow systems. These buildings include a twelve-story multifamily residential building, a five-story mechanically ventilated office building with an atrium, a seven-story mechanically ventilated office building with an underground parking garage, and a one-story school building. The air change rates and interzonal airflows of these buildings are predicted for a range of wind speeds, indoor-outdoor temperature differences, and percentages of outdoor air intake in the supply air Simulations of radon transport were also performed in the buildings to investigate the effects of indoor-outdoor temperature difference and wind speed on indoor radon concentrations

  6. Implementation of an Online Chemistry Model to a Large Eddy Simulation Model (PALM-4U0

    Science.gov (United States)

    Mauder, M.; Khan, B.; Forkel, R.; Banzhaf, S.; Russo, E. E.; Sühring, M.; Kanani-Sühring, F.; Raasch, S.; Ketelsen, K.

    2017-12-01

    Large Eddy Simulation (LES) models permit to resolve relevant scales of turbulent motion, so that these models can capture the inherent unsteadiness of atmospheric turbulence. However, LES models are so far hardly applied for urban air quality studies, in particular chemical transformation of pollutants. In this context, BMBF (Bundesministerium für Bildung und Forschung) funded a joint project, MOSAIK (Modellbasierte Stadtplanung und Anwendung im Klimawandel / Model-based city planning and application in climate change) with the main goal to develop a new highly efficient urban climate model (UCM) that also includes atmospheric chemical processes. The state-of-the-art LES model PALM; Maronga et al, 2015, Geosci. Model Dev., 8, doi:10.5194/gmd-8-2515-2015), has been used as a core model for the new UCM named as PALM-4U. For the gas phase chemistry, a fully coupled 'online' chemistry model has been implemented into PALM. The latest version of the Kinetic PreProcessor (KPP) Version 2.3, has been utilized for the numerical integration of chemical species. Due to the high computational demands of the LES model, compromises in the description of chemical processes are required. Therefore, a reduced chemistry mechanism, which includes only major pollutants namely O3, NO, NO2, CO, a highly simplified VOC chemistry and a small number of products have been implemented. This work shows preliminary results of the advection, and chemical transformation of atmospheric pollutants. Non-cyclic boundaries have been used for inflow and outflow in east-west directions while periodic boundary conditions have been implemented to the south-north lateral boundaries. For practical applications, our approach is to go beyond the simulation of single street canyons to chemical transformation, advection and deposition of air pollutants in the larger urban canopy. Tests of chemistry schemes and initial studies of chemistry-turbulence, transport and transformations are presented.

  7. Uncertainty Quantification for Large-Scale Ice Sheet Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Ghattas, Omar [Univ. of Texas, Austin, TX (United States)

    2016-02-05

    This report summarizes our work to develop advanced forward and inverse solvers and uncertainty quantification capabilities for a nonlinear 3D full Stokes continental-scale ice sheet flow model. The components include: (1) forward solver: a new state-of-the-art parallel adaptive scalable high-order-accurate mass-conservative Newton-based 3D nonlinear full Stokes ice sheet flow simulator; (2) inverse solver: a new adjoint-based inexact Newton method for solution of deterministic inverse problems governed by the above 3D nonlinear full Stokes ice flow model; and (3) uncertainty quantification: a novel Hessian-based Bayesian method for quantifying uncertainties in the inverse ice sheet flow solution and propagating them forward into predictions of quantities of interest such as ice mass flux to the ocean.

  8. A comparison of updating algorithms for large $N$ reduced models

    CERN Document Server

    Pérez, Margarita García; Keegan, Liam; Okawa, Masanori; Ramos, Alberto

    2015-01-01

    We investigate Monte Carlo updating algorithms for simulating $SU(N)$ Yang-Mills fields on a single-site lattice, such as for the Twisted Eguchi-Kawai model (TEK). We show that performing only over-relaxation (OR) updates of the gauge links is a valid simulation algorithm for the Fabricius and Haan formulation of this model, and that this decorrelates observables faster than using heat-bath updates. We consider two different methods of implementing the OR update: either updating the whole $SU(N)$ matrix at once, or iterating through $SU(2)$ subgroups of the $SU(N)$ matrix, we find the same critical exponent in both cases, and only a slight difference between the two.

  9. A noise generation and propagation model for large wind farms

    DEFF Research Database (Denmark)

    Bertagnolio, Franck

    2016-01-01

    A wind turbine noise calculation model is combined with a ray tracing method in order to estimate wind farm noise in its surrounding assuming an arbitrary topography. The wind turbine noise model is used to generate noise spectra for which each turbine is approximated as a point source. However......, the detailed three-dimensional directivity features are taken into account for the further calculation of noise propagation over the surrounding terrain. An arbitrary number of turbines constituting a wind farm can be spatially distributed. The noise from each individual turbine is propagated into the far......-field using the ray tracing method. These results are added up assuming the noise from each turbine is uncorrelated. The methodology permits to estimate a wind farm noise map over the surrounding terrain in a reasonable amount of computational time on a personal computer....

  10. Biofidelic Human Activity Modeling and Simulation with Large Variability

    Science.gov (United States)

    2014-11-25

    exact match or a close representation. Efforts were made to ensure that the activity models can be integrated into widely used game engines and image...integrated into widely used game engines and image generators. ABOUT THE AUTHORS Dr. John Camp is a computer research scientist employed by AFRL. Dr...M&S) has been increasingly used in simulation-based training and virtual reality ( VR ). However, human M&S technology currently used in various

  11. Large area application of a corn hazard model. [Soviet Union

    Science.gov (United States)

    Ashburn, P.; Taylor, T. W. (Principal Investigator)

    1981-01-01

    An application test of the crop calendar portion of a corn (maize) stress indicator model developed by the early warning, crop condition assessment component of AgRISTARS was performed over the corn for grain producing regions of the U.S.S.R. during the 1980 crop year using real data. Performance of the crop calendar submodel was favorable; efficiency gains in meteorological data analysis time were on a magnitude of 85 to 90 percent.

  12. Chemical Modeling for Large-Eddy Simulation of Turbulent Combustion

    Science.gov (United States)

    2009-03-31

    Swirl Burner 11 2 Development of an Interactive Platform for Generation, Comparison, and Evaluation of Kinetic Models for JP-8 Surrogate Fuels 13...the refined mesh resolution is increased. Application of the RLSG to a turbulent bunsen flame, however, showed that the flame front solution remained... bunsen flame. A schematic of this LES is shown in Fig. 4. The contour cut plane shows the temperature field, while the isocontour shows the level

  13. Effects of uncertainty in model predictions of individual tree volume on large area volume estimates

    Science.gov (United States)

    Ronald E. McRoberts; James A. Westfall

    2014-01-01

    Forest inventory estimates of tree volume for large areas are typically calculated by adding model predictions of volumes for individual trees. However, the uncertainty in the model predictions is generally ignored with the result that the precision of the large area volume estimates is overestimated. The primary study objective was to estimate the effects of model...

  14. Modeling a Large Data Acquisition Network in a Simulation Framework

    CERN Document Server

    Colombo, Tommaso; The ATLAS collaboration

    2015-01-01

    The ATLAS detector at CERN records particle collision “events” delivered by the Large Hadron Collider. Its data-acquisition system is a distributed software system that identifies, selects, and stores interesting events in near real-time, with an aggregate throughput of several 10 GB/s. It is a distributed software system executed on a farm of roughly 2000 commodity worker nodes communicating via TCP/IP on an Ethernet network. Event data fragments are received from the many detector readout channels and are buffered, collected together, analyzed and either stored permanently or discarded. This system, and data-acquisition systems in general, are sensitive to the latency of the data transfer from the readout buffers to the worker nodes. Challenges affecting this transfer include the many-to-one communication pattern and the inherently bursty nature of the traffic. In this paper we introduce the main performance issues brought about by this workload, focusing in particular on the so-called TCP incast pathol...

  15. Massive cortical reorganization in sighted Braille readers.

    Science.gov (United States)

    Siuda-Krzywicka, Katarzyna; Bola, Łukasz; Paplińska, Małgorzata; Sumera, Ewa; Jednoróg, Katarzyna; Marchewka, Artur; Śliwińska, Magdalena W; Amedi, Amir; Szwed, Marcin

    2016-03-15

    The brain is capable of large-scale reorganization in blindness or after massive injury. Such reorganization crosses the division into separate sensory cortices (visual, somatosensory...). As its result, the visual cortex of the blind becomes active during tactile Braille reading. Although the possibility of such reorganization in the normal, adult brain has been raised, definitive evidence has been lacking. Here, we demonstrate such extensive reorganization in normal, sighted adults who learned Braille while their brain activity was investigated with fMRI and transcranial magnetic stimulation (TMS). Subjects showed enhanced activity for tactile reading in the visual cortex, including the visual word form area (VWFA) that was modulated by their Braille reading speed and strengthened resting-state connectivity between visual and somatosensory cortices. Moreover, TMS disruption of VWFA activity decreased their tactile reading accuracy. Our results indicate that large-scale reorganization is a viable mechanism recruited when learning complex skills.

  16. Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant.

    Science.gov (United States)

    Steenwijk, Martijn D; Geurts, Jeroen J G; Daams, Marita; Tijms, Betty M; Wink, Alle Meije; Balk, Lisanne J; Tewarie, Prejaas K; Uitdehaag, Bernard M J; Barkhof, Frederik; Vrenken, Hugo; Pouwels, Petra J W

    2016-01-01

    Grey matter atrophy is common in multiple sclerosis. However, in contrast with other neurodegenerative diseases, it is unclear whether grey matter atrophy in multiple sclerosis is a diffuse 'global' process or develops, instead, according to distinct anatomical patterns. Using source-based morphometry we searched for anatomical patterns of co-varying cortical thickness and assessed their relationships with white matter pathology, physical disability and cognitive functioning. Magnetic resonance imaging was performed at 3 T in 208 patients with long-standing multiple sclerosis (141 females; age = 53.7 ± 9.6 years; disease duration = 20.2 ± 7.1 years) and 60 age- and sex-matched healthy controls. Spatial independent component analysis was performed on cortical thickness maps derived from 3D T1-weighted images across all subjects to identify co-varying patterns. The loadings, which reflect the presence of each cortical thickness pattern in a subject, were compared between patients with multiple sclerosis and healthy controls with generalized linear models. Stepwise linear regression analyses were used to assess whether white matter pathology was associated with these loadings and to identify the cortical thickness patterns that predict measures of physical and cognitive dysfunction. Ten cortical thickness patterns were identified, of which six had significantly lower loadings in patients with multiple sclerosis than in controls: the largest loading differences corresponded to the pattern predominantly involving the bilateral temporal pole and entorhinal cortex, and the pattern involving the bilateral posterior cingulate cortex. In patients with multiple sclerosis, overall white matter lesion load was negatively associated with the loadings of these two patterns. The final model for physical dysfunction as measured with Expanded Disability Status Scale score (adjusted R(2) = 0.297; P atrophy patterns relevant for multiple sclerosis were found. This suggests that

  17. Highly efficient model updating for structural condition assessment of large-scale bridges.

    Science.gov (United States)

    2015-02-01

    For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

  18. Small- and large-signal modeling of InP HBTs in transferred-substrate technology

    DEFF Research Database (Denmark)

    Johansen, Tom Keinicke; Rudolph, Matthias; Jensen, Thomas

    2014-01-01

    a direct parameter extraction methodology dedicated to III–V based HBTs. It is shown that the modeling of measured S-parameters can be improved in the millimeter-wave frequency range by augmenting the small-signal model with a description of AC current crowding. The extracted elements of the small......-signal model structure are employed as a starting point for the extraction of a large-signal model. The developed large-signal model for the TS-HBTs accurately predicts the DC over temperature and small-signal performance over bias as well as the large-signal performance at millimeter-wave frequencies....

  19. Model Selection and Hypothesis Testing for Large-Scale Network Models with Overlapping Groups

    Directory of Open Access Journals (Sweden)

    Tiago P. Peixoto

    2015-03-01

    Full Text Available The effort to understand network systems in increasing detail has resulted in a diversity of methods designed to extract their large-scale structure from data. Unfortunately, many of these methods yield diverging descriptions of the same network, making both the comparison and understanding of their results a difficult challenge. A possible solution to this outstanding issue is to shift the focus away from ad hoc methods and move towards more principled approaches based on statistical inference of generative models. As a result, we face instead the more well-defined task of selecting between competing generative processes, which can be done under a unified probabilistic framework. Here, we consider the comparison between a variety of generative models including features such as degree correction, where nodes with arbitrary degrees can belong to the same group, and community overlap, where nodes are allowed to belong to more than one group. Because such model variants possess an increasing number of parameters, they become prone to overfitting. In this work, we present a method of model selection based on the minimum description length criterion and posterior odds ratios that is capable of fully accounting for the increased degrees of freedom of the larger models and selects the best one according to the statistical evidence available in the data. In applying this method to many empirical unweighted networks from different fields, we observe that community overlap is very often not supported by statistical evidence and is selected as a better model only for a minority of them. On the other hand, we find that degree correction tends to be almost universally favored by the available data, implying that intrinsic node proprieties (as opposed to group properties are often an essential ingredient of network formation.

  20. Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

    Directory of Open Access Journals (Sweden)

    Lorenzo L. Pesce

    2013-01-01

    Full Text Available Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons and processor pool sizes (1 to 256 processors. Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

  1. Large-scale modeling of epileptic seizures: scaling properties of two parallel neuronal network simulation algorithms.

    Science.gov (United States)

    Pesce, Lorenzo L; Lee, Hyong C; Hereld, Mark; Visser, Sid; Stevens, Rick L; Wildeman, Albert; van Drongelen, Wim

    2013-01-01

    Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determined the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.

  2. Lhx2 regulates the timing of β-catenin-dependent cortical neurogenesis.

    Science.gov (United States)

    Hsu, Lea Chia-Ling; Nam, Sean; Cui, Yi; Chang, Ching-Pu; Wang, Chia-Fang; Kuo, Hung-Chih; Touboul, Jonathan D; Chou, Shen-Ju

    2015-09-29

    The timing of cortical neurogenesis has a major effect on the size and organization of the mature cortex. The deletion of the LIM-homeodomain transcription factor Lhx2 in cortical progenitors by Nestin-cre leads to a dramatically smaller cortex. Here we report that Lhx2 regulates the cortex size by maintaining the cortical progenitor proliferation and delaying the initiation of neurogenesis. The loss of Lhx2 in cortical progenitors results in precocious radial glia differentiation and a temporal shift of cortical neurogenesis. We further investigated the underlying mechanisms at play and demonstrated that in the absence of Lhx2, the Wnt/β-catenin pathway failed to maintain progenitor proliferation. We developed and applied a mathematical model that reveals how precocious neurogenesis affected cortical surface and thickness. Thus, we concluded that Lhx2 is required for β-catenin function in maintaining cortical progenitor proliferation and controls the timing of cortical neurogenesis.

  3. The Cauchy problem for a model of immiscible gas flow with large data

    Energy Technology Data Exchange (ETDEWEB)

    Sande, Hilde

    2008-12-15

    The thesis consists of an introduction and two papers; 1. The solution of the Cauchy problem with large data for a model of a mixture of gases. 2. Front tracking for a model of immiscible gas flow with large data. (AG) refs, figs

  4. Cortical Control of Zona Incerta

    Science.gov (United States)

    Barthó, Péter; Slézia, Andrea; Varga, Viktor; Bokor, Hajnalka; Pinault, Didier; Buzsáki, György; Acsády, László

    2009-01-01

    The zona incerta (ZI) is at the crossroad of almost all major ascending and descending fiber tracts and targets numerous brain centers from the thalamus to the spinal cord. Effective ascending drive of ZI cells has been described, but the role of descending cortical signals in patterning ZI activity is unknown. Cortical control over ZI function was examined during slow cortical waves (1-3 Hz), paroxysmal high-voltage spindles (HVSs), and 5-9 Hz oscillations in anesthetized rats. In all conditions, rhythmic cortical activity significantly altered the firing pattern of ZI neurons recorded extracellularly and labeled with the juxtacellular method. During slow oscillations, the majority of ZI neurons became synchronized to the depth-negative phase (“up state”) of the cortical waves to a degree comparable to thalamocortical neurons. During HVSs, ZI cells displayed highly rhythmic activity in tight synchrony with the cortical oscillations. ZI neurons responded to short epochs of cortical 5-9 Hz oscillations, with a change in the interspike interval distribution and with an increase in spectral density in the 5-9 Hz band as measured by wavelet analysis. Morphological reconstruction revealed that most ZI cells have mediolaterally extensive dendritic trees and very long dendritic segments. Cortical terminals established asymmetrical synapses on ZI cells with very long active zones. These data suggest efficient integration of widespread cortical signals by single ZI neurons and strong cortical drive. We propose that the efferent GABAergic signal of ZI neurons patterned by the cortical activity can play a critical role in synchronizing thalamocortical and brainstem rhythms. PMID:17301175

  5. A mouse model for studying large-scale neuronal networks using EEG mapping techniques.

    Science.gov (United States)

    Mégevand, Pierre; Quairiaux, Charles; Lascano, Agustina M; Kiss, Jozsef Z; Michel, Christoph M

    2008-08-15

    Human functional imaging studies are increasingly focusing on the identification of large-scale neuronal networks, their temporal properties, their development, and their plasticity and recovery after brain lesions. A method targeting large-scale networks in rodents would open the possibility to investigate their neuronal and molecular basis in detail. We here present a method to study such networks in mice with minimal invasiveness, based on the simultaneous recording of epicranial EEG from 32 electrodes regularly distributed over the head surface. Spatiotemporal analysis of the electrical potential maps similar to human EEG imaging studies allows quantifying the dynamics of the global neuronal activation with sub-millisecond resolution. We tested the feasibility, stability and reproducibility of the method by recording the electrical activity evoked by mechanical stimulation of the mystacial vibrissae. We found a series of potential maps with different spatial configurations that suggested the activation of a large-scale network with generators in several somatosensory and motor areas of both hemispheres. The spatiotemporal activation pattern was stable both across mice and in the same mouse across time. We also performed 16-channel intracortical recordings of the local field potential across cortical layers in different brain areas and found tight spatiotemporal concordance with the generators estimated from the epicranial maps. Epicranial EEG mapping thus allows assessing sensory processing by large-scale neuronal networks in living mice with minimal invasiveness, complementing existing approaches to study the neurophysiological mechanisms of interaction within the network in detail and to characterize their developmental, experience-dependent and lesion-induced plasticity in normal and transgenic animals.

  6. Comparing the performance of SIMD computers by running large air pollution models

    DEFF Research Database (Denmark)

    Brown, J.; Hansen, Per Christian; Wasniewski, J.

    1996-01-01

    To compare the performance and use of three massively parallel SIMD computers, we implemented a large air pollution model on these computers. Using a realistic large-scale model, we gained detailed insight about the performance of the computers involved when used to solve large-scale scientific...... problems that involve several types of numerical computations. The computers used in our study are the Connection Machines CM-200 and CM-5, and the MasPar MP-2216...

  7. Cortical inactivation by cooling in small animals

    Directory of Open Access Journals (Sweden)

    Ben eCoomber

    2011-06-01

    Full Text Available Reversible inactivation of the cortex by surface cooling is a powerful method for studying the function of a particular area. Implanted cooling cryoloops have been used to study the role of individual cortical areas in auditory processing of awake-behaving cats. Cryoloops have also been used in rodents for reversible inactivation of the cortex, but recently there has been a concern that the cryoloop may also cool non-cortical structures either directly or via the perfusion of blood, cooled as it passed close to the cooling loop. In this study we have confirmed that the loop can inactivate most of the auditory cortex without causing a significant reduction in temperature of the auditory thalamus or other sub-cortical structures. We placed a cryoloop on the surface of the guinea pig cortex, cooled it to 2°C and measured thermal gradients across the neocortical surface. We found that the temperature dropped to 20-24°C among cells within a radius of about 2.5mm away from the loop. This temperature drop was sufficient to reduce activity of most cortical cells and led to the inactivation of almost the entire auditory region. When the temperature of thalamus, midbrain, and middle ear were measured directly during cortical cooling, there was a small drop in temperature (about 4°C but this was not sufficient to directly reduce neural activity. In an effort to visualise the extent of neural inactivation we measured the uptake of thallium ions following an intravenous injection. This confirmed that there was a large reduction of activity across much of the ipsilateral cortex and only a small reduction in subcortical structures.

  8. Stochastic amplification of fluctuations in cortical up-states.

    Directory of Open Access Journals (Sweden)

    Jorge Hidalgo

    Full Text Available Cortical neurons are bistable; as a consequence their local field potentials can fluctuate between quiescent and active states, generating slow 0.5 2 Hz oscillations which are widely known as transitions between Up and Down States. Despite a large number of studies on Up-Down transitions, deciphering its nature, mechanisms and function are still today challenging tasks. In this paper we focus on recent experimental evidence, showing that a class of spontaneous oscillations can emerge within the Up states. In particular, a non-trivial peak around 20 Hz appears in their associated power-spectra, what produces an enhancement of the activity power for higher frequencies (in the 30-90 Hz band. Moreover, this rhythm within Ups seems to be an emergent or collective phenomenon given that individual neurons do not lock to it as they remain mostly unsynchronized. Remarkably, similar oscillations (and the concomitant peak in the spectrum do not appear in the Down states. Here we shed light on these findings by using different computational models for the dynamics of cortical networks in presence of different levels of physiological complexity. Our conclusion, supported by both theory and simulations, is that the collective phenomenon of "stochastic amplification of fluctuations"--previously described in other contexts such as Ecology and Epidemiology--explains in an elegant and parsimonious manner, beyond model-dependent details, this extra-rhythm emerging only in the Up states but not in the Downs.

  9. Stochastic Amplification of Fluctuations in Cortical Up-States

    Science.gov (United States)

    Hidalgo, Jorge; Seoane, Luís F.; Cortés, Jesús M.; Muñoz, Miguel A.

    2012-01-01

    Cortical neurons are bistable; as a consequence their local field potentials can fluctuate between quiescent and active states, generating slow Hz oscillations which are widely known as transitions between Up and Down States. Despite a large number of studies on Up-Down transitions, deciphering its nature, mechanisms and function are still today challenging tasks. In this paper we focus on recent experimental evidence, showing that a class of spontaneous oscillations can emerge within the Up states. In particular, a non-trivial peak around Hz appears in their associated power-spectra, what produces an enhancement of the activity power for higher frequencies (in the Hz band). Moreover, this rhythm within Ups seems to be an emergent or collective phenomenon given that individual neurons do not lock to it as they remain mostly unsynchronized. Remarkably, similar oscillations (and the concomitant peak in the spectrum) do not appear in the Down states. Here we shed light on these findings by using different computational models for the dynamics of cortical networks in presence of different levels of physiological complexity. Our conclusion, supported by both theory and simulations, is that the collective phenomenon of “stochastic amplification of fluctuations” – previously described in other contexts such as Ecology and Epidemiology – explains in an elegant and parsimonious manner, beyond model-dependent details, this extra-rhythm emerging only in the Up states but not in the Downs. PMID:22879879

  10. The sheep as a large osteoporotic model for orthopaedic research in humans

    DEFF Research Database (Denmark)

    Cheng, L.; Ding, Ming; Li, Z.

    2008-01-01

    Although small animals as rodents are very popular animals for osteoporosis models , large animals models are necessary for research of human osteoporotic diseases. Sheep osteoporosis models are becoming more important because of its unique advantages for osteoporosis reseach. Sheep are docile...... intake restriction and glucocorticoid application are the most effective methods for sheep osteoporosis model. Sheep osteoporosis model is an ideal animal model for studying various medicines reacting to osteoporosis and other treatment methods such as prosthetic replacement reacting to osteoporotic...

  11. Visual cortical areas of the mouse: comparison of parcellation and network structure with primates

    Science.gov (United States)

    Laramée, Marie-Eve; Boire, Denis

    2015-01-01

    Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals. PMID:25620914

  12. Visual cortical areas of the mouse: comparison of parcellation and network structure with primates

    Directory of Open Access Journals (Sweden)

    Marie-Eve eLaramée

    2015-01-01

    Full Text Available Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals.

  13. High-spatial-resolution mapping of the oxygen concentration in cortical tissue (Conference Presentation)

    Science.gov (United States)

    Jaswal, Rajeshwer S.; Yaseen, Mohammad A.; Fu, Buyin; Boas, David A.; Sakadžic, Sava

    2016-03-01

    Due to a lack of imaging tools for high-resolution imaging of cortical tissue oxygenation, the detailed maps of the oxygen partial pressure (PO2) around arterioles, venules, and capillaries remain largely unknown. Therefore, we have limited knowledge about the mechanisms that secure sufficient oxygen delivery in microvascular domains during brain activation, and provide some metabolic reserve capacity in diseases that affect either microvascular networks or the regulation of cerebral blood flow (CBF). To address this challenge, we applied a Two-Photon PO2 Microscopy to map PO2 at different depths in mice cortices. Measurements were performed through the cranial window in the anesthetized healthy mice as well as in the mouse models of microvascular dysfunctions. In addition, microvascular morphology was recorded by the two-photon microscopy at the end of each experiment and subsequently segmented. Co-registration of the PO2 measurements and exact microvascular morphology enabled quantification of the tissue PO2 dependence on distance from the arterioles, capillaries, and venules at various depths. Our measurements reveal significant spatial heterogeneity of the cortical tissue PO2 distribution that is dominated by the high oxygenation in periarteriolar spaces. In cases of impaired oxygen delivery due to microvascular dysfunction, significant reduction in tissue oxygenation away from the arterioles was observed. These tissue domains may be the initial sites of cortical injury that can further exacerbate the progression of the disease.

  14. Hiperostosis cortical infantil

    OpenAIRE

    Salvador Javier Santos Medina; Orelvis Pérez Duerto

    2015-01-01

    La enfermedad de Caffey, o hiperostosis cortical infantil, es una rara enfermedad ósea autolimitada, que aparece de preferencia en lactantes con signos inespecíficos sistémicos; el más relevante es la reacción subperióstica e hiperostosis en varios huesos del cuerpo, con predilección en el 75-80 % de los casos por la mandíbula. Su pronóstico es bueno, la mayoría no deja secuelas. El propósito del presente trabajo es describir las características clínicas, presentes en un lactante de cinco mes...

  15. Progressive posterior cortical dysfunction

    Directory of Open Access Journals (Sweden)

    Fábio Henrique de Gobbi Porto

    Full Text Available Abstract Progressive posterior cortical dysfunction (PPCD is an insidious syndrome characterized by prominent disorders of higher visual processing. It affects both dorsal (occipito-parietal and ventral (occipito-temporal pathways, disturbing visuospatial processing and visual recognition, respectively. We report a case of a 67-year-old woman presenting with progressive impairment of visual functions. Neurologic examination showed agraphia, alexia, hemispatial neglect (left side visual extinction, complete Balint's syndrome and visual agnosia. Magnetic resonance imaging showed circumscribed atrophy involving the bilateral parieto-occipital regions, slightly more predominant to the right . Our aim was to describe a case of this syndrome, to present a video showing the main abnormalities, and to discuss this unusual presentation of dementia. We believe this article can contribute by improving the recognition of PPCD.

  16. A Mechanistic Link from GABA to Cortical Architecture and Perception.

    Science.gov (United States)

    Kolasinski, James; Logan, John P; Hinson, Emily L; Manners, Daniel; Divanbeighi Zand, Amir P; Makin, Tamar R; Emir, Uzay E; Stagg, Charlotte J

    2017-06-05

    Understanding both the organization of the human cortex and its relation to the performance of distinct functions is fundamental in neuroscience. The primary sensory cortices display topographic organization, whereby receptive fields follow a characteristic pattern, from tonotopy to retinotopy to somatotopy [1]. GABAergic signaling is vital to the maintenance of cortical receptive fields [2]; however, it is unclear how this fine-grain inhibition relates to measurable patterns of perception [3, 4]. Based on perceptual changes following perturbation of the GABAergic system, it is conceivable that the resting level of cortical GABAergic tone directly relates to the spatial specificity of activation in response to a given input [5-7]. The specificity of cortical activation can be considered in terms of cortical tuning: greater cortical tuning yields more localized recruitment of cortical territory in response to a given input. We applied a combination of fMRI, MR spectroscopy, and psychophysics to substantiate the link between the cortical neurochemical milieu, the tuning of cortical activity, and variability in perceptual acuity, using human somatosensory cortex as a model. We provide data that explain human perceptual acuity in terms of both the underlying cellular and metabolic processes. Specifically, higher concentrations of sensorimotor GABA are associated with more selective cortical tuning, which in turn is associated with enhanced perception. These results show anatomical and neurochemical specificity and are replicated in an independent cohort. The mechanistic link from neurochemistry to perception provides a vital step in understanding population variability in sensory behavior, informing metabolic therapeutic interventions to restore perceptual abilities clinically. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  17. Plasticity of cortical excitatory-inhibitory balance.

    Science.gov (United States)

    Froemke, Robert C

    2015-07-08

    Synapses are highly plastic and are modified by changes in patterns of neural activity or sensory experience. Plasticity of cortical excitatory synapses is thought to be important for learning and memory, leading to alterations in sensory representations and cognitive maps. However, these changes must be coordinated across other synapses within local circuits to preserve neural coding schemes and the organization of excitatory and inhibitory inputs, i.e., excitatory-inhibitory balance. Recent studies indicate that inhibitory synapses are also plastic and are controlled directly by a large number of neuromodulators, particularly during episodes of learning. Many modulators transiently alter excitatory-inhibitory balance by decreasing inhibition, and thus disinhibition has emerged as a major mechanism by which neuromodulation might enable long-term synaptic modifications naturally. This review examines the relationships between neuromodulation and synaptic plasticity, focusing on the induction of long-term changes that collectively enhance cortical excitatory-inhibitory balance for improving perception and behavior.

  18. Functional cortical mapping of scale illusion

    International Nuclear Information System (INIS)

    Wang, Li-qun; Kuriki, Shinya

    2011-01-01

    We have studied cortical activation using 1.5 T fMRI during 'Scale Illusion', a kind of auditory illusion, in which subjects perceive smooth melodies while listening to dichotic irregular pitch sequences consisting of scale tones, in repeated phrases composed of eight tones. Four male and four female subjects listened to different stimuli, that including illusion-inducing tone sequence, monaural tone sequence and perceived pitch sequence with a control of white noises delivered to the right and left ears in random order. 32 scans with a repetition time (TR) 3 s Between 3 s interval for each type of the four stimuli were performed. In BOLD signals, activation was observed in the prefrontal and temporal cortices, parietal lobule and occipital areas by first-level group analysis. However, there existed large intersubject variability such that systematic tendency of the activation was not clear. The study will be continued to obtain larger number of subjects for group analysis. (author)

  19. Cortical layers: Cyto-, myelo-, receptor- and synaptic architecture in human cortical areas.

    Science.gov (United States)

    Palomero-Gallagher, Nicola; Zilles, Karl

    2017-08-12

    Cortical layers have classically been identified by their distinctive and prevailing cell types and sizes, as well as the packing densities of cell bodies or myelinated fibers. The densities of multiple receptors for classical neurotransmitters also vary across the depth of the cortical ribbon, and thus determine the neurochemical properties of cyto- and myeloarchitectonic layers. However, a systematic comparison of the correlations between these histologically definable layers and the laminar distribution of transmitter receptors is currently lacking. We here analyze the densities of 17 different receptors of various transmitter systems in the layers of eight cytoarchitectonically identified, functionally (motor, sensory, multimodal) and hierarchically (primary and secondary sensory, association) distinct areas of the human cerebral cortex. Maxima of receptor densities are found in different layers when comparing different cortical regions, i.e. laminar receptor densities demonstrate differences in receptorarchitecture between isocortical areas, notably between motor and primary sensory cortices, specifically the primary visual and somatosensory cortices, as well as between allocortical and isocortical areas. Moreover, considerable differences are found between cytoarchitectonical and receptor architectonical laminar patterns. Whereas the borders of cyto- and myeloarchitectonic layers are well comparable, the laminar profiles of receptor densities rarely coincide with the histologically defined borders of layers. Instead, highest densities of most receptors are found where the synaptic density is maximal, i.e. in the supragranular layers, particularly in layers II-III. The entorhinal cortex as an example of the allocortex shows a peculiar laminar organization, which largely deviates from that of all the other cortical areas analyzed here. Copyright © 2017. Published by Elsevier Inc.

  20. Modeling the Effect of Climate Change on Large Fire Size, Counts, and Intensities Using the Large Fire Simulator (FSim)

    Science.gov (United States)

    Riley, K. L.; Haas, J. R.; Finney, M.; Abatzoglou, J. T.

    2013-12-01

    Changes in climate can be expected to cause changes in wildfire activity due to a combination of shifts in weather (temperature, precipitation, relative humidity, wind speed and direction) and vegetation. Changes in vegetation could include type conversions, altered forest structure, and shifts in species composition, the effects of which could be mitigated or exacerbated by management activities. Further, changes in suppression response and effectiveness may alter potential wildfire activity, as well as the consequences of wildfire. Feedbacks among these factors are extremely complex and uncertain. The ability to anticipate changes driven by fire weather (largely outside of human control) can lead to development of fire and fuel management strategies aimed at mitigating current and future risk. Therefore, in this study we focus on isolating the effects of climate-induced changes in weather on wildfire activity. Specifically, we investigated the effect of changes in weather on fire activity in the Canadian Rockies ecoregion, which encompasses Glacier National Park and several large wilderness areas to the south. To model the ignition, growth, and containment of wildfires, we used the Large Fire Simulator (FSim), which we coupled with current and projected future climatic conditions. Weather streams were based on data from 14 downscaled Global Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) using the Representative Concentration Pathways (RCP) 45 and 85 for the years 2040-2060. While all GCMs indicate increases in temperature for this area, which would be expected to exacerbate fire activity, precipitation predictions for the summer wildfire season are more variable, ranging from a decrease of approximately 50 mm to an increase of approximately 50 mm. Windspeeds are generally predicted to decrease, which would reduce rates of spread and fire intensity. The net effect of these weather changes on the size, number, and intensity

  1. Neuregulin 3 Mediates Cortical Plate Invasion and Laminar Allocation of GABAergic Interneurons

    Directory of Open Access Journals (Sweden)

    Giorgia Bartolini

    2017-01-01

    Full Text Available Neural circuits in the cerebral cortex consist of excitatory pyramidal cells and inhibitory interneurons. These two main classes of cortical neurons follow largely different genetic programs, yet they assemble into highly specialized circuits during development following a very precise choreography. Previous studies have shown that signals produced by pyramidal cells influence the migration of cortical interneurons, but the molecular nature of these factors has remained elusive. Here, we identified Neuregulin 3 (Nrg3 as a chemoattractive factor expressed by developing pyramidal cells that guides the allocation of cortical interneurons in the developing cortical plate. Gain- and loss-of-function approaches reveal that Nrg3 modulates the migration of interneurons into the cortical plate in a process that is dependent on the tyrosine kinase receptor ErbB4. Perturbation of Nrg3 signaling in conditional mutants leads to abnormal lamination of cortical interneurons. Nrg3 is therefore a critical mediator in the assembly of cortical inhibitory circuits.

  2. Using radar altimetry to update a large-scale hydrological model of the Brahmaputra river basin

    DEFF Research Database (Denmark)

    Finsen, F.; Milzow, Christian; Smith, R.

    2014-01-01

    of the Brahmaputra is excellent (17 high-quality virtual stations from ERS-2, 6 from Topex and 10 from Envisat are available for the Brahmaputra). In this study, altimetry data are used to update a large-scale Budyko-type hydrological model of the Brahmaputra river basin in real time. Altimetry measurements...... improved model performance considerably. The Nash-Sutcliffe model efficiency increased from 0.77 to 0.83. Real-time river basin modelling using radar altimetry has the potential to improve the predictive capability of large-scale hydrological models elsewhere on the planet....

  3. High-Degree Neurons Feed Cortical Computations.

    Directory of Open Access Journals (Sweden)

    Nicholas M Timme

    2016-05-01

    Full Text Available Recent work has shown that functional connectivity among cortical neurons is highly varied, with a small percentage of neurons having many more connections than others. Also, recent theoretical developments now make it possible to quantify how neurons modify information from the connections they receive. Therefore, it is now possible to investigate how information modification, or computation, depends on the number of connections a neuron receives (in-degree or sends out (out-degree. To do this, we recorded the simultaneous spiking activity of hundreds of neurons in cortico-hippocampal slice cultures using a high-density 512-electrode array. This preparation and recording method combination produced large numbers of neurons recorded at temporal and spatial resolutions that are not currently available in any in vivo recording system. We utilized transfer entropy (a well-established method for detecting linear and nonlinear interactions in time series and the partial information decomposition (a powerful, recently developed tool for dissecting multivariate information processing into distinct parts to quantify computation between neurons where information flows converged. We found that computations did not occur equally in all neurons throughout the networks. Surprisingly, neurons that computed large amounts of information tended to receive connections from high out-degree neurons. However, the in-degree of a neuron was not related to the amount of information it computed. To gain insight into these findings, we developed a simple feedforward network model. We found that a degree-modified Hebbian wiring rule best reproduced the pattern of computation and degree correlation results seen in the real data. Interestingly, this rule also maximized signal propagation in the presence of network-wide correlations, suggesting a mechanism by which cortex could deal with common random background input. These are the first results to show that the extent to

  4. Analytical model of the statistical properties of contrast of large-scale ionospheric inhomogeneities.

    Science.gov (United States)

    Vsekhsvyatskaya, I. S.; Evstratova, E. A.; Kalinin, Yu. K.; Romanchuk, A. A.

    1989-08-01

    A new analytical model is proposed for the distribution of variations of the relative electron-density contrast of large-scale ionospheric inhomogeneities. The model is characterized by other-than-zero skewness and kurtosis. It is shown that the model is applicable in the interval of horizontal dimensions of inhomogeneities from hundreds to thousands of kilometers.

  5. Large-signal PIN diode model for ultra-fast photodetectors

    DEFF Research Database (Denmark)

    Krozer, Viktor; Fritsche, C

    2005-01-01

    A large-signal model for PIN photodetector is presented, which can be applied to ultra-fast photodetection and THz signal generation. The model takes into account the tunnelling and avalanche breakdown, which is important for avalanche photodiodes. The model is applied to ultra-fast superlattice ...

  6. Cortical spatiotemporal dimensionality reduction for visual grouping

    OpenAIRE

    Cocci, Giacomo; Barbieri, Davide; Citti, Giovanna; Sarti, Alessandro

    2015-01-01

    The visual systems of many mammals, including humans, are able to integrate the geometric information of visual stimuli and perform cognitive tasks at the first stages of the cortical processing. This is thought to be the result of a combination of mechanisms, which include feature extraction at the single cell level and geometric processing by means of cell connectivity. We present a geometric model of such connectivities in the space of detected features associated with spatiotemporal visua...

  7. How uncertainty in socio-economic variables affects large-scale transport model forecasts

    DEFF Research Database (Denmark)

    Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo

    2015-01-01

    time, especially with respect to large-scale transport models. The study described in this paper contributes to fill the gap by investigating the effects of uncertainty in socio-economic variables growth rate projections on large-scale transport model forecasts, using the Danish National Transport......A strategic task assigned to large-scale transport models is to forecast the demand for transport over long periods of time to assess transport projects. However, by modelling complex systems transport models have an inherent uncertainty which increases over time. As a consequence, the longer...... the period forecasted the less reliable is the forecasted model output. Describing uncertainty propagation patterns over time is therefore important in order to provide complete information to the decision makers. Among the existing literature only few studies analyze uncertainty propagation patterns over...

  8. Cortical-Cortical Interactions And Sensory Information Processing in Autism

    Science.gov (United States)

    2008-04-30

    Additionally, these cortical areas have been implicated from significantly elevated TOJ thresholds (worse performance) in subjects with dyslexia [5...of the fact that above-average TOJ thresholds occur in subjects with known damage to these same cortical areas ( dyslexia [5], dystonia [6-8], and...Tomma-Halme J, Lahti-Nuuttila P, Service E, Virsu V: Rate of information segregation in developmentally dyslexic children . Brain Lang 2000, 75:66-81

  9. Large-Signal Code TESLA: Improvements in the Implementation and in the Model

    National Research Council Canada - National Science Library

    Chernyavskiy, Igor A; Vlasov, Alexander N; Anderson, Jr., Thomas M; Cooke, Simon J; Levush, Baruch; Nguyen, Khanh T

    2006-01-01

    We describe the latest improvements made in the large-signal code TESLA, which include transformation of the code to a Fortran-90/95 version with dynamical memory allocation and extension of the model...

  10. Large Deviations for Stochastic Models of Two-Dimensional Second Grade Fluids

    Energy Technology Data Exchange (ETDEWEB)

    Zhai, Jianliang, E-mail: zhaijl@ustc.edu.cn [University of Science and Technology of China, School of Mathematical Sciences (China); Zhang, Tusheng, E-mail: Tusheng.Zhang@manchester.ac.uk [University of Manchester, School of Mathematics (United Kingdom)

    2017-06-15

    In this paper, we establish a large deviation principle for stochastic models of incompressible second grade fluids. The weak convergence method introduced by Budhiraja and Dupuis (Probab Math Statist 20:39–61, 2000) plays an important role.

  11. Various approaches to the modelling of large scale 3-dimensional circulation in the Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Shaji, C.; Bahulayan, N.; Rao, A.D.; Dube, S.K.

    In this paper, the three different approaches to the modelling of large scale 3-dimensional flow in the ocean such as the diagnostic, semi-diagnostic (adaptation) and the prognostic are discussed in detail. Three-dimensional solutions are obtained...

  12. Analysis and Modelling of Pedestrian Movement Dynamics at Large-scale Events

    NARCIS (Netherlands)

    Duives, D.C.

    2016-01-01

    To what extent can we model the movements of pedestrians who walk across a large-scale event terrain? This dissertation answers this question by analysing the operational movement dynamics of pedestrians in crowds at several large music and sport events in the Netherlands and extracting the key

  13. Measurements in SUGRA Models with Large $\\tan\\beta$ at LHC

    CERN Document Server

    Hinchliffe, Ian

    1999-01-01

    We present an example of a scenario of particle production and decay in supersymmetry models in which the supersymmetry breaking is transmitted to the observable world via gravitational interactions. The case is chosen so that there is a large production of tau leptons in the final state. It is characteristic of large $\\tan\\beta$ that decays into muons and electrons may be supressed.

  14. [Visualization of local cortical defects in Charcot foot using microcomputed tomography].

    Science.gov (United States)

    Senck, S; Plank, B; Kastner, J; Ramadani, F; Trieb, K; Hofstaetter, S G

    2015-01-01

    In the pathogenesis of diabetic neuropathic osteoarthropathy (Charcot's foot) fractures cause chronic destruction of soft tissue and bone structure. To improve an early diagnosis of Charcot foot, modern diagnostic imaging is mainly based on magnetic resonance imaging (MRI), for example in relation to the detection of cortical bone fractures. In this study we investigated the cortical microstructure in cases of Charcot foot with respect to fractures and porosity in order to visualize local cortical defects. This may substantiate recent efforts in a reclassification based on MRI. Using microcomputed tomography (microCT) we investigated bone parameters, such as cortical thickness and porosity in order to quantify the local metatarsal microstructure in cases of Charcot foot. All bone samples showed a high degree of cortical porosity including pores that perforated the cortical bone. The data suggest that areas with reduced cortical thickness coincide with large cortical pores that may serve as initial points for fractures. Whether the detected microfractures are physiological or artefacts of preparation could not be determined. By means of microCT we were able to visualize and quantify the extent of cortical porosity for the first time in high resolution. The data suggest that both cortical fractures and cortical porosity play an important role in the pathogenesis in cases of Charcot foot.

  15. Monte Carlo model of light transport in scintillating fibers and large scintillators

    International Nuclear Information System (INIS)

    Chakarova, R.

    1995-01-01

    A Monte Carlo model is developed which simulates the light transport in a scintillator surrounded by a transparent layer with different surface properties. The model is applied to analyse the light collection properties of scintillating fibers and a large scintillator wrapped in aluminium foil. The influence of the fiber interface characteristics on the light yield is investigated in detail. Light output results as well as time distributions are obtained for the large scintillator case. 15 refs, 16 figs

  16. Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

    Science.gov (United States)

    West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

    2016-01-01

    Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

  17. Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

    Science.gov (United States)

    Li, J.

    2017-12-01

    Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

  18. Unaltered Network Activity and Interneuronal Firing During Spontaneous Cortical Dynamics In Vivo in a Mouse Model of Severe Myoclonic Epilepsy of Infancy.

    Science.gov (United States)

    De Stasi, Angela Michela; Farisello, Pasqualina; Marcon, Iacopo; Cavallari, Stefano; Forli, Angelo; Vecchia, Dania; Losi, Gabriele; Mantegazza, Massimo; Panzeri, Stefano; Carmignoto, Giorgio; Bacci, Alberto; Fellin, Tommaso

    2016-04-01

    Severe myoclonic epilepsy of infancy (SMEI) is associated with loss of function of the SCN1A gene encoding the NaV1.1 sodium channel isoform. Previous studies in Scn1a(-/+) mice during the pre-epileptic period reported selective reduction in interneuron excitability and proposed this as the main pathological mechanism underlying SMEI. Yet, the functional consequences of this interneuronal dysfunction at the circuit level in vivo are unknown. Here, we investigated whether Scn1a(-/+) mice showed alterations in cortical network function. We found that various forms of spontaneous network activity were similar in Scn1a(-/+) during the pre-epileptic period compared with wild-type (WT) in vivo. Importantly, in brain slices from Scn1a(-/+) mice, the excitability of parvalbumin (PV) and somatostatin (SST) interneurons was reduced, epileptiform activity propagated more rapidly, and complex synaptic changes were observed. However, in vivo, optogenetic reduction of firing in PV or SST cells in WT mice modified ongoing network activities, and juxtasomal recordings from identified PV and SST interneurons showed unaffected interneuronal firing during spontaneous cortical dynamics in Scn1a(-/+) compared with WT. These results demonstrate that interneuronal hypoexcitability is not observed in Scn1a(-/+) mice during spontaneous activities in vivo and suggest that additional mechanisms may contribute to homeostatic rearrangements and the pathogenesis of SMEI. © The Author 2016. Published by Oxford University Press.

  19. Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

    Directory of Open Access Journals (Sweden)

    A. F. Van Loon

    2012-11-01

    Full Text Available 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 drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP. For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity, drought propagation features (pooling, attenuation, lag, lengthening, and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought.

    Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an

  20. Large animal and primate models of spinal cord injury for the testing of novel therapies.

    Science.gov (United States)

    Kwon, Brian K; Streijger, Femke; Hill, Caitlin E; Anderson, Aileen J; Bacon, Mark; Beattie, Michael S; Blesch, Armin; Bradbury, Elizabeth J; Brown, Arthur; Bresnahan, Jacqueline C; Case, Casey C; Colburn, Raymond W; David, Samuel; Fawcett, James W; Ferguson, Adam R; Fischer, Itzhak; Floyd, Candace L; Gensel, John C; Houle, John D; Jakeman, Lyn B; Jeffery, Nick D; Jones, Linda Ann Truett; Kleitman, Naomi; Kocsis, Jeffery; Lu, Paul; Magnuson, David S K; Marsala, Martin; Moore, Simon W; Mothe, Andrea J; Oudega, Martin; Plant, Giles W; Rabchevsky, Alexander Sasha; Schwab, Jan M; Silver, Jerry; Steward, Oswald; Xu, Xiao-Ming; Guest, James D; Tetzlaff, Wolfram

    2015-07-01

    Large animal and primate models of spinal cord injury (SCI) are being increasingly utilized for the testing of novel therapies. While these represent intermediary animal species between rodents and humans and offer the opportunity to pose unique research questions prior to clinical trials, the role that such large animal and primate models should play in the translational pipeline is unclear. In this initiative we engaged members of the SCI research community in a questionnaire and round-table focus group discussion around the use of such models. Forty-one SCI researchers from academia, industry, and granting agencies were asked to complete a questionnaire about their opinion regarding the use of large animal and primate models in the context of testing novel therapeutics. The questions centered around how large animal and primate models of SCI would be best utilized in the spectrum of preclinical testing, and how much testing in rodent models was warranted before employing these models. Further questions were posed at a focus group meeting attended by the respondents. The group generally felt that large animal and primate models of SCI serve a potentially useful role in the translational pipeline for novel therapies, and that the rational use of these models would depend on the type of therapy and specific research question being addressed. While testing within these models should not be mandatory, the detection of beneficial effects using these models lends additional support for translating a therapy to humans. These models provides an opportunity to evaluate and refine surgical procedures prior to use in humans, and safety and bio-distribution in a spinal cord more similar in size and anatomy to that of humans. Our results reveal that while many feel that these models are valuable in the testing of novel therapies, important questions remain unanswered about how they should be used and how data derived from them should be interpreted. Copyright © 2015 Elsevier

  1. Altered Cortical Swallowing Processing in Patients with Functional Dysphagia: A Preliminary Study

    Science.gov (United States)

    Wollbrink, Andreas; Warnecke, Tobias; Winkels, Martin; Pantev, Christo; Dziewas, Rainer

    2014-01-01

    Objective Current neuroimaging research on functional disturbances provides growing evidence for objective neuronal correlates of allegedly psychogenic symptoms, thereby shifting the disease concept from a psychological towards a neurobiological model. Functional dysphagia is such a rare condition, whose pathogenetic mechanism is largely unknown. In the absence of any organic reason for a patient's persistent swallowing complaints, sensorimotor processing abnormalities involving central neural pathways constitute a potential etiology. Methods In this pilot study we measured cortical swallow-related activation in 5 patients diagnosed with functional dysphagia and a matched group of healthy subjects applying magnetoencephalography. Source localization of cortical activation was done with synthetic aperture magnetometry. To test for significant differences in cortical swallowing processing between groups, a non-parametric permutation test was afterwards performed on individual source localization maps. Results Swallowing task performance was comparable between groups. In relation to control subjects, in whom activation was symmetrically distributed in rostro-medial parts of the sensorimotor cortices of both hemispheres, patients showed prominent activation of the right insula, dorsolateral prefrontal cortex and lateral premotor, motor as well as inferolateral parietal cortex. Furthermore, activation was markedly reduced in the left medial primary sensory cortex as well as right medial sensorimotor cortex and adjacent supplementary motor area (pdysphagia - a condition with assumed normal brain function - seems to be associated with distinctive changes of the swallow-related cortical activation pattern. Alterations may reflect exaggerated activation of a widely distributed vigilance, self-monitoring and salience rating network that interferes with down-stream deglutition sensorimotor control. PMID:24586948

  2. Modeling and Control of a Large Nuclear Reactor A Three-Time-Scale Approach

    CERN Document Server

    Shimjith, S R; Bandyopadhyay, B

    2013-01-01

    Control analysis and design of large nuclear reactors requires a suitable mathematical model representing the steady state and dynamic behavior of the reactor with reasonable accuracy. This task is, however, quite challenging because of several complex dynamic phenomena existing in a reactor. Quite often, the models developed would be of prohibitively large order, non-linear and of complex structure not readily amenable for control studies. Moreover, the existence of simultaneously occurring dynamic variations at different speeds makes the mathematical model susceptible to numerical ill-conditioning, inhibiting direct application of standard control techniques. This monograph introduces a technique for mathematical modeling of large nuclear reactors in the framework of multi-point kinetics, to obtain a comparatively smaller order model in standard state space form thus overcoming these difficulties. It further brings in innovative methods for controller design for systems exhibiting multi-time-scale property,...

  3. Recent Advances in Detailed Chemical Kinetic Models for Large Hydrocarbon and Biodiesel Transportation Fuels

    Energy Technology Data Exchange (ETDEWEB)

    Westbrook, C K; Pitz, W J; Curran, H J; Herbinet, O; Mehl, M

    2009-03-30

    n-Hexadecane and 2,2,4,4,6,8,8-heptamethylnonane represent the primary reference fuels for diesel that are used to determine cetane number, a measure of the ignition property of diesel fuel. With the development of chemical kinetics models for these two primary reference fuels for diesel, a new capability is now available to model diesel fuel ignition. Also, we have developed chemical kinetic models for a whole series of large n-alkanes and a large iso-alkane to represent these chemical classes in fuel surrogates for conventional and future fuels. Methyl decanoate and methyl stearate are large methyl esters that are closely related to biodiesel fuels, and kinetic models for these molecules have also been developed. These chemical kinetic models are used to predict the effect of the fuel molecule size and structure on ignition characteristics under conditions found in internal combustion engines.

  4. Optimization of large-scale heterogeneous system-of-systems models.

    Energy Technology Data Exchange (ETDEWEB)

    Parekh, Ojas; Watson, Jean-Paul; Phillips, Cynthia Ann; Siirola, John; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Lee, Herbert K. H. (University of California, Santa Cruz, Santa Cruz, CA); Hart, William Eugene; Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Woodruff, David L. (University of California, Davis, Davis, CA)

    2012-01-01

    Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.

  5. Stroke Lesions in a Large Upper Limb Rehabilitation Trial Cohort Rarely Match Lesions in Common Preclinical Models.

    Science.gov (United States)

    Edwardson, Matthew A; Wang, Ximing; Liu, Brent; Ding, Li; Lane, Christianne J; Park, Caron; Nelsen, Monica A; Jones, Theresa A; Wolf, Steven L; Winstein, Carolee J; Dromerick, Alexander W

    2017-06-01

    Stroke patients with mild-moderate upper extremity motor impairments and minimal sensory and cognitive deficits provide a useful model to study recovery and improve rehabilitation. Laboratory-based investigators use lesioning techniques for similar goals. To determine whether stroke lesions in an upper extremity rehabilitation trial cohort match lesions from the preclinical stroke recovery models used to drive translational research. Clinical neuroimages from 297 participants enrolled in the Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (ICARE) study were reviewed. Images were characterized based on lesion type (ischemic or hemorrhagic), volume, vascular territory, depth (cortical gray matter, cortical white matter, subcortical), old strokes, and leukoaraiosis. Lesions were compared with those of preclinical stroke models commonly used to study upper limb recovery. Among the ischemic stroke participants, median infarct volume was 1.8 mL, with most lesions confined to subcortical structures (61%) including the anterior choroidal artery territory (30%) and the pons (23%). Of ICARE participants, stroke patients, but they represent a clinically and scientifically important subgroup. Compared with lesions in general stroke populations and widely studied animal models of recovery, ICARE participants had smaller, more subcortically based strokes. Improved preclinical-clinical translational efforts may require better alignment of lesions between preclinical and human stroke recovery models.

  6. A Regression Algorithm for Model Reduction of Large-Scale Multi-Dimensional Problems

    Science.gov (United States)

    Rasekh, Ehsan

    2011-11-01

    Model reduction is an approach for fast and cost-efficient modelling of large-scale systems governed by Ordinary Differential Equations (ODEs). Multi-dimensional model reduction has been suggested for reduction of the linear systems simultaneously with respect to frequency and any other parameter of interest. Multi-dimensional model reduction is also used to reduce the weakly nonlinear systems based on Volterra theory. Multiple dimensions degrade the efficiency of reduction by increasing the size of the projection matrix. In this paper a new methodology is proposed to efficiently build the reduced model based on regression analysis. A numerical example confirms the validity of the proposed regression algorithm for model reduction.

  7. A dynamic programming approach for quickly estimating large network-based MEV models

    DEFF Research Database (Denmark)

    Mai, Tien; Frejinger, Emma; Fosgerau, Mogens

    2017-01-01

    by a rooted, directed graph where each node without successor is an alternative. We formulate a family of MEV models as dynamic discrete choice models on graphs of correlation structures and show that the dynamic models are consistent with MEV theory and generalize the network MEV model (Daly and Bierlaire......We propose a way to estimate a family of static Multivariate Extreme Value (MEV) models with large choice sets in short computational time. The resulting model is also straightforward and fast to use for prediction. Following Daly and Bierlaire (2006), the correlation structure is defined...

  8. The Hamburg large scale geostrophic ocean general circulation model. Cycle 1

    International Nuclear Information System (INIS)

    Maier-Reimer, E.; Mikolajewicz, U.

    1992-02-01

    The rationale for the Large Scale Geostrophic ocean circulation model (LSG-OGCM) is based on the observations that for a large scale ocean circulation model designed for climate studies, the relevant characteristic spatial scales are large compared with the internal Rossby radius throughout most of the ocean, while the characteristic time scales are large compared with the periods of gravity modes and barotropic Rossby wave modes. In the present version of the model, the fast modes have been filtered out by a conventional technique of integrating the full primitive equations, including all terms except the nonlinear advection of momentum, by an implicit time integration method. The free surface is also treated prognostically, without invoking a rigid lid approximation. The numerical scheme is unconditionally stable and has the additional advantage that it can be applied uniformly to the entire globe, including the equatorial and coastal current regions. (orig.)

  9. Hiperostosis cortical infantil

    Directory of Open Access Journals (Sweden)

    Salvador Javier Santos Medina

    2015-04-01

    Full Text Available La enfermedad de Caffey, o hiperostosis cortical infantil, es una rara enfermedad ósea autolimitada, que aparece de preferencia en lactantes con signos inespecíficos sistémicos; el más relevante es la reacción subperióstica e hiperostosis en varios huesos del cuerpo, con predilección en el 75-80 % de los casos por la mandíbula. Su pronóstico es bueno, la mayoría no deja secuelas. El propósito del presente trabajo es describir las características clínicas, presentes en un lactante de cinco meses de edad, atendido en el Hospital Pediátrico Provincial “Mártires de Las Tunas” con este diagnóstico, quien ingresó en el servicio de miscelánea B por una celulitis facial. Presentaba aumento de volumen en la región geniana izquierda, febrícola e inapetencia. Se impuso tratamiento con cefazolina y se egresó a los siete días. Acudió nuevamente con tumefacción blanda y difusa de ambas hemicaras, irritabilidad y fiebre. Se interconsultó con cirugía maxilofacial, se indicaron estudios sanguíneos y radiológicos. Se diagnosticó como enfermedad de Caffey, basado en la edad del niño, tumefacción facial sin signos inflamatorios agudos e hiperostosis en ambas corticales mandibulares a la radiografía AP mandíbula; unido a anemia ligera, leucocitosis y eritrosedimentación acelerada. El paciente se trató sintomáticamente y con antinflamatorios no esteroideos. Esta rara entidad se debe tener presente en casos de niños y lactantes con irritabilidad y fiebre inespecífica

  10. Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research

    Science.gov (United States)

    de Jong, Martijn G.; Steenkamp, Jan-Benedict E. M.

    2010-01-01

    We present a class of finite mixture multilevel multidimensional ordinal IRT models for large scale cross-cultural research. Our model is proposed for confirmatory research settings. Our prior for item parameters is a mixture distribution to accommodate situations where different groups of countries have different measurement operations, while…

  11. On Applications of Rasch Models in International Comparative Large-Scale Assessments: A Historical Review

    Science.gov (United States)

    Wendt, Heike; Bos, Wilfried; Goy, Martin

    2011-01-01

    Several current international comparative large-scale assessments of educational achievement (ICLSA) make use of "Rasch models", to address functions essential for valid cross-cultural comparisons. From a historical perspective, ICLSA and Georg Rasch's "models for measurement" emerged at about the same time, half a century ago. However, the…

  12. A simple atmospheric boundary layer model applied to large eddy simulations of wind turbine wakes

    DEFF Research Database (Denmark)

    Troldborg, Niels; Sørensen, Jens Nørkær; Mikkelsen, Robert Flemming

    2014-01-01

    A simple model for including the influence of the atmospheric boundary layer in connection with large eddy simulations of wind turbine wakes is presented and validated by comparing computed results with measurements as well as with direct numerical simulations. The model is based on an immersed...

  13. Induction of continuous expanding infrarenal aortic aneurysms in a large porcine animal model

    DEFF Research Database (Denmark)

    Kloster, Brian Ozeraitis; Lund, Lars; Lindholt, Jes S.

    2015-01-01

    BackgroundA large animal model with a continuous expanding infrarenal aortic aneurysm gives access to a more realistic AAA model with anatomy and physiology similar to humans, and thus allows for new experimental research in the natural history and treatment options of the disease. Methods10 pigs...

  14. Somatostatin-expressing inhibitory interneurons in cortical circuits

    Directory of Open Access Journals (Sweden)

    Iryna Yavorska

    2016-09-01

    Full Text Available Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles. SOM cells can be differentially modulated by behavioral state depending on their class, sensory system, and behavioral paradigm. The functional effects of such modulation have been studied with optogenetic manipulation of SOM cells, which produces effects on learning and memory, task performance, and the integration of cortical activity. Different classes of SOM cells participate in distinct disinhibitory circuits with different inhibitory partners and in different cortical layers. Through these disinhibitory circuits, SOM cells help encode the behavioral relevance of sensory stimuli by regulating the activity of cortical neurons based on subcortical and intracortical modulatory input. Associative learning leads to long-term changes in the strength of connectivity of SOM cells with other neurons, often influencing the strength of inhibitory input they receive. Thus despite their heterogeneity and variability across cortical areas, current evidence shows that SOM neurons perform unique neural computations, forming not only distinct molecular but also functional subclasses of cortical inhibitory interneurons.

  15. Alterations in Cerebral Cortical Glucose and Glutamine Metabolism Precedes Amyloid Plaques in the APPswe/PSEN1dE9 Mouse Model of Alzheimer's Disease

    DEFF Research Database (Denmark)

    Andersen, Jens V; Christensen, Sofie K; Aldana, Blanca I

    2017-01-01

    by mass spectrometry. The ATP synthesis rate of isolated whole-brain mitochondria was assessed by an on-line luciferin-luciferase assay. Significantly increased (13)C labeling of intracellular lactate and alanine and decreased tricarboxylic acid (TCA) cycle activity were observed from cerebral cortical...... rate tended to be decreased in isolated whole-brain mitochondria of APPswe/PSEN1dE9 mice. Thus, several cerebral metabolic changes are evident in the APPswe/PSEN1dE9 mouse prior to amyloid plaque deposition, including altered glucose metabolism, hampered glutamine processing and mitochondrial......Alterations in brain energy metabolism have been suggested to be of fundamental importance for the development of Alzheimer's disease (AD). However, specific changes in brain energetics in the early stages of AD are poorly known. The aim of this study was to investigate cerebral energy metabolism...

  16. Control-Oriented Model of Molar Scavenge Oxygen Fraction for Exhaust Recirculation in Large Diesel Engines

    DEFF Research Database (Denmark)

    Nielsen, Kræn Vodder; Blanke, Mogens; Eriksson, Lars

    2016-01-01

    therefore focus on deriving and validating a mean-value model of a large two-stroke crosshead diesel engines with EGR. The model introduces a number of amendments and extensions to previous, complex models and shows in theory and practice that a simplified nonlinear model captures all essential dynamics...... the behavior of the scavenge oxygen fraction well over the entire envelope of load and blower speed range that are relevant for EGR. The simplicity of the new model makes it suitable for observer and control design, which are essential steps to meet the emission requirements for marine diesel engines that take......Exhaust gas recirculation (EGR) systems have been introduced to large marine engines in order to reduce NOx formation. Adequate modelling for control design is one of the bottlenecks to design EGR control that also meets emission requirements during transient loading conditions. This paper...

  17. Analogue scale modelling of extensional tectonic processes using a large state-of-the-art centrifuge

    Science.gov (United States)

    Park, Heon-Joon; Lee, Changyeol

    2017-04-01

    Analogue scale modelling of extensional tectonic processes such as rifting and basin opening has been numerously conducted. Among the controlling factors, gravitational acceleration (g) on the scale models was regarded as a constant (Earth's gravity) in the most of the analogue model studies, and only a few model studies considered larger gravitational acceleration by using a centrifuge (an apparatus generating large centrifugal force by rotating the model at a high speed). Although analogue models using a centrifuge allow large scale-down and accelerated deformation that is derived by density differences such as salt diapir, the possible model size is mostly limited up to 10 cm. A state-of-the-art centrifuge installed at the KOCED Geotechnical Centrifuge Testing Center, Korea Advanced Institute of Science and Technology (KAIST) allows a large surface area of the scale-models up to 70 by 70 cm under the maximum capacity of 240 g-tons. Using the centrifuge, we will conduct analogue scale modelling of the extensional tectonic processes such as opening of the back-arc basin. Acknowledgement This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (grant number 2014R1A6A3A04056405).

  18. Optimizing Prediction Using Bayesian Model Averaging: Examples Using Large-Scale Educational Assessments.

    Science.gov (United States)

    Kaplan, David; Lee, Chansoon

    2018-01-01

    This article provides a review of Bayesian model averaging as a means of optimizing the predictive performance of common statistical models applied to large-scale educational assessments. The Bayesian framework recognizes that in addition to parameter uncertainty, there is uncertainty in the choice of models themselves. A Bayesian approach to addressing the problem of model uncertainty is the method of Bayesian model averaging. Bayesian model averaging searches the space of possible models for a set of submodels that satisfy certain scientific principles and then averages the coefficients across these submodels weighted by each model's posterior model probability (PMP). Using the weighted coefficients for prediction has been shown to yield optimal predictive performance according to certain scoring rules. We demonstrate the utility of Bayesian model averaging for prediction in education research with three examples: Bayesian regression analysis, Bayesian logistic regression, and a recently developed approach for Bayesian structural equation modeling. In each case, the model-averaged estimates are shown to yield better prediction of the outcome of interest than any submodel based on predictive coverage and the log-score rule. Implications for the design of large-scale assessments when the goal is optimal prediction in a policy context are discussed.

  19. Large-scale hydrology in Europe : observed patterns and model performance

    Energy Technology Data Exchange (ETDEWEB)

    Gudmundsson, Lukas

    2011-06-15

    In a changing climate, terrestrial water storages are of great interest as water availability impacts key aspects of ecosystem functioning. Thus, a better understanding of the variations of wet and dry periods will contribute to fully grasp processes of the earth system such as nutrient cycling and vegetation dynamics. Currently, river runoff from small, nearly natural, catchments is one of the few variables of the terrestrial water balance that is regularly monitored with detailed spatial and temporal coverage on large scales. River runoff, therefore, provides a foundation to approach European hydrology with respect to observed patterns on large scales, with regard to the ability of models to capture these.The analysis of observed river flow from small catchments, focused on the identification and description of spatial patterns of simultaneous temporal variations of runoff. These are dominated by large-scale variations of climatic variables but also altered by catchment processes. It was shown that time series of annual low, mean and high flows follow the same atmospheric drivers. The observation that high flows are more closely coupled to large scale atmospheric drivers than low flows, indicates the increasing influence of catchment properties on runoff under dry conditions. Further, it was shown that the low-frequency variability of European runoff is dominated by two opposing centres of simultaneous variations, such that dry years in the north are accompanied by wet years in the south.Large-scale hydrological models are simplified representations of our current perception of the terrestrial water balance on large scales. Quantification of the models strengths and weaknesses is the prerequisite for a reliable interpretation of simulation results. Model evaluations may also enable to detect shortcomings with model assumptions and thus enable a refinement of the current perception of hydrological systems. The ability of a multi model ensemble of nine large

  20. Application of simplified models to CO2 migration and immobilization in large-scale geological systems

    KAUST Repository

    Gasda, Sarah E.

    2012-07-01

    Long-term stabilization of injected carbon dioxide (CO 2) is an essential component of risk management for geological carbon sequestration operations. However, migration and trapping phenomena are inherently complex, involving processes that act over multiple spatial and temporal scales. One example involves centimeter-scale density instabilities in the dissolved CO 2 region leading to large-scale convective mixing that can be a significant driver for CO 2 dissolution. Another example is the potentially important effect of capillary forces, in addition to buoyancy and viscous forces, on the evolution of mobile CO 2. Local capillary effects lead to a capillary transition zone, or capillary fringe, where both fluids are present in the mobile state. This small-scale effect may have a significant impact on large-scale plume migration as well as long-term residual and dissolution trapping. Computational models that can capture both large and small-scale effects are essential to predict the role of these processes on the long-term storage security of CO 2 sequestration operations. Conventional modeling tools are unable to resolve sufficiently all of these relevant processes when modeling CO 2 migration in large-scale geological systems. Herein, we present a vertically-integrated approach to CO 2 modeling that employs upscaled representations of these subgrid processes. We apply the model to the Johansen formation, a prospective site for sequestration of Norwegian CO 2 emissions, and explore the sensitivity of CO 2 migration and trapping to subscale physics. Model results show the relative importance of different physical processes in large-scale simulations. The ability of models such as this to capture the relevant physical processes at large spatial and temporal scales is important for prediction and analysis of CO 2 storage sites. © 2012 Elsevier Ltd.

  1. Motor cortical plasticity in Parkinson's disease.

    Science.gov (United States)

    Udupa, Kaviraja; Chen, Robert

    2013-09-04

    In Parkinson's disease (PD), there are alterations of the basal ganglia (BG) thalamocortical networks, primarily due to degeneration of nigrostriatal dopaminergic neurons. These changes in subcortical networks lead to plastic changes in primary motor cortex (M1), which mediates cortical motor output and is a potential target for treatment of PD. Studies investigating the motor cortical plasticity using non-invasive transcranial magnetic stimulation (TMS) have found altered plasticity in PD, but there are inconsistencies among these studies. This is likely because plasticity depends on many factors such as the extent of dopaminergic loss and disease severity, response to dopaminergic replacement therapies, development of l-DOPA-induced dyskinesias (LID), the plasticity protocol used, medication, and stimulation status in patients treated with deep brain stimulation (DBS). The influences of LID and DBS on BG and M1 plasticity have been explored in animal models and in PD patients. In addition, many other factors such age, genetic factors (e.g., brain derived neurotropic factor and other neurotransmitters or receptors polymorphism), emotional state, time of the day, physical fitness have been documented to play role in the extent of plasticity induced by TMS in human studies. In this review, we summarize the studies that investigated M1 plasticity in PD and demonstrate how these afore-mentioned factors affect motor cortical plasticity in PD. We conclude that it is important to consider the clinical, demographic, and technical factors that influence various plasticity protocols while developing these protocols as diagnostic or prognostic tools in PD. We also discuss how the modulation of cortical excitability and the plasticity with these non-invasive brain stimulation techniques facilitate the understanding of the pathophysiology of PD and help design potential therapeutic possibilities in this disorder.

  2. From Principles to Details: Integrated Framework for Architecture Modelling of Large Scale Software Systems

    Directory of Open Access Journals (Sweden)

    Andrzej Zalewski

    2013-06-01

    Full Text Available There exist numerous models of software architecture (box models, ADL’s, UML, architectural decisions, architecture modelling frameworks (views, enterprise architecture frameworks and even standards recommending practice for the architectural description. We show in this paper, that there is still a gap between these rather abstract frameworks/standards and existing architecture models. Frameworks and standards define what should be modelled rather than which models should be used and how these models are related to each other. We intend to prove that a less abstract modelling framework is needed for the effective modelling of large scale software intensive systems. It should provide a more precise guidance kinds of models to be employed and how they should relate to each other. The paper defines principles that can serve as base for an integrated model. Finally, structure of such a model has been proposed. It comprises three layers: the upper one – architectural policy – reflects corporate policy and strategies in architectural terms, the middle one –system organisation pattern – represents the core structural concepts and their rationale at a given level of scope, the lower one contains detailed architecture models. Architectural decisions play an important role here: they model the core architectural concepts explaining detailed models as well as organise the entire integrated model and the relations between its submodels.

  3. Groundwater Flow and Thermal Modeling to Support a Preferred Conceptual Model for the Large Hydraulic Gradient North of Yucca Mountain

    International Nuclear Information System (INIS)

    McGraw, D.; Oberlander, P.

    2007-01-01

    The purpose of this study is to report on the results of a preliminary modeling framework to investigate the causes of the large hydraulic gradient north of Yucca Mountain. This study builds on the Saturated Zone Site-Scale Flow and Transport Model (referenced herein as the Site-scale model (Zyvoloski, 2004a)), which is a three-dimensional saturated zone model of the Yucca Mountain area. Groundwater flow was simulated under natural conditions. The model framework and grid design describe the geologic layering and the calibration parameters describe the hydrogeology. The Site-scale model is calibrated to hydraulic heads, fluid temperature, and groundwater flowpaths. One area of interest in the Site-scale model represents the large hydraulic gradient north of Yucca Mountain. Nearby water levels suggest over 200 meters of hydraulic head difference in less than 1,000 meters horizontal distance. Given the geologic conceptual models defined by various hydrogeologic reports (Faunt, 2000, 2001; Zyvoloski, 2004b), no definitive explanation has been found for the cause of the large hydraulic gradient. Luckey et al. (1996) presents several possible explanations for the large hydraulic gradient as provided below: The gradient is simply the result of flow through the upper volcanic confining unit, which is nearly 300 meters thick near the large gradient. The gradient represents a semi-perched system in which flow in the upper and lower aquifers is predominantly horizontal, whereas flow in the upper confining unit would be predominantly vertical. The gradient represents a drain down a buried fault from the volcanic aquifers to the lower Carbonate Aquifer. The gradient represents a spillway in which a fault marks the effective northern limit of the lower volcanic aquifer. The large gradient results from the presence at depth of the Eleana Formation, a part of the Paleozoic upper confining unit, which overlies the lower Carbonate Aquifer in much of the Death Valley region. The

  4. Groundwater Flow and Thermal Modeling to Support a Preferred Conceptual Model for the Large Hydraulic Gradient North of Yucca Mountain

    Energy Technology Data Exchange (ETDEWEB)

    McGraw, D.; Oberlander, P.

    2007-12-18

    The purpose of this study is to report on the results of a preliminary modeling framework to investigate the causes of the large hydraulic gradient north of Yucca Mountain. This study builds on the Saturated Zone Site-Scale Flow and Transport Model (referenced herein as the Site-scale model (Zyvoloski, 2004a), which is a three-dimensional saturated zone model of the Yucca Mountain area. Groundwater flow was simulated under natural conditions. The model framework and grid design describe the geologic layering and the calibration parameters describe the hydrogeology. The Site-scale model is calibrated to hydraulic heads, fluid temperature, and groundwater flowpaths. One area of interest in the Site-scale model represents the large hydraulic gradient north of Yucca Mountain. Nearby water levels suggest over 200 meters of hydraulic head difference in less than 1,000 meters horizontal distance. Given the geologic conceptual models defined by various hydrogeologic reports (Faunt, 2000, 2001; Zyvoloski, 2004b), no definitive explanation has been found for the cause of the large hydraulic gradient. Luckey et al. (1996) presents several possible explanations for the large hydraulic gradient as provided below: The gradient is simply the result of flow through the upper volcanic confining unit, which is nearly 300 meters thick near the large gradient. The gradient represents a semi-perched system in which flow in the upper and lower aquifers is predominantly horizontal, whereas flow in the upper confining unit would be predominantly vertical. The gradient represents a drain down a buried fault from the volcanic aquifers to the lower Carbonate Aquifer. The gradient represents a spillway in which a fault marks the effective northern limit of the lower volcanic aquifer. The large gradient results from the presence at depth of the Eleana Formation, a part of the Paleozoic upper confining unit, which overlies the lower Carbonate Aquifer in much of the Death Valley region. The

  5. Modeling and Control of Direct Driven PMSG for Ultra Large Wind Turbines

    OpenAIRE

    Ahmed M. Hemeida; Wael A. Farag; Osama A. Mahgoub

    2011-01-01

    This paper focuses on developing an integrated reliable and sophisticated model for ultra large wind turbines And to study the performance and analysis of vector control on large wind turbines. With the advance of power electronics technology, direct driven multi-pole radial flux PMSG (Permanent Magnet Synchronous Generator) has proven to be a good choice for wind turbines manufacturers. To study the wind energy conversion systems, it is important to develop a wind turbin...

  6. Diffuse and Focal Brain Injury in a Large Animal Model of PTE: Mechanisms Underlying Epileptogenesis

    Science.gov (United States)

    2017-10-01

    Conclusions: A) Contusion injury validation and neuropathology B) Grid electrode development and testing C) Wireless Large Animal Custom Enclosure...In addition, we will test the NF-L and GFAP immunoassay to begin quantification of this biomarkers, as well as collecting serum from the animals pre...AWARD NUMBER: W81XWH-16-1-0675 TITLE: Diffuse and Focal Brain Injury in a Large Animal Model of PTE: Mechanisms Underlying Epileptogenesis

  7. Molecular dynamics simulations of large integral membrane proteins with an implicit membrane model.

    Science.gov (United States)

    Tanizaki, Seiichiro; Feig, Michael

    2006-01-12

    The heterogeneous dielectric generalized Born (HDGB) methodology is an the extension of the GBMV model for the simulation of integral membrane proteins with an implicit membrane environment. Three large integral membrane proteins, the bacteriorhodopsin monomer and trimer and the BtuCD protein, were simulated with the HDGB model in order to evaluate how well thermodynamic and dynamic properties are reproduced. Effects of the truncation of electrostatic interactions were examined. For all proteins, the HDGB model was able to generate stable trajectories that remained close to the starting experimental structures, in excellent agreement with explicit membrane simulations. Dynamic properties evaluated through a comparison of B-factors are also in good agreement with experiment and explicit membrane simulations. However, overall flexibility was slightly underestimated with the HDGB model unless a very large electrostatic cutoff is employed. Results with the HDGB model are further compared with equivalent simulations in implicit aqueous solvent, demonstrating that the membrane environment leads to more realistic simulations.

  8. The three-point function as a probe of models for large-scale structure

    International Nuclear Information System (INIS)

    Frieman, J.A.; Gaztanaga, E.

    1993-01-01

    The authors analyze the consequences of models of structure formation for higher-order (n-point) galaxy correlation functions in the mildly non-linear regime. Several variations of the standard Ω = 1 cold dark matter model with scale-invariant primordial perturbations have recently been introduced to obtain more power on large scales, R p ∼20 h -1 Mpc, e.g., low-matter-density (non-zero cosmological constant) models, open-quote tilted close-quote primordial spectra, and scenarios with a mixture of cold and hot dark matter. They also include models with an effective scale-dependent bias, such as the cooperative galaxy formation scenario of Bower, et al. The authors show that higher-order (n-point) galaxy correlation functions can provide a useful test of such models and can discriminate between models with true large-scale power in the density field and those where the galaxy power arises from scale-dependent bias: a bias with rapid scale-dependence leads to a dramatic decrease of the hierarchical amplitudes Q J at large scales, r approx-gt R p . Current observational constraints on the three-point amplitudes Q 3 and S 3 can place limits on the bias parameter(s) and appear to disfavor, but not yet rule out, the hypothesis that scale-dependent bias is responsible for the extra power observed on large scales

  9. Model checking methodology for large systems, faults and asynchronous behaviour. SARANA 2011 work report

    International Nuclear Information System (INIS)

    Lahtinen, J.; Launiainen, T.; Heljanko, K.; Ropponen, J.

    2012-01-01

    Digital instrumentation and control (I and C) systems are challenging to verify. They enable complicated control functions, and the state spaces of the models easily become too large for comprehensive verification through traditional methods. Model checking is a formal method that can be used for system verification. A number of efficient model checking systems are available that provide analysis tools to determine automatically whether a given state machine model satisfies the desired safety properties. This report reviews the work performed in the Safety Evaluation and Reliability Analysis of Nuclear Automation (SARANA) project in 2011 regarding model checking. We have developed new, more exact modelling methods that are able to capture the behaviour of a system more realistically. In particular, we have developed more detailed fault models depicting the hardware configuration of a system, and methodology to model function-block-based systems asynchronously. In order to improve the usability of our model checking methods, we have developed an algorithm for model checking large modular systems. The algorithm can be used to verify properties of a model that could otherwise not be verified in a straightforward manner. (orig.)

  10. Model checking methodology for large systems, faults and asynchronous behaviour. SARANA 2011 work report

    Energy Technology Data Exchange (ETDEWEB)

    Lahtinen, J. [VTT Technical Research Centre of Finland, Espoo (Finland); Launiainen, T.; Heljanko, K.; Ropponen, J. [Aalto Univ., Espoo (Finland). Dept. of Information and Computer Science

    2012-07-01

    Digital instrumentation and control (I and C) systems are challenging to verify. They enable complicated control functions, and the state spaces of the models easily become too large for comprehensive verification through traditional methods. Model checking is a formal method that can be used for system verification. A number of efficient model checking systems are available that provide analysis tools to determine automatically whether a given state machine model satisfies the desired safety properties. This report reviews the work performed in the Safety Evaluation and Reliability Analysis of Nuclear Automation (SARANA) project in 2011 regarding model checking. We have developed new, more exact modelling methods that are able to capture the behaviour of a system more realistically. In particular, we have developed more detailed fault models depicting the hardware configuration of a system, and methodology to model function-block-based systems asynchronously. In order to improve the usability of our model checking methods, we have developed an algorithm for model checking large modular systems. The algorithm can be used to verify properties of a model that could otherwise not be verified in a straightforward manner. (orig.)

  11. Software engineering the mixed model for genome-wide association studies on large samples.

    Science.gov (United States)

    Zhang, Zhiwu; Buckler, Edward S; Casstevens, Terry M; Bradbury, Peter J

    2009-11-01

    Mixed models improve the ability to detect phenotype-genotype associations in the presence of population stratification and multiple levels of relatedness in genome-wide association studies (GWAS), but for large data sets the resource consumption becomes impractical. At the same time, the sample size and number of markers used for GWAS is increasing dramatically, resulting in greater statistical power to detect those associations. The use of mixed models with increasingly large data sets depends on the availability of software for analyzing those models. While multiple software packages implement the mixed model method, no single package provides the best combination of fast computation, ability to handle large samples, flexible modeling and ease of use. Key elements of association analysis with mixed models are reviewed, including modeling phenotype-genotype associations using mixed models, population stratification, kinship and its estimation, variance component estimation, use of best linear unbiased predictors or residuals in place of raw phenotype, improving efficiency and software-user interaction. The available software packages are evaluated, and suggestions made for future software development.

  12. Prospectus: towards the development of high-fidelity models of wall turbulence at large Reynolds number

    Science.gov (United States)

    Klewicki, J. C.; Chini, G. P.; Gibson, J. F.

    2017-01-01

    Recent and on-going advances in mathematical methods and analysis techniques, coupled with the experimental and computational capacity to capture detailed flow structure at increasingly large Reynolds numbers, afford an unprecedented opportunity to develop realistic models of high Reynolds number turbulent wall-flow dynamics. A distinctive attribute of this new generation of models is their grounding in the Navier–Stokes equations. By adhering to this challenging constraint, high-fidelity models ultimately can be developed that not only predict flow properties at high Reynolds numbers, but that possess a mathematical structure that faithfully captures the underlying flow physics. These first-principles models are needed, for example, to reliably manipulate flow behaviours at extreme Reynolds numbers. This theme issue of Philosophical Transactions of the Royal Society A provides a selection of contributions from the community of researchers who are working towards the development of such models. Broadly speaking, the research topics represented herein report on dynamical structure, mechanisms and transport; scale interactions and self-similarity; model reductions that restrict nonlinear interactions; and modern asymptotic theories. In this prospectus, the challenges associated with modelling turbulent wall-flows at large Reynolds numbers are briefly outlined, and the connections between the contributing papers are highlighted. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’. PMID:28167585

  13. Large-scale 3-D modeling by integration of resistivity models and borehole data through inversion

    DEFF Research Database (Denmark)

    Foged, N.; Marker, Pernille Aabye; Christiansen, A. V.

    2014-01-01

    and the borehole data set in one variable. Finally, we use k-means clustering to generate a 3-D model of the subsurface structures. We apply the procedure to the Norsminde survey in Denmark, integrating approximately 700 boreholes and more than 100 000 resistivity models from an airborne survey...... in the parameterization of the 3-D model covering 156 km2. The final five-cluster 3-D model differentiates between clay materials and different high-resistivity materials from information held in the resistivity model and borehole observations, respectively....

  14. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

  15. Use of the LQ model with large fraction sizes results in underestimation of isoeffect doses

    International Nuclear Information System (INIS)

    Sheu, Tommy; Molkentine, Jessica; Transtrum, Mark K.; Buchholz, Thomas A.; Withers, Hubert Rodney; Thames, Howard D.; Mason, Kathy A.

    2013-01-01

    Purpose: To test the appropriateness of the linear-quadratic (LQ) model to describe survival of jejunal crypt clonogens after split doses with variable (small 1–6 Gy, large 8–13 Gy) first dose, as a model of its appropriateness for both small and large fraction sizes. Methods: C3Hf/KamLaw mice were exposed to whole body irradiation using 300 kVp X-rays at a dose rate of 1.84 Gy/min, and the number of viable jejunal crypts was determined using the microcolony assay. 14 Gy total dose was split into unequal first and second fractions separated by 4 h. Data were analyzed using the LQ model, the lethal potentially lethal (LPL) model, and a repair-saturation (RS) model. Results: Cell kill was greater in the group receiving the larger fraction first, creating an asymmetry in the plot of survival vs size of first dose, as opposed to the prediction of the LQ model of a symmetric response. There was a significant difference in the estimated βs (higher β after larger first doses), but no significant difference in the αs, when large doses were given first vs small doses first. This difference results in underestimation (based on present data by approximately 8%) of isoeffect doses using LQ model parameters based on small fraction sizes. While the LPL model also predicted a symmetric response inconsistent with the data, the RS model results were consistent with the observed asymmetry. Conclusion: The LQ model underestimates doses for isoeffective crypt-cell survival with large fraction sizes (in the present setting, >9 Gy)

  16. Cortical Correlates of Fitts’ Law

    Directory of Open Access Journals (Sweden)

    Peter eIfft

    2011-12-01

    Full Text Available Fitts' law describes the fundamental trade-off between movement accuracy and speed: It states that the duration of reaching movements is a function of target size and distance. While Fitts' law has been extensively studied in ergonomics and has guided the design of human-computer interfaces, there have been few studies on its neuronal correlates. To elucidate sensorimotor cortical activity underlying Fitts’ law, we implanted two monkeys with multielectrode arrays in the primary motor (M1 and primary somatosensory (S1 cortices. The monkeys performed reaches with a joystick-controlled cursor towards targets of different size. The reaction time, movement time and movement velocity changed with target size, and M1 and S1 activity reflected these changes. Moreover, modifications of cortical activity could not be explained by changes of movement parameters alone, but required target size as an additional parameter. Neuronal representation of target size was especially prominent during the early reaction time period where it influenced the slope of the firing rate rise preceding movement initiation. During the movement period, cortical activity was mostly correlated with movement velocity. Neural decoders were applied to simultaneously decode target size and motor parameters from cortical modulations. We suggest using such classifiers to improve neuroprosthetic control.

  17. Global models underestimate large decadal declining and rising water storage trends relative to GRACE satellite data.

    Science.gov (United States)

    Scanlon, Bridget R; Zhang, Zizhan; Save, Himanshu; Sun, Alexander Y; Müller Schmied, Hannes; van Beek, Ludovicus P H; Wiese, David N; Wada, Yoshihide; Long, Di; Reedy, Robert C; Longuevergne, Laurent; Döll, Petra; Bierkens, Marc F P

    2018-02-06

    Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002-2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) to trends from three Gravity Recovery and Climate Experiment (GRACE) satellite solutions in 186 river basins (∼60% of global land area). Medians of modeled basin water storage trends greatly underestimate GRACE-derived large decreasing (≤-0.5 km 3 /y) and increasing (≥0.5 km 3 /y) trends. Decreasing trends from GRACE are mostly related to human use (irrigation) and climate variations, whereas increasing trends reflect climate variations. For example, in the Amazon, GRACE estimates a large increasing trend of ∼43 km 3 /y, whereas most models estimate decreasing trends (-71 to 11 km 3 /y). Land water storage trends, summed over all basins, are positive for GRACE (∼71-82 km 3 /y) but negative for models (-450 to -12 km 3 /y), contributing opposing trends to global mean sea level change. Impacts of climate forcing on decadal land water storage trends exceed those of modeled human intervention by about a factor of 2. The model-GRACE comparison highlights potential areas of future model development, particularly simulated water storage. The inability of models to capture large decadal water storage trends based on GRACE indicates that model projections of climate and human-induced water storage changes may be underestimated. Copyright © 2018 the Author(s). Published by PNAS.

  18. Meson productions at large transverse momentum in core-valence parton model

    CERN Document Server

    Biyajima, M

    1976-01-01

    A quark parton model with an impulse approximation is presented for describing from small momentum to large momentum phenomena in inclusive reactions. An annihilation process by quark-antiquark collision and a pair creation process by gluon-gluon collision are assumed to be dominant. By making use of these two diagrams the authors can explain the particle ratios in addition to the various large p/sub T/-distributions at FNAL and CERN-ISR. Model calculations suggests that gluon collisions are playing an important role as well as quark-antiquark annihilation process. (24 refs).

  19. Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

    Directory of Open Access Journals (Sweden)

    Wenwen Cai

    2014-09-01

    Full Text Available Terrestrial gross primary production (GPP is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000–2010 varied from 95.10 to 139.71 Pg C∙yr−1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.

  20. VISTopic: A visual analytics system for making sense of large document collections using hierarchical topic modeling

    Directory of Open Access Journals (Sweden)

    Yi Yang

    2017-03-01

    Full Text Available Effective analysis of large text collections remains a challenging problem given the growing volume of available text data. Recently, text mining techniques have been rapidly developed for automatically extracting key information from massive text data. Topic modeling, as one of the novel techniques that extracts a thematic structure from documents, is widely used to generate text summarization and foster an overall understanding of the corpus content. Although powerful, this technique may not be directly applicable for general analytics scenarios since the topics and topic–document relationship are often presented probabilistically in models. Moreover, information that plays an important role in knowledge discovery, for example, times and authors, is hardly reflected in topic modeling for comprehensive analysis. In this paper, we address this issue by presenting a visual analytics system, VISTopic, to help users make sense of large document collections based on topic modeling. VISTopic first extracts a set of hierarchical topics using a novel hierarchical latent tree model (HLTM (Liu et al., 2014. In specific, a topic view accounting for the model features is designed for overall understanding and interactive exploration of the topic organization. To leverage multi-perspective information for visual analytics, VISTopic further provides an evolution view to reveal the trend of topics and a document view to show details of topical documents. Three case studies based on the dataset of IEEE VIS conference demonstrate the effectiveness of our system in gaining insights from large document collections. Keywords: Topic-modeling, Text visualization, Visual analytics

  1. Irregular dynamics in up and down cortical states.

    Directory of Open Access Journals (Sweden)

    Jorge F Mejias

    Full Text Available Complex coherent dynamics is present in a wide variety of neural systems. A typical example is the voltage transitions between up and down states observed in cortical areas in the brain. In this work, we study this phenomenon via a biologically motivated stochastic model of up and down transitions. The model is constituted by a simple bistable rate dynamics, where the synaptic current is modulated by short-term synaptic processes which introduce stochasticity and temporal correlations. A complete analysis of our model, both with mean-field approaches and numerical simulations, shows the appearance of complex transitions between high (up and low (down neural activity states, driven by the synaptic noise, with permanence times in the up state distributed according to a power-law. We show that the experimentally observed large fluctuation in up and down permanence times can be explained as the result of sufficiently noisy dynamical synapses with sufficiently large recovery times. Static synapses cannot account for this behavior, nor can dynamical synapses in the absence of noise.

  2. Microfluidic very large scale integration (VLSI) modeling, simulation, testing, compilation and physical synthesis

    CERN Document Server

    Pop, Paul; Madsen, Jan

    2016-01-01

    This book presents the state-of-the-art techniques for the modeling, simulation, testing, compilation and physical synthesis of mVLSI biochips. The authors describe a top-down modeling and synthesis methodology for the mVLSI biochips, inspired by microelectronics VLSI methodologies. They introduce a modeling framework for the components and the biochip architecture, and a high-level microfluidic protocol language. Coverage includes a topology graph-based model for the biochip architecture, and a sequencing graph to model for biochemical application, showing how the application model can be obtained from the protocol language. The techniques described facilitate programmability and automation, enabling developers in the emerging, large biochip market. · Presents the current models used for the research on compilation and synthesis techniques of mVLSI biochips in a tutorial fashion; · Includes a set of "benchmarks", that are presented in great detail and includes the source code of several of the techniques p...

  3. Large eddy simulation of spanwise rotating turbulent channel flow with dynamic variants of eddy viscosity model

    Science.gov (United States)

    Jiang, Zhou; Xia, Zhenhua; Shi, Yipeng; Chen, Shiyi

    2018-04-01

    A fully developed spanwise rotating turbulent channel flow has been numerically investigated utilizing large-eddy simulation. Our focus is to assess the performances of the dynamic variants of eddy viscosity models, including dynamic Vreman's model (DVM), dynamic wall adapting local eddy viscosity (DWALE) model, dynamic σ (Dσ ) model, and the dynamic volumetric strain-stretching (DVSS) model, in this canonical flow. The results with dynamic Smagorinsky model (DSM) and direct numerical simulations (DNS) are used as references. Our results show that the DVM has a wrong asymptotic behavior in the near wall region, while the other three models can correctly predict it. In the high rotation case, the DWALE can get reliable mean velocity profile, but the turbulence intensities in the wall-normal and spanwise directions show clear deviations from DNS data. DVSS exhibits poor predictions on both the mean velocity profile and turbulence intensities. In all three cases, Dσ performs the best.

  4. The pig as a large animal model for influenza a virus infection

    DEFF Research Database (Denmark)

    Skovgaard, Kerstin; Brogaard, Louise; Larsen, Lars Erik

    It is increasingly realized that large animal models like the pig are exceptionally human like and serve as an excellent model for disease and inflammation. Pigs are fully susceptible to human influenza, share many similarities with humans regarding lung physiology and innate immune cell infiltra......It is increasingly realized that large animal models like the pig are exceptionally human like and serve as an excellent model for disease and inflammation. Pigs are fully susceptible to human influenza, share many similarities with humans regarding lung physiology and innate immune cell...... of immune factors including several genes known to be centrally involved in the viral defence was quantified by high throughput qPCR (BioMark, Fluidigm). Likewise, miRNAs were quantified using the BioMark (Fluidigm) as well as by MiRCURY LNATM (Exiqon). During the first 24 hours of infection we found...

  5. The Large Office Environment - Measurement and Modeling of the Wideband Radio Channel

    DEFF Research Database (Denmark)

    Andersen, Jørgen Bach; Nielsen, Jesper Ødum; Bauch, Gerhard

    2006-01-01

    In a future 4G or WLAN wideband application we can imagine multiple users in a large office environment con-sisting of a single room with partitions. Up to now, indoor radio channel measurement and modelling has mainly concentrated on scenarios with several office rooms and corridors. We present...... here measurements at 5.8GHz for 100 MHz bandwidth and a novel modelling approach for the wideband radio channel in a large office room envi-ronment. An acoustic like reverberation theory is pro-posed that allows to specify a tapped delay line model just from the room dimensions and an average...... calculated from the measurements. The pro-posed model can likely also be applied to indoor hot spot scenarios....

  6. Modeling and experiments of biomass combustion in a large-scale grate boiler

    DEFF Research Database (Denmark)

    Yin, Chungen; Rosendahl, Lasse; Kær, Søren Knudsen

    2007-01-01

    is inherently more difficult due to the complexity of the solid biomass fuel bed on the grate, the turbulent reacting flow in the combustion chamber and the intensive interaction between them. This paper presents the CFD validation efforts for a modern large-scale biomass-fired grate boiler. Modeling......Grate furnaces are currently a main workhorse in large-scale firing of biomass for heat and power production. A biomass grate fired furnace can be interpreted as a cross-flow reactor, where biomass is fed in a thick layer perpendicular to the primary air flow. The bottom of the biomass bed...... is exposed to preheated inlet air while the top of the bed resides within the furnace. Mathematical modeling is an efficient way to understand and improve the operation and design of combustion systems. Compared to modeling of pulverized fuel furnaces, CFD modeling of biomass-fired grate furnaces...

  7. Improved large-signal GaN HEMT model suitable for intermodulation distortion analysis

    Science.gov (United States)

    Liu, Lin-Sheng; Luo, Ji

    2011-12-01

    In this article, a complete empirical large-signal model of GaN high electron-mobility transistors (HEMTs) is presented. The developed nonlinear model employs differentiable trigonometric function continuously to describe the drain-source current characteristic and its higher order derivatives, making itself suitable for the simulation of intermodulation distortion (IMD) in microwave circuits. Besides, an improved charge-conservative gate charge model is proposed to accurately trace the nonlinear gate-source and gate-drain capacitances. The model validity is demonstrated for different 0.25-µm gate-length GaN HEMTs. The simulation results of small-signal S-parameters, radio frequency (RF) large-signal power performances and two-tone IMD products show an excellent agreement with the measured data.

  8. Large deformation analysis of adhesive by Eulerian method with new material model

    International Nuclear Information System (INIS)

    Maeda, K; Nishiguchi, K; Iwamoto, T; Okazawa, S

    2010-01-01

    The material model to describe large deformation of a pressure sensitive adhesive (PSA) is presented. A relationship between stress and strain of PSA includes viscoelasticity and rubber-elasticity. Therefore, we propose the material model for describing viscoelasticity and rubber-elasticity, and extend the presented material model to the rate form for three dimensional finite element analysis. After proposing the material model for PSA, we formulate the Eulerian method to simulate large deformation behavior. In the Eulerian calculation, the Piecewise Linear Interface Calculation (PLIC) method for capturing material surface is employed. By using PLIC method, we can impose dynamic and kinematic boundary conditions on captured material surface. The representative two computational examples are calculated to check validity of the present methods.

  9. Phase-field-based lattice Boltzmann modeling of large-density-ratio two-phase flows

    Science.gov (United States)

    Liang, Hong; Xu, Jiangrong; Chen, Jiangxing; Wang, Huili; Chai, Zhenhua; Shi, Baochang

    2018-03-01

    In this paper, we present a simple and accurate lattice Boltzmann (LB) model for immiscible two-phase flows, which is able to deal with large density contrasts. This model utilizes two LB equations, one of which is used to solve the conservative Allen-Cahn equation, and the other is adopted to solve the incompressible Navier-Stokes equations. A forcing distribution function is elaborately designed in the LB equation for the Navier-Stokes equations, which make it much simpler than the existing LB models. In addition, the proposed model can achieve superior numerical accuracy compared with previous Allen-Cahn type of LB models. Several benchmark two-phase problems, including static droplet, layered Poiseuille flow, and spinodal decomposition are simulated to validate the present LB model. It is found that the present model can achieve relatively small spurious velocity in the LB community, and the obtained numerical results also show good agreement with the analytical solutions or some available results. Lastly, we use the present model to investigate the droplet impact on a thin liquid film with a large density ratio of 1000 and the Reynolds number ranging from 20 to 500. The fascinating phenomena of droplet splashing is successfully reproduced by the present model and the numerically predicted spreading radius exhibits to obey the power law reported in the literature.

  10. Bilevel Traffic Evacuation Model and Algorithm Design for Large-Scale Activities

    Directory of Open Access Journals (Sweden)

    Danwen Bao

    2017-01-01

    Full Text Available This paper establishes a bilevel planning model with one master and multiple slaves to solve traffic evacuation problems. The minimum evacuation network saturation and shortest evacuation time are used as the objective functions for the upper- and lower-level models, respectively. The optimizing conditions of this model are also analyzed. An improved particle swarm optimization (PSO method is proposed by introducing an electromagnetism-like mechanism to solve the bilevel model and enhance its convergence efficiency. A case study is carried out using the Nanjing Olympic Sports Center. The results indicate that, for large-scale activities, the average evacuation time of the classic model is shorter but the road saturation distribution is more uneven. Thus, the overall evacuation efficiency of the network is not high. For induced emergencies, the evacuation time of the bilevel planning model is shortened. When the audience arrival rate is increased from 50% to 100%, the evacuation time is shortened from 22% to 35%, indicating that the optimization effect of the bilevel planning model is more effective compared to the classic model. Therefore, the model and algorithm presented in this paper can provide a theoretical basis for the traffic-induced evacuation decision making of large-scale activities.

  11. Parameterization of a Hydrological Model for a Large, Ungauged Urban Catchment

    Directory of Open Access Journals (Sweden)

    Gerald Krebs

    2016-10-01

    Full Text Available Urbanization leads to the replacement of natural areas by impervious surfaces and affects the catchment hydrological cycle with adverse environmental impacts. Low impact development tools (LID that mimic hydrological processes of natural areas have been developed and applied to mitigate these impacts. Hydrological simulations are one possibility to evaluate the LID performance but the associated small-scale processes require a highly spatially distributed and explicit modeling approach. However, detailed data for model development are often not available for large urban areas, hampering the model parameterization. In this paper we propose a methodology to parameterize a hydrological model to a large, ungauged urban area by maintaining at the same time a detailed surface discretization for direct parameter manipulation for LID simulation and a firm reliance on available data for model conceptualization. Catchment delineation was based on a high-resolution digital elevation model (DEM and model parameterization relied on a novel model regionalization approach. The impact of automated delineation and model regionalization on simulation results was evaluated for three monitored study catchments (5.87–12.59 ha. The simulated runoff peak was most sensitive to accurate catchment discretization and calibration, while both the runoff volume and the fit of the hydrograph were less affected.

  12. Scale breaking effects in the quark-parton model for large P perpendicular phenomena

    International Nuclear Information System (INIS)

    Baier, R.; Petersson, B.

    1977-01-01

    We discuss how the scaling violations suggested by an asymptotically free parton model, i.e., the Q 2 -dependence of the transverse momentum of partons within hadrons may affect the parton model description of large p perpendicular phenomena. We show that such a mechanism can provide an explanation for the magnitude of the opposite side correlations and their dependence on the trigger momentum. (author)

  13. Programming in the Large based on the Business Process Modeling Notation

    OpenAIRE

    Emig, Christian; Momm, Christof; Weisser, Jochen; Abeck, Sebastian

    2005-01-01

    A software application is related to the processes it supports. Today, UML diagrams esp. use case diagrams and activity diagrams are often used to model the relevant aspects of the processes within the analysis phase. In the design phase the models are manually mapped to the business layer of the software application. In the context of Service-oriented Architectures (SOA) Programming in the Large takes a different approach: Business processes are described in a programming language, i.e. a pr...

  14. Peptide-Based Scaffolds Support Human Cortical Progenitor Graft Integration to Reduce Atrophy and Promote Functional Repair in a Model of Stroke

    Directory of Open Access Journals (Sweden)

    Fahad A. Somaa

    2017-08-01

    Full Text Available Stem cell transplants offer significant hope for brain repair following ischemic damage. Pre-clinical work suggests that therapeutic mechanisms may be multi-faceted, incorporating bone-fide circuit reconstruction by transplanted neurons, but also protection/regeneration of host circuitry. Here, we engineered hydrogel scaffolds to form “bio-bridges” within the necrotic lesion cavity, providing physical and trophic support to transplanted human embryonic stem cell-derived cortical progenitors, as well as residual host neurons. Scaffolds were fabricated by the self-assembly of peptides for a laminin-derived epitope (IKVAV, thereby mimicking the brain’s major extracellular protein. Following focal ischemia in rats, scaffold-supported cell transplants induced progressive motor improvements over 9 months, compared to cell- or scaffold-only implants. These grafts were larger, exhibited greater neuronal differentiation, and showed enhanced electrophysiological properties reflective of mature, integrated neurons. Varying graft timing post-injury enabled us to attribute repair to both neuroprotection and circuit replacement. These findings highlight strategies to improve the efficiency of stem cell grafts for brain repair.

  15. Cortical interneuron dysfunction in epilepsy associated with autism spectrum disorders.

    Science.gov (United States)

    Jacob, John

    2016-02-01

    Autism and epilepsy are two associated disorders that are highly prevalent, share common developmental origins, and demonstrate substantial heritability. In this review, cross-disciplinary data in a rapidly evolving field that bridges neurology and psychiatry are synthesized to identify shared biologic mechanisms. The relationship between these debilitating, lifelong conditions is examined at the clinical, genetic, and neurophysiologic levels in humans and in animal models. Scopus and PubMed searches were used to identify relevant literature. Clinical observations have prompted speculation about the interdependence of autism and epilepsy, but causal relationships have proved difficult to determine. Despite their heritability, the genetic basis of autism spectrum disorder (ASD) and epilepsy has remained largely elusive until the advent of next-generation sequencing. This approach has revealed that mutations that are either causal or confer an increased disease risk are found in numerous different genes, any one of which accounts for only a small percentage of cases. Conversely, even cases with identical clinical phenotypes can be genetically heterogeneous. Candidate gene identification has facilitated the development of mouse genetic models, which in parallel with human studies have implicated shared brain regions and circuits that mediate disease expression. Diverse genetic causes of ASD and epilepsy converge on cortical interneuron circuits as one important mediator of both disorders. Cortical interneurons are among the most diverse cell types in the brain and their unique chemical and electrical coupling exert a powerful inhibitory influence on excitatory neurons via the release of the neurotransmitter, γ-aminobutyric acid (GABA). These multifaceted approaches have validated theories derived from the field of developmental neurobiology, which propose that the neurologic and neuropsychiatric manifestations are caused by an altered ratio of excitation to

  16. The five factors of personality and regional cortical variability in the Baltimore longitudinal study of aging.

    Science.gov (United States)

    Kapogiannis, Dimitrios; Sutin, Angelina; Davatzikos, Christos; Costa, Paul; Resnick, Susan

    2013-11-01

    Although personality changes have been associated with brain lesions and atrophy caused by neurodegenerative diseases and aging, neuroanatomical correlates of personality in healthy individuals and their stability over time have received relatively little investigation. In this study, we explored regional gray matter (GM) volumetric associations of the five-factor model of personality. Eighty-seven healthy older adults took the NEO Personality Inventory and had brain MRI at two time points 2 years apart. We performed GM segmentation followed by regional analysis of volumes examined in normalized space map creation and voxel based morphometry-type statistical inference in SPM8. We created a regression model including all five factors and important covariates. Next, a conjunction analysis identified associations between personality scores and GM volumes that were replicable across time, also using cluster-level Family-Wise-Error correction. Larger right orbitofrontal and dorsolateral prefrontal cortices and rolandic operculum were associated with lower Neuroticism; larger left temporal, dorsolateral prefrontal, and anterior cingulate cortices with higher Extraversion; larger right frontopolar and smaller orbitofrontal and insular cortices with higher Openness; larger right orbitofrontal cortex with higher Agreeableness; larger dorsolateral prefrontal and smaller frontopolar cortices with higher Conscientiousness. In summary, distinct personality traits were associated with stable individual differences in GM volumes. As expected for higher-order traits, regions performing a large number of cognitive and affective functions were implicated. Our findings highlight personality-related variation that may be related to individual differences in brain structure that merit additional attention in neuroimaging research. Copyright © 2012 Wiley Periodicals, Inc.

  17. Cortical cartography reveals political and physical maps.

    Science.gov (United States)

    Loring, David W; Gaillard, William Davis; Bookheimer, Susan Y; Meador, Kimford J; Ojemann, Jeffrey G

    2014-05-01

    Advances in functional imaging have provided noninvasive techniques to probe brain organization of multiple constructs including language and memory. Because of high overall rates of agreements with older techniques, including Wada testing and cortical stimulation mapping (CSM), some have proposed that those approaches should be largely abandoned because of their invasiveness, and replaced with noninvasive functional imaging methods. High overall agreement, however, is based largely on concordant language lateralization in series dominated by cases of typical cerebral dominance. Advocating a universal switch from Wada testing and cortical stimulation mapping to functional magnetic resonance imaging (fMRI) or magnetoencephalography (MEG) ignores the differences in specific expertise across epilepsy centers, many of which often have greater skill with one approach rather than the other, and that Wada, CSM, fMRI, and MEG protocols vary across institutions resulting in different outcomes and reliability. Specific patient characteristics also affect whether Wada or CSM might influence surgical management, making it difficult to accept broad recommendations against currently useful clinical tools. Although the development of noninvasive techniques has diminished the frequency of more invasive approaches, advocating their use to replace Wada testing and CSM across all epilepsy surgery programs without consideration of the different skills, protocols, and expertise at any given center site is ill-advised. Wiley Periodicals, Inc. © 2014 International League Against Epilepsy.

  18. Imaging the Chicxulub central crater zone from large scale seismic acoustic wave propagation and gravity modeling

    Science.gov (United States)

    Fucugauchi, J. U.; Ortiz-Aleman, C.; Martin, R.

    2017-12-01

    Large complex craters are characterized by central uplifts that represent large-scale differential movement of deep basement from the transient cavity. Here we investigate the central sector of the large multiring Chicxulub crater, which has been surveyed by an array of marine, aerial and land-borne geophysical methods. Despite high contrasts in physical properties,contrasting results for the central uplift have been obtained, with seismic reflection surveys showing lack of resolution in the central zone. We develop an integrated seismic and gravity model for the main structural elements, imaging the central basement uplift and melt and breccia units. The 3-D velocity model built from interpolation of seismic data is validated using perfectly matched layer seismic acoustic wave propagation modeling, optimized at grazing incidence using shift in the frequency domain. Modeling shows significant lack of illumination in the central sector, masking presence of the central uplift. Seismic energy remains trapped in an upper low velocity zone corresponding to the sedimentary infill, melt/breccias and surrounding faulted blocks. After conversion of seismic velocities into a volume of density values, we use massive parallel forward gravity modeling to constrain the size and shape of the central uplift that lies at 4.5 km depth, providing a high-resolution image of crater structure.The Bouguer anomaly and gravity response of modeled units show asymmetries, corresponding to the crater structure and distribution of post-impact carbonates, breccias, melt and target sediments

  19. Absorption and scattering coefficient dependence of laser-Doppler flowmetry models for large tissue volumes

    International Nuclear Information System (INIS)

    Binzoni, T; Leung, T S; Ruefenacht, D; Delpy, D T

    2006-01-01

    Based on quasi-elastic scattering theory (and random walk on a lattice approach), a model of laser-Doppler flowmetry (LDF) has been derived which can be applied to measurements in large tissue volumes (e.g. when the interoptode distance is >30 mm). The model holds for a semi-infinite medium and takes into account the transport-corrected scattering coefficient and the absorption coefficient of the tissue, and the scattering coefficient of the red blood cells. The model holds for anisotropic scattering and for multiple scattering of the photons by the moving scatterers of finite size. In particular, it has also been possible to take into account the simultaneous presence of both Brownian and pure translational movements. An analytical and simplified version of the model has also been derived and its validity investigated, for the case of measurements in human skeletal muscle tissue. It is shown that at large optode spacing it is possible to use the simplified model, taking into account only a 'mean' light pathlength, to predict the blood flow related parameters. It is also demonstrated that the 'classical' blood volume parameter, derived from LDF instruments, may not represent the actual blood volume variations when the investigated tissue volume is large. The simplified model does not need knowledge of the tissue optical parameters and thus should allow the development of very simple and cost-effective LDF hardware

  20. A turbulence model for large interfaces in high Reynolds two-phase CFD

    International Nuclear Information System (INIS)

    Coste, P.; Laviéville, J.

    2015-01-01

    Highlights: • Two-phase CFD commonly involves interfaces much larger than the computational cells. • A two-phase turbulence model is developed to better take them into account. • It solves k–epsilon transport equations in each phase. • The special treatments and transfer terms at large interfaces are described. • Validation cases are presented. - Abstract: A model for two-phase (six-equation) CFD modelling of turbulence is presented, for the regions of the flow where the liquid–gas interface takes place on length scales which are much larger than the typical computational cell size. In the other regions of the flow, the liquid or gas volume fractions range from 0 to 1. Heat and mass transfer, compressibility of the fluids, are included in the system, which is used at high Reynolds numbers in large scale industrial calculations. In this context, a model based on k and ε transport equations in each phase was chosen. The paper describes the model, with a focus on the large interfaces, which require special treatments and transfer terms between the phases, including some approaches inspired from wall functions. The validation of the model is based on high Reynolds number experiments with turbulent quantities measurements of a liquid jet impinging a free surface and an air water stratified flow. A steam–water stratified condensing flow experiment is also used for an indirect validation in the case of heat and mass transfer

  1. The Estimation of Cortical Activity for Brain-Computer Interface: Applications in a Domotic Context

    OpenAIRE

    Babiloni, F.; Cincotti, F.; Marciani, M.; Salinari, S.; Astolfi, L.; Tocci, A.; Aloise, F.; Fallani, F. De Vico; Bufalari, S.; Mattia, D.

    2007-01-01

    In order to analyze whether the use of the cortical activity, estimated from noninvasive EEG recordings, could be useful to detect mental states related to the imagination of limb movements, we estimate cortical activity from high-resolution EEG recordings in a group of healthy subjects by using realistic head models. Such cortical activity was estimated in region of interest associated with the subject's Brodmann areas by using a depth-weighted minimum norm...

  2. Zone modelling of the thermal performances of a large-scale bloom reheating furnace

    International Nuclear Information System (INIS)

    Tan, Chee-Keong; Jenkins, Joana; Ward, John; Broughton, Jonathan; Heeley, Andy

    2013-01-01

    This paper describes the development and comparison of a two- (2D) and three-dimensional (3D) mathematical models, based on the zone method of radiation analysis, to simulate the thermal performances of a large bloom reheating furnace. The modelling approach adopted in the current paper differs from previous work since it takes into account the net radiation interchanges between the top and bottom firing sections of the furnace and also allows for enthalpy exchange due to the flows of combustion products between these sections. The models were initially validated at two different furnace throughput rates using experimental and plant's model data supplied by Tata Steel. The results to-date demonstrated that the model predictions are in good agreement with measured heating profiles of the blooms encountered in the actual furnace. It was also found no significant differences between the predictions from the 2D and 3D models. Following the validation, the 2D model was then used to assess the impact of the furnace responses to changing throughput rate. It was found that the potential furnace response to changing throughput rate influences the settling time of the furnace to the next steady state operation. Overall the current work demonstrates the feasibility and practicality of zone modelling and its potential for incorporation into a model based furnace control system. - Highlights: ► 2D and 3D zone models of large-scale bloom reheating furnace. ► The models were validated with experimental and plant model data. ► Examine the transient furnace response to changing the furnace throughput rates. ► No significant differences found between the predictions from the 2D and 3D models.

  3. Atlantis model outputs - Developing end-to-end models of the California Current Large Marine Ecosystem

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The purpose of this project is to develop spatially discrete end-to-end models of the California Current LME, linking oceanography, biogeochemistry, food web...

  4. Analysis and Design Environment for Large Scale System Models and Collaborative Model Development Project

    Data.gov (United States)

    National Aeronautics and Space Administration — As NASA modeling efforts grow more complex and more distributed among many working groups, new tools and technologies are required to integrate their efforts...

  5. Analysis and Design Environment for Large Scale System Models and Collaborative Model Development, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — As NASA modeling efforts grow more complex and more distributed among many working groups, new tools and technologies are required to integrate their efforts...

  6. Mixed-signal instrumentation for large-signal device characterization and modelling

    NARCIS (Netherlands)

    Marchetti, M.

    2013-01-01

    This thesis concentrates on the development of advanced large-signal measurement and characterization tools to support technology development, model extraction and validation, and power amplifier (PA) designs that address the newly introduced third and fourth generation (3G and 4G) wideband

  7. Using a Student-Manipulated Model to Enhance Student Learning in a Large Lecture Class

    Science.gov (United States)

    Gray, Kyle; Steer, David; McConnell, David; Owens, Katharine

    2010-01-01

    Despite years of formal education, approximately one-third of all undergraduate students still cannot explain the causes of the seasons. Student manipulation of a handheld model is one approach to teaching this concept; however, the large number of students in many introductory classes can dissuade instructors from utilizing this teaching…

  8. A large deviations approach to the transient of the Erlang loss model

    NARCIS (Netherlands)

    Mandjes, M.R.H.; Ridder, Annemarie

    2001-01-01

    This paper deals with the transient behavior of the Erlang loss model. After scaling both arrival rate and number of trunks, an asymptotic analysis of the blocking probability is given. Apart from that, the most likely path to blocking is given. Compared to Shwartz and Weiss [Large Deviations for

  9. Fluid-conveying flexible pipes modeled by large-deflection finite elements in multibody systems

    NARCIS (Netherlands)

    Meijaard, Jacob Philippus

    2013-01-01

    The modeling and simulation of flexible multibody systems containing fluid-conveying pipes are considered. It is assumed that the mass-flow rate is prescribed and constant and the pipe cross section is piecewise uniform. An existing beam element capable of handling large motions is modified to

  10. Wind turbine large-eddy simulations on very coarse grid resolutions using an actuator line model

    NARCIS (Netherlands)

    Martínez-Tossas, Luis A.; Stevens, Richard J.A.M.; Meneveau, Charles

    2016-01-01

    In this work the accuracy of the Actuator Line Model (ALM) in Large Eddy Simulations of wind turbine flow is studied under the specific conditions of very coarse spatial resolutions. For finely-resolved conditions, it is known that ALM provides better accuracy compared to the standard Actuator Disk

  11. Wind Farm Large-Eddy Simulations on Very Coarse Grid Resolutions using an Actuator Line Model

    NARCIS (Netherlands)

    Martinez, L.A.; Meneveau, C.; Stevens, Richard Johannes Antonius Maria

    2016-01-01

    In this work the accuracy of the Actuator Line Model (ALM) in Large Eddy Simula- tions of wind turbine flow is studied under the speci c conditions of very coarse spatial resolutions. For finely-resolved conditions, it is known that ALM provides better accuracy compared to the standard Actuator Disk

  12. On large-scale shell-model calculations in sup 4 He

    Energy Technology Data Exchange (ETDEWEB)

    Bishop, R.F.; Flynn, M.F. (Manchester Univ. (UK). Inst. of Science and Technology); Bosca, M.C.; Buendia, E.; Guardiola, R. (Granada Univ. (Spain). Dept. de Fisica Moderna)

    1990-03-01

    Most shell-model calculations of {sup 4}He require very large basis spaces for the energy spectrum to stabilise. Coupled cluster methods and an exact treatment of the centre-of-mass motion dramatically reduce the number of configurations. We thereby obtain almost exact results with small bases, but which include states of very high excitation energy. (author).

  13. Formation and disruption of tonotopy in a large-scale model of the auditory cortex

    Czech Academy of Sciences Publication Activity Database

    Tomková, M.; Tomek, J.; Novák, Ondřej; Zelenka, Ondřej; Syka, Josef; Brom, C.

    2015-01-01

    Roč. 39, č. 2 (2015), s. 131-153 ISSN 0929-5313 R&D Projects: GA ČR(CZ) GAP303/12/1347 Institutional support: RVO:68378041 Keywords : auditory cortex * large-scale model * spiking neuron * oscillation * STDP * tonotopy Subject RIV: FH - Neurology Impact factor: 1.871, year: 2015

  14. Large Deviations for the Annealed Ising Model on Inhomogeneous Random Graphs: Spins and Degrees

    Science.gov (United States)

    Dommers, Sander; Giardinà, Cristian; Giberti, Claudio; Hofstad, Remco van der

    2018-04-01

    We prove a large deviations principle for the total spin and the number of edges under the annealed Ising measure on generalized random graphs. We also give detailed results on how the annealing over the Ising model changes the degrees of the vertices in the graph and show how it gives rise to interesting correlated random graphs.

  15. Large-order behavior of nondecoupling effects in the standard model and triviality

    International Nuclear Information System (INIS)

    Aoki, K.

    1994-01-01

    We compute some nondecoupling effects in the standard model, such as the ρ parameter, to all orders in the coupling constant expansion. We analyze their large order behavior and explicitly show how they are related to the nonperturbative cutoff dependence of these nondecoupling effects due to the triviality of the theory

  16. Identifiability in N-mixture models: a large-scale screening test with bird data.

    Science.gov (United States)

    Kéry, Marc

    2018-02-01

    Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

  17. Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

    Science.gov (United States)

    Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

    2015-11-01

    Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

  18. Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

    KAUST Repository

    Sang, Huiyan

    2011-12-01

    This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors. © 2012 Institute of Mathematical Statistics.

  19. Flexible non-linear predictive models for large-scale wind turbine diagnostics

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole

    2017-01-01

    We demonstrate how flexible non-linear models can provide accurate and robust predictions on turbine component temperature sensor data using data-driven principles and only a minimum of system modeling. The merits of different model architectures are evaluated using data from a large set...... of turbines operating under diverse conditions. We then go on to test the predictive models in a diagnostic setting, where the output of the models are used to detect mechanical faults in rotor bearings. Using retrospective data from 22 actual rotor bearing failures, the fault detection performance...... of the models are quantified using a structured framework that provides the metrics required for evaluating the performance in a fleet wide monitoring setup. It is demonstrated that faults are identified with high accuracy up to 45 days before a warning from the hard-threshold warning system....

  20. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Zhaosheng Yang

    2014-01-01

    Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

  1. Contribution of Large Pig for Renal Ischemia-Reperfusion and Transplantation Studies: The Preclinical Model

    Directory of Open Access Journals (Sweden)

    S. Giraud

    2011-01-01

    Full Text Available Animal experimentation is necessary to characterize human diseases and design adequate therapeutic interventions. In renal transplantation research, the limited number of in vitro models involves a crucial role for in vivo models and particularly for the porcine model. Pig and human kidneys are anatomically similar (characterized by multilobular structure in contrast to rodent and dog kidneys unilobular. The human proximity of porcine physiology and immune systems provides a basic knowledge of graft recovery and inflammatory physiopathology through in vivo studies. In addition, pig large body size allows surgical procedures similar to humans, repeated collections of peripheral blood or renal biopsies making pigs ideal for medical training and for the assessment of preclinical technologies. However, its size is also its main drawback implying expensive housing. Nevertheless, pig models are relevant alternatives to primate models, offering promising perspectives with developments of transgenic modulation and marginal donor models facilitating data extrapolation to human conditions.

  2. Hybrid Reynolds-Averaged/Large Eddy Simulation of the Flow in a Model SCRamjet Cavity Flameholder

    Science.gov (United States)

    Baurle, R. A.

    2016-01-01

    Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. Experimental data available for this configuration include velocity statistics obtained from particle image velocimetry. Several turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged/large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This e ort was undertaken to not only assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community, but to also begin to understand how this capability can best be used to augment standard Reynolds-averaged simulations. The numerical errors were quantified for the steady-state simulations, and at least qualitatively assessed for the scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results displayed a high degree of variability when comparing the flameholder fuel distributions obtained from each turbulence model. This prompted the consideration of applying the higher-fidelity scale-resolving simulations as a surrogate "truth" model to calibrate the Reynolds-averaged closures in a non-reacting setting prior to their use for the combusting simulations. In general, the Reynolds-averaged velocity profile predictions at the lowest fueling level matched the particle imaging measurements almost as well as was observed for the non-reacting condition. However, the velocity field predictions proved to be more sensitive to the flameholder fueling rate than was indicated in the measurements.

  3. A cooperative strategy for parameter estimation in large scale systems biology models.

    Science.gov (United States)

    Villaverde, Alejandro F; Egea, Jose A; Banga, Julio R

    2012-06-22

    Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs ("threads") that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and

  4. A cooperative strategy for parameter estimation in large scale systems biology models

    Directory of Open Access Journals (Sweden)

    Villaverde Alejandro F

    2012-06-01

    Full Text Available Abstract Background Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. Results A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS, is presented. Its key feature is the cooperation between different programs (“threads” that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS. Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. Conclusions The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here

  5. Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size.

    Science.gov (United States)

    Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram

    2017-04-01

    Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.

  6. Response variability in balanced cortical networks

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Ursta, C.; Hertz, J.

    2006-01-01

    We study the spike statistics of neurons in a network with dynamically balanced excitation and inhibition. Our model, intended to represent a generic cortical column, comprises randomly connected excitatory and inhibitory leaky integrate-and-fire neurons, driven by excitatory input from an external...... factors is possible. We find that the irregularity of spike trains is controlled mainly by the strength of the synapses relative to the difference between the firing threshold and the postfiring reset level of the membrane potential. For moderately strong synapses, we find spike statistics very similar...

  7. Abnormalities of cortical structures in adolescent-onset conduct disorder.

    Science.gov (United States)

    Jiang, Y; Guo, X; Zhang, J; Gao, J; Wang, X; Situ, W; Yi, J; Zhang, X; Zhu, X; Yao, S; Huang, B

    2015-12-01

    Converging evidence has revealed both functional and structural abnormalities in adolescents with early-onset conduct disorder (EO-CD). The neurological abnormalities underlying EO-CD may be different from that of adolescent-onset conduct disorder (AO-CD) patients. However, the cortical structure in AO-CD patients remains largely unknown. The aim of the present study was to investigate the cortical alterations in AO-CD patients. We investigated T1-weighted brain images from AO-CD patients and age-, gender- and intelligence quotient-matched controls. Cortical structures including thickness, folding and surface area were measured using the surface-based morphometric method. Furthermore, we assessed impulsivity and antisocial symptoms using the Barratt Impulsiveness Scale (BIS) and the Antisocial Process Screening Device (APSD). Compared with the controls, we found significant cortical thinning in the paralimbic system in AO-CD patients. For the first time, we observed cortical thinning in the precuneus/posterior cingulate cortex (PCC) in AO-CD patients which has not been reported in EO-CD patients. Prominent folding abnormalities were found in the paralimbic structures and frontal cortex while diminished surface areas were shown in the precentral and inferior temporal cortex. Furthermore, cortical thickness of the paralimbic structures was found to be negatively correlated with impulsivity and antisocial behaviors measured by the BIS and APSD, respectively. The present study indicates that AO-CD is characterized by cortical structural abnormalities in the paralimbic system, and, in particular, we highlight the potential role of deficient structures including the precuneus and PCC in the etiology of AO-CD.

  8. REIONIZATION ON LARGE SCALES. I. A PARAMETRIC MODEL CONSTRUCTED FROM RADIATION-HYDRODYNAMIC SIMULATIONS

    International Nuclear Information System (INIS)

    Battaglia, N.; Trac, H.; Cen, R.; Loeb, A.

    2013-01-01

    We present a new method for modeling inhomogeneous cosmic reionization on large scales. Utilizing high-resolution radiation-hydrodynamic simulations with 2048 3 dark matter particles, 2048 3 gas cells, and 17 billion adaptive rays in a L = 100 Mpc h –1 box, we show that the density and reionization redshift fields are highly correlated on large scales (∼> 1 Mpc h –1 ). This correlation can be statistically represented by a scale-dependent linear bias. We construct a parametric function for the bias, which is then used to filter any large-scale density field to derive the corresponding spatially varying reionization redshift field. The parametric model has three free parameters that can be reduced to one free parameter when we fit the two bias parameters to simulation results. We can differentiate degenerate combinations of the bias parameters by combining results for the global ionization histories and correlation length between ionized regions. Unlike previous semi-analytic models, the evolution of the reionization redshift field in our model is directly compared cell by cell against simulations and performs well in all tests. Our model maps the high-resolution, intermediate-volume radiation-hydrodynamic simulations onto lower-resolution, larger-volume N-body simulations (∼> 2 Gpc h –1 ) in order to make mock observations and theoretical predictions

  9. Application of Pareto-efficient combustion modeling framework to large eddy simulations of turbulent reacting flows

    Science.gov (United States)

    Wu, Hao; Ihme, Matthias

    2017-11-01

    The modeling of turbulent combustion requires the consideration of different physico-chemical processes, involving a vast range of time and length scales as well as a large number of scalar quantities. To reduce the computational complexity, various combustion models are developed. Many of them can be abstracted using a lower-dimensional manifold representation. A key issue in using such lower-dimensional combustion models is the assessment as to whether a particular combustion model is adequate in representing a certain flame configuration. The Pareto-efficient combustion (PEC) modeling framework was developed to perform dynamic combustion model adaptation based on various existing manifold models. In this work, the PEC model is applied to a turbulent flame simulation, in which a computationally efficient flamelet-based combustion model is used in together with a high-fidelity finite-rate chemistry model. The combination of these two models achieves high accuracy in predicting pollutant species at a relatively low computational cost. The relevant numerical methods and parallelization techniques are also discussed in this work.

  10. A 3D thermal runaway propagation model for a large format lithium ion battery module

    International Nuclear Information System (INIS)

    Feng, Xuning; Lu, Languang; Ouyang, Minggao; Li, Jiangqiu; He, Xiangming

    2016-01-01

    In this paper, a 3D thermal runaway (TR) propagation model is built for a large format lithium ion battery module. The 3D TR propagation model is built based on the energy balance equation. Empirical equations are utilized to simplify the calculation of the chemical kinetics for TR, whereas equivalent thermal resistant layer is employed to simplify the heat transfer through the thin thermal layer. The 3D TR propagation model is validated by experiment and can provide beneficial discussions on the mechanisms of TR propagation. According to the modeling analysis of the 3D model, the TR propagation can be delayed or prevented through: 1) increasing the TR triggering temperature; 2) reducing the total electric energy released during TR; 3) enhancing the heat dissipation level; 4) adding extra thermal resistant layer between adjacent batteries. The TR propagation is successfully prevented in the model and validated by experiment. The model with 3D temperature distribution provides a beneficial tool for researchers to study the TR propagation mechanisms and for engineers to design a safer battery pack. - Highlights: • A 3D thermal runaway (TR) propagation model for Li-ion battery pack is built. • The 3D TR propagation model can fit experimental results well. • Temperature distributions during TR propagation are presented using the 3D model. • Modeling analysis provides solutions for the prevention of TR propagation. • Quantified solutions to prevent TR propagation in battery pack are discussed.

  11. Cardiac regeneration using pluripotent stem cells—Progression to large animal models

    Directory of Open Access Journals (Sweden)

    James J.H. Chong

    2014-11-01

    Full Text Available Pluripotent stem cells (PSCs have indisputable cardiomyogenic potential and therefore have been intensively investigated as a potential cardiac regenerative therapy. Current directed differentiation protocols are able to produce high yields of cardiomyocytes from PSCs and studies in small animal models of cardiovascular disease have proven sustained engraftment and functional efficacy. Therefore, the time is ripe for cardiac regenerative therapies using PSC derivatives to be tested in large animal models that more closely resemble the hearts of humans. In this review, we discuss the results of our recent study using human embryonic stem cell derived cardiomyocytes (hESC-CM in a non-human primate model of ischemic cardiac injury. Large scale remuscularization, electromechanical coupling and short-term arrhythmias demonstrated by our hESC-CM grafts are discussed in the context of other studies