Diffusion Forecasting Model with Basis Functions from QR-Decomposition

NASA Astrophysics Data System (ADS)

Harlim, John; Yang, Haizhao

2018-06-01

The diffusion forecasting is a nonparametric approach that provably solves the Fokker-Planck PDE corresponding to Itô diffusion without knowing the underlying equation. The key idea of this method is to approximate the solution of the Fokker-Planck equation with a discrete representation of the shift (Koopman) operator on a set of basis functions generated via the diffusion maps algorithm. While the choice of these basis functions is provably optimal under appropriate conditions, computing these basis functions is quite expensive since it requires the eigendecomposition of an N× N diffusion matrix, where N denotes the data size and could be very large. For large-scale forecasting problems, only a few leading eigenvectors are computationally achievable. To overcome this computational bottleneck, a new set of basis functions constructed by orthonormalizing selected columns of the diffusion matrix and its leading eigenvectors is proposed. This computation can be carried out efficiently via the unpivoted Householder QR factorization. The efficiency and effectiveness of the proposed algorithm will be shown in both deterministically chaotic and stochastic dynamical systems; in the former case, the superiority of the proposed basis functions over purely eigenvectors is significant, while in the latter case forecasting accuracy is improved relative to using a purely small number of eigenvectors. Supporting arguments will be provided on three- and six-dimensional chaotic ODEs, a three-dimensional SDE that mimics turbulent systems, and also on the two spatial modes associated with the boreal winter Madden-Julian Oscillation obtained from applying the Nonlinear Laplacian Spectral Analysis on the measured Outgoing Longwave Radiation.

Diffusion Forecasting Model with Basis Functions from QR-Decomposition

NASA Astrophysics Data System (ADS)

Harlim, John; Yang, Haizhao

2017-12-01

The diffusion forecasting is a nonparametric approach that provably solves the Fokker-Planck PDE corresponding to Itô diffusion without knowing the underlying equation. The key idea of this method is to approximate the solution of the Fokker-Planck equation with a discrete representation of the shift (Koopman) operator on a set of basis functions generated via the diffusion maps algorithm. While the choice of these basis functions is provably optimal under appropriate conditions, computing these basis functions is quite expensive since it requires the eigendecomposition of an N× N diffusion matrix, where N denotes the data size and could be very large. For large-scale forecasting problems, only a few leading eigenvectors are computationally achievable. To overcome this computational bottleneck, a new set of basis functions constructed by orthonormalizing selected columns of the diffusion matrix and its leading eigenvectors is proposed. This computation can be carried out efficiently via the unpivoted Householder QR factorization. The efficiency and effectiveness of the proposed algorithm will be shown in both deterministically chaotic and stochastic dynamical systems; in the former case, the superiority of the proposed basis functions over purely eigenvectors is significant, while in the latter case forecasting accuracy is improved relative to using a purely small number of eigenvectors. Supporting arguments will be provided on three- and six-dimensional chaotic ODEs, a three-dimensional SDE that mimics turbulent systems, and also on the two spatial modes associated with the boreal winter Madden-Julian Oscillation obtained from applying the Nonlinear Laplacian Spectral Analysis on the measured Outgoing Longwave Radiation.

Diffusion Tensor Magnetic Resonance Imaging Strategies for Color Mapping of Human Brain Anatomy

PubMed Central

Boujraf, Saïd

2018-01-01

Background: A color mapping of fiber tract orientation using diffusion tensor imaging (DTI) can be prominent in clinical practice. The goal of this paper is to perform a comparative study of visualized diffusion anisotropy in the human brain anatomical entities using three different color-mapping techniques based on diffusion-weighted imaging (DWI) and DTI. Methods: The first technique is based on calculating a color map from DWIs measured in three perpendicular directions. The second technique is based on eigenvalues derived from the diffusion tensor. The last technique is based on three eigenvectors corresponding to sorted eigenvalues derived from the diffusion tensor. All magnetic resonance imaging measurements were achieved using a 1.5 Tesla Siemens Vision whole body imaging system. A single-shot DW echoplanar imaging sequence used a Stejskal–Tanner approach. Trapezoidal diffusion gradients are used. The slice orientation was transverse. The basic measurement yielded a set of 13 images. Each series consists of a single image without diffusion weighting, besides two DWIs for each of the next six noncollinear magnetic field gradient directions. Results: The three types of color maps were calculated consequently using the DWI obtained and the DTI. Indeed, we established an excellent similarity between the image data in the color maps and the fiber directions of known anatomical structures (e.g., corpus callosum and gray matter). Conclusions: In the meantime, rotationally invariant quantities such as the eigenvectors of the diffusion tensor reflected better, the real orientation found in the studied tissue. PMID:29928631

Ischemic lesion volume determination on diffusion weighted images vs. apparent diffusion coefficient maps.

PubMed

Bråtane, Bernt Tore; Bastan, Birgul; Fisher, Marc; Bouley, James; Henninger, Nils

2009-07-07

Though diffusion weighted imaging (DWI) is frequently used for identifying the ischemic lesion in focal cerebral ischemia, the understanding of spatiotemporal evolution patterns observed with different analysis methods remains imprecise. DWI and calculated apparent diffusion coefficient (ADC) maps were serially obtained in rat stroke models (MCAO): permanent, 90 min, and 180 min temporary MCAO. Lesion volumes were analyzed in a blinded and randomized manner by 2 investigators using (i) a previously validated ADC threshold, (ii) visual determination of hypointense regions on ADC maps, and (iii) visual determination of hyperintense regions on DWI. Lesion volumes were correlated with 24 hour 2,3,5-triphenyltetrazoliumchloride (TTC)-derived infarct volumes. TTC-derived infarct volumes were not significantly different from the ADC and DWI-derived lesion volumes at the last imaging time points except for significantly smaller DWI lesions in the pMCAO model (p=0.02). Volumetric calculation based on TTC-derived infarct also correlated significantly stronger to volumetric calculation based on last imaging time point derived lesions on ADC maps than DWI (p<0.05). Following reperfusion, lesion volumes on the ADC maps significantly reduced but no change was observed on DWI. Visually determined lesion volumes on ADC maps and DWI by both investigators correlated significantly with threshold-derived lesion volumes on ADC maps with the former method demonstrating a stronger correlation. There was also a better interrater agreement for ADC map analysis than for DWI analysis. Ischemic lesion determination by ADC was more accurate in final infarct prediction, rater independent, and provided exclusive information on ischemic lesion reversibility.

A Simple Secure Hash Function Scheme Using Multiple Chaotic Maps

NASA Astrophysics Data System (ADS)

Ahmad, Musheer; Khurana, Shruti; Singh, Sushmita; AlSharari, Hamed D.

2017-06-01

The chaotic maps posses high parameter sensitivity, random-like behavior and one-way computations, which favor the construction of cryptographic hash functions. In this paper, we propose to present a novel hash function scheme which uses multiple chaotic maps to generate efficient variable-sized hash functions. The message is divided into four parts, each part is processed by a different 1D chaotic map unit yielding intermediate hash code. The four codes are concatenated to two blocks, then each block is processed through 2D chaotic map unit separately. The final hash value is generated by combining the two partial hash codes. The simulation analyses such as distribution of hashes, statistical properties of confusion and diffusion, message and key sensitivity, collision resistance and flexibility are performed. The results reveal that the proposed anticipated hash scheme is simple, efficient and holds comparable capabilities when compared with some recent chaos-based hash algorithms.

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI.

PubMed

Gulban, Omer F; De Martino, Federico; Vu, An T; Yacoub, Essa; Uğurbil, Kamil; Lenglet, Christophe

2018-05-10

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results. Copyright © 2018 Elsevier Inc. All rights reserved.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future.

PubMed

Salama, Gayle R; Heier, Linda A; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John

2017-01-01

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma—Foundations and Future

PubMed Central

Salama, Gayle R.; Heier, Linda A.; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John

2018-01-01

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes. PMID:29403420

Spatiotemporal mapping of diffusion dynamics and organization in plasma membranes

NASA Astrophysics Data System (ADS)

Bag, Nirmalya; Ng, Xue Wen; Sankaran, Jagadish; Wohland, Thorsten

2016-09-01

Imaging fluorescence correlation spectroscopy (FCS) and the related FCS diffusion law have been applied in recent years to investigate the diffusion modes of lipids and proteins in membranes. These efforts have provided new insights into the membrane structure below the optical diffraction limit, new information on the existence of lipid domains, and on the influence of the cytoskeleton on membrane dynamics. However, there has been no systematic study to evaluate how domain size, domain density, and the probe partition coefficient affect the resulting imaging FCS diffusion law parameters. Here, we characterize the effects of these factors on the FCS diffusion law through simulations and experiments on lipid bilayers and live cells. By segmenting images into smaller 7  ×  7 pixel areas, we can evaluate the FCS diffusion law on areas smaller than 2 µm and thus provide detailed maps of information on the membrane structure and heterogeneity at this length scale. We support and extend this analysis by deriving a mathematical expression to calculate the mean squared displacement (MSDACF) from the autocorrelation function of imaging FCS, and demonstrate that the MSDACF plots depend on the existence of nanoscopic domains. Based on the results, we derive limits for the detection of domains depending on their size, density, and relative viscosity in comparison to the surroundings. Finally, we apply these measurements to bilayers and live cells using imaging total internal reflection FCS and single plane illumination microscopy FCS.

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

DOE PAGES

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; ...

2017-10-10

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. Itmore » relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.« less

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. Itmore » relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.« less

Transport, diffusion, and energy studies in the Arnold-Beltrami-Childress map

NASA Astrophysics Data System (ADS)

Das, Swetamber; Gupte, Neelima

2017-09-01

We study the transport and diffusion properties of passive inertial particles described by a six-dimensional dissipative bailout embedding map. The base map chosen for the study is the three-dimensional incompressible Arnold-Beltrami-Childress (ABC) map chosen as a representation of volume preserving flows. There are two distinct cases: the two-action and the one-action cases, depending on whether two or one of the parameters (A ,B ,C ) exceed 1. The embedded map dynamics is governed by two parameters (α ,γ ), which quantify the mass density ratio and dissipation, respectively. There are important differences between the aerosol (α <1 ) and the bubble (α >1 ) regimes. We have studied the diffusive behavior of the system and constructed the phase diagram in the parameter space by computing the diffusion exponents η . Three classes have been broadly classified—subdiffusive transport (η <1 ), normal diffusion (η ≈1 ), and superdiffusion (η >1 ) with η ≈2 referred to as the ballistic regime. Correlating the diffusive phase diagram with the phase diagram for dynamical regimes seen earlier, we find that the hyperchaotic bubble regime is largely correlated with normal and superdiffusive behavior. In contrast, in the aerosol regime, ballistic superdiffusion is seen in regions that largely show periodic dynamical behaviors, whereas subdiffusive behavior is seen in both periodic and chaotic regimes. The probability distributions of the diffusion exponents show power-law scaling for both aerosol and bubbles in the superdiffusive regimes. We further study the Poincáre recurrence times statistics of the system. Here, we find that recurrence time distributions show power law regimes due to the existence of partial barriers to transport in the phase space. Moreover, the plot of average particle kinetic energies versus the mass density ratio for the two-action case exhibits a devil's staircase-like structure for higher dissipation values. We explain these results

Soot Volume Fraction Maps for Normal and Reduced Gravity Laminar Acetylene Jet Diffusion Flames

NASA Technical Reports Server (NTRS)

Greenberg, Paul S.; Ku, Jerry C.

1997-01-01

The study of soot particulate distribution inside gas jet diffusion flames is important to the understanding of fundamental soot particle and thermal radiative transport processes, as well as providing findings relevant to spacecraft fire safety, soot emissions, and radiant heat loads for combustors used in air-breathing propulsion systems. Compared to those under normal gravity (1-g) conditions, the elimination of buoyancy-induced flows is expected to significantly change the flow field in microgravity (O g) flames, resulting in taller and wider flames with longer particle residence times. Work by Bahadori and Edelman demonstrate many previously unreported qualitative and semi-quantitative results, including flame shape and radiation, for sooting laminar zas jet diffusion flames. Work by Ku et al. report soot aggregate size and morphology analyses and data and model predictions of soot volume fraction maps for various gas jet diffusion flames. In this study, we present the first 1-g and 0-g comparisons of soot volume fraction maps for laminar acetylene and nitrogen-diluted acetylene jet diffusion flames. Volume fraction is one of the most useful properties in the study of sooting diffusion flames. The amount of radiation heat transfer depends directly on the volume fraction and this parameter can be measured from line-of-sight extinction measurements. Although most Soot aggregates are submicron in size, the primary particles (20 to 50 nm in diameter) are in the Rayleigh limit, so the extinction absorption) cross section of aggregates can be accurately approximated by the Rayleigh solution as a function of incident wavelength, particles' complex refractive index, and particles' volume fraction.

Mapping Diffusion in a Living Cell via the Phasor Approach

PubMed Central

Ranjit, Suman; Lanzano, Luca; Gratton, Enrico

2014-01-01

Diffusion of a fluorescent protein within a cell has been measured using either fluctuation-based techniques (fluorescence correlation spectroscopy (FCS) or raster-scan image correlation spectroscopy) or particle tracking. However, none of these methods enables us to measure the diffusion of the fluorescent particle at each pixel of the image. Measurement using conventional single-point FCS at every individual pixel results in continuous long exposure of the cell to the laser and eventual bleaching of the sample. To overcome this limitation, we have developed what we believe to be a new method of scanning with simultaneous construction of a fluorescent image of the cell. In this believed new method of modified raster scanning, as it acquires the image, the laser scans each individual line multiple times before moving to the next line. This continues until the entire area is scanned. This is different from the original raster-scan image correlation spectroscopy approach, where data are acquired by scanning each frame once and then scanning the image multiple times. The total time of data acquisition needed for this method is much shorter than the time required for traditional FCS analysis at each pixel. However, at a single pixel, the acquired intensity time sequence is short; requiring nonconventional analysis of the correlation function to extract information about the diffusion. These correlation data have been analyzed using the phasor approach, a fit-free method that was originally developed for analysis of FLIM images. Analysis using this method results in an estimation of the average diffusion coefficient of the fluorescent species at each pixel of an image, and thus, a detailed diffusion map of the cell can be created. PMID:25517145

Diffusion maps for high-dimensional single-cell analysis of differentiation data.

PubMed

Haghverdi, Laleh; Buettner, Florian; Theis, Fabian J

2015-09-15

Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analyzing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalization, followed by dimension reduction and clustering to identify subgroups. However, in the case of cellular differentiation, we would not expect clear clusters to be present but instead expect the cells to follow continuous branching lineages. Here, we propose the use of diffusion maps to deal with the problem of defining differentiation trajectories. We adapt this method to single-cell data by adequate choice of kernel width and inclusion of uncertainties or missing measurement values, which enables the establishment of a pseudotemporal ordering of single cells in a high-dimensional gene expression space. We expect this output to reflect cell differentiation trajectories, where the data originates from intrinsic diffusion-like dynamics. Starting from a pluripotent stage, cells move smoothly within the transcriptional landscape towards more differentiated states with some stochasticity along their path. We demonstrate the robustness of our method with respect to extrinsic noise (e.g. measurement noise) and sampling density heterogeneities on simulated toy data as well as two single-cell quantitative polymerase chain reaction datasets (i.e. mouse haematopoietic stem cells and mouse embryonic stem cells) and an RNA-Seq data of human pre-implantation embryos. We show that diffusion maps perform considerably better than Principal Component Analysis and are advantageous over other techniques for non-linear dimension reduction such as t-distributed Stochastic Neighbour Embedding for preserving the global structures and pseudotemporal ordering of cells. The Matlab implementation of diffusion maps for single-cell data is available at https://www.helmholtz-muenchen.de/icb/single-cell-diffusion-map

Rapid in vivo apparent diffusion coefficient mapping of hyperpolarized (13) C metabolites.

PubMed

Koelsch, Bertram L; Reed, Galen D; Keshari, Kayvan R; Chaumeil, Myriam M; Bok, Robert; Ronen, Sabrina M; Vigneron, Daniel B; Kurhanewicz, John; Larson, Peder E Z

2015-09-01

Hyperpolarized (13) C magnetic resonance allows for the study of real-time metabolism in vivo, including significant hyperpolarized (13) C lactate production in many tumors. Other studies have shown that aggressive and highly metastatic tumors rapidly transport lactate out of cells. Thus, the ability to not only measure the production of hyperpolarized (13) C lactate but also understand its compartmentalization using diffusion-weighted MR will provide unique information for improved tumor characterization. We used a bipolar, pulsed-gradient, double spin echo imaging sequence to rapidly generate diffusion-weighted images of hyperpolarized (13) C metabolites. Our methodology included a simultaneously acquired B1 map to improve apparent diffusion coefficient (ADC) accuracy and a diffusion-compensated variable flip angle scheme to improve ADC precision. We validated this sequence and methodology in hyperpolarized (13) C phantoms. Next, we generated ADC maps of several hyperpolarized (13) C metabolites in a normal rat, rat brain tumor, and prostate cancer mouse model using both preclinical and clinical trial-ready hardware. ADC maps of hyperpolarized (13) C metabolites provide information about the localization of these molecules in the tissue microenvironment. The methodology presented here allows for further studies to investigate ADC changes due to disease state that may provide unique information about cancer aggressiveness and metastatic potential. © 2014 Wiley Periodicals, Inc.

Benchmark calculations of excess electrons in water cluster cavities: balancing the addition of atom-centered diffuse functions versus floating diffuse functions.

PubMed

Zhang, Changzhe; Bu, Yuxiang

2016-09-14

Diffuse functions have been proved to be especially crucial for the accurate characterization of excess electrons which are usually bound weakly in intermolecular zones far away from the nuclei. To examine the effects of diffuse functions on the nature of the cavity-shaped excess electrons in water cluster surroundings, both the HOMO and LUMO distributions, vertical detachment energies (VDEs) and visible absorption spectra of two selected (H2O)24(-) isomers are investigated in the present work. Two main types of diffuse functions are considered in calculations including the Pople-style atom-centered diffuse functions and the ghost-atom-based floating diffuse functions. It is found that augmentation of atom-centered diffuse functions contributes to a better description of the HOMO (corresponding to the VDE convergence), in agreement with previous studies, but also leads to unreasonable diffuse characters of the LUMO with significant red-shifts in the visible spectra, which is against the conventional point of view that the more the diffuse functions, the better the results. The issue of designing extra floating functions for excess electrons has also been systematically discussed, which indicates that the floating diffuse functions are necessary not only for reducing the computational cost but also for improving both the HOMO and LUMO accuracy. Thus, the basis sets with a combination of partial atom-centered diffuse functions and floating diffuse functions are recommended for a reliable description of the weakly bound electrons. This work presents an efficient way for characterizing the electronic properties of weakly bound electrons accurately by balancing the addition of atom-centered diffuse functions and floating diffuse functions and also by balancing the computational cost and accuracy of the calculated results, and thus is very useful in the relevant calculations of various solvated electron systems and weakly bound anionic systems.

Influence Function Learning in Information Diffusion Networks.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-06-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data.

Influence Function Learning in Information Diffusion Networks

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Can we learn the influence of a set of people in a social network from cascades of information diffusion? This question is often addressed by a two-stage approach: first learn a diffusion model, and then calculate the influence based on the learned model. Thus, the success of this approach relies heavily on the correctness of the diffusion model which is hard to verify for real world data. In this paper, we exploit the insight that the influence functions in many diffusion models are coverage functions, and propose a novel parameterization of such functions using a convex combination of random basis functions. Moreover, we propose an efficient maximum likelihood based algorithm to learn such functions directly from cascade data, and hence bypass the need to specify a particular diffusion model in advance. We provide both theoretical and empirical analysis for our approach, showing that the proposed approach can provably learn the influence function with low sample complexity, be robust to the unknown diffusion models, and significantly outperform existing approaches in both synthetic and real world data. PMID:25973445

Study on monostable and bistable reaction-diffusion equations by iteration of travelling wave maps

NASA Astrophysics Data System (ADS)

Yi, Taishan; Chen, Yuming

2017-12-01

In this paper, based on the iterative properties of travelling wave maps, we develop a new method to obtain spreading speeds and asymptotic propagation for monostable and bistable reaction-diffusion equations. Precisely, for Dirichlet problems of monostable reaction-diffusion equations on the half line, by making links between travelling wave maps and integral operators associated with the Dirichlet diffusion kernel (the latter is NOT invariant under translation), we obtain some iteration properties of the Dirichlet diffusion and some a priori estimates on nontrivial solutions of Dirichlet problems under travelling wave transformation. We then provide the asymptotic behavior of nontrivial solutions in the space-time region for Dirichlet problems. These enable us to develop a unified method to obtain results on heterogeneous steady states, travelling waves, spreading speeds, and asymptotic spreading behavior for Dirichlet problem of monostable reaction-diffusion equations on R+ as well as of monostable/bistable reaction-diffusion equations on R.

Eulerian Mapping Closure Approach for Probability Density Function of Concentration in Shear Flows

NASA Technical Reports Server (NTRS)

He, Guowei; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

The Eulerian mapping closure approach is developed for uncertainty propagation in computational fluid mechanics. The approach is used to study the Probability Density Function (PDF) for the concentration of species advected by a random shear flow. An analytical argument shows that fluctuation of the concentration field at one point in space is non-Gaussian and exhibits stretched exponential form. An Eulerian mapping approach provides an appropriate approximation to both convection and diffusion terms and leads to a closed mapping equation. The results obtained describe the evolution of the initial Gaussian field, which is in agreement with direct numerical simulations.

Spatial Mapping of Translational Diffusion Coefficients Using Diffusion Tensor Imaging: A Mathematical Description

PubMed Central

SHETTY, ANIL N.; CHIANG, SHARON; MALETIC-SAVATIC, MIRJANA; KASPRIAN, GREGOR; VANNUCCI, MARINA; LEE, WESLEY

2016-01-01

In this article, we discuss the theoretical background for diffusion weighted imaging and diffusion tensor imaging. Molecular diffusion is a random process involving thermal Brownian motion. In biological tissues, the underlying microstructures restrict the diffusion of water molecules, making diffusion directionally dependent. Water diffusion in tissue is mathematically characterized by the diffusion tensor, the elements of which contain information about the magnitude and direction of diffusion and is a function of the coordinate system. Thus, it is possible to generate contrast in tissue based primarily on diffusion effects. Expressing diffusion in terms of the measured diffusion coefficient (eigenvalue) in any one direction can lead to errors. Nowhere is this more evident than in white matter, due to the preferential orientation of myelin fibers. The directional dependency is removed by diagonalization of the diffusion tensor, which then yields a set of three eigenvalues and eigenvectors, representing the magnitude and direction of the three orthogonal axes of the diffusion ellipsoid, respectively. For example, the eigenvalue corresponding to the eigenvector along the long axis of the fiber corresponds qualitatively to diffusion with least restriction. Determination of the principal values of the diffusion tensor and various anisotropic indices provides structural information. We review the use of diffusion measurements using the modified Stejskal–Tanner diffusion equation. The anisotropy is analyzed by decomposing the diffusion tensor based on symmetrical properties describing the geometry of diffusion tensor. We further describe diffusion tensor properties in visualizing fiber tract organization of the human brain. PMID:27441031

Integrating diffusion maps with umbrella sampling: Application to alanine dipeptide

NASA Astrophysics Data System (ADS)

Ferguson, Andrew L.; Panagiotopoulos, Athanassios Z.; Debenedetti, Pablo G.; Kevrekidis, Ioannis G.

2011-04-01

Nonlinear dimensionality reduction techniques can be applied to molecular simulation trajectories to systematically extract a small number of variables with which to parametrize the important dynamical motions of the system. For molecular systems exhibiting free energy barriers exceeding a few kBT, inadequate sampling of the barrier regions between stable or metastable basins can lead to a poor global characterization of the free energy landscape. We present an adaptation of a nonlinear dimensionality reduction technique known as the diffusion map that extends its applicability to biased umbrella sampling simulation trajectories in which restraining potentials are employed to drive the system into high free energy regions and improve sampling of phase space. We then propose a bootstrapped approach to iteratively discover good low-dimensional parametrizations by interleaving successive rounds of umbrella sampling and diffusion mapping, and we illustrate the technique through a study of alanine dipeptide in explicit solvent.

Enhancing scattering images for orientation recovery with diffusion map

DOE PAGES

Winter, Martin; Saalmann, Ulf; Rost, Jan M.

2016-02-12

We explore the possibility for orientation recovery in single-molecule coherent diffractive imaging with diffusion map. This algorithm approximates the Laplace-Beltrami operator, which we diagonalize with a metric that corresponds to the mapping of Euler angles onto scattering images. While suitable for images of objects with specific properties we show why this approach fails for realistic molecules. Here, we introduce a modification of the form factor in the scattering images which facilitates the orientation recovery and should be suitable for all recovery algorithms based on the distance of individual images. (C) 2016 Optical Society of America

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

NASA Astrophysics Data System (ADS)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-09-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.

Apparent diffusion coefficient mapping in medulloblastoma predicts non-infiltrative surgical planes.

PubMed

Marupudi, Neena I; Altinok, Deniz; Goncalves, Luis; Ham, Steven D; Sood, Sandeep

2016-11-01

An appropriate surgical approach for posterior fossa lesions is to start tumor removal from areas with a defined plane to where tumor is infiltrating the brainstem or peduncles. This surgical approach minimizes risk of damage to eloquent areas. Although magnetic resonance imaging (MRI) is the current standard preoperative imaging obtained for diagnosis and surgical planning of pediatric posterior fossa tumors, it offers limited information on the infiltrative planes between tumor and normal structures in patients with medulloblastomas. Because medulloblastomas demonstrate diffusion restriction on apparent diffusion coefficient map (ADC map) sequences, we investigated the role of ADC map in predicting infiltrative and non-infiltrative planes along the brain stem and/or cerebellar peduncles by medulloblastomas prior to surgery. Thirty-four pediatric patients with pathologically confirmed medulloblastomas underwent surgical resection at our facility from 2004 to 2012. An experienced pediatric neuroradiologist reviewed the brain MRIs/ADC map, assessing the planes between the tumor and cerebellar peduncles/brain stem. An independent evaluator documented surgical findings from operative reports for comparison to the radiographic findings. The radiographic findings were statistically compared to the documented intraoperative findings to determine predictive value of the test in identifying tumor infiltration of the brain stem cerebellar peduncles. Twenty-six patients had preoperative ADC mapping completed and thereby, met inclusion criteria. Mean age at time of surgery was 8.3 ± 4.6 years. Positive predictive value of ADC maps to predict tumor invasion of the brain stem and cerebellar peduncles ranged from 69 to 88 %; negative predictive values ranged from 70 to 89 %. Sensitivity approached 93 % while specificity approached 78 %. ADC maps are valuable in predicting the infiltrative and non-infiltrative planes along the tumor and brain stem interface in

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G., E-mail: yannis@princeton.edu, E-mail: gerhard.hummer@biophys.mpg.de

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlapmore » with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.« less

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

PubMed Central

Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard

2014-01-01

Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space. PMID:25240340

Efficient global fiber tracking on multi-dimensional diffusion direction maps

NASA Astrophysics Data System (ADS)

Klein, Jan; Köhler, Benjamin; Hahn, Horst K.

2012-02-01

Global fiber tracking algorithms have recently been proposed which were able to compute results of unprecedented quality. They account for avoiding accumulation errors by a global optimization process at the cost of a high computation time of several hours or even days. In this paper, we introduce a novel global fiber tracking algorithm which, for the first time, globally optimizes the underlying diffusion direction map obtained from DTI or HARDI data, instead of single fiber segments. As a consequence, the number of iterations in the optimization process can drastically be reduced by about three orders of magnitude. Furthermore, in contrast to all previous algorithms, the density of the tracked fibers can be adjusted after the optimization within a few seconds. We evaluated our method for diffusion-weighted images obtained from software phantoms, healthy volunteers, and tumor patients. We show that difficult fiber bundles, e.g., the visual pathways or tracts for different motor functions can be determined and separated in an excellent quality. Furthermore, crossing and kissing bundles are correctly resolved. On current standard hardware, a dense fiber tracking result of a whole brain can be determined in less than half an hour which is a strong improvement compared to previous work.

Raman and CT scan mapping of chalcogenide glass diffusion generated gradient index profiles

NASA Astrophysics Data System (ADS)

Lindberg, G. P.; Berg, R. H.; Deegan, J.; Benson, R.; Salvaggio, P. S.; Gross, N.; Weinstein, B. A.; Gibson, D.; Bayya, S.; Sanghera, J.; Nguyen, V.; Kotov, M.

2016-05-01

Metrology of a gradient index (GRIN) material is non-trivial, especially in the realm of infrared and large refractive index. Traditional methods rely on index matching fluids which are not available for indexes as high as those found in the chalcogenide glasses (2.4-3.2). By diffusing chalcogenide glasses of similar composition one can blend the properties in a continuous way. In an effort to measure this we will present data from both x-ray computed tomography scans (CT scans) and Raman mapping scans of the diffusion profiles. Proof of concept measurements on undiffused bonded sheets of chalcogenide glasses were presented previously. The profiles measured will be of axially stacked sheets of chalcogenide glasses diffused to create a linear GRIN profile and nested tubes of chalcogenide glasses diffused to create a radial parabolic GRIN profile. We will show that the x-ray absorption in the CT scan and the intensity of select Raman peaks spatially measured through the material are indicators of the concentration of the diffusion ions and correlate to the spatial change in refractive index. We will also present finite element modeling (FEM) results and compare them to post precision glass molded (PGM) elements that have undergone CT and Raman mapping.

Structural and functional correlates of visual field asymmetry in the human brain by diffusion kurtosis MRI and functional MRI.

PubMed

O'Connell, Caitlin; Ho, Leon C; Murphy, Matthew C; Conner, Ian P; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C

2016-11-09

Human visual performance has been observed to show superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine whether the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI, respectively, in 15 healthy individuals at 3 T. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In diffusion kurtosis MRI, the brain regions mapping to the lower visual field showed higher mean kurtosis, but not fractional anisotropy or mean diffusivity compared with the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing.

The Green's functions for peridynamic non-local diffusion.

PubMed

Wang, L J; Xu, J F; Wang, J X

2016-09-01

In this work, we develop the Green's function method for the solution of the peridynamic non-local diffusion model in which the spatial gradient of the generalized potential in the classical theory is replaced by an integral of a generalized response function in a horizon. We first show that the general solutions of the peridynamic non-local diffusion model can be expressed as functionals of the corresponding Green's functions for point sources, along with volume constraints for non-local diffusion. Then, we obtain the Green's functions by the Fourier transform method for unsteady and steady diffusions in infinite domains. We also demonstrate that the peridynamic non-local solutions converge to the classical differential solutions when the non-local length approaches zero. Finally, the peridynamic analytical solutions are applied to an infinite plate heated by a Gauss source, and the predicted variations of temperature are compared with the classical local solutions. The peridynamic non-local diffusion model predicts a lower rate of variation of the field quantities than that of the classical theory, which is consistent with experimental observations. The developed method is applicable to general diffusion-type problems.

Sub-diffusive scattering parameter maps recovered using wide-field high-frequency structured light imaging.

PubMed

Kanick, Stephen Chad; McClatchy, David M; Krishnaswamy, Venkataramanan; Elliott, Jonathan T; Paulsen, Keith D; Pogue, Brian W

2014-10-01

This study investigates the hypothesis that structured light reflectance imaging with high spatial frequency patterns [Formula: see text] can be used to quantitatively map the anisotropic scattering phase function distribution [Formula: see text] in turbid media. Monte Carlo simulations were used in part to establish a semi-empirical model of demodulated reflectance ([Formula: see text]) in terms of dimensionless scattering [Formula: see text] and [Formula: see text], a metric of the first two moments of the [Formula: see text] distribution. Experiments completed in tissue-simulating phantoms showed that simultaneous analysis of [Formula: see text] spectra sampled at multiple [Formula: see text] in the frequency range [0.05-0.5] [Formula: see text] allowed accurate estimation of both [Formula: see text] in the relevant tissue range [0.4-1.8] [Formula: see text], and [Formula: see text] in the range [1.4-1.75]. Pilot measurements of a healthy volunteer exhibited [Formula: see text]-based contrast between scar tissue and surrounding normal skin, which was not as apparent in wide field diffuse imaging. These results represent the first wide-field maps to quantify sub-diffuse scattering parameters, which are sensitive to sub-microscopic tissue structures and composition, and therefore, offer potential for fast diagnostic imaging of ultrastructure on a size scale that is relevant to surgical applications.

Decoupling function and anatomy in atlases of functional connectivity patterns: language mapping in tumor patients.

PubMed

Langs, Georg; Sweet, Andrew; Lashkari, Danial; Tie, Yanmei; Rigolo, Laura; Golby, Alexandra J; Golland, Polina

2014-12-01

In this paper we construct an atlas that summarizes functional connectivity characteristics of a cognitive process from a population of individuals. The atlas encodes functional connectivity structure in a low-dimensional embedding space that is derived from a diffusion process on a graph that represents correlations of fMRI time courses. The functional atlas is decoupled from the anatomical space, and thus can represent functional networks with variable spatial distribution in a population. In practice the atlas is represented by a common prior distribution for the embedded fMRI signals of all subjects. We derive an algorithm for fitting this generative model to the observed data in a population. Our results in a language fMRI study demonstrate that the method identifies coherent and functionally equivalent regions across subjects. The method also successfully maps functional networks from a healthy population used as a training set to individuals whose language networks are affected by tumors. Copyright © 2014. Published by Elsevier Inc.

Integrating Concept Mapping and the Learning Cycle To Teach Diffusion and Osmosis Concepts to High School Biology Students.

ERIC Educational Resources Information Center

Odom, Arthur L.; Kelly, Paul V.

2001-01-01

Explores the effectiveness of concept mapping, the learning cycle, expository instruction, and a combination of concept mapping/learning cycle in promoting conceptual understanding of diffusion and osmosis. Concludes that the concept mapping/learning cycle and concept mapping treatment groups significantly outperformed the expository treatment…

The Green’s functions for peridynamic non-local diffusion

PubMed Central

Wang, L. J.; Xu, J. F.

2016-01-01

In this work, we develop the Green’s function method for the solution of the peridynamic non-local diffusion model in which the spatial gradient of the generalized potential in the classical theory is replaced by an integral of a generalized response function in a horizon. We first show that the general solutions of the peridynamic non-local diffusion model can be expressed as functionals of the corresponding Green’s functions for point sources, along with volume constraints for non-local diffusion. Then, we obtain the Green’s functions by the Fourier transform method for unsteady and steady diffusions in infinite domains. We also demonstrate that the peridynamic non-local solutions converge to the classical differential solutions when the non-local length approaches zero. Finally, the peridynamic analytical solutions are applied to an infinite plate heated by a Gauss source, and the predicted variations of temperature are compared with the classical local solutions. The peridynamic non-local diffusion model predicts a lower rate of variation of the field quantities than that of the classical theory, which is consistent with experimental observations. The developed method is applicable to general diffusion-type problems. PMID:27713658

Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map

PubMed Central

Kafieh, Raheleh; Rabbani, Hossein; Abramoff, Michael D.; Sonka, Milan

2013-01-01

Optical coherence tomography (OCT) is a powerful and noninvasive method for retinal imaging. In this paper, we introduce a fast segmentation method based on a new variant of spectral graph theory named diffusion maps. The research is performed on spectral domain (SD) OCT images depicting macular and optic nerve head appearance. The presented approach does not require edge-based image information in localizing most of boundaries and relies on regional image texture. Consequently, the proposed method demonstrates robustness in situations of low image contrast or poor layer-to-layer image gradients. Diffusion mapping applied to 2D and 3D OCT datasets is composed of two steps, one for partitioning the data into important and less important sections, and another one for localization of internal layers. In the first step, the pixels/voxels are grouped in rectangular/cubic sets to form a graph node. The weights of the graph are calculated based on geometric distances between pixels/voxels and differences of their mean intensity. The first diffusion map clusters the data into three parts, the second of which is the area of interest. The other two sections are eliminated from the remaining calculations. In the second step, the remaining area is subjected to another diffusion map assessment and the internal layers are localized based on their textural similarities. The proposed method was tested on 23 datasets from two patient groups (glaucoma and normals). The mean unsigned border positioning errors (mean ± SD) was 8.52 ± 3.13 and 7.56 ± 2.95 μm for the 2D and 3D methods, respectively. PMID:23837966

Structural and Functional Correlates of Visual Field Asymmetry in the Human Brain by Diffusion Kurtosis MRI and Functional MRI

PubMed Central

O’Connell, Caitlin; Ho, Leon C.; Murphy, Matthew C.; Conner, Ian P.; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C.

2016-01-01

Human visual performance has been observed to exhibit superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine if the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI (DKI), respectively in 15 healthy individuals at 3 Tesla. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In DKI, the brain regions mapping to the lower visual field exhibited higher mean kurtosis but not fractional anisotropy or mean diffusivity when compared to the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing. PMID:27631541

Functional-to-form mapping for assembly design automation

NASA Astrophysics Data System (ADS)

Xu, Z. G.; Liu, W. M.; Shen, W. D.; Yang, D. Y.; Liu, T. T.

2017-11-01

Assembly-level function-to-form mapping is the most effective procedure towards design automation. The research work mainly includes: the assembly-level function definitions, product network model and the two-step mapping mechanisms. The function-to-form mapping is divided into two steps, i.e. mapping of function-to-behavior, called the first-step mapping, and the second-step mapping, i.e. mapping of behavior-to-structure. After the first step mapping, the three dimensional transmission chain (or 3D sketch) is studied, and the feasible design computing tools are developed. The mapping procedure is relatively easy to be implemented interactively, but, it is quite difficult to finish it automatically. So manual, semi-automatic, automatic and interactive modification of the mapping model are studied. A mechanical hand F-F mapping process is illustrated to verify the design methodologies.

FADTTS: functional analysis of diffusion tensor tract statistics.

PubMed

Zhu, Hongtu; Kong, Linglong; Li, Runze; Styner, Martin; Gerig, Guido; Lin, Weili; Gilmore, John H

2011-06-01

The aim of this paper is to present a functional analysis of a diffusion tensor tract statistics (FADTTS) pipeline for delineating the association between multiple diffusion properties along major white matter fiber bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these white matter tract properties in various diffusion tensor imaging studies. The FADTTS integrates five statistical tools: (i) a multivariate varying coefficient model for allowing the varying coefficient functions in terms of arc length to characterize the varying associations between fiber bundle diffusion properties and a set of covariates, (ii) a weighted least squares estimation of the varying coefficient functions, (iii) a functional principal component analysis to delineate the structure of the variability in fiber bundle diffusion properties, (iv) a global test statistic to test hypotheses of interest, and (v) a simultaneous confidence band to quantify the uncertainty in the estimated coefficient functions. Simulated data are used to evaluate the finite sample performance of FADTTS. We apply FADTTS to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment. FADTTS can be used to facilitate the understanding of normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles. The advantages of FADTTS compared with the other existing approaches are that they are capable of modeling the structured inter-subject variability, testing the joint effects, and constructing their simultaneous confidence bands. However, FADTTS is not crucial for estimation and reduces to the functional analysis method for the single measure. Copyright © 2011 Elsevier Inc. All rights reserved.

Rapid exploration of configuration space with diffusion-map-directed molecular dynamics.

PubMed

Zheng, Wenwei; Rohrdanz, Mary A; Clementi, Cecilia

2013-10-24

The gap between the time scale of interesting behavior in macromolecular systems and that which our computational resources can afford often limits molecular dynamics (MD) from understanding experimental results and predicting what is inaccessible in experiments. In this paper, we introduce a new sampling scheme, named diffusion-map-directed MD (DM-d-MD), to rapidly explore molecular configuration space. The method uses a diffusion map to guide MD on the fly. DM-d-MD can be combined with other methods to reconstruct the equilibrium free energy, and here, we used umbrella sampling as an example. We present results from two systems: alanine dipeptide and alanine-12. In both systems, we gain tremendous speedup with respect to standard MD both in exploring the configuration space and reconstructing the equilibrium distribution. In particular, we obtain 3 orders of magnitude of speedup over standard MD in the exploration of the configurational space of alanine-12 at 300 K with DM-d-MD. The method is reaction coordinate free and minimally dependent on a priori knowledge of the system. We expect wide applications of DM-d-MD to other macromolecular systems in which equilibrium sampling is not affordable by standard MD.

Rapid Exploration of Configuration Space with Diffusion Map-directed-Molecular Dynamics

PubMed Central

Zheng, Wenwei; Rohrdanz, Mary A.; Clementi, Cecilia

2013-01-01

The gap between the timescale of interesting behavior in macromolecular systems and that which our computational resources can afford oftentimes limits Molecular Dynamics (MD) from understanding experimental results and predicting what is inaccessible in experiments. In this paper, we introduce a new sampling scheme, named Diffusion Map-directed-MD (DM-d-MD), to rapidly explore molecular configuration space. The method uses diffusion map to guide MD on the fly. DM-d-MD can be combined with other methods to reconstruct the equilibrium free energy, and here we used umbrella sampling as an example. We present results from two systems: alanine dipeptide and alanine-12. In both systems we gain tremendous speedup with respect to standard MD both in exploring the configuration space and reconstructing the equilibrium distribution. In particular, we obtain 3 orders of magnitude of speedup over standard MD in the exploration of the configurational space of alanine-12 at 300K with DM-d-MD. The method is reaction coordinate free and minimally dependent on a priori knowledge of the system. We expect wide applications of DM-d-MD to other macromolecular systems in which equilibrium sampling is not affordable by standard MD. PMID:23865517

Structured illumination diffuse optical tomography for noninvasive functional neuroimaging in mice.

PubMed

Reisman, Matthew D; Markow, Zachary E; Bauer, Adam Q; Culver, Joseph P

2017-04-01

Optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to superficial cortical tissues. Diffuse optical tomography (DOT) techniques provide noninvasive imaging, but previous DOT systems for rodent neuroimaging have been limited either by sparse spatial sampling or by slow speed. Here, we develop a DOT system with asymmetric source-detector sampling that combines the high-density spatial sampling (0.4 mm) detection of a scientific complementary metal-oxide-semiconductor camera with the rapid (2 Hz) imaging of a few ([Formula: see text]) structured illumination (SI) patterns. Analysis techniques are developed to take advantage of the system's flexibility and optimize trade-offs among spatial sampling, imaging speed, and signal-to-noise ratio. An effective source-detector separation for the SI patterns was developed and compared with light intensity for a quantitative assessment of data quality. The light fall-off versus effective distance was also used for in situ empirical optimization of our light model. We demonstrated the feasibility of this technique by noninvasively mapping the functional response in the somatosensory cortex of the mouse following electrical stimulation of the forepaw.

A Stable Finite-Difference Scheme for Population Growth and Diffusion on a Map

PubMed Central

Callegari, S.; Lake, G. R.; Tkachenko, N.; Weissmann, J. D.; Zollikofer, Ch. P. E.

2017-01-01

We describe a general Godunov-type splitting for numerical simulations of the Fisher–Kolmogorov–Petrovski–Piskunov growth and diffusion equation on a world map with Neumann boundary conditions. The procedure is semi-implicit, hence quite stable. Our principal application for this solver is modeling human population dispersal over geographical maps with changing paleovegetation and paleoclimate in the late Pleistocene. As a proxy for carrying capacity we use Net Primary Productivity (NPP) to predict times for human arrival in the Americas. PMID:28085882

A Stable Finite-Difference Scheme for Population Growth and Diffusion on a Map.

PubMed

Petersen, W P; Callegari, S; Lake, G R; Tkachenko, N; Weissmann, J D; Zollikofer, Ch P E

2017-01-01

We describe a general Godunov-type splitting for numerical simulations of the Fisher-Kolmogorov-Petrovski-Piskunov growth and diffusion equation on a world map with Neumann boundary conditions. The procedure is semi-implicit, hence quite stable. Our principal application for this solver is modeling human population dispersal over geographical maps with changing paleovegetation and paleoclimate in the late Pleistocene. As a proxy for carrying capacity we use Net Primary Productivity (NPP) to predict times for human arrival in the Americas.

FAST Mapping of Diffuse HI Gas in the Local Universe

NASA Astrophysics Data System (ADS)

Zhu, M.; Pisano, D. J.; Ai, M.; Jiao, Q.

2016-02-01

We propose to use the Five hundred meter Aperture Spherical radio Telescope (FAST) to map the diffuse intergalactic HI gas in the local universe at column densities of NHI=1018 cm-2 and below. The major science goal is to study gas accretion during galaxy evolution, and trace cosmic web features in the local universe. We disuss the technical feasibilty of such a deep survey, and have conducted test observations with the Arecibo 305 m telescope. Our preliminary results shows that, with about a few thousand hours of observing time, FAST will be able to map several hundred square degree regions at 1 σ of NHI=2×1017 cm-2 level out to a distance of 5-10 Mpc, and with a volume 1000 larger than that of the Local Group.

Time-resolved mapping of water diffusion coefficients in a working soft actuator device.

PubMed

Naji, Leila; Chudek, John A; Baker, Richard T

2008-08-14

Diffusion-weighted imaging was employed to spatially map the distribution of the diffusion coefficient of water, D, in bare, water-soaked, Li(+)-exchanged, cast Nafion and in an ionic polymer-metal composite (IPMC) soft actuator element, prepared from this bare Nafion by impregnation with Pt electrodes. D was evaluated in two orthogonal directions: along one of the long dimensions of the sample (Dx) and through its thickness (Dz). D-maps of the IPMC element were obtained both in the absence of an applied potential and in situ during the application of a 3 V dc potential across the thickness of the sample. In the bare Nafion, D-maps showed uniform values of both Dx and Dz of about 6 x 10 (-10) m(2) s(-1). In the IPMC two effects were observed: (i) D at the electroded surfaces of the IPMC was higher than at the center of the sample; (ii) this difference was much greater in Dz than in Dx . Both effects were explained by the influence of the impregnated Pt electrodes on polymer structure. The D-maps in the electrochemical measurements showed high values of D (up to 8 x 10(-10) m(2) s(-1)) at the cathode and low values (from 1 x 10(-10) m(2) s(-1)) at the anode. This was explained in terms of the effect on the Nafion nanostructure of the forced electro-migration of Li(H2O)x(+) species toward the cathode.

Diffusion MRI at 25: Exploring brain tissue structure and function

PubMed Central

Bihan, Denis Le; Johansen-Berg, Heidi

2013-01-01

Diffusion MRI (or dMRI) came into existence in the mid-1980s. During the last 25 years, diffusion MRI has been extraordinarily successful (with more than 300,000 entries on Google Scholar for diffusion MRI). Its main clinical domain of application has been neurological disorders, especially for the management of patients with acute stroke. It is also rapidly becoming a standard for white matter disorders, as diffusion tensor imaging (DTI) can reveal abnormalities in white matter fiber structure and provide outstanding maps of brain connectivity. The ability to visualize anatomical connections between different parts of the brain, non-invasively and on an individual basis, has emerged as a major breakthrough for neurosciences. The driving force of dMRI is to monitor microscopic, natural displacements of water molecules that occur in brain tissues as part of the physical diffusion process. Water molecules are thus used as a probe that can reveal microscopic details about tissue architecture, either normal or in a diseased state. PMID:22120012

Quantitative analysis of diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) for brain disorders

NASA Astrophysics Data System (ADS)

Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon

2013-07-01

This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.

Cubic map algebra functions for spatio-temporal analysis

USGS Publications Warehouse

Mennis, J.; Viger, R.; Tomlin, C.D.

2005-01-01

We propose an extension of map algebra to three dimensions for spatio-temporal data handling. This approach yields a new class of map algebra functions that we call "cube functions." Whereas conventional map algebra functions operate on data layers representing two-dimensional space, cube functions operate on data cubes representing two-dimensional space over a third-dimensional period of time. We describe the prototype implementation of a spatio-temporal data structure and selected cube function versions of conventional local, focal, and zonal map algebra functions. The utility of cube functions is demonstrated through a case study analyzing the spatio-temporal variability of remotely sensed, southeastern U.S. vegetation character over various land covers and during different El Nin??o/Southern Oscillation (ENSO) phases. Like conventional map algebra, the application of cube functions may demand significant data preprocessing when integrating diverse data sets, and are subject to limitations related to data storage and algorithm performance. Solutions to these issues include extending data compression and computing strategies for calculations on very large data volumes to spatio-temporal data handling.

Functional materials discovery using energy-structure-function maps

NASA Astrophysics Data System (ADS)

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A.; Chong, Samantha Y.; Slater, Benjamin J.; McMahon, David P.; Bonillo, Baltasar; Stackhouse, Chloe J.; Stephenson, Andrew; Kane, Christopher M.; Clowes, Rob; Hasell, Tom; Cooper, Andrew I.; Day, Graeme M.

2017-03-01

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

Functional materials discovery using energy-structure-function maps.

PubMed

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A; Chong, Samantha Y; Slater, Benjamin J; McMahon, David P; Bonillo, Baltasar; Stackhouse, Chloe J; Stephenson, Andrew; Kane, Christopher M; Clowes, Rob; Hasell, Tom; Cooper, Andrew I; Day, Graeme M

2017-03-30

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

High Resolution IRAS Maps and IR Emission of M31 -- II. Diffuse Component and Interstellar Dust

NASA Technical Reports Server (NTRS)

Xu, C.; Helou, G.

1995-01-01

Large-scale dust heating and cooling in the diffuse medium of M31 is studied using the high resolution (HiRes) IRAS maps in conjunction with UV, optical (UBV), and the HI maps. A dust heating/cooling model is developed based on a radiative transfer model which assumes a 'Sandwich' configuration of dust and stars takes account of the effect of dust grain scattering.

Diffusion-Weighted Magnetic Resonance Imaging to Evaluate Major Salivary Gland Function Before and After Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dirix, Piet; Keyzer, Frederik de; Vandecaveye, Vincent

2008-08-01

Purpose: To evaluate diffusion-weighted (DW)-MRI as a noninvasive tool to investigate major salivary gland function before and after radiotherapy (RT) for head and neck cancer (HNC). Methods and Materials: DW-MRI was performed in 8 HNC patients before and after parotid-sparing RT (mean dose to the contralateral parotid gland <26 Gy). A DW sequence was performed once at rest and then repeated continuously during salivary stimulation. Apparent diffusion coefficient (ADC) maps for both parotid and submandibular glands were calculated. Findings were compared with salivary gland scintigraphy. Results: Before RT, the mean ADC value at rest was significantly lower in the parotidmore » than in the submandibular glands. During the first 5 min of stimulation, the ADC value of the salivary glands showed a decrease, followed by a steady increase until a peak ADC, significantly higher than the baseline value, was reached after a median of 17 min. The baseline ADC value at rest was significantly higher after RT than before RT in the nonspared salivary glands but not in the spared parotid glands. In the contralateral parotid glands, the same response was seen as before RT. This pattern was completely lost in the nonspared glands. These results corresponded with remaining or loss of salivary function, respectively, as confirmed by salivary gland scintigraphy. Conclusions: Diffusion-weighted-MRI allows noninvasive evaluation of functional changes in the major salivary glands after RT and is a promising tool for investigating radiation-induced xerostomia.« less

Mapping functional connectivity

Treesearch

Peter Vogt; Joseph R. Ferrari; Todd R. Lookingbill; Robert H. Gardner; Kurt H. Riitters; Katarzyna Ostapowicz

2009-01-01

An objective and reliable assessment of wildlife movement is important in theoretical and applied ecology. The identification and mapping of landscape elements that may enhance functional connectivity is usually a subjective process based on visual interpretations of species movement patterns. New methods based on mathematical morphology provide a generic, flexible,...

Diffusion-weighted magnetic resonance imaging and apparent diffusion coefficient mapping for diagnosing infectious spondylodiscitis: a preliminary study.

PubMed

Chen, Tai-Yuan; Wu, Te-Chang; Tsui, Yu-Kun; Chen, Hou-Hsun; Lin, Chien-Jen; Lee, Huey-Jen; Wu, Tai-Ching

2015-01-01

Though diffusion-weighted (DW) magnetic resonance imaging (MRI) is useful for diagnosing many pathologies, its use in infectious spondylodiscitis is unclear. We aimed to evaluate the use of DW MRI and apparent diffusion coefficient (ADC) mapping for the diagnosis of infectious spondylodiscitis. In this retrospective study, 17 patients with confirmed infectious spondylodiscitis were matched by age and level of infected disc with 17 patients with degenerative disc disease (DDD) and 17 healthy controls. All patients received conventional MRI and diffusion-weighted imaging (DWI) in the same imaging session. ADC values of the 3 groups of patients were compared. The mean age of each group was 67.4 ± 11.6 years. The mean ADCs of the normal control, DDD, and infectious spondylodiscitis groups were 1.76 ± 0.19 × 10(-3) , 1.12 ± 0.22 × 10(-3) , and 1.27 ± 0.38 × 10(-3) mm2 /second, respectively. The ADCs of the DDD and infectious spondylodiscitis groups were both significantly lower than that of the normal control group (both, P < 0.001). These data suggest that DWI/ADC MRI may be useful in the early diagnosis of infectious spondylodiscitis. © 2014 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.

Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.

PubMed

Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura; Prah, Melissa; Hectors, Stefanie; Arlinghaus, Lori; Muzi, Mark; Solaiyappan, Meiyappan; Jacobs, Michael; Fung, Maggie; Shukla-Dave, Amita; McManus, Kevin; Boss, Michael; Taouli, Bachir; Yankeelov, Thomas E; Quarles, Christopher Chad; Schmainda, Kathleen; Chenevert, Thomas L; Newitt, David C

2018-01-01

This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.

Arnold diffusion for a complete family of perturbations

NASA Astrophysics Data System (ADS)

Delshams, Amadeu; Schaefer, Rodrigo G.

2017-01-01

In this work we illustrate the Arnold diffusion in a concrete example — the a priori unstable Hamiltonian system of 2 + 1/2 degrees of freedom H( p, q, I, φ, s) = p 2/2+ cos q - 1 + I 2/2 + h( q, φ, s; ɛ) — proving that for any small periodic perturbation of the form h( q, φ, s; ɛ) = ɛ cos q ( a 00 + a 10 cos φ + a 01 cos s) ( a 10 a 01 ≠ 0) there is global instability for the action. For the proof we apply a geometrical mechanism based on the so-called scattering map. This work has the following structure: In the first stage, for a more restricted case ( I* π/2 μ, μ = a 10/ a 01), we use only one scattering map, with a special property: the existence of simple paths of diffusion called highways. Later, in the general case we combine a scattering map with the inner map (inner dynamics) to prove the more general result (the existence of instability for any μ). The bifurcations of the scattering map are also studied as a function of μ. Finally, we give an estimate for the time of diffusion, and we show that this time is primarily the time spent under the scattering map.

Nanoscale diffusive memristor crossbars as physical unclonable functions.

PubMed

Zhang, R; Jiang, H; Wang, Z R; Lin, P; Zhuo, Y; Holcomb, D; Zhang, D H; Yang, J J; Xia, Q

2018-02-08

Physical unclonable functions have emerged as promising hardware security primitives for device authentication and key generation in the era of the Internet of Things. Herein, we report novel physical unclonable functions built upon the crossbars of nanoscale diffusive memristors that translate the stochastic distribution of Ag clusters in a SiO 2 matrix into a random binary bitmap that serves as a device fingerprint. The random dispersion of Ag led to an uneven number of clusters at each cross-point, which in turn resulted in a stochastic ability to switch in the Ag:SiO 2 diffusive memristors in an array. The randomness of the dispersion was a barrier to fingerprint cloning and the unique fingerprints of each device were persistent after fabrication. Using an optimized fabrication procedure, we maximized the randomness and achieved an inter-class Hamming distance of 50.68%. We also discovered that the bits were not flipping after over 10 4 s at 400 K, suggesting superior reliability of our physical unclonable functions. In addition, our diffusive memristor-based physical unclonable functions were easy to fabricate and did not require complicated post-processing for digitization and thus, provide new opportunities in hardware security applications.

Mapping the conduction band edge density of states of γ-In2Se3 by diffuse reflectance spectra

NASA Astrophysics Data System (ADS)

Kumar, Pradeep; Vedeshwar, Agnikumar G.

2018-03-01

It is demonstrated that the measured diffuse reflectance spectra of γ-In2Se3 can be used to map the conduction band edge density of states through Kubelka-Munk analysis. The Kubelka-Munk function derived from the measured spectra almost mimics the calculated density of states in the vicinity of conduction band edge. The calculation of density of states was carried out using first-principles approach yielding the structural, electronic, and optical properties. The calculations were carried out implementing various functionals and only modified Tran and Blaha (TB-MBJ) results tally closest with the experimental result of band gap. The electronic and optical properties were calculated using FP-LAPW + lo approach based on the Density Functional Theory formalism implementing only TB-mBJ functional. The electron and hole effective masses have been calculated as me * = 0.25 m 0 and mh * = 1.11 m 0 , respectively. The optical properties clearly indicate the anisotropic nature of γ-In2Se3.

Planck 2015 results. X. Diffuse component separation: Foreground maps

NASA Astrophysics Data System (ADS)

Planck Collaboration; Adam, R.; Ade, P. A. R.; Aghanim, N.; Alves, M. I. R.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Helou, G.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Le Jeune, M.; Leahy, J. P.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Orlando, E.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reach, W. T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Strong, A. W.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, F.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Wilkinson, A.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

Planck has mapped the microwave sky in temperature over nine frequency bands between 30 and 857 GHz and in polarization over seven frequency bands between 30 and 353 GHz in polarization. In this paper we consider the problem of diffuse astrophysical component separation, and process these maps within a Bayesian framework to derive an internally consistent set of full-sky astrophysical component maps. Component separation dedicated to cosmic microwave background (CMB) reconstruction is described in a companion paper. For the temperature analysis, we combine the Planck observations with the 9-yr Wilkinson Microwave Anisotropy Probe (WMAP) sky maps and the Haslam et al. 408 MHz map, to derive a joint model of CMB, synchrotron, free-free, spinning dust, CO, line emission in the 94 and 100 GHz channels, and thermal dust emission. Full-sky maps are provided for each component, with an angular resolution varying between 7.´5 and 1deg. Global parameters (monopoles, dipoles, relative calibration, and bandpass errors) are fitted jointly with the sky model, and best-fit values are tabulated. For polarization, the model includes CMB, synchrotron, and thermal dust emission. These models provide excellent fits to the observed data, with rms temperature residuals smaller than 4μK over 93% of the sky for all Planck frequencies up to 353 GHz, and fractional errors smaller than 1% in the remaining 7% of the sky. The main limitations of the temperature model at the lower frequencies are internal degeneracies among the spinning dust, free-free, and synchrotron components; additional observations from external low-frequency experiments will be essential to break these degeneracies. The main limitations of the temperature model at the higher frequencies are uncertainties in the 545 and 857 GHz calibration and zero-points. For polarization, the main outstanding issues are instrumental systematics in the 100-353 GHz bands on large angular scales in the form of temperature

Planck 2015 results: X. Diffuse component separation: Foreground maps

DOE PAGES

Adam, R.; Ade, P. A. R.; Aghanim, N.; ...

2016-09-20

We report that Planck has mapped the microwave sky in temperature over nine frequency bands between 30 and 857 GHz and in polarization over seven frequency bands between 30 and 353 GHz in polarization. In this paper we consider the problem of diffuse astrophysical component separation, and process these maps within a Bayesian framework to derive an internally consistent set of full-sky astrophysical component maps. Component separation dedicated to cosmic microwave background (CMB) reconstruction is described in a companion paper. For the temperature analysis, we combine the Planck observations with the 9-yr Wilkinson Microwave Anisotropy Probe (WMAP) sky maps andmore » the Haslam et al. 408 MHz map, to derive a joint model of CMB, synchrotron, free-free, spinning dust, CO, line emission in the 94 and 100 GHz channels, and thermal dust emission. Full-sky maps are provided for each component, with an angular resolution varying between 7.5 and 1deg. Global parameters (monopoles, dipoles, relative calibration, and bandpass errors) are fitted jointly with the sky model, and best-fit values are tabulated. For polarization, the model includes CMB, synchrotron, and thermal dust emission. These models provide excellent fits to the observed data, with rms temperature residuals smaller than 4μK over 93% of the sky for all Planck frequencies up to 353 GHz, and fractional errors smaller than 1% in the remaining 7% of the sky. The main limitations of the temperature model at the lower frequencies are internal degeneracies among the spinning dust, free-free, and synchrotron components; additional observations from external low-frequency experiments will be essential to break these degeneracies. The main limitations of the temperature model at the higher frequencies are uncertainties in the 545 and 857 GHz calibration and zero-points. For polarization, the main outstanding issues are instrumental systematics in the 100–353 GHz bands on large angular scales in the form of

Response variance in functional maps: neural darwinism revisited.

PubMed

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response Variance in Functional Maps: Neural Darwinism Revisited

PubMed Central

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population. PMID:23874733

Surface-to-volume ratio mapping of tumor microstructure using oscillating gradient diffusion weighted imaging

PubMed Central

Reynaud, Olivier; Winters, Kerryanne Veronica; Hoang, Dung Minh; Wadghiri, Youssef Zaim; Novikov, Dmitry S; Kim, Sungheon Gene

2015-01-01

Purpose To disentangle the free diffusivity (D0) and cellular membrane restrictions, via their surface-to-volume ratio (S/V), using the frequency-dependence of the diffusion coefficient D(ω), measured in brain tumors in the short diffusion-time regime using oscillating gradients (OGSE). Methods In vivo and ex vivo OGSE experiments were performed on mice bearing the GL261 murine glioma model (n=10) to identify the relevant time/frequency (t/ω) domain where D(ω) linearly decreases with ω−1/2. Parametric maps (S/V, D0) are compared to conventional DWI metrics. The impact of frequency range and temperature (20°C vs. 37°C) on S/V and D0 is investigated ex vivo. Results The validity of the short diffusion-time regime is demonstrated in vivo and ex vivo. Ex vivo measurements confirm that the purely geometric restrictions embodied in S/V are independent from temperature and frequency range, while the temperature dependence of the free diffusivity D0 is similar to that of pure water. Conclusion Our results suggest that D(ω) in the short diffusion-time regime can be used to uncouple the purely geometric restriction effect, such as S/V, from the intrinsic medium diffusivity properties, and provides a non-empirical and objective way to interpret frequency/time-dependent diffusion changes in tumors in terms of objective biophysical tissue parameters. PMID:26207354

Consistency functional map propagation for repetitive patterns

NASA Astrophysics Data System (ADS)

Wang, Hao

2017-09-01

Repetitive patterns appear frequently in both man-made and natural environments. Automatically and robustly detecting such patterns from an image is a challenging problem. We study repetitive pattern alignment by embedding segmentation cue with a functional map model. However, this model cannot tackle the repetitive patterns directly due to the large photometric and geometric variations. Thus, a consistency functional map propagation (CFMP) algorithm that extends the functional map with dynamic propagation is proposed to address this issue. This propagation model is acquired in two steps. The first one aligns the patterns from a local region, transferring segmentation functions among patterns. It can be cast as an L norm optimization problem. The latter step updates the template segmentation for the next round of pattern discovery by merging the transferred segmentation functions. Extensive experiments and comparative analyses have demonstrated an encouraging performance of the proposed algorithm in detection and segmentation of repetitive patterns.

Interleaved multishot imaging by spatiotemporal encoding: A fast, self-referenced method for high-definition diffusion and functional MRI.

PubMed

Schmidt, Rita; Seginer, Amir; Frydman, Lucio

2016-05-01

Single-shot imaging by spatiotemporal encoding (SPEN) can provide higher immunity to artifacts than its echo planar imaging-based counterparts. Further improvements in resolution and signal-to-noise ratio could be made by rescinding the sequence's single-scan nature. To explore this option, an interleaved SPEN version was developed that was capable of delivering optimized images due to its use of a referenceless correction algorithm. A characteristic element of SPEN encoding is the absence of aliasing when its signals are undersampled along the low-bandwidth dimension. This feature was exploited in this study to segment a SPEN experiment into a number of interleaved shots whose inaccuracies were automatically compared and corrected as part of a navigator-free image reconstruction analysis. This could account for normal phase noises, as well as for object motions during the signal collection. The ensuing interleaved SPEN method was applied to phantoms and human volunteers and delivered high-quality images even in inhomogeneous or mobile environments. Submillimeter functional MRI activation maps confined to gray matter regions as well as submillimeter diffusion coefficient maps of human brains were obtained. We have developed an interleaved SPEN approach for the acquisition of high-definition images that promises a wider range of functional and diffusion MRI applications even in challenging environments. © 2015 Wiley Periodicals, Inc.

A Semiparametric Approach for Composite Functional Mapping of Dynamic Quantitative Traits

PubMed Central

Yang, Runqing; Gao, Huijiang; Wang, Xin; Zhang, Ji; Zeng, Zhao-Bang; Wu, Rongling

2007-01-01

Functional mapping has emerged as a powerful tool for mapping quantitative trait loci (QTL) that control developmental patterns of complex dynamic traits. Original functional mapping has been constructed within the context of simple interval mapping, without consideration of separate multiple linked QTL for a dynamic trait. In this article, we present a statistical framework for mapping QTL that affect dynamic traits by capitalizing on the strengths of functional mapping and composite interval mapping. Within this so-called composite functional-mapping framework, functional mapping models the time-dependent genetic effects of a QTL tested within a marker interval using a biologically meaningful parametric function, whereas composite interval mapping models the time-dependent genetic effects of the markers outside the test interval to control the genome background using a flexible nonparametric approach based on Legendre polynomials. Such a semiparametric framework was formulated by a maximum-likelihood model and implemented with the EM algorithm, allowing for the estimation and the test of the mathematical parameters that define the QTL effects and the regression coefficients of the Legendre polynomials that describe the marker effects. Simulation studies were performed to investigate the statistical behavior of composite functional mapping and compare its advantage in separating multiple linked QTL as compared to functional mapping. We used the new mapping approach to analyze a genetic mapping example in rice, leading to the identification of multiple QTL, some of which are linked on the same chromosome, that control the developmental trajectory of leaf age. PMID:17947431

Deep-tissue temperature mapping by multi-illumination photoacoustic tomography aided by a diffusion optical model: a numerical study

NASA Astrophysics Data System (ADS)

Zhou, Yuan; Tang, Eric; Luo, Jianwen; Yao, Junjie

2018-01-01

Temperature mapping during thermotherapy can help precisely control the heating process, both temporally and spatially, to efficiently kill the tumor cells and prevent the healthy tissues from heating damage. Photoacoustic tomography (PAT) has been used for noninvasive temperature mapping with high sensitivity, based on the linear correlation between the tissue's Grüneisen parameter and temperature. However, limited by the tissue's unknown optical properties and thus the optical fluence at depths beyond the optical diffusion limit, the reported PAT thermometry usually takes a ratiometric measurement at different temperatures and thus cannot provide absolute measurements. Moreover, ratiometric measurement over time at different temperatures has to assume that the tissue's optical properties do not change with temperatures, which is usually not valid due to the temperature-induced hemodynamic changes. We propose an optical-diffusion-model-enhanced PAT temperature mapping that can obtain the absolute temperature distribution in deep tissue, without the need of multiple measurements at different temperatures. Based on the initial acoustic pressure reconstructed from multi-illumination photoacoustic signals, both the local optical fluence and the optical parameters including absorption and scattering coefficients are first estimated by the optical-diffusion model, then the temperature distribution is obtained from the reconstructed Grüneisen parameters. We have developed a mathematic model for the multi-illumination PAT of absolute temperatures, and our two-dimensional numerical simulations have shown the feasibility of this new method. The proposed absolute temperature mapping method may set the technical foundation for better temperature control in deep tissue in thermotherapy.

Improved Diffuse Foreground Subtraction with the ILC Method: CMB Map and Angular Power Spectrum Using Planck and WMAP Observations

NASA Astrophysics Data System (ADS)

Sudevan, Vipin; Aluri, Pavan K.; Yadav, Sarvesh Kumar; Saha, Rajib; Souradeep, Tarun

2017-06-01

We report an improved technique for diffuse foreground minimization from Cosmic Microwave Background (CMB) maps using a new multiphase iterative harmonic space internal-linear-combination (HILC) approach. Our method nullifies a foreground leakage that was present in the old and usual iterative HILC method. In phase 1 of the multiphase technique, we obtain an initial cleaned map using the single iteration HILC approach over the desired portion of the sky. In phase 2, we obtain a final CMB map using the iterative HILC approach; however, now, to nullify the leakage, during each iteration, some of the regions of the sky that are not being cleaned in the current iteration are replaced by the corresponding cleaned portions of the phase 1 map. We bring all input frequency maps to a common and maximum possible beam and pixel resolution at the beginning of the analysis, which significantly reduces data redundancy, memory usage, and computational cost, and avoids, during the HILC weight calculation, the deconvolution of partial sky harmonic coefficients by the azimuthally symmetric beam and pixel window functions, which in a strict mathematical sense, are not well defined. Using WMAP 9 year and Planck 2015 frequency maps, we obtain foreground-cleaned CMB maps and a CMB angular power spectrum for the multipole range 2≤slant {\\ell }≤slant 2500. Our power spectrum matches the published Planck results with some differences at different multipole ranges. We validate our method by performing Monte Carlo simulations. Finally, we show that the weights for HILC foreground minimization have the intrinsic characteristic that they also tend to produce a statistically isotropic CMB map.

A new mapping function in table-mounted eye tracker

NASA Astrophysics Data System (ADS)

Tong, Qinqin; Hua, Xiao; Qiu, Jian; Luo, Kaiqing; Peng, Li; Han, Peng

2018-01-01

Eye tracker is a new apparatus of human-computer interaction, which has caught much attention in recent years. Eye tracking technology is to obtain the current subject's "visual attention (gaze)" direction by using mechanical, electronic, optical, image processing and other means of detection. While the mapping function is one of the key technology of the image processing, and is also the determination of the accuracy of the whole eye tracker system. In this paper, we present a new mapping model based on the relationship among the eyes, the camera and the screen that the eye gazed. Firstly, according to the geometrical relationship among the eyes, the camera and the screen, the framework of mapping function between the pupil center and the screen coordinate is constructed. Secondly, in order to simplify the vectors inversion of the mapping function, the coordinate of the eyes, the camera and screen was modeled by the coaxial model systems. In order to verify the mapping function, corresponding experiment was implemented. It is also compared with the traditional quadratic polynomial function. And the results show that our approach can improve the accuracy of the determination of the gazing point. Comparing with other methods, this mapping function is simple and valid.

Application of diffusion maps to identify human factors of self-reported anomalies in aviation.

PubMed

Andrzejczak, Chris; Karwowski, Waldemar; Mikusinski, Piotr

2012-01-01

A study investigating what factors are present leading to pilots submitting voluntary anomaly reports regarding their flight performance was conducted. Diffusion Maps (DM) were selected as the method of choice for performing dimensionality reduction on text records for this study. Diffusion Maps have seen successful use in other domains such as image classification and pattern recognition. High-dimensionality data in the form of narrative text reports from the NASA Aviation Safety Reporting System (ASRS) were clustered and categorized by way of dimensionality reduction. Supervised analyses were performed to create a baseline document clustering system. Dimensionality reduction techniques identified concepts or keywords within records, and allowed the creation of a framework for an unsupervised document classification system. Results from the unsupervised clustering algorithm performed similarly to the supervised methods outlined in the study. The dimensionality reduction was performed on 100 of the most commonly occurring words within 126,000 text records describing commercial aviation incidents. This study demonstrates that unsupervised machine clustering and organization of incident reports is possible based on unbiased inputs. Findings from this study reinforced traditional views on what factors contribute to civil aviation anomalies, however, new associations between previously unrelated factors and conditions were also found.

Remediating High School Students' Misconceptions Concerning Diffusion and Osmosis through Concept Mapping and Conceptual Change Text.

ERIC Educational Resources Information Center

Tekkaya, Ceren

2003-01-01

Investigates the effectiveness of combining conceptual change text and concept mapping strategies on students' understanding of diffusion and osmosis. Results indicate that while the average percentage of students in the experimental group holding a scientifically correct view rose, the percentage of correct responses in the control group…

Real space mapping of oxygen vacancy diffusion and electrochemical transformations by hysteretic current reversal curve measurements

DOEpatents

Kalinin, Sergei V.; Balke, Nina; Borisevich, Albina Y.; Jesse, Stephen; Maksymovych, Petro; Kim, Yunseok; Strelcov, Evgheni

2014-06-10

An excitation voltage biases an ionic conducting material sample over a nanoscale grid. The bias sweeps a modulated voltage with increasing maximal amplitudes. A current response is measured at grid locations. Current response reversal curves are mapped over maximal amplitudes of the bias cycles. Reversal curves are averaged over the grid for each bias cycle and mapped over maximal bias amplitudes for each bias cycle. Average reversal curve areas are mapped over maximal amplitudes of the bias cycles. Thresholds are determined for onset and ending of electrochemical activity. A predetermined number of bias sweeps may vary in frequency where each sweep has a constant number of cycles and reversal response curves may indicate ionic diffusion kinetics.

Diffusion of responsibility attenuates altruistic punishment: A functional magnetic resonance imaging effective connectivity study.

PubMed

Feng, Chunliang; Deshpande, Gopikrishna; Liu, Chao; Gu, Ruolei; Luo, Yue-Jia; Krueger, Frank

2016-02-01

Humans altruistically punish violators of social norms to enforce cooperation and pro-social behaviors. However, such altruistic behaviors diminish when others are present, due to a diffusion of responsibility. We investigated the neural signatures underlying the modulations of diffusion of responsibility on altruistic punishment, conjoining a third-party punishment task with event-related functional magnetic resonance imaging and multivariate Granger causality mapping. In our study, participants acted as impartial third-party decision-makers and decided how to punish norm violations under two different social contexts: alone (i.e., full responsibility) or in the presence of putative other third-party decision makers (i.e., diffused responsibility). Our behavioral results demonstrated that the diffusion of responsibility served as a mediator of context-dependent punishment. In the presence of putative others, participants who felt less responsible also punished less severely in response to norm violations. Our neural results revealed that underlying this behavioral effect was a network of interconnected brain regions. For unfair relative to fair splits, the presence of others led to attenuated responses in brain regions implicated in signaling norm violations (e.g., AI) and to increased responses in brain regions implicated in calculating values of norm violations (e.g., vmPFC, precuneus) and mentalizing about others (dmPFC). The dmPFC acted as the driver of the punishment network, modulating target regions, such as AI, vmPFC, and precuneus, to adjust altruistic punishment behavior. Our results uncovered the neural basis of the influence of diffusion of responsibility on altruistic punishment and highlighted the role of the mentalizing network in this important phenomenon. Hum Brain Mapp 37:663-677, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Function representation with circle inversion map systems

NASA Astrophysics Data System (ADS)

Boreland, Bryson; Kunze, Herb

2017-01-01

The fractals literature develops the now well-known concept of local iterated function systems (using affine maps) with grey-level maps (LIFSM) as an approach to function representation in terms of the associated fixed point of the so-called fractal transform. While originally explored as a method to achieve signal (and 2-D image) compression, more recent work has explored various aspects of signal and image processing using this machinery. In this paper, we develop a similar framework for function representation using circle inversion map systems. Given a circle C with centre õ and radius r, inversion with respect to C transforms the point p˜ to the point p˜', such that p˜ and p˜' lie on the same radial half-line from õ and d(õ, p˜)d(õ, p˜') = r2, where d is Euclidean distance. We demonstrate the results with an example.

Insight from uncertainty: bootstrap-derived diffusion metrics differentially predict memory function among older adults.

PubMed

Vorburger, Robert S; Habeck, Christian G; Narkhede, Atul; Guzman, Vanessa A; Manly, Jennifer J; Brickman, Adam M

2016-01-01

Diffusion tensor imaging suffers from an intrinsic low signal-to-noise ratio. Bootstrap algorithms have been introduced to provide a non-parametric method to estimate the uncertainty of the measured diffusion parameters. To quantify the variability of the principal diffusion direction, bootstrap-derived metrics such as the cone of uncertainty have been proposed. However, bootstrap-derived metrics are not independent of the underlying diffusion profile. A higher mean diffusivity causes a smaller signal-to-noise ratio and, thus, increases the measurement uncertainty. Moreover, the goodness of the tensor model, which relies strongly on the complexity of the underlying diffusion profile, influences bootstrap-derived metrics as well. The presented simulations clearly depict the cone of uncertainty as a function of the underlying diffusion profile. Since the relationship of the cone of uncertainty and common diffusion parameters, such as the mean diffusivity and the fractional anisotropy, is not linear, the cone of uncertainty has a different sensitivity. In vivo analysis of the fornix reveals the cone of uncertainty to be a predictor of memory function among older adults. No significant correlation occurs with the common diffusion parameters. The present work not only demonstrates the cone of uncertainty as a function of the actual diffusion profile, but also discloses the cone of uncertainty as a sensitive predictor of memory function. Future studies should incorporate bootstrap-derived metrics to provide more comprehensive analysis.

Impact of functional focal versus diffuse coronary artery disease on bypass graft patency.

PubMed

Shiono, Yasutsugu; Kubo, Takashi; Honda, Kentaro; Katayama, Yosuke; Aoki, Hiroshi; Satogami, Keisuke; Kashiyama, Kuninobu; Taruya, Akira; Nishiguchi, Tsuyoshi; Kuroi, Akio; Orii, Makoto; Kameyama, Takeyoshi; Yamano, Takashi; Yamaguchi, Tomoyuki; Matsuo, Yoshiki; Ino, Yasushi; Tanaka, Atsushi; Hozumi, Takeshi; Nishimura, Yoshiharu; Okamura, Yoshitaka; Akasaka, Takashi

2016-11-01

Pressure guidewire pullback recording can differentiate between functional focal and diffuse disease types in coronary artery disease. The aim of this study was to compare the outcome of coronary artery bypass graft (CABG) patency between patients with functional focal versus diffuse disease types in recipient coronary arteries. We investigated 89 patients who underwent pressure guidewire pullback in the left anterior descending (LAD) artery before CABG using internal mammary artery (IMA). Based on the pressure guidewire pullback data, the LAD lesions were classified into functional focal disease (abrupt pressure step-up; n=58) or functional diffuse disease (gradual pressure increase; n=31). Follow-up computed tomography (CT) angiography was conducted within 1year after CABG to assess the bypass graft patency. Pre CABG, LAD angiographic percent diameter stenosis (57±10% vs. 54±12%, p=0.228) and fractional flow reserve (FFR) (0.68±0.07 vs. 0.69±0.07, p=0.244) were not different between the functional focal and diffuse disease groups. The CABG procedure characteristics were similarly comparable between the two groups. In the follow-up CT angiography after CABG, occlusion or string sign of the IMA graft to LAD was more frequently observed in the functional diffuse disease group than in the functional focal disease group (26% vs. 7%, p=0.021). In CABG, functional diffuse disease in the recipient coronary artery was associated with an increased risk of the graft failure in comparison with functional focal disease. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Prognostic value of diffusion-weighted imaging summation scores or apparent diffusion coefficient maps in newborns with hypoxic-ischemic encephalopathy.

PubMed

Cavalleri, Francesca; Lugli, Licia; Pugliese, Marisa; D'Amico, Roberto; Todeschini, Alessandra; Della Casa, Elisa; Gallo, Claudio; Frassoldati, Rossella; Ferrari, Fabrizio

2014-09-01

The diagnostic and prognostic assessment of newborn infants with hypoxic-ischemic encephalopathy (HIE) comprises, among other tools, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps. To compare the ability of DWI and ADC maps in newborns with HIE to predict the neurodevelopmental outcome at 2 years of age. Thirty-four term newborns with HIE admitted to the Neonatal Intensive Care Unit of Modena University Hospital from 2004 to 2008 were consecutively enrolled in the study. All newborns received EEG, conventional MRI and DWI within the first week of life. DWI was analyzed by means of summation (S) score and regional ADC measurements. Neurodevelopmental outcome was assessed with a standard 1-4 scale and the Griffiths Mental Developmental Scales - Revised (GMDS-R). When the outcome was evaluated with a standard 1-4 scale, the DWI S scores showed very high area under the curve (AUC) (0.89) whereas regional ADC measurements in specific subregions had relatively modest predictive value. The lentiform nucleus was the region with the highest AUC (0.78). When GMDS-R were considered, DWI S scores were good to excellent predictors for some GMDS-R subscales. The predictive value of ADC measurements was both region- and subscale-specific. In particular, ADC measurements in some regions (basal ganglia, white matter or rolandic cortex) were excellent predictors for specific GMDS-R with AUCs up to 0.93. DWI S scores showed the highest prognostic value for the neurological outcome at 2 years of age. Regional ADC measurements in specific subregions proved to be highly prognostic for specific neurodevelopmental outcomes.

Characterization of Diffusion Metric Map Similarity in Data From a Clinical Data Repository Using Histogram Distances

PubMed Central

Warner, Graham C.; Helmer, Karl G.

2018-01-01

As the sharing of data is mandated by funding agencies and journals, reuse of data has become more prevalent. It becomes imperative, therefore, to develop methods to characterize the similarity of data. While users can group data based on the acquisition parameters stored in the file headers, these gives no indication whether a file can be combined with other data without increasing the variance in the data set. Methods have been implemented that characterize the signal-to-noise ratio or identify signal drop-outs in the raw image files, but potential users of data often have access to calculated metric maps and these are more difficult to characterize and compare. Here we describe a histogram-distance-based method applied to diffusion metric maps of fractional anisotropy and mean diffusivity that were generated using data extracted from a repository of clinically-acquired MRI data. We describe the generation of the data set, the pitfalls specific to diffusion MRI data, and the results of the histogram distance analysis. We find that, in general, data from GE scanners are less similar than are data from Siemens scanners. We also find that the distribution of distance metric values is not Gaussian at any selection of the acquisition parameters considered here (field strength, number of gradient directions, b-value, and vendor). PMID:29568257

Identification of early and distinct glioblastoma response patterns treated by boron neutron capture therapy not predicted by standard radiographic assessment using functional diffusion map

PubMed Central

2013-01-01

Background Radiologic response of brain tumors is traditionally assessed according to the Macdonald criteria 10 weeks from the start of therapy. Because glioblastoma (GB) responds in days rather than weeks after boron neutron capture therapy (BNCT) that is a form of tumor-selective particle radiation, it is inconvenient to use the Macdonald criteria to assess the therapeutic efficacy of BNCT by gadolinium-magnetic resonance imaging (Gd-MRI). Our study assessed the utility of functional diffusion map (fDM) for evaluating response patterns in GB treated by BNCT. Methods The fDM is an image assessment using time-dependent changes of apparent diffusion coefficient (ADC) in tumors on a voxel-by-voxel approach. Other than time-dependent changes of ADC, fDM can automatically assess minimum/maximum ADC, Response Evaluation Criteria In Solid Tumors (RECIST), and the volume of enhanced lesions on Gd-MRI over time. We assessed 17 GB patients treated by BNCT using fDM. Additionally, in order to verify our results, we performed a histopathological examination using F98 rat glioma models. Results Only the volume of tumor with decreased ADC by fDM at 2 days after BNCT was a good predictor for GB patients treated by BNCT (P value = 0.022 by log-rank test and 0.033 by wilcoxon test). In a histopathological examination, brain sections of F98 rat glioma models treated by BNCT showed cell swelling of both the nuclei and the cytoplasm compared with untreated rat glioma models. Conclusions The fDM could identify response patterns in BNCT-treated GB earlier than a standard radiographic assessment. Early detection of treatment failure can allow a change or supplementation before tumor progression and might lead to an improvement of GB patients’ prognosis. PMID:23915330

Fluid Registration of Diffusion Tensor Images Using Information Theory

PubMed Central

Chiang, Ming-Chang; Leow, Alex D.; Klunder, Andrea D.; Dutton, Rebecca A.; Barysheva, Marina; Rose, Stephen E.; McMahon, Katie L.; de Zubicaray, Greig I.; Toga, Arthur W.; Thompson, Paul M.

2008-01-01

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data. PMID:18390342

Self-diffusion in MgO--a density functional study.

PubMed

Runevall, Odd; Sandberg, Nils

2011-08-31

Density functional theory calculations have been performed to study self-diffusion in magnesium oxide, a model material for a wide range of ionic compounds. Formation energies and entropies of Schottky defects and divacancies were obtained by means of total energy and phonon calculations in supercell configurations. Transition state theory was used to estimate defect migration rates, with migration energies taken from static calculations, and the corresponding frequency factors estimated from the phonon spectrum. In all static calculations we corrected for image effects using either a multipole expansion or an extrapolation to the low concentration limit. It is shown that both methods give similar results. The results for self-diffusion of Mg and O confirm the previously established picture, namely that in materials of nominal purity, Mg diffuses extrinsically by a single vacancy mechanism, while O diffuses intrinsically by a divacancy mechanism. Quantitatively, the current results are in very good agreement with experiments concerning O diffusion, while for Mg the absolute diffusion rate is generally underestimated by a factor of 5-10. The reason for this discrepancy is discussed.

Minimalism through intraoperative functional mapping.

PubMed

Berger, M S

1996-01-01

Intraoperative stimulation mapping may be used to avoid unnecessary risk to functional regions subserving language and sensori-motor pathways. Based on the data presented here, language localization is variable in the entire population, with only certainty existing for the inferior frontal region responsible for motor speech. Anatomical landmarks such as the anterior temporal tip for temporal lobe language sites and the posterior aspect of the lateral sphenoid wing for the frontal lobe language zones are unreliable in avoiding postoperative aphasias. Thus, individual mapping to identify essential language sites has the greatest likelihood of avoiding permanent deficits in naming, reading, and motor speech. In a similar approach, motor and sensory pathways from the cortex and underlying white matter may be reliably stimulated and mapped in both awake and asleep patients. Although these techniques require an additional operative time and equipment nominally priced, the result is often gratifying, as postoperative morbidity has been greatly reduced in the process of incorporating these surgical strategies. The patients quality of life is improved in terms of seizure control, with or without antiepileptic drugs. This avoids having to perform a second costly operative procedure, which is routinely done when extraoperative stimulation and recording is done via subdural grids. In addition, an aggressive tumor resection at the initial operation lengthens the time to tumor recurrence and often obviates the need for a subsequent reoperation. Thus, intraoperative functional mapping may be best alluded to as a surgical technique that results in "minimalism in the long term".

Complementary aspects of diffusion imaging and fMRI; I: structure and function.

PubMed

Mulkern, Robert V; Davis, Peter E; Haker, Steven J; Estepar, Raul San Jose; Panych, Lawrence P; Maier, Stephan E; Rivkin, Michael J

2006-05-01

Studying the intersection of brain structure and function is an important aspect of modern neuroscience. The development of magnetic resonance imaging (MRI) over the last 25 years has provided new and powerful tools for the study of brain structure and function. Two tools in particular, diffusion imaging and functional MRI (fMRI), are playing increasingly important roles in elucidating the complementary aspects of brain structure and function. In this work, we review basic technical features of diffusion imaging and fMRI for studying the integrity of white matter structural components and for determining the location and extent of cortical activation in gray matter, respectively. We then review a growing body of literature in which the complementary aspects of diffusion imaging and fMRI, applied as separate examinations but analyzed in tandem, have been exploited to enhance our knowledge of brain structure and function.

Strain map of the tongue in normal and ALS speech patterns from tagged and diffusion MRI

NASA Astrophysics Data System (ADS)

Xing, Fangxu; Prince, Jerry L.; Stone, Maureen; Reese, Timothy G.; Atassi, Nazem; Wedeen, Van J.; El Fakhri, Georges; Woo, Jonghye

2018-03-01

Amyotrophic Lateral Sclerosis (ALS) is a neurological disease that causes death of neurons controlling muscle movements. Loss of speech and swallowing functions is a major impact due to degeneration of the tongue muscles. In speech studies using magnetic resonance (MR) techniques, diffusion tensor imaging (DTI) is used to capture internal tongue muscle fiber structures in three-dimensions (3D) in a non-invasive manner. Tagged magnetic resonance images (tMRI) are used to record tongue motion during speech. In this work, we aim to combine information obtained with both MR imaging techniques to compare the functionality characteristics of the tongue between normal and ALS subjects. We first extracted 3D motion of the tongue using tMRI from fourteen normal subjects in speech. The estimated motion sequences were then warped using diffeomorphic registration into the b0 spaces of the DTI data of two normal subjects and an ALS patient. We then constructed motion atlases by averaging all warped motion fields in each b0 space, and computed strain in the line of action along the muscle fiber directions provided by tractography. Strain in line with the fiber directions provides a quantitative map of the potential active region of the tongue during speech. Comparison between normal and ALS subjects explores the changing volume of compressing tongue tissues in speech facing the situation of muscle degradation. The proposed framework provides for the first time a dynamic map of contracting fibers in ALS speech patterns, and has the potential to provide more insight into the detrimental effects of ALS on speech.

Strain Map of the Tongue in Normal and ALS Speech Patterns from Tagged and Diffusion MRI.

PubMed

Xing, Fangxu; Prince, Jerry L; Stone, Maureen; Reese, Timothy G; Atassi, Nazem; Wedeen, Van J; El Fakhri, Georges; Woo, Jonghye

2018-02-01

Amyotrophic Lateral Sclerosis (ALS) is a neurological disease that causes death of neurons controlling muscle movements. Loss of speech and swallowing functions is a major impact due to degeneration of the tongue muscles. In speech studies using magnetic resonance (MR) techniques, diffusion tensor imaging (DTI) is used to capture internal tongue muscle fiber structures in three-dimensions (3D) in a non-invasive manner. Tagged magnetic resonance images (tMRI) are used to record tongue motion during speech. In this work, we aim to combine information obtained with both MR imaging techniques to compare the functionality characteristics of the tongue between normal and ALS subjects. We first extracted 3D motion of the tongue using tMRI from fourteen normal subjects in speech. The estimated motion sequences were then warped using diffeomorphic registration into the b0 spaces of the DTI data of two normal subjects and an ALS patient. We then constructed motion atlases by averaging all warped motion fields in each b0 space, and computed strain in the line of action along the muscle fiber directions provided by tractography. Strain in line with the fiber directions provides a quantitative map of the potential active region of the tongue during speech. Comparison between normal and ALS subjects explores the changing volume of compressing tongue tissues in speech facing the situation of muscle degradation. The proposed framework provides for the first time a dynamic map of contracting fibers in ALS speech patterns, and has the potential to provide more insight into the detrimental effects of ALS on speech.

Mapping specific soil functions based on digital soil property maps

NASA Astrophysics Data System (ADS)

Pásztor, László; Fodor, Nándor; Farkas-Iványi, Kinga; Szabó, József; Bakacsi, Zsófia; Koós, Sándor

2016-04-01

Quantification of soil functions and services is a great challenge in itself even if the spatial relevance is supposed to be identified and regionalized. Proxies and indicators are widely used in ecosystem service mapping. Soil services could also be approximated by elementary soil features. One solution is the association of soil types with services as basic principle. Soil property maps however provide quantified spatial information, which could be utilized more versatilely for the spatial inference of soil functions and services. In the frame of the activities referred as "Digital, Optimized, Soil Related Maps and Information in Hungary" (DOSoReMI.hu) numerous soil property maps have been compiled so far with proper DSM techniques partly according to GSM.net specifications, partly by slightly or more strictly changing some of its predefined parameters (depth intervals, pixel size, property etc.). The elaborated maps have been further utilized, since even DOSoReMI.hu was intended to take steps toward the regionalization of higher level soil information (secondary properties, functions, services). In the meantime the recently started AGRAGIS project requested spatial soil related information in order to estimate agri-environmental related impacts of climate change and support the associated vulnerability assessment. One of the most vulnerable services of soils in the context of climate change is their provisioning service. In our work it was approximated by productivity, which was estimated by a sequential scenario based crop modelling. It took into consideration long term (50 years) time series of both measured and predicted climatic parameters as well as accounted for the potential differences in agricultural practice and crop production. The flexible parametrization and multiple results of modelling was then applied for the spatial assessment of sensitivity, vulnerability, exposure and adaptive capacity of soils in the context of the forecasted changes in

High-Resolution Sequence-Function Mapping of Full-Length Proteins

PubMed Central

Kowalsky, Caitlin A.; Klesmith, Justin R.; Stapleton, James A.; Kelly, Vince; Reichkitzer, Nolan; Whitehead, Timothy A.

2015-01-01

Comprehensive sequence-function mapping involves detailing the fitness contribution of every possible single mutation to a gene by comparing the abundance of each library variant before and after selection for the phenotype of interest. Deep sequencing of library DNA allows frequency reconstruction for tens of thousands of variants in a single experiment, yet short read lengths of current sequencers makes it challenging to probe genes encoding full-length proteins. Here we extend the scope of sequence-function maps to entire protein sequences with a modular, universal sequence tiling method. We demonstrate the approach with both growth-based selections and FACS screening, offer parameters and best practices that simplify design of experiments, and present analytical solutions to normalize data across independent selections. Using this protocol, sequence-function maps covering full sequences can be obtained in four to six weeks. Best practices introduced in this manuscript are fully compatible with, and complementary to, other recently published sequence-function mapping protocols. PMID:25790064

Quiet echo planar imaging for functional and diffusion MRI

PubMed Central

Price, Anthony N.; Cordero‐Grande, Lucilio; Malik, Shaihan; Ferrazzi, Giulio; Gaspar, Andreia; Hughes, Emer J.; Christiaens, Daan; McCabe, Laura; Schneider, Torben; Rutherford, Mary A.; Hajnal, Joseph V.

2017-01-01

Purpose To develop a purpose‐built quiet echo planar imaging capability for fetal functional and diffusion scans, for which acoustic considerations often compromise efficiency and resolution as well as angular/temporal coverage. Methods The gradient waveforms in multiband‐accelerated single‐shot echo planar imaging sequences have been redesigned to minimize spectral content. This includes a sinusoidal read‐out with a single fundamental frequency, a constant phase encoding gradient, overlapping smoothed CAIPIRINHA blips, and a novel strategy to merge the crushers in diffusion MRI. These changes are then tuned in conjunction with the gradient system frequency response function. Results Maintained image quality, SNR, and quantitative diffusion values while reducing acoustic noise up to 12 dB (A) is illustrated in two adult experiments. Fetal experiments in 10 subjects covering a range of parameters depict the adaptability and increased efficiency of quiet echo planar imaging. Conclusion Purpose‐built for highly efficient multiband fetal echo planar imaging studies, the presented framework reduces acoustic noise for all echo planar imaging‐based sequences. Full optimization by tuning to the gradient frequency response functions allows for a maximally time‐efficient scan within safe limits. This allows ambitious in‐utero studies such as functional brain imaging with high spatial/temporal resolution and diffusion scans with high angular/spatial resolution to be run in a highly efficient manner at acceptable sound levels. Magn Reson Med 79:1447–1459, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:28653363

Intraoperative Functional Mapping and Monitoring during Glioma Surgery

PubMed Central

SAITO, Taiichi; MURAGAKI, Yoshihiro; MARUYAMA, Takashi; TAMURA, Manabu; NITTA, Masayuki; OKADA, Yoshikazu

2015-01-01

Glioma surgery represents a significant advance with respect to improving resection rates using new surgical techniques, including intraoperative functional mapping, monitoring, and imaging. Functional mapping under awake craniotomy can be used to detect individual eloquent tissues of speech and/or motor functions in order to prevent unexpected deficits and promote extensive resection. In addition, monitoring the patient’s neurological findings during resection is also very useful for maximizing the removal rate and minimizing deficits by alarming that the touched area is close to eloquent regions and fibers. Assessing several types of evoked potentials, including motor evoked potentials (MEPs), sensory evoked potentials (SEPs) and visual evoked potentials (VEPs), is also helpful for performing surgical monitoring in patients under general anesthesia (GA). We herein review the utility of intraoperative mapping and monitoring the assessment of neurological findings, with a particular focus on speech and the motor function, in patients undergoing glioma surgery. PMID:25744346

Road Map For Diffusion Of Innovation In Health Care.

PubMed

Balas, E Andrew; Chapman, Wendy W

2018-02-01

New scientific knowledge and innovation are often slow to disseminate. In other cases, providers rush into adopting what appears to be a clinically relevant innovation, based on a single clinical trial. In reality, adopting innovations without appropriate translation and repeated testing of practical application is problematic. In this article we provide examples of clinical innovations (for example, tight glucose control in critically ill patients) that were adopted inappropriately and that caused what we term a malfunction. To address the issue of malfunctions, we review various examples and suggest frameworks for the diffusion of knowledge leading to the adoption of useful innovations. The resulting model is termed an integrated road map for coordinating knowledge transformation and innovation adoption. We make recommendations for the targeted development of practice change procedures, practice change assessment, structured descriptions of tested interventions, intelligent knowledge management technologies, and policy support for knowledge transformation, including further standardization to facilitate sharing among institutions.

Mapping carrier diffusion in single silicon core-shell nanowires with ultrafast optical microscopy.

PubMed

Seo, M A; Yoo, J; Dayeh, S A; Picraux, S T; Taylor, A J; Prasankumar, R P

2012-12-12

Recent success in the fabrication of axial and radial core-shell heterostructures, composed of one or more layers with different properties, on semiconductor nanowires (NWs) has enabled greater control of NW-based device operation for various applications. (1-3) However, further progress toward significant performance enhancements in a given application is hindered by the limited knowledge of carrier dynamics in these structures. In particular, the strong influence of interfaces between different layers in NWs on transport makes it especially important to understand carrier dynamics in these quasi-one-dimensional systems. Here, we use ultrafast optical microscopy (4) to directly examine carrier relaxation and diffusion in single silicon core-only and Si/SiO(2) core-shell NWs with high temporal and spatial resolution in a noncontact manner. This enables us to reveal strong coherent phonon oscillations and experimentally map electron and hole diffusion currents in individual semiconductor NWs for the first time.

Mapping immune cell infiltration using restricted diffusion MRI.

PubMed

Yeh, Fang-Cheng; Liu, Li; Hitchens, T Kevin; Wu, Yijen L

2017-02-01

Diffusion MRI provides a noninvasive way to assess tissue microstructure. Based on diffusion MRI, we propose a model-free method called restricted diffusion imaging (RDI) to quantify restricted diffusion and correlate it with cellularity. An analytical relation between q-space signals and the density of restricted spins was derived to quantify restricted diffusion. A phantom study was conducted to investigate the performance of RDI, and RDI was applied to an animal study to assess immune cell infiltration in myocardial tissues with ischemia-reperfusion injury. Our phantom study showed a correlation coefficient of 0.998 between cell density and the restricted diffusion quantified by RDI. The animal study also showed that the high-value regions in RDI matched well with the macrophage infiltration areas in the H&E stained slides. In comparison with diffusion tensor imaging (DTI), RDI exhibited its outperformance to detect macrophage infiltration and delineate inflammatory myocardium. RDI can be used to reveal cell density and detect immune cell infiltration. RDI exhibits better specificity than the diffusivity measurement derived from DTI. Magn Reson Med 77:603-612, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Mapping Prefrontal Cortex Functions in Human Infancy

ERIC Educational Resources Information Center

Grossmann, Tobias

2013-01-01

It has long been thought that the prefrontal cortex, as the seat of most higher brain functions, is functionally silent during most of infancy. This review highlights recent work concerned with the precise mapping (localization) of brain activation in human infants, providing evidence that prefrontal cortex exhibits functional activation much…

Sparse Solution of Fiber Orientation Distribution Function by Diffusion Decomposition

PubMed Central

Yeh, Fang-Cheng; Tseng, Wen-Yih Isaac

2013-01-01

Fiber orientation is the key information in diffusion tractography. Several deconvolution methods have been proposed to obtain fiber orientations by estimating a fiber orientation distribution function (ODF). However, the L 2 regularization used in deconvolution often leads to false fibers that compromise the specificity of the results. To address this problem, we propose a method called diffusion decomposition, which obtains a sparse solution of fiber ODF by decomposing the diffusion ODF obtained from q-ball imaging (QBI), diffusion spectrum imaging (DSI), or generalized q-sampling imaging (GQI). A simulation study, a phantom study, and an in-vivo study were conducted to examine the performance of diffusion decomposition. The simulation study showed that diffusion decomposition was more accurate than both constrained spherical deconvolution and ball-and-sticks model. The phantom study showed that the angular error of diffusion decomposition was significantly lower than those of constrained spherical deconvolution at 30° crossing and ball-and-sticks model at 60° crossing. The in-vivo study showed that diffusion decomposition can be applied to QBI, DSI, or GQI, and the resolved fiber orientations were consistent regardless of the diffusion sampling schemes and diffusion reconstruction methods. The performance of diffusion decomposition was further demonstrated by resolving crossing fibers on a 30-direction QBI dataset and a 40-direction DSI dataset. In conclusion, diffusion decomposition can improve angular resolution and resolve crossing fibers in datasets with low SNR and substantially reduced number of diffusion encoding directions. These advantages may be valuable for human connectome studies and clinical research. PMID:24146772

Measuring diffusion-relaxation correlation maps using non-uniform field gradients of single-sided NMR devices.

PubMed

Nogueira d'Eurydice, Marcel; Galvosas, Petrik

2014-11-01

Single-sided NMR systems are becoming a relevant tool in industry and laboratory environments due to their low cost, low maintenance and capacity to evaluate quantity and quality of hydrogen based materials. The performance of such devices has improved significantly over the last decade, providing increased field homogeneity, field strength and even controlled static field gradients. For a class of these devices, the configuration of the permanent magnets provides a linear variation of the magnetic field and can be used in diffusion measurements. However, magnet design depends directly on its application and, according to the purpose, the field homogeneity may significantly be compromised. This may prevent the determination of diffusion properties of fluids based on the natural inhomogeneity of the field using known techniques. This work introduces a new approach that extends the applicability of diffusion-editing CPMG experiments to NMR devices with highly inhomogeneous magnetic fields, which do not vary linearly in space. Herein, we propose a method to determine a custom diffusion kernel based on the gradient distribution, which can be seen as a signature of each NMR device. This new diffusion kernel is then utilised in the 2D inverse Laplace transform (2D ILT) in order to determine diffusion-relaxation correlation maps of homogeneous multi-phasic fluids. The experiments were performed using NMR MObile Lateral Explore (MOLE), which is a single-sided NMR device designed to maximise the volume at the sweet spot with enhanced depth penetration. Copyright © 2014 Elsevier Inc. All rights reserved.

Task-evoked brain functional magnetic susceptibility mapping by independent component analysis (χICA).

PubMed

Chen, Zikuan; Calhoun, Vince D

2016-03-01

Conventionally, independent component analysis (ICA) is performed on an fMRI magnitude dataset to analyze brain functional mapping (AICA). By solving the inverse problem of fMRI, we can reconstruct the brain magnetic susceptibility (χ) functional states. Upon the reconstructed χ dataspace, we propose an ICA-based brain functional χ mapping method (χICA) to extract task-evoked brain functional map. A complex division algorithm is applied to a timeseries of fMRI phase images to extract temporal phase changes (relative to an OFF-state snapshot). A computed inverse MRI (CIMRI) model is used to reconstruct a 4D brain χ response dataset. χICA is implemented by applying a spatial InfoMax ICA algorithm to the reconstructed 4D χ dataspace. With finger-tapping experiments on a 7T system, the χICA-extracted χ-depicted functional map is similar to the SPM-inferred functional χ map by a spatial correlation of 0.67 ± 0.05. In comparison, the AICA-extracted magnitude-depicted map is correlated with the SPM magnitude map by 0.81 ± 0.05. The understanding of the inferiority of χICA to AICA for task-evoked functional map is an ongoing research topic. For task-evoked brain functional mapping, we compare the data-driven ICA method with the task-correlated SPM method. In particular, we compare χICA with AICA for extracting task-correlated timecourses and functional maps. χICA can extract a χ-depicted task-evoked brain functional map from a reconstructed χ dataspace without the knowledge about brain hemodynamic responses. The χICA-extracted brain functional χ map reveals a bidirectional BOLD response pattern that is unavailable (or different) from AICA. Copyright © 2016 Elsevier B.V. All rights reserved.

Diffusion tensor optical coherence tomography

NASA Astrophysics Data System (ADS)

Marks, Daniel L.; Blackmon, Richard L.; Oldenburg, Amy L.

2018-01-01

In situ measurements of diffusive particle transport provide insight into tissue architecture, drug delivery, and cellular function. Analogous to diffusion-tensor magnetic resonance imaging (DT-MRI), where the anisotropic diffusion of water molecules is mapped on the millimeter scale to elucidate the fibrous structure of tissue, here we propose diffusion-tensor optical coherence tomography (DT-OCT) for measuring directional diffusivity and flow of optically scattering particles within tissue. Because DT-OCT is sensitive to the sub-resolution motion of Brownian particles as they are constrained by tissue macromolecules, it has the potential to quantify nanoporous anisotropic tissue structure at micrometer resolution as relevant to extracellular matrices, neurons, and capillaries. Here we derive the principles of DT-OCT, relating the detected optical signal from a minimum of six probe beams with the six unique diffusion tensor and three flow vector components. The optimal geometry of the probe beams is determined given a finite numerical aperture, and a high-speed hardware implementation is proposed. Finally, Monte Carlo simulations are employed to assess the ability of the proposed DT-OCT system to quantify anisotropic diffusion of nanoparticles in a collagen matrix, an extracellular constituent that is known to become highly aligned during tumor development.

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Asymmetric neighborhood functions accelerate ordering process of self-organizing maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ota, Kaiichiro; Aoki, Takaaki; Kurata, Koji

2011-02-15

A self-organizing map (SOM) algorithm can generate a topographic map from a high-dimensional stimulus space to a low-dimensional array of units. Because a topographic map preserves neighborhood relationships between the stimuli, the SOM can be applied to certain types of information processing such as data visualization. During the learning process, however, topological defects frequently emerge in the map. The presence of defects tends to drastically slow down the formation of a globally ordered topographic map. To remove such topological defects, it has been reported that an asymmetric neighborhood function is effective, but only in the simple case of mapping one-dimensionalmore » stimuli to a chain of units. In this paper, we demonstrate that even when high-dimensional stimuli are used, the asymmetric neighborhood function is effective for both artificial and real-world data. Our results suggest that applying the asymmetric neighborhood function to the SOM algorithm improves the reliability of the algorithm. In addition, it enables processing of complicated, high-dimensional data by using this algorithm.« less

Leading non-Gaussian corrections for diffusion orientation distribution function.

PubMed

Jensen, Jens H; Helpern, Joseph A; Tabesh, Ali

2014-02-01

An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed from the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves on the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common. 2013 John Wiley & Sons, Ltd.

Leading Non-Gaussian Corrections for Diffusion Orientation Distribution Function

PubMed Central

Jensen, Jens H.; Helpern, Joseph A.; Tabesh, Ali

2014-01-01

An analytical representation of the leading non-Gaussian corrections for a class of diffusion orientation distribution functions (dODFs) is presented. This formula is constructed out of the diffusion and diffusional kurtosis tensors, both of which may be estimated with diffusional kurtosis imaging (DKI). By incorporating model-independent non-Gaussian diffusion effects, it improves upon the Gaussian approximation used in diffusion tensor imaging (DTI). This analytical representation therefore provides a natural foundation for DKI-based white matter fiber tractography, which has potential advantages over conventional DTI-based fiber tractography in generating more accurate predictions for the orientations of fiber bundles and in being able to directly resolve intra-voxel fiber crossings. The formula is illustrated with numerical simulations for a two-compartment model of fiber crossings and for human brain data. These results indicate that the inclusion of the leading non-Gaussian corrections can significantly affect fiber tractography in white matter regions, such as the centrum semiovale, where fiber crossings are common. PMID:24738143

Geomorphic control of radionuclide diffusion in desert soils

USGS Publications Warehouse

Pelletier, J.D.; Harrington, C.D.; Whitney, J.W.; Cline, M.; DeLong, S.B.; Keating, G.; Ebert, T.K.

2005-01-01

Diffusion is a standard model for the vertical migration of radionuclides in soil profiles. Here we show that diffusivity values inferred from fallout 137CS profiles in soils on the Fortymile Wash alluvial fan, Nye County, Nevada, have a strong inverse correlation with the age of the geomorphic surface. This result suggests that radionuclide-bound particles are predominantly transported by infiltration rather than by bulk-mixing processes such as wetting/ drying, freeze/thaw, and bioturbation. Our results provide a preliminary basis for using soil-geomorphic mapping, point-based calibration data, and the diffusion model to predict radionuclide trans desert soils within a pedotransfer-function approach. Copyright 2005 by the American Geophysical Union.

Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.

PubMed

Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D

2013-05-30

The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.

Rotation and diffusion of naphthalene on Pt(111)

NASA Astrophysics Data System (ADS)

Kolsbjerg, E. L.; Goubert, G.; McBreen, P. H.; Hammer, B.

2018-03-01

The behavior of naphthalene on Pt(111) surfaces is studied by combining insight from scanning tunneling microscopy (STM) and van der Waals enabled density functional theory. Adsorption, diffusion, and rotation are investigated by a series of variable temperature STM experiments revealing naphthalene ability to rotate on-site with ease with a rotational barrier of 0.69 eV. Diffusion to neighbouring sites is found to be more difficult. The experimental results are in good agreement with the theoretical investigations which confirm that the barrier for diffusion is slightly higher than the one for rotation. The theoretical barriers for rotation and translation are found to be 0.75 and 0.78 eV, respectively. An automatic mapping of the possible diffusion pathways reveals very detailed diffusion paths with many small local minima that would have been practically impossible to find manually. This automated procedure provides detailed insight into the preferred diffusion pathways that are important for our understanding of molecule-substrate interactions.

A global interaction network maps a wiring diagram of cellular function

PubMed Central

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

The Halo mass function from Excursion Set Theory. II. The Diffusing Barrier

NASA Astrophysics Data System (ADS)

Maggiore, Michele; Riotto, Antonio

2010-07-01

In excursion set theory, the computation of the halo mass function is mapped into a first-passage time process in the presence of a barrier, which in the spherical collapse model is a constant and in the ellipsoidal collapse model is a fixed function of the variance of the smoothed density field. However, N-body simulations show that dark matter halos grow through a mixture of smooth accretion, violent encounters, and fragmentations, and modeling halo collapse as spherical, or even as ellipsoidal, is a significant oversimplification. In addition, the very definition of what is a dark matter halo, both in N-body simulations and observationally, is a difficult problem. We propose that some of the physical complications inherent to a realistic description of halo formation can be included in the excursion set theory framework, at least at an effective level, by taking into account that the critical value for collapse is not a fixed constant δ c , as in the spherical collapse model, nor a fixed function of the variance σ of the smoothed density field, as in the ellipsoidal collapse model, but rather is itself a stochastic variable, whose scatter reflects a number of complicated aspects of the underlying dynamics. Solving the first-passage time problem in the presence of a diffusing barrier we find that the exponential factor in the Press-Schechter mass function changes from exp{-δ2 c /2σ2} to exp{-aδ2 c /2σ2}, where a = 1/(1 + DB ) and DB is the diffusion coefficient of the barrier. The numerical value of DB , and therefore the corresponding value of a, depends among other things on the algorithm used for identifying halos. We discuss the physical origin of the stochasticity of the barrier and, from recent N-body simulations that studied the properties of the collapse barrier, we deduce a value DB ~= 0.25. Our model then predicts a ~= 0.80, in excellent agreement with the exponential fall off of the mass function found in N-body simulations, for the same halo

Density probability distribution functions of diffuse gas in the Milky Way

NASA Astrophysics Data System (ADS)

Berkhuijsen, E. M.; Fletcher, A.

2008-10-01

In a search for the signature of turbulence in the diffuse interstellar medium (ISM) in gas density distributions, we determined the probability distribution functions (PDFs) of the average volume densities of the diffuse gas. The densities were derived from dispersion measures and HI column densities towards pulsars and stars at known distances. The PDFs of the average densities of the diffuse ionized gas (DIG) and the diffuse atomic gas are close to lognormal, especially when lines of sight at |b| < 5° and |b| >= 5° are considered separately. The PDF of at high |b| is twice as wide as that at low |b|. The width of the PDF of the DIG is about 30 per cent smaller than that of the warm HI at the same latitudes. The results reported here provide strong support for the existence of a lognormal density PDF in the diffuse ISM, consistent with a turbulent origin of density structure in the diffuse gas.

Linking late cognitive outcome with glioma surgery location using resection cavity maps.

PubMed

Hendriks, Eef J; Habets, Esther J J; Taphoorn, Martin J B; Douw, Linda; Zwinderman, Aeilko H; Vandertop, W Peter; Barkhof, Frederik; Klein, Martin; De Witt Hamer, Philip C

2018-05-01

Patients with a diffuse glioma may experience cognitive decline or improvement upon resective surgery. To examine the impact of glioma location, cognitive alteration after glioma surgery was quantified and related to voxel-based resection probability maps. A total of 59 consecutive patients (range 18-67 years of age) who had resective surgery between 2006 and 2011 for a supratentorial nonenhancing diffuse glioma (grade I-III, WHO 2007) were included in this observational cohort study. Standardized neuropsychological examination and MRI were obtained before and after surgery. Intraoperative stimulation mapping guided resections towards neurological functions (language, sensorimotor function, and visual fields). Maps of resected regions were constructed in standard space. These resection cavity maps were compared between patients with and without new cognitive deficits (z-score difference >1.5 SD between baseline and one year after resection), using a voxel-wise randomization test and calculation of false discovery rates. Brain regions significantly associated with cognitive decline were classified in standard cortical and subcortical anatomy. Cognitive improvement in any domain occurred in 10 (17%) patients, cognitive decline in any domain in 25 (42%), and decline in more than one domain in 10 (17%). The most frequently affected subdomains were attention in 10 (17%) patients and information processing speed in 9 (15%). Resection regions associated with decline in more than one domain were predominantly located in the right hemisphere. For attention decline, no specific region could be identified. For decline in information speed, several regions were found, including the frontal pole and the corpus callosum. Cognitive decline after resective surgery of diffuse glioma is prevalent, in particular, in patients with a tumor located in the right hemisphere without cognitive function mapping. © The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

VMF3/GPT3: refined discrete and empirical troposphere mapping functions

NASA Astrophysics Data System (ADS)

Landskron, Daniel; Böhm, Johannes

2018-04-01

Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of 3°. Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a 5°× 5° as well as a 1°× 1° global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.

CortiQ-based Real-Time Functional Mapping for Epilepsy Surgery.

PubMed

Kapeller, Christoph; Korostenskaja, Milena; Prueckl, Robert; Chen, Po-Ching; Lee, Ki Heyeong; Westerveld, Michael; Salinas, Christine M; Cook, Jane C; Baumgartner, James E; Guger, Christoph

2015-06-01

To evaluate the use of the cortiQ-based mapping system (g.tec medication engineering GmbH, Austria) for real-time functional mapping (RTFM) and to compare it to results from electrical cortical stimulation mapping (ESM) and functional magnetic resonance imaging (fMRI). Electrocorticographic activity was recorded in 3 male patients with intractable epilepsy by using cortiQ mapping system and analyzed in real time. Activation related to motor, sensory, and receptive language tasks was determined by evaluating the power of the high gamma frequency band (60-170 Hz). The sensitivity and specificity of RTFM were tested against ESM and fMRI results. "Next-neighbor" approach demonstrated [sensitivity/specificity %] (1) RTFM against ESM: 100.00/79.70 for hand motor; 100.00/73.87 for hand sensory; -/87 for language (it was not identified by the ESM); (2) RTFM against fMRI: 100.00/84.4 for hand motor; 66.70/85.35 for hand sensory; and 87.85/77.70 for language. The results of the quantitative "next-neighbor" RTFM evaluation were concordant to those from ESM and fMRI. The RTFM correlates well with localization of hand motor function provided by ESM and fMRI, which may offer added localization in the operating room and guidance for extraoperative ESM mapping. Real-time functional mapping correlates with fMRI language activation when ESM findings are negative. It has fewer limitations than ESM and greater flexibility in activation paradigms and measuring responses.

Causal electric charge diffusion and balance functions in relativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Kapusta, Joseph I.; Plumberg, Christopher

2018-01-01

We study the propagation and diffusion of electric charge fluctuations in high-energy heavy-ion collisions using the Cattaneo form for the dissipative part of the electric current. As opposed to the ordinary diffusion equation this form limits the speed at which charge can propagate. Including the noise term in the current, which arises uniquely from the fluctuation-dissipation theorem, we calculate the balance functions for charged hadrons in a simple 1+1-dimensional Bjorken hydrodynamical model. Limiting the speed of propagation of charge fluctuations increases the height and reduces the width of these balance functions when plotted versus rapidity. We also estimate the numerical value of the associated diffusion time constant from anti-de Sitter-space/conformal-field theory.

Dynamic physiological modeling for functional diffuse optical tomography

PubMed Central

Diamond, Solomon Gilbert; Huppert, Theodore J.; Kolehmainen, Ville; Franceschini, Maria Angela; Kaipio, Jari P.; Arridge, Simon R.; Boas, David A.

2009-01-01

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis. PMID:16242967

Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.

PubMed

Chen, Minghan; Li, Fei; Wang, Shuo; Cao, Young

2017-03-14

Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. In this paper, we demonstrate that in the 1D domain, highly nonlinear reaction dynamics given by Hill function may also have dramatic change when discretization size is smaller than a critical value. Moreover, we discuss methods to avoid this problem: smoothing over space, fixed length smoothing over space and a hybrid method. Our analysis reveals that the switch-like Hill dynamics reduces to a linear function of discretization size when the discretization size is small enough. The three proposed methods could correctly (under certain precision) simulate Hill function dynamics in the microscopic RDME system.

ZEEMAN DOPPLER MAPS: ALWAYS UNIQUE, NEVER SPURIOUS?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stift, Martin J.; Leone, Francesco

Numerical models of atomic diffusion in magnetic atmospheres of ApBp stars predict abundance structures that differ from the empirical maps derived with (Zeeman) Doppler mapping (ZDM). An in-depth analysis of this apparent disagreement investigates the detectability by means of ZDM of a variety of abundance structures, including (warped) rings predicted by theory, but also complex spot-like structures. Even when spectra of high signal-to-noise ratio are available, it can prove difficult or altogether impossible to correctly recover shapes, positions, and abundances of a mere handful of spots, notwithstanding the use of all four Stokes parameters and an exactly known field geometry;more » the recovery of (warped) rings can be equally challenging. Inversions of complex abundance maps that are based on just one or two spectral lines usually permit multiple solutions. It turns out that it can by no means be guaranteed that any of the regularization functions in general use for ZDM (maximum entropy or Tikhonov) will lead to a true abundance map instead of some spurious one. Attention is drawn to the need for a study that would elucidate the relation between the stratified, field-dependent abundance structures predicted by diffusion theory on the one hand, and empirical maps obtained by means of “canonical” ZDM, i.e., with mean atmospheres and unstratified abundances, on the other hand. Finally, we point out difficulties arising from the three-dimensional nature of the atomic diffusion process in magnetic ApBp star atmospheres.« less

Multi-Sensor Mapping of Diffuse Degassing of C-O-H Compounds in Terrestrial Hydrothermal Systems

NASA Astrophysics Data System (ADS)

Schwandner, F. M.; Shock, E. L.

2004-12-01

In-situ single-sensor detection and mapping of diffuse degassing phenomena in hydrothermal and volcanic areas can be used to elucidate subsurface tectonic structures, assess emission rates, and to monitor emission variability (Williams 1985; Chiodini et al. 1996, Werner et al., 2003). More than one technique has been deployed to measure several gas species simultaneously (e.g., Crenshaw et al. 1982), and correlations of one gas species (usually CO2) with physical parameters like heat flux (Brombach et al., 2001), or with one other gas species (Rn, He) have been demonstrated (Barberi & Carapezza 1994; Williams-Jones et al., 2000). Recently, correlations of multiple gas species with one another were reported (Schwandner et al., 2004), leading to the possibility of quantitative mapping of subsurface hydrothermal chemical processes by simultaneous measurement of reaction partners and products that continuously and diffusely degas. In the present study, we joined a fully-quantitative multi-sensor instrument (Draeger Multiwarn II) to a modified accumulation-chamber sensing method (Chiodini et al., 1996) and measured diffuse degassing of CH4, H2, CO2, CO, and H2S. In this approach, each batch of gas that is recirculated through the detector is simultaneously analyzed by all sensors. To test this approach we chose two magmatically influenced, hydrothermally active areas at Yellowstone National Park (USA): Sylvan Springs and the Greater Obsidian Pool Area. The area near Obsidian Pool was previously studied during a diffuse CO2 degassing campaign (Werner & Brantley, 2004). Preliminary results show that elevated reduced gas emissions appear to be most prominent near hydrothermal pools, whereas CO2-dominated degassing anomalies highlight subsurface tectonic structures. This multimodal distribution allows us to distinguish deep degassing sources (CO2 anomalies) from shallow localized hydrothermal processes (reduced gas anomalies). The results permit us to positively identify

Changes in diffusion path length with old age in diffuse optical tomography

NASA Astrophysics Data System (ADS)

Bonnéry, Clément; Leclerc, Paul-Olivier; Desjardins, Michèle; Hoge, Rick; Bherer, Louis; Pouliot, Philippe; Lesage, Frédéric

2012-05-01

Diffuse, optical near infrared imaging is increasingly being used in various neurocognitive contexts where changes in optical signals are interpreted through activation maps. Statistical population comparison of different age or clinical groups rely on the relative homogeneous distribution of measurements across subjects in order to infer changes in brain function. In the context of an increasing use of diffuse optical imaging with older adult populations, changes in tissue properties and anatomy with age adds additional confounds. Few studies investigated these changes with age. Duncan et al. measured the so-called diffusion path length factor (DPF) in a large population but did not explore beyond the age of 51 after which physiological and anatomical changes are expected to occur [Pediatr. Res. 39(5), 889-894 (1996)]. With increasing interest in studying the geriatric population with optical imaging, we studied changes in tissue properties in young and old subjects using both magnetic resonance imaging (MRI)-guided Monte-Carlo simulations and time-domain diffuse optical imaging. Our results, measured in the frontal cortex, show changes in DPF that are smaller than previously measured by Duncan et al. in a younger population. The origin of these changes are studied using simulations and experimental measures.

Symplectic Propagation of the Map, Tangent Map and Tangent Map Derivative through Quadrupole and Combined-Function Dipole Magnets without Truncation

NASA Astrophysics Data System (ADS)

Bruhwiler, D. L.; Cary, J. R.; Shasharina, S.

1998-04-01

The MAPA accelerator modeling code symplectically advances the full nonlinear map, tangent map and tangent map derivative through all accelerator elements. The tangent map and its derivative are nonlinear generalizations of Browns first- and second-order matrices(K. Brown, SLAC-75, Rev. 4 (1982), pp. 107-118.), and they are valid even near the edges of the dynamic aperture, which may be beyond the radius of convergence for a truncated Taylor series. In order to avoid truncation of the map and its derivatives, the Hamiltonian is split into pieces for which the map can be obtained analytically. Yoshidas method(H. Yoshida, Phys. Lett. A 150 (1990), pp. 262-268.) is then used to obtain a symplectic approximation to the map, while the tangent map and its derivative are appropriately composed at each step to obtain them with equal accuracy. We discuss our splitting of the quadrupole and combined-function dipole Hamiltonians and show that typically few steps are required for a high-energy accelerator.

Thalamic diffusion differences related to cognitive function in white matter lesions.

PubMed

Fernández-Andújar, Marina; Soriano-Raya, Juan José; Miralbell, Júlia; López-Cancio, Elena; Cáceres, Cynthia; Bargalló, Núria; Barrios, Maite; Arenillas, Juan Francisco; Toran, Pere; Alzamora, Maite; Clemente, Imma; Dávalos, Antoni; Mataró, Maria

2014-05-01

Cerebral white matter lesions (WMLs) are related to cognitive deficits, probably due to a disruption of frontal-subcortical circuits. We explored thalamic diffusion differences related to white matter lesions (WMLs) and their association with cognitive function in middle-aged individuals. Ninety-six participants from the Barcelona-AsIA Neuropsychology Study were included. Participants were classified into groups based on low grade and high grade of periventricular hyperintensities (PVHs) and deep white matter hyperintensities (DWMHs). Tract-Based Spatial Statistics was used to study thalamic diffusion differences between groups. Mean fractional anisotropy (FA) values in significant areas were calculated for each subject and correlated with cognitive performance. Participants with high-grade PVHs and DWMHs showed lower FA thalamic values compared to those with low-grade PVHs and DWMHs, respectively. Decreased FA thalamic values in high-grade DWMHs, but not high-grade PVH, were related to lower levels of performance in psychomotor speed, verbal fluency, and visuospatial skills. Thalamic diffusion differences are related to lower cognitive function only in participants with high-grade DWMHs. These results support the hypothesis that fronto-subcortical disruption is associated with cognitive function only in DWMHs. Copyright © 2014 Elsevier Inc. All rights reserved.

Characterizing the structure of diffuse emission in Hi-GAL maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elia, D.; Molinari, S.; Rygl, K. L. J.

We present a study of the structure of the Galactic interstellar medium (ISM) through the Δ-variance technique, related to the power spectrum and the fractal properties of infrared/submillimeter maps. Through this method, it is possible to provide quantitative parameters, which are useful for characterizing different morphological and physical conditions, and better constraining the theoretical models. In this respect, the Herschel Infrared Galactic Plane Survey, carried out at five photometric bands from 70 to 500 μm, constitutes a unique database for applying statistical tools to a variety of regions across the Milky Way. In this paper, we derive a robust estimatemore » of the power-law portion of the power spectrum of four contiguous 2° × 2° Hi-GAL tiles located in the third Galactic quadrant (217° ≲ ℓ ≲ 225°, –2° ≲ b ≲ 0°). The low level of confusion along the line of sight, testified by CO observations, makes this region an ideal case. We find very different values for the power spectrum slope from tile to tile but also from wavelength to wavelength (2 ≲ β ≲ 3), with similarities between fields attributable to components located at the same distance. Thanks to comparisons with models of turbulence, an explanation of the determined slopes in terms of the fractal geometry is also provided, and possible relations with the underlying physics are investigated. In particular, an anti-correlation between ISM fractal dimension and star formation efficiency is found for the two main distance components observed in these fields. A possible link between the fractal properties of the diffuse emission and the resulting clump mass function is discussed.« less

Diffusion kurtosis imaging of the liver at 3 Tesla: in vivo comparison to standard diffusion-weighted imaging.

PubMed

Budjan, Johannes; Sauter, Elke A; Zoellner, Frank G; Lemke, Andreas; Wambsganss, Jens; Schoenberg, Stefan O; Attenberger, Ulrike I

2018-01-01

Background Functional techniques like diffusion-weighted imaging (DWI) are gaining more and more importance in liver magnetic resonance imaging (MRI). Diffusion kurtosis imaging (DKI) is an advanced technique that might help to overcome current limitations of DWI. Purpose To evaluate DKI for the differentiation of hepatic lesions in comparison to conventional DWI at 3 Tesla. Material and Methods Fifty-six consecutive patients were examined using a routine abdominal MR protocol at 3 Tesla which included DWI with b-values of 50, 400, 800, and 1000 s/mm 2 . Apparent diffusion coefficient maps were calculated applying a standard mono-exponential fit, while a non-Gaussian kurtosis fit was used to obtain DKI maps. ADC as well as Kurtosis-corrected diffusion ( D) values were quantified by region of interest analysis and compared between lesions. Results Sixty-eight hepatic lesions (hepatocellular carcinoma [HCC] [n = 25]; hepatic adenoma [n = 4], cysts [n = 18]; hepatic hemangioma [HH] [n = 18]; and focal nodular hyperplasia [n = 3]) were identified. Differentiation of malignant and benign lesions was possible based on both DWI ADC as well as DKI D-values ( P values were in the range of 0.04 to < 0.0001). Conclusion In vivo abdominal DKI calculated using standard b-values is feasible and enables quantitative differentiation between malignant and benign liver lesions. Assessment of conventional ADC values leads to similar results when using b-values below 1000 s/mm 2 for DKI calculation.

Assessment of tropospheric delay mapping function models in Egypt: Using PTD database model

NASA Astrophysics Data System (ADS)

Abdelfatah, M. A.; Mousa, Ashraf E.; El-Fiky, Gamal S.

2018-06-01

For space geodetic measurements, estimates of tropospheric delays are highly correlated with site coordinates and receiver clock biases. Thus, it is important to use the most accurate models for the tropospheric delay to reduce errors in the estimates of the other parameters. Both the zenith delay value and mapping function should be assigned correctly to reduce such errors. Several mapping function models can treat the troposphere slant delay. The recent models were not evaluated for the Egyptian local climate conditions. An assessment of these models is needed to choose the most suitable one. The goal of this paper is to test the quality of global mapping function which provides high consistency with precise troposphere delay (PTD) mapping functions. The PTD model is derived from radiosonde data using ray tracing, which consider in this paper as true value. The PTD mapping functions were compared, with three recent total mapping functions model and another three separate dry and wet mapping function model. The results of the research indicate that models are very close up to zenith angle 80°. Saastamoinen and 1/cos z model are behind accuracy. Niell model is better than VMF model. The model of Black and Eisner is a good model. The results also indicate that the geometric range error has insignificant effect on slant delay and the fluctuation of azimuth anti-symmetric is about 1%.

Oxygen vacancy diffusion in bulk SrTiO3 from density functional theory calculations

DOE PAGES

Zhang, Lipeng; Liu, Bin; Zhuang, Houlong; ...

2016-04-01

Point defects and point defect diffusion contribute significantly to the properties of perovskite materials. However, even for the prototypical case of oxygen vacancies in SrTiO 3 (STO), predictions vary widely. Here we present a comprehensive and systematic study of the diffusion barriers for this material. We use density functional theory (DFT) and assess the role of different cell sizes, density functionals, and charge states. Our results show that vacancy-induced octahedral rotations, which are limited by the boundary conditions of the supercell, can significantly affect the computed oxygen vacancy diffusion energy barrier. The diffusion energy barrier of a charged oxygen vacancymore » is lower than that of a neutral one. Unexpectedly, we find that with increasing supercell size, the effects of the oxygen vacancy charge state, the type of DFT exchange and correlation functional on the energy barrier diminish, and the different DFT predictions asymptote to a value in the range of 0.39-0.49 eV. This work provides important insight and guidance that should be considered for investigations of point defect diffusion in other perovskite materials and in oxide superlattices.« less

Variable-order fractional MSD function to describe the evolution of protein lateral diffusion ability in cell membranes

NASA Astrophysics Data System (ADS)

Yin, Deshun; Qu, Pengfei

2018-02-01

Protein lateral diffusion is considered anomalous in the plasma membrane. And this diffusion is related to membrane microstructure. In order to better describe the property of protein lateral diffusion and find out the inner relationship between protein lateral diffusion and membrane microstructure, this article applies variable-order fractional mean square displacement (f-MSD) function for characterizing the anomalous diffusion. It is found that the variable order can reflect the evolution of diffusion ability. The results of numerical simulation demonstrate variable-order f-MSD function can predict the tendency of anomalous diffusion during the process of confined diffusion. It is also noted that protein lateral diffusion ability during the processes of confined and hop diffusion can be split into three parts. In addition, the comparative analyses reveal that the variable order is related to the confinement-domain size and microstructure of compartment boundary too.

Pre-seizure state identified by diffuse optical tomography

PubMed Central

Zhang, Tao; Zhou, Junli; Jiang, Ruixin; Yang, Hao; Carney, Paul R.; Jiang, Huabei

2014-01-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Here we demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking such brain activities with high spatiotemporal resolution. We detected early hemodynamic responses with heterogeneous patterns, along with intracranial electroencephalogram gamma power changes, several minutes preceding the electroencephalographic seizure onset, supporting the presence of a “pre-seizure” state. We also observed the decoupling between local hemodynamic and neural activities. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways. PMID:24445927

Resolving power for the diffusion orientation distribution function.

PubMed

Jensen, Jens H; Helpern, Joseph A

2016-08-01

The diffusion orientation distribution function (dODF) is primarily used for white matter fiber tractography. Here the resolving power of the dODF is investigated for a simple diffusion model of two intersecting axonal fiber bundles. The resolving power for the dODF is evaluated using the Sparrow criterion. This is determined for the exact dODF and also for q-space imaging (QSI), q-ball, and kurtosis approximations. Based on theoretical and numerical calculations, the resolving power is found to depend on the eigenvalues of the diffusion model and on the degree of radial weighting for the dODF. The resolving powers of the QSI and q-ball dODFs improve with increased b-value. The kurtosis dODF has a resolving power similar to that of the exact dODF. The dODFs, whether exact or approximate, have finite resolving powers that limit their sensitivity to fiber crossings. The resolving powers for the different dODFs considered here provide convenient benchmarks for assessing and comparing their performance. Magn Reson Med 76:679-688, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena.

PubMed

De Domenico, Manlio

2017-04-21

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Diffusion Geometry Unravels the Emergence of Functional Clusters in Collective Phenomena

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2017-04-01

Collective phenomena emerge from the interaction of natural or artificial units with a complex organization. The interplay between structural patterns and dynamics might induce functional clusters that, in general, are different from topological ones. In biological systems, like the human brain, the overall functionality is often favored by the interplay between connectivity and synchronization dynamics, with functional clusters that do not coincide with anatomical modules in most cases. In social, sociotechnical, and engineering systems, the quest for consensus favors the emergence of clusters. Despite the unquestionable evidence for mesoscale organization of many complex systems and the heterogeneity of their interconnectivity, a way to predict and identify the emergence of functional modules in collective phenomena continues to elude us. Here, we propose an approach based on random walk dynamics to define the diffusion distance between any pair of units in a networked system. Such a metric allows us to exploit the underlying diffusion geometry to provide a unifying framework for the intimate relationship between metastable synchronization, consensus, and random search dynamics in complex networks, pinpointing the functional mesoscale organization of synthetic and biological systems.

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.

PubMed

Bertleff, Marco; Domsch, Sebastian; Weingärtner, Sebastian; Zapp, Jascha; O'Brien, Kieran; Barth, Markus; Schad, Lothar R

2017-12-01

Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least-squares regression (LSR) and state-of-the-art multi-step fitting (LSR-MS) in Monte-Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR-MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo-diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR-MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR-MS, 19%; LSR, 8%), D* (ANN, 21%; LSR-MS, 25%; LSR, 23%) and K (ANN, 0%; LSR-MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR-MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state-of-the-art method LSR-MS with several advantages in the estimation of IVIM-kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times. Copyright © 2017 John Wiley & Sons, Ltd.

Comparing diffuse optical tomography and functional magnetic resonance imaging signals during a cognitive task: pilot study

PubMed Central

Hernández-Martin, Estefania; Marcano, Francisco; Casanova, Oscar; Modroño, Cristian; Plata-Bello, Julio; González-Mora, Jose Luis

2017-01-01

Abstract. Diffuse optical tomography (DOT) measures concentration changes in both oxy- and deoxyhemoglobin providing three-dimensional images of local brain activations. A pilot study, which compares both DOT and functional magnetic resonance imaging (fMRI) volumes through t-maps given by canonical statistical parametric mapping (SPM) processing for both data modalities, is presented. The DOT series were processed using a method that is based on a Bayesian filter application on raw DOT data to remove physiological changes and minimum description length application index to select a number of singular values, which reduce the data dimensionality during image reconstruction and adaptation of DOT volume series to normalized standard space. Therefore, statistical analysis is performed with canonical SPM software in the same way as fMRI analysis is done, accepting DOT volumes as if they were fMRI volumes. The results show the reproducibility and ruggedness of the method to process DOT series on group analysis using cognitive paradigms on the prefrontal cortex. Difficulties such as the fact that scalp–brain distances vary between subjects or cerebral activations are difficult to reproduce due to strategies used by the subjects to solve arithmetic problems are considered. T-images given by fMRI and DOT volume series analyzed in SPM show that at the functional level, both DOT and fMRI measures detect the same areas, although DOT provides complementary information to fMRI signals about cerebral activity. PMID:28386575

Aeroelastic Flutter Behavior of Cantilever within a Nozzle-Diffuser Geometry

NASA Astrophysics Data System (ADS)

Tosi, Luis Phillipe; Colonius, Tim; Sherrit, Stewart; Lee, Hyeong Jae

2015-11-01

Aeroelastic flutter arises when the motion of a structure and its surrounding flowing fluid are coupled in a constructive manner, causing large amplitudes of vibration in the immersed solid. A cantilevered beam in axial flow within a nozzle-diffuser geometry exhibits interesting resonance behavior that presents good prospects for internal flow energy harvesting. Different modes can be excited as a function of throat velocity, nozzle geometry, fluid and cantilever material parameters. This work explores the relationship between the aeroelastic flutter instability boundaries and relevant non-dimensional parameters via experiments. Results suggest that for a linear expansion diffuser geometry, a non-dimensional stiffness, non-dimensional mass, and non-dimensional throat size are the critical parameters in mapping the instability. This map can serve as a guide to future work concerning possible electrical output and failure prediction in energy harvesters.

A computational kinetic model of diffusion for molecular systems.

PubMed

Teo, Ivan; Schulten, Klaus

2013-09-28

Regulation of biomolecular transport in cells involves intra-protein steps like gating and passage through channels, but these steps are preceded by extra-protein steps, namely, diffusive approach and admittance of solutes. The extra-protein steps develop over a 10-100 nm length scale typically in a highly particular environment, characterized through the protein's geometry, surrounding electrostatic field, and location. In order to account for solute energetics and mobility of solutes in this environment at a relevant resolution, we propose a particle-based kinetic model of diffusion based on a Markov State Model framework. Prerequisite input data consist of diffusion coefficient and potential of mean force maps generated from extensive molecular dynamics simulations of proteins and their environment that sample multi-nanosecond durations. The suggested diffusion model can describe transport processes beyond microsecond duration, relevant for biological function and beyond the realm of molecular dynamics simulation. For this purpose the systems are represented by a discrete set of states specified by the positions, volumes, and surface elements of Voronoi grid cells distributed according to a density function resolving the often intricate relevant diffusion space. Validation tests carried out for generic diffusion spaces show that the model and the associated Brownian motion algorithm are viable over a large range of parameter values such as time step, diffusion coefficient, and grid density. A concrete application of the method is demonstrated for ion diffusion around and through the Eschericia coli mechanosensitive channel of small conductance ecMscS.

Self-Organizing Maps and Parton Distribution Functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

K. Holcomb, Simonetta Liuti, D. Z. Perry

2011-05-01

We present a new method to extract parton distribution functions from high energy experimental data based on a specific type of neural networks, the Self-Organizing Maps. We illustrate the features of our new procedure that are particularly useful for an anaysis directed at extracting generalized parton distributions from data. We show quantitative results of our initial analysis of the parton distribution functions from inclusive deep inelastic scattering.

Interest of diffusion-weighted echo-planar MR imaging and apparent diffusion coefficient mapping in gynecological malignancies: a review.

PubMed

Levy, Antonin; Medjhoul, Aïcha; Caramella, Caroline; Zareski, Elise; Berges, Oscar; Chargari, Cyrus; Boulet, Bérénice; Bidault, François; Dromain, Clarisse; Balleyguier, Corinne

2011-05-01

Magnetic resonance imaging (MRI) remains the standard modality for the local staging of gynecological malignancies but it has several limitations, particularly for lymph node staging or evaluating peritoneal carcinomatosis. Consequently, there has been a growing interest in functional imaging modalities. Based on molecular diffusion, diffusion-weighted imaging (DWI) is a unique, noninvasive modality that provides excellent tissue contrast and was shown to improve the radiological diagnosis of malignant tumors. Using quantitative apparent diffusion coefficient (ADC) measurement of DWI provides a new tool for better distinguishing malignant tissues from benign tumors. The aim of the present review is to report on the results of DWI for the assessment of patients with gynecological malignancies. An analysis of the literature suggests that DWI studies would improve the diagnosis of cervical and endometrial tumors. It may also improve the assessment of tumor extension in patients with peritoneal carcinomatosis from gynecological malignancies. However, since the signal intensity of some cancers can range from high intensity to low intensity, a degree of uncertainty was demonstrated due to the proximity of the normal uterine myometrium and ovaries. Interestingly, there is also evidence that ADC might improve the follow-up and monitoring of patients who receive anticancer therapies, including chemotherapy or radiation therapy. Copyright © 2011 Wiley-Liss, Inc.

Functional imaging and assessment of the glucose diffusion rate in epithelial tissues in optical coherence tomography

NASA Astrophysics Data System (ADS)

Larin, K. V.; Tuchin, V. V.

2008-06-01

Functional imaging, monitoring and quantitative description of glucose diffusion in epithelial and underlying stromal tissues in vivo and controlling of the optical properties of tissues are extremely important for many biomedical applications including the development of noninvasive or minimally invasive glucose sensors as well as for therapy and diagnostics of various diseases, such as cancer, diabetic retinopathy, and glaucoma. Recent progress in the development of a noninvasive molecular diffusion biosensor based on optical coherence tomography (OCT) is described. The diffusion of glucose was studied in several epithelial tissues both in vitro and in vivo. Because OCT provides depth-resolved imaging of tissues with high in-depth resolution, the glucose diffusion is described not only as a function of time but also as a function of depth.

The effect of diffuse basis functions on valence bond structural weights

NASA Astrophysics Data System (ADS)

Galbraith, John Morrison; James, Andrew M.; Nemes, Coleen T.

2014-03-01

Structural weights and bond dissociation energies have been determined for H-F, H-X, and F-X molecules (-X = -OH, -NH2, and -CH3) at the valence bond self-consistent field (VBSCF) and breathing orbital valence bond (BOVB) levels of theory with the aug-cc-pVDZ and 6-31++G(d,p) basis sets. At the BOVB level, the aug-cc-pVDZ basis set yields a counterintuitive ordering of ionic structural weights when the initial heavy atom s-type basis functions are included. For H-F, H-OH, and F-X, the ordering follows chemical intuition when these basis functions are not included. These counterintuitive weights are shown to be a result of the diffuse polarisation function on one VB fragment being spatially located, in part, on the other VB fragment. Except in the case of F-CH3, this problem is corrected with the 6-31++G(d,p) basis set. The initial heavy atom s-type functions are shown to make an important contribution to the VB orbitals and bond dissociation energies and, therefore, should not be excluded. It is recommended to not use diffuse basis sets in valence bond calculations unless absolutely necessary. If diffuse basis sets are needed, the 6-31++G(d,p) basis set should be used with caution and the structural weights checked against VBSCF values which have been shown to follow the expected ordering in all cases.

Graphical function mapping as a new way to explore cause-and-effect chains

USGS Publications Warehouse

Evans, Mary Anne

2016-01-01

Graphical function mapping provides a simple method for improving communication within interdisciplinary research teams and between scientists and nonscientists. This article introduces graphical function mapping using two examples and discusses its usefulness. Function mapping projects the outcome of one function into another to show the combined effect. Using this mathematical property in a simpler, even cartoon-like, graphical way allows the rapid combination of multiple information sources (models, empirical data, expert judgment, and guesses) in an intuitive visual to promote further discussion, scenario development, and clear communication.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

A Self-Contained Mapping Closure Approximation for Scalar Mixing

NASA Technical Reports Server (NTRS)

He, Guo-Wei; Zhang, Zi-Fan

2003-01-01

Scalar turbulence exhibits interplays of coherent structures and random fluctuations over a broad range of spatial and temporal scales. This feature necessitates a probabilistic description of the scalar dynamics, which can be achieved comprehensively by using probability density functions (PDFs). Therefore, the challenge is to obtain the scalar PDFs (Lundgren 1967; Dopazo 1979). Generally, the evolution of a scalar is governed by three dynamical processes: advection, diffusion and reaction. In a PDF approach (Pope 1985), the advection and reaction can be treated exactly but the effect of molecular diffusion has to be modeled. It has been shown (Pope 1985) that the effect of molecular diffusion can be expressed as conditional dissipation rates or conditional diffusions. The currently used models for the conditional dissipation rates and conditional diffusions (Pope 1991) have resisted deduction from the fundamental equations and are unable to yield satisfactory results for the basic test cases of decaying scalars in isotropic turbulence, although they have achieved some success in a variety of individual cases. The recently developed mapping closure approach (Pope 1991; Chen, Chen & Kraichnan 1989; Kraichnan 1990; Klimenko & Pope 2003) provides a deductive method for conditional dissipation rates and conditional di usions, and the models obtained can successfully describe the shape relaxation of the scalar PDF from an initial double delta distribution to a Gaussian one. However, the mapping closure approach is not able to provide the rate at which the scalar evolves. The evolution rate has to be modeled. Therefore, the mapping closure approach is not closed. In this letter, we will address this problem.

An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

Pressure recovery performance of conical diffusers at high subsonic Mach numbers

NASA Technical Reports Server (NTRS)

Dolan, F. X.; Runstadler, P. W., Jr.

1973-01-01

The pressure recovery performance of conical diffusers has been measured for a wide range of geometries and inlet flow conditions. The approximate level and location (in terms of diffuser geometry of optimum performance were determined. Throat Mach numbers from low subsonic (m sub t equals 0.2) through choking (m sub t equals 1.0) were investigated in combination with throat blockage from 0.03 to 0.12. For fixed Mach number, performance was measured over a fourfold range of inlet Reynolds number. Maps of pressure recovery are presented as a function of diffuser geometry for fixed sets of inlet conditions. The influence of inlet blockage, throat Mach number, and inlet Reynolds number is discussed.

Detection of early seizures by diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zhang, Tao; Hajihashemi, M. Reza; Zhou, Junli; Carney, Paul R.; Jiang, Huabei

2015-03-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Besides, preclinical seizure experiments need to be conducted in awake animals with images reconstructed and displayed in real-time. We demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking brain activities with high spatiotemporal resolution. We developed methods to conduct seizure experiments in fully awake rats using a subject-specific helmet and a restraining mechanism. For the first time, we detected early hemodynamic responses with heterogeneous patterns several minutes preceding the electroencephalographic seizure onset, supporting the presence of a "pre-seizure" state both in anesthetized and awake rats. Using a novel time-series analysis of scattering images, we show that the analysis of scattered diffuse light is a sensitive and reliable modality for detecting changes in neural activity associated with generalized seizure. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways.

Comparison of CT perfusion summary maps to early diffusion-weighted images in suspected acute middle cerebral artery stroke.

PubMed

Benson, John; Payabvash, Seyedmehdi; Salazar, Pascal; Jagadeesan, Bharathi; Palmer, Christopher S; Truwit, Charles L; McKinney, Alexander M

2015-04-01

To assess the accuracy and reliability of one vendor's (Vital Images, Toshiba Medical, Minnetonka, MN) automated CT perfusion (CTP) summary maps in identification and volume estimation of infarcted tissue in patients with acute middle cerebral artery (MCA) distribution infarcts. From 1085 CTP examinations over 5.5 years, 43 diffusion-weighted imaging (DWI)-positive patients were included who underwent both CTP and DWI <12 h after symptom onset, with another 43 age-matched patients as controls (DWI-negative). Automated delay-corrected postprocessing software (DC-SVD) generated both infarct "core only" and "core+penumbra" CTP summary maps. Three reviewers independently tabulated Alberta Stroke Program Early CT scores (ASPECTS) of both CTP summary maps and coregistered DWI. Of 86 included patients, 36 had DWI infarct volumes ≤70 ml, 7 had volumes >70 ml, and 43 were negative; the automated CTP "core only" map correctly classified each as >70 ml or ≤70 ml, while the "core+penumbra" map misclassified 4 as >70 ml. There were strong correlations between DWI volume with both summary map-based volumes: "core only" (r=0.93), and "core+penumbra" (r=0.77) (both p<0.0001). Agreement between ASPECTS scores of infarct core on DWI with summary maps was 0.65-0.74 for "core only" map, and 0.61-0.65 for "core+penumbra" (both p<0.0001). Using DWI-based ASPECTS scores as the standard, the accuracy of the CTP-based maps were 79.1-86.0% for the "core only" map, and 83.7-88.4% for "core+penumbra." Automated CTP summary maps appear to be relatively accurate in both the detection of acute MCA distribution infarcts, and the discrimination of volumes using a 70 ml threshold. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Tissue microstructure features derived from anomalous diffusion measurements in magnetic resonance imaging.

PubMed

Yu, Qiang; Reutens, David; O'Brien, Kieran; Vegh, Viktor

2017-02-01

Tissue microstructure features, namely axon radius and volume fraction, provide important information on the function of white matter pathways. These parameters vary on the scale much smaller than imaging voxels (microscale) yet influence the magnetic resonance imaging diffusion signal at the image voxel scale (macroscale) in an anomalous manner. Researchers have already mapped anomalous diffusion parameters from magnetic resonance imaging data, but macroscopic variations have not been related to microscale influences. With the aid of a tissue model, we aimed to connect anomalous diffusion parameters to axon radius and volume fraction using diffusion-weighted magnetic resonance imaging measurements. An ex vivo human brain experiment was performed to directly validate axon radius and volume fraction measurements in the human brain. These findings were validated using electron microscopy. Additionally, we performed an in vivo study on nine healthy participants to map axon radius and volume fraction along different regions of the corpus callosum projecting into various cortical areas identified using tractography. We found a clear relationship between anomalous diffusion parameters and axon radius and volume fraction. We were also able to map accurately the trend in axon radius along the corpus callosum, and in vivo findings resembled the low-high-low-high behaviour in axon radius demonstrated previously. Axon radius and volume fraction measurements can potentially be used in brain connectivity studies and to understand the implications of white matter structure in brain diseases and disorders. Hum Brain Mapp 38:1068-1081, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Analytic expressions for ULF wave radiation belt radial diffusion coefficients

PubMed Central

Ozeke, Louis G; Mann, Ian R; Murphy, Kyle R; Jonathan Rae, I; Milling, David K

2014-01-01

We present analytic expressions for ULF wave-derived radiation belt radial diffusion coefficients, as a function of L and Kp, which can easily be incorporated into global radiation belt transport models. The diffusion coefficients are derived from statistical representations of ULF wave power, electric field power mapped from ground magnetometer data, and compressional magnetic field power from in situ measurements. We show that the overall electric and magnetic diffusion coefficients are to a good approximation both independent of energy. We present example 1-D radial diffusion results from simulations driven by CRRES-observed time-dependent energy spectra at the outer boundary, under the action of radial diffusion driven by the new ULF wave radial diffusion coefficients and with empirical chorus wave loss terms (as a function of energy, Kp and L). There is excellent agreement between the differential flux produced by the 1-D, Kp-driven, radial diffusion model and CRRES observations of differential electron flux at 0.976 MeV—even though the model does not include the effects of local internal acceleration sources. Our results highlight not only the importance of correct specification of radial diffusion coefficients for developing accurate models but also show significant promise for belt specification based on relatively simple models driven by solar wind parameters such as solar wind speed or geomagnetic indices such as Kp. Key Points Analytic expressions for the radial diffusion coefficients are presented The coefficients do not dependent on energy or wave m value The electric field diffusion coefficient dominates over the magnetic PMID:26167440

Technique of diffusion weighted imaging and its application in stroke

NASA Astrophysics Data System (ADS)

Li, Enzhong; Tian, Jie; Han, Ying; Wang, Huifang; Li, Wu; He, Huiguang

2003-05-01

To study the application of diffusion weighted imaging and image post processing in the diagnosis of stroke, especially in acute stroke, 205 patients were examined by 1.5 T or 1.0 T MRI scanner and the images such as T1, T2 and diffusion weighted images were obtained. Image post processing was done with "3D Med System" developed by our lab to analyze data and acquire the apparent diffusion coefficient (ADC) map. In acute and subacute stage of stroke, the signal in cerebral infarction areas changed to hyperintensity in T2- and diffusion-weighted images, normal or hypointensity in T1-weighted images. In hyperacute stage, however, the signal was hyperintense just in the diffusion weighted imaes; others were normal. In the chronic stage, the signal in T1- and diffusion-weighted imaging showed hypointensity and hyperintensity in T2 weighted imaging. Because ADC declined obviously in acute and subacute stage of stroke, the lesion area was hypointensity in ADC map. With the development of the disease, ADC gradually recovered and then changed to hyperintensity in ADC map in chronic stage. Using diffusion weighted imaging and ADC mapping can make a diagnosis of stroke, especially in the hyperacute stage of stroke, and can differentiate acute and chronic stroke.

A Radiation Chemistry Code Based on the Greens Functions of the Diffusion Equation

NASA Technical Reports Server (NTRS)

Plante, Ianik; Wu, Honglu

2014-01-01

Ionizing radiation produces several radiolytic species such as.OH, e-aq, and H. when interacting with biological matter. Following their creation, radiolytic species diffuse and chemically react with biological molecules such as DNA. Despite years of research, many questions on the DNA damage by ionizing radiation remains, notably on the indirect effect, i.e. the damage resulting from the reactions of the radiolytic species with DNA. To simulate DNA damage by ionizing radiation, we are developing a step-by-step radiation chemistry code that is based on the Green's functions of the diffusion equation (GFDE), which is able to follow the trajectories of all particles and their reactions with time. In the recent years, simulations based on the GFDE have been used extensively in biochemistry, notably to simulate biochemical networks in time and space and are often used as the "gold standard" to validate diffusion-reaction theories. The exact GFDE for partially diffusion-controlled reactions is difficult to use because of its complex form. Therefore, the radial Green's function, which is much simpler, is often used. Hence, much effort has been devoted to the sampling of the radial Green's functions, for which we have developed a sampling algorithm This algorithm only yields the inter-particle distance vector length after a time step; the sampling of the deviation angle of the inter-particle vector is not taken into consideration. In this work, we show that the radial distribution is predicted by the exact radial Green's function. We also use a technique developed by Clifford et al. to generate the inter-particle vector deviation angles, knowing the inter-particle vector length before and after a time step. The results are compared with those predicted by the exact GFDE and by the analytical angular functions for free diffusion. This first step in the creation of the radiation chemistry code should help the understanding of the contribution of the indirect effect in the

Diffusion Cartograms for the Display of Periodic Table Data

ERIC Educational Resources Information Center

Winter, Mark J.

2011-01-01

Mapping methods employed by geographers, known as diffusion cartograms (diffusion-based density-equalizing maps), are used to present visually interesting and informative plots for data such as income, health, voting patterns, and resource availability. The algorithm involves changing the sizes of geographic regions such as countries or provinces…

Assessing Diffusion in the Extra-Cellular Space of Brain Tissue by Dynamic MRI Mapping of Contrast Agent Concentrations

NASA Astrophysics Data System (ADS)

Mériaux, Sébastien; Conti, Allegra; Larrat, Benoît

2018-05-01

The characterization of extracellular space (ECS) architecture represents valuable information for the understanding of transport mechanisms occurring in brain parenchyma. ECS tortuosity reflects the hindrance imposed by cell membranes to molecular diffusion. Numerous strategies have been proposed to measure the diffusion through ECS and to estimate its tortuosity. The first method implies the perfusion for several hours of a radiotracer which effective diffusion coefficient D* is determined after post mortem processing. The most well-established techniques are real-time iontophoresis that measures the concentration of a specific ion at known distance from its release point, and integrative optical imaging that relies on acquiring microscopy images of macromolecules labelled with fluorophore. After presenting these methods, we focus on a recent Magnetic Resonance Imaging (MRI)-based technique that consists in acquiring concentration maps of a contrast agent diffusing within ECS. Thanks to MRI properties, molecular diffusion and tortuosity can be estimated in 3D for deep brain regions. To further discuss the reliability of this technique, we point out the influence of the delivery method on the estimation of D*. We compare the value of D* for a contrast agent intracerebrally injected, with its value when the agent is delivered to the brain after an ultrasound-induced blood-brain barrier (BBB) permeabilization. Several studies have already shown that tortuosity may be modified in pathological conditions. Therefore, we believe that MRI-based techniques could be useful in a clinical context for characterizing the diffusion properties of pathological ECS and thus predicting the drug biodistribution into the targeted area.

Structure-Function Network Mapping and Its Assessment via Persistent Homology

PubMed Central

2017-01-01

Understanding the relationship between brain structure and function is a fundamental problem in network neuroscience. This work deals with the general method of structure-function mapping at the whole-brain level. We formulate the problem as a topological mapping of structure-function connectivity via matrix function, and find a stable solution by exploiting a regularization procedure to cope with large matrices. We introduce a novel measure of network similarity based on persistent homology for assessing the quality of the network mapping, which enables a detailed comparison of network topological changes across all possible thresholds, rather than just at a single, arbitrary threshold that may not be optimal. We demonstrate that our approach can uncover the direct and indirect structural paths for predicting functional connectivity, and our network similarity measure outperforms other currently available methods. We systematically validate our approach with (1) a comparison of regularized vs. non-regularized procedures, (2) a null model of the degree-preserving random rewired structural matrix, (3) different network types (binary vs. weighted matrices), and (4) different brain parcellation schemes (low vs. high resolutions). Finally, we evaluate the scalability of our method with relatively large matrices (2514x2514) of structural and functional connectivity obtained from 12 healthy human subjects measured non-invasively while at rest. Our results reveal a nonlinear structure-function relationship, suggesting that the resting-state functional connectivity depends on direct structural connections, as well as relatively parsimonious indirect connections via polysynaptic pathways. PMID:28046127

[From Brownian motion to mind imaging: diffusion MRI].

PubMed

Le Bihan, Denis

2006-11-01

The success of diffusion MRI, which was introduced in the mid 1980s is deeply rooted in the powerful concept that during their random, diffusion-driven movements water molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. The observation of these movements thus provides valuable information on the structure and the geometric organization of tissues. The most successful application of diffusion MRI has been in brain ischemia, following the discovery that water diffusion drops at a very early stage of the ischemic event. Diffusion MRI provides some patients with the opportunity to receive suitable treatment at a very acute stage when brain tissue might still be salvageable. On the other hand, diffusion is modulated by the spatial orientation of large bundles of myelinated axons running in parallel through in brain white matter. This feature can be exploited to map out the orientation in space of the white matter tracks and to visualize the connections between different parts of the brain on an individual basis. Furthermore, recent data suggest that diffusion MRI may also be used to visualize rapid dynamic tissue changes, such as neuronal swelling, associated with cortical activation, offering a new and direct approach to brain functional imaging.

An Exploration into Diffusion Tensor Imaging in the Bovine Ocular Lens

PubMed Central

Vaghefi, Ehsan; Donaldson, Paul J.

2013-01-01

We describe our development of the diffusion tensor imaging modality for the bovine ocular lens. Diffusion gradients were added to a spin-echo pulse sequence and the relevant parameters of the sequence were refined to achieve good diffusion weighting in the lens tissue, which demonstrated heterogeneous regions of diffusive signal attenuation. Decay curves for b-value (loosely summarizes the strength of diffusion weighting) and TE (determines the amount of magnetic resonance imaging-obtained signal) were used to estimate apparent diffusion coefficients (ADC) and T2 in different lens regions. The ADCs varied by over an order of magnitude and revealed diffusive anisotropy in the lens. Up to 30 diffusion gradient directions, and 8 signal acquisition averages, were applied to lenses in culture in order to improve maps of diffusion tensor eigenvalues, equivalent to ADC, across the lens. From these maps, fractional anisotropy maps were calculated and compared to known spatial distributions of anisotropic molecular fluxes in the lens. This comparison suggested new hypotheses and experiments to quantitatively assess models of circulation in the avascular lens. PMID:23459990

Functional quantitative susceptibility mapping (fQSM).

PubMed

Balla, Dávid Z; Sanchez-Panchuelo, Rosa M; Wharton, Samuel J; Hagberg, Gisela E; Scheffler, Klaus; Francis, Susan T; Bowtell, Richard

2014-10-15

Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a powerful technique, typically based on the statistical analysis of the magnitude component of the complex time-series. Here, we additionally interrogated the phase data of the fMRI time-series and used quantitative susceptibility mapping (QSM) in order to investigate the potential of functional QSM (fQSM) relative to standard magnitude BOLD fMRI. High spatial resolution data (1mm isotropic) were acquired every 3 seconds using zoomed multi-slice gradient-echo EPI collected at 7 T in single orientation (SO) and multiple orientation (MO) experiments, the latter involving 4 repetitions with the subject's head rotated relative to B0. Statistical parametric maps (SPM) were reconstructed for magnitude, phase and QSM time-series and each was subjected to detailed analysis. Several fQSM pipelines were evaluated and compared based on the relative number of voxels that were coincidentally found to be significant in QSM and magnitude SPMs (common voxels). We found that sensitivity and spatial reliability of fQSM relative to the magnitude data depended strongly on the arbitrary significance threshold defining "activated" voxels in SPMs, and on the efficiency of spatio-temporal filtering of the phase time-series. Sensitivity and spatial reliability depended slightly on whether MO or SO fQSM was performed and on the QSM calculation approach used for SO data. Our results present the potential of fQSM as a quantitative method of mapping BOLD changes. We also critically discuss the technical challenges and issues linked to this intriguing new technique. Copyright © 2014 Elsevier Inc. All rights reserved.

Functional implications of orientation maps in primary visual cortex

NASA Astrophysics Data System (ADS)

Koch, Erin; Jin, Jianzhong; Alonso, Jose M.; Zaidi, Qasim

2016-11-01

Stimulus orientation in the primary visual cortex of primates and carnivores is mapped as iso-orientation domains radiating from pinwheel centres, where orientation preferences of neighbouring cells change circularly. Whether this orientation map has a function is currently debated, because many mammals, such as rodents, do not have such maps. Here we show that two fundamental properties of visual cortical responses, contrast saturation and cross-orientation suppression, are stronger within cat iso-orientation domains than at pinwheel centres. These differences develop when excitation (not normalization) from neighbouring oriented neurons is applied to different cortical orientation domains and then balanced by inhibition from un-oriented neurons. The functions of the pinwheel mosaic emerge from these local intra-cortical computations: Narrower tuning, greater cross-orientation suppression and higher contrast gain of iso-orientation cells facilitate extraction of object contours from images, whereas broader tuning, greater linearity and less suppression of pinwheel cells generate selectivity for surface patterns and textures.

Mapping Ionic Currents and Reactivity on the Nanoscale: Electrochemical Strain Microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalinin, S.V.

2010-10-19

Solid-state electrochemical processes in oxides underpin a broad spectrum of energy and information storage devices, ranging from Li-ion and Li-air batteries, to solid oxide fuel cells (SOFC) to electroresistive and memristive systems. These functionalities are controlled by the bias-driven diffusive and electromigration transport of mobile ionic species, as well as intricate a set of electrochemical and defect-controlled reactions at interfaces and in bulk. Despite the wealth of device-level and atomistic studies, little is known on the mesoscopic mechanisms of ion diffusion and electronic transport on the level of grain clusters, individual grains, and extended defects. The development of the capabilitymore » for probing ion transport on the nanometer scale is a key to deciphering complex interplay between structure, functionality, and performance in these systems. Here we introduce Electrochemical Strain Microscopy, a scanning probe microscopy technique based on strong strain-bias coupling in the systems in which local ion concentrations are changed by electrical fields. The imaging capability, as well as time- and voltage spectroscopies analogous to traditional current based electrochemical characterization methods are developed. The reversible intercalation of Li and mapping electrochemical activity in LiCoO2 is demonstrated, illustrating higher Li diffusivity at non-basal planes and grain boundaries. In Si-anode device structure, the direct mapping of Li diffusion at extended defects and evolution of Li-activity with charge state is explored. The electrical field-dependence of Li mobility is studied to determine the critical bias required for the onset of electrochemical transformation, allowing reaction and diffusion processes in the battery system to be separated at each location. Finally, the applicability of ESM for probing oxygen vacancy diffusion and oxygen reduction/evolution reactions is illustrated, and the high resolution ESM maps are correlated

Many-to-one form-to-function mapping weakens parallel morphological evolution.

PubMed

Thompson, Cole J; Ahmed, Newaz I; Veen, Thor; Peichel, Catherine L; Hendry, Andrew P; Bolnick, Daniel I; Stuart, Yoel E

2017-11-01

Evolutionary ecologists aim to explain and predict evolutionary change under different selective regimes. Theory suggests that such evolutionary prediction should be more difficult for biomechanical systems in which different trait combinations generate the same functional output: "many-to-one mapping." Many-to-one mapping of phenotype to function enables multiple morphological solutions to meet the same adaptive challenges. Therefore, many-to-one mapping should undermine parallel morphological evolution, and hence evolutionary predictability, even when selection pressures are shared among populations. Studying 16 replicate pairs of lake- and stream-adapted threespine stickleback (Gasterosteus aculeatus), we quantified three parts of the teleost feeding apparatus and used biomechanical models to calculate their expected functional outputs. The three feeding structures differed in their form-to-function relationship from one-to-one (lower jaw lever ratio) to increasingly many-to-one (buccal suction index, opercular 4-bar linkage). We tested for (1) weaker linear correlations between phenotype and calculated function, and (2) less parallel evolution across lake-stream pairs, in the many-to-one systems relative to the one-to-one system. We confirm both predictions, thus supporting the theoretical expectation that increasing many-to-one mapping undermines parallel evolution. Therefore, sole consideration of morphological variation within and among populations might not serve as a proxy for functional variation when multiple adaptive trait combinations exist. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

T1 and T2 Mapping in Cardiology: "Mapping the Obscure Object of Desire".

PubMed

Mavrogeni, Sophie; Apostolou, Dimitris; Argyriou, Panayiotis; Velitsista, Stella; Papa, Lilika; Efentakis, Stelios; Vernardos, Evangelos; Kanoupaki, Mikela; Kanoupakis, George; Manginas, Athanassios

The increasing use of cardiovascular magnetic resonance (CMR) is based on its capability to perform biventricular function assessment and tissue characterization without radiation and with high reproducibility. The use of late gadolinium enhancement (LGE) gave the potential of non-invasive biopsy for fibrosis quantification. However, LGE is unable to detect diffuse myocardial disease. Native T1 mapping and extracellular volume fraction (ECV) provide knowledge about pathologies affecting both the myocardium and interstitium that is otherwise difficult to identify. Changes of myocardial native T1 reflect cardiac diseases (acute coronary syndromes, infarction, myocarditis, and diffuse fibrosis, all with high T1) and systemic diseases such as cardiac amyloid (high T1), Anderson-Fabry disease (low T1), and siderosis (low T1). The ECV, an index generated by native and post-contrast T1 mapping, measures the cellular and extracellular interstitial matrix (ECM) compartments. This myocyte-ECM dichotomy has important implications for identifying specific therapeutic targets of great value for heart failure treatment. On the other hand, T2 mapping is superior compared with myocardial T1 and ECM for assessing the activity of myocarditis in recent-onset heart failure. Although these indices can significantly affect the clinical decision making, multicentre studies and a community-wide approach (including MRI vendors, funding, software, contrast agent manufacturers, and clinicians) are still missing. © 2017 S. Karger AG, Basel.

On the mapping associated with the complex representation of functions and processes.

NASA Technical Reports Server (NTRS)

Harger, R. O.

1972-01-01

The mapping between function spaces that is implied by the representation of a real 'bandpass' function by a complex 'low-pass' function is explicitly accepted. The discussion is extended to the representation of stationary random processes where the mapping is between spaces of random processes. This approach clarifies the nature of the complex representation, especially in the case of random processes and, in addition, derives the properties of the complex representation.-

Efficient Green's Function Reaction Dynamics (GFRD) simulations for diffusion-limited, reversible reactions

NASA Astrophysics Data System (ADS)

Bashardanesh, Zahedeh; Lötstedt, Per

2018-03-01

In diffusion controlled reversible bimolecular reactions in three dimensions, a dissociation step is typically followed by multiple, rapid re-association steps slowing down the simulations of such systems. In order to improve the efficiency, we first derive an exact Green's function describing the rate at which an isolated pair of particles undergoing reversible bimolecular reactions and unimolecular decay separates beyond an arbitrarily chosen distance. Then the Green's function is used in an algorithm for particle-based stochastic reaction-diffusion simulations for prediction of the dynamics of biochemical networks. The accuracy and efficiency of the algorithm are evaluated using a reversible reaction and a push-pull chemical network. The computational work is independent of the rates of the re-associations.

Functional imaging and assessment of the glucose diffusion rate in epithelial tissues in optical coherence tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larin, K V; Tuchin, V V

2008-06-30

Functional imaging, monitoring and quantitative description of glucose diffusion in epithelial and underlying stromal tissues in vivo and controlling of the optical properties of tissues are extremely important for many biomedical applications including the development of noninvasive or minimally invasive glucose sensors as well as for therapy and diagnostics of various diseases, such as cancer, diabetic retinopathy, and glaucoma. Recent progress in the development of a noninvasive molecular diffusion biosensor based on optical coherence tomography (OCT) is described. The diffusion of glucose was studied in several epithelial tissues both in vitro and in vivo. Because OCT provides depth-resolved imaging ofmore » tissues with high in-depth resolution, the glucose diffusion is described not only as a function of time but also as a function of depth. (special issue devoted to application of laser technologies in biophotonics and biomedical studies)« less

Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma.

PubMed

Takahashi, Masahiro; Kozawa, Eito; Tanisaka, Megumi; Hasegawa, Kousei; Yasuda, Masanori; Sakai, Fumikazu

2016-06-01

We explored the role of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating uterine carcinosarcoma and endometrial carcinoma. We retrospectively evaluated findings in 13 patients with uterine carcinosarcoma and 50 patients with endometrial carcinoma who underwent diffusion-weighted imaging (b = 0, 500, 1000 s/mm(2) ) at 3T with acquisition of corresponding ADC maps. We derived histogram data from regions of interest drawn on all slices of the ADC maps in which tumor was visualized, excluding areas of necrosis and hemorrhage in the tumor. We used the Mann-Whitney test to evaluate the capacity of histogram parameters (mean ADC value, 5th to 95th percentiles, skewness, kurtosis) to discriminate uterine carcinosarcoma and endometrial carcinoma and analyzed the receiver operating characteristic (ROC) curve to determine the optimum threshold value for each parameter and its corresponding sensitivity and specificity. Carcinosarcomas demonstrated significantly higher mean vales of ADC, 95th, 90th, 75th, 50th, 25th percentiles and kurtosis than endometrial carcinomas (P < 0.05). ROC curve analysis of the 75th percentile yielded the best area under the ROC curve (AUC; 0.904), sensitivity of 100%, and specificity of 78.0%, with a cutoff value of 1.034 × 10(-3) mm(2) /s. Histogram analysis of ADC maps might be helpful for discriminating uterine carcinosarcomas and endometrial carcinomas. J. Magn. Reson. Imaging 2016;43:1301-1307. © 2015 Wiley Periodicals, Inc.

DiffNet: automatic differential functional summarization of dE-MAP networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes

2014-10-01

The study of genetic interaction networks that respond to changing conditions is an emerging research problem. Recently, Bandyopadhyay et al. (2010) proposed a technique to construct a differential network (dE-MAPnetwork) from two static gene interaction networks in order to map the interaction differences between them under environment or condition change (e.g., DNA-damaging agent). This differential network is then manually analyzed to conclude that DNA repair is differentially effected by the condition change. Unfortunately, manual construction of differential functional summary from a dE-MAP network that summarizes all pertinent functional responses is time-consuming, laborious and error-prone, impeding large-scale analysis on it. To this end, we propose DiffNet, a novel data-driven algorithm that leverages Gene Ontology (go) annotations to automatically summarize a dE-MAP network to obtain a high-level map of functional responses due to condition change. We tested DiffNet on the dynamic interaction networks following MMS treatment and demonstrated the superiority of our approach in generating differential functional summaries compared to state-of-the-art graph clustering methods. We studied the effects of parameters in DiffNet in controlling the quality of the summary. We also performed a case study that illustrates its utility. Copyright © 2014 Elsevier Inc. All rights reserved.

Nonlinear stability in reaction-diffusion systems via optimal Lyapunov functions

NASA Astrophysics Data System (ADS)

Lombardo, S.; Mulone, G.; Trovato, M.

2008-06-01

We define optimal Lyapunov functions to study nonlinear stability of constant solutions to reaction-diffusion systems. A computable and finite radius of attraction for the initial data is obtained. Applications are given to the well-known Brusselator model and a three-species model for the spatial spread of rabies among foxes.

Decay of random correlation functions for unimodal maps

NASA Astrophysics Data System (ADS)

Baladi, Viviane; Benedicks, Michael; Maume-Deschamps, Véronique

2000-10-01

Since the pioneering results of Jakobson and subsequent work by Benedicks-Carleson and others, it is known that quadratic maps tfa( χ) = a - χ2 admit a unique absolutely continuous invariant measure for a positive measure set of parameters a. For topologically mixing tfa, Young and Keller-Nowicki independently proved exponential decay of correlation functions for this a.c.i.m. and smooth observables. We consider random compositions of small perturbations tf + ωt, with tf = tfa or another unimodal map satisfying certain nonuniform hyperbolicity axioms, and ωt chosen independently and identically in [-ɛ, ɛ]. Baladi-Viana showed exponential mixing of the associated Markov chain, i.e., averaging over all random itineraries. We obtain stretched exponential bounds for the random correlation functions of Lipschitz observables for the sample measure μωof almost every itinerary.

A comprehensive neuropsychological mapping battery for functional magnetic resonance imaging.

PubMed

Karakas, Sirel; Baran, Zeynel; Ceylan, Arzu Ozkan; Tileylioglu, Emre; Tali, Turgut; Karakas, Hakki Muammer

2013-11-01

Existing batteries for FMRI do not precisely meet the criteria for comprehensive mapping of cognitive functions within minimum data acquisition times using standard scanners and head coils. The goal was to develop a battery of neuropsychological paradigms for FMRI that can also be used in other brain imaging techniques and behavioural research. Participants were 61 healthy, young adult volunteers (48 females and 13 males, mean age: 22.25 ± 3.39 years) from the university community. The battery included 8 paradigms for basic (visual, auditory, sensory-motor, emotional arousal) and complex (language, working memory, inhibition/interference control, learning) cognitive functions. Imaging was performed using standard functional imaging capabilities (1.5-T MR scanner, standard head coil). Structural and functional data series were analysed using Brain Voyager QX2.9 and Statistical Parametric Mapping-8. For basic processes, activation centres for individuals were within a distance of 3-11 mm of the group centres of the target regions and for complex cognitive processes, between 7 mm and 15 mm. Based on fixed-effect and random-effects analyses, the distance between the activation centres was 0-4 mm. There was spatial variability between individual cases; however, as shown by the distances between the centres found with fixed-effect and random-effects analyses, the coordinates for individual cases can be used to represent those of the group. The findings show that the neuropsychological brain mapping battery described here can be used in basic science studies that investigate the relationship of the brain to the mind and also as functional localiser in clinical studies for diagnosis, follow-up and pre-surgical mapping. © 2013.

Whole Brain Functional Connectivity Pattern Homogeneity Mapping.

PubMed

Wang, Lijie; Xu, Jinping; Wang, Chao; Wang, Jiaojian

2018-01-01

Mounting studies have demonstrated that brain functions are determined by its external functional connectivity patterns. However, how to characterize the voxel-wise similarity of whole brain functional connectivity pattern is still largely unknown. In this study, we introduced a new method called functional connectivity homogeneity (FcHo) to delineate the voxel-wise similarity of whole brain functional connectivity patterns. FcHo was defined by measuring the whole brain functional connectivity patterns similarity of a given voxel with its nearest 26 neighbors using Kendall's coefficient concordance (KCC). The robustness of this method was tested in four independent datasets selected from a large repository of MRI. Furthermore, FcHo mapping results were further validated using the nearest 18 and six neighbors and intra-subject reproducibility with each subject scanned two times. We also compared FcHo distribution patterns with local regional homogeneity (ReHo) to identify the similarity and differences of the two methods. Finally, FcHo method was used to identify the differences of whole brain functional connectivity patterns between professional Chinese chess players and novices to test its application. FcHo mapping consistently revealed that the high FcHo was mainly distributed in association cortex including parietal lobe, frontal lobe, occipital lobe and default mode network (DMN) related areas, whereas the low FcHo was mainly found in unimodal cortex including primary visual cortex, sensorimotor cortex, paracentral lobule and supplementary motor area. These results were further supported by analyses of the nearest 18 and six neighbors and intra-subject similarity. Moreover, FcHo showed both similar and different whole brain distribution patterns compared to ReHo. Finally, we demonstrated that FcHo can effectively identify the whole brain functional connectivity pattern differences between professional Chinese chess players and novices. Our findings indicated

Pitfalls of diffusion-weighted imaging of the female pelvis

PubMed Central

Duarte, Ana Luisa; Dias, João Lopes; Cunha, Teresa Margarida

2018-01-01

Diffusion-weighted imaging (DWI) is widely used in protocols for magnetic resonance imaging (MRI) of the female pelvis. It provides functional and structural information about biological tissues, without the use of ionizing radiation or intravenous administration of contrast medium. High signal intensity on DWI with simultaneous low signal intensity on apparent diffusion coefficient maps is usually associated with malignancy. However, that pattern can also be seen in many benign lesions, a fact that should be recognized by radiologists. Correlating DWI findings with those of conventional (T1- and T2-weighted) MRI sequences and those of contrast-enhanced MRI sequences is mandatory in order to avoid potential pitfalls. The aim of this review article is the description of the most relevant physiological and benign pathological conditions of the female pelvis that can show restricted diffusion on DWI. PMID:29559764

A radial basis function Galerkin method for inhomogeneous nonlocal diffusion

DOE PAGES

Lehoucq, Richard B.; Rowe, Stephen T.

2016-02-01

We introduce a discretization for a nonlocal diffusion problem using a localized basis of radial basis functions. The stiffness matrix entries are assembled by a special quadrature routine unique to the localized basis. Combining the quadrature method with the localized basis produces a well-conditioned, sparse, symmetric positive definite stiffness matrix. We demonstrate that both the continuum and discrete problems are well-posed and present numerical results for the convergence behavior of the radial basis function method. As a result, we explore approximating the solution to anisotropic differential equations by solving anisotropic nonlocal integral equations using the radial basis function method.

Using Immediate-Early Genes to Map Hippocampal Subregional Functions

ERIC Educational Resources Information Center

Kubik, Stepan; Miyashita, Teiko; Guzowski, John F.

2007-01-01

Different functions have been suggested for the hippocampus and its subdivisions along both transversal and longitudinal axes. Expression of immediate-early genes (IEGs) has been used to map specific functions onto neuronal activity in different areas of the brain including the hippocampus (IEG imaging). Here we review IEG studies on hippocampal…

Complex Geometric Models of Diffusion and Relaxation in Healthy and Damaged White Matter

PubMed Central

Farrell, Jonathan A.D.; Smith, Seth A.; Reich, Daniel S.; Calabresi, Peter A.; van Zijl, Peter C.M.

2010-01-01

Which aspects of tissue microstructure affect diffusion weighted MRI signals? Prior models, many of which use Monte-Carlo simulations, have focused on relatively simple models of the cellular microenvironment and have not considered important anatomic details. With the advent of higher-order analysis models for diffusion imaging, such as high-angular-resolution diffusion imaging (HARDI), more realistic models are necessary. This paper presents and evaluates the reproducibility of simulations of diffusion in complex geometries. Our framework is quantitative, does not require specialized hardware, is easily implemented with little programming experience, and is freely available as open-source software. Models may include compartments with different diffusivities, permeabilities, and T2 time constants using both parametric (e.g., spheres and cylinders) and arbitrary (e.g., mesh-based) geometries. Three-dimensional diffusion displacement-probability functions are mapped with high reproducibility, and thus can be readily used to assess reproducibility of diffusion-derived contrasts. PMID:19739233

Spatial Mapping of Structural and Connectional Imaging Data for the Developing Human Brain with Diffusion Tensor Imaging

PubMed Central

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao

2014-01-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302

Putting atomic diffusion theory of magnetic ApBp stars to the test: evaluation of the predictions of time-dependent diffusion models

NASA Astrophysics Data System (ADS)

Kochukhov, O.; Ryabchikova, T. A.

2018-02-01

A series of recent theoretical atomic diffusion studies has address the challenging problem of predicting inhomogeneous vertical and horizontal chemical element distributions in the atmospheres of magnetic ApBp stars. Here we critically assess the most sophisticated of such diffusion models - based on a time-dependent treatment of the atomic diffusion in a magnetized stellar atmosphere - by direct comparison with observations as well by testing the widely used surface mapping tools with the spectral line profiles predicted by this theory. We show that the mean abundances of Fe and Cr are grossly underestimated by the time-dependent theoretical diffusion model, with discrepancies reaching a factor of 1000 for Cr. We also demonstrate that Doppler imaging inversion codes, based either on modelling of individual metal lines or line-averaged profiles simulated according to theoretical three-dimensional abundance distribution, are able to reconstruct correct horizontal chemical spot maps despite ignoring the vertical abundance variation. These numerical experiments justify a direct comparison of the empirical two-dimensional Doppler maps with theoretical diffusion calculations. This comparison is generally unfavourable for the current diffusion theory, as very few chemical elements are observed to form overabundance rings in the horizontal field regions as predicted by the theory and there are numerous examples of element accumulations in the vicinity of radial field zones, which cannot be explained by diffusion calculations.

Calculation of the second term of the exact Green's function of the diffusion equation for diffusion-controlled chemical reactions

NASA Astrophysics Data System (ADS)

Plante, Ianik

2016-01-01

The exact Green's function of the diffusion equation (GFDE) is often considered to be the gold standard for the simulation of partially diffusion-controlled reactions. As the GFDE with angular dependency is quite complex, the radial GFDE is more often used. Indeed, the exact GFDE is expressed as a Legendre expansion, the coefficients of which are given in terms of an integral comprising Bessel functions. This integral does not seem to have been evaluated analytically in existing literature. While the integral can be evaluated numerically, the Bessel functions make the integral oscillate and convergence is difficult to obtain. Therefore it would be of great interest to evaluate the integral analytically. The first term was evaluated previously, and was found to be equal to the radial GFDE. In this work, the second term of this expansion was evaluated. As this work has shown that the first two terms of the Legendre polynomial expansion can be calculated analytically, it raises the question of the possibility that an analytical solution exists for the other terms.

Accurate and reproducible functional maps in 127 human cell types via 2D genome segmentation

PubMed Central

Hardison, Ross C.

2017-01-01

Abstract The Roadmap Epigenomics Consortium has published whole-genome functional annotation maps in 127 human cell types by integrating data from studies of multiple epigenetic marks. These maps have been widely used for studying gene regulation in cell type-specific contexts and predicting the functional impact of DNA mutations on disease. Here, we present a new map of functional elements produced by applying a method called IDEAS on the same data. The method has several unique advantages and outperforms existing methods, including that used by the Roadmap Epigenomics Consortium. Using five categories of independent experimental datasets, we compared the IDEAS and Roadmap Epigenomics maps. While the overall concordance between the two maps is high, the maps differ substantially in the prediction details and in their consistency of annotation of a given genomic position across cell types. The annotation from IDEAS is uniformly more accurate than the Roadmap Epigenomics annotation and the improvement is substantial based on several criteria. We further introduce a pipeline that improves the reproducibility of functional annotation maps. Thus, we provide a high-quality map of candidate functional regions across 127 human cell types and compare the quality of different annotation methods in order to facilitate biomedical research in epigenomics. PMID:28973456

Functional imaging of small tissue volumes with diffuse optical tomography

NASA Astrophysics Data System (ADS)

Klose, Alexander D.; Hielscher, Andreas H.

2006-03-01

Imaging of dynamic changes in blood parameters, functional brain imaging, and tumor imaging are the most advanced application areas of diffuse optical tomography (DOT). When dealing with the image reconstruction problem one is faced with the fact that near-infrared photons, unlike X-rays, are highly scattered when they traverse biological tissue. Image reconstruction schemes are required that model the light propagation inside biological tissue and predict measurements on the tissue surface. By iteratively changing the tissue-parameters until the predictions agree with the real measurements, a spatial distribution of optical properties inside the tissue is found. The optical properties can be related to the tissue oxygenation, inflammation, or to the fluorophore concentration of a biochemical marker. If the model of light propagation is inaccurate, the reconstruction process will lead to an inaccurate result as well. Here, we focus on difficulties that are encountered when DOT is employed for functional imaging of small tissue volumes, for example, in cancer studies involving small animals, or human finger joints for early diagnosis of rheumatoid arthritis. Most of the currently employed image reconstruction methods rely on the diffusion theory that is an approximation to the equation of radiative transfer. But, in the cases of small tissue volumes and tissues that contain low scattering regions diffusion theory has been shown to be of limited applicability Therefore, we employ a light propagation model that is based on the equation of radiative transfer, which promises to overcome the limitations.

Granger-causality maps of diffusion processes.

PubMed

Wahl, Benjamin; Feudel, Ulrike; Hlinka, Jaroslav; Wächter, Matthias; Peinke, Joachim; Freund, Jan A

2016-02-01

Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes.

Comparison of Absolute Apparent Diffusion Coefficient (ADC) Values in ADC Maps Generated Across Different Postprocessing Software: Reproducibility in Endometrial Carcinoma.

PubMed

Ghosh, Adarsh; Singh, Tulika; Singla, Veenu; Bagga, Rashmi; Khandelwal, Niranjan

2017-12-01

Apparent diffusion coefficient (ADC) maps are usually generated by builtin software provided by the MRI scanner vendors; however, various open-source postprocessing software packages are available for image manipulation and parametric map generation. The purpose of this study is to establish the reproducibility of absolute ADC values obtained using different postprocessing software programs. DW images with three b values were obtained with a 1.5-T MRI scanner, and the trace images were obtained. ADC maps were automatically generated by the in-line software provided by the vendor during image generation and were also separately generated on postprocessing software. These ADC maps were compared on the basis of ROIs using paired t test, Bland-Altman plot, mountain plot, and Passing-Bablok regression plot. There was a statistically significant difference in the mean ADC values obtained from the different postprocessing software programs when the same baseline trace DW images were used for the ADC map generation. For using ADC values as a quantitative cutoff for histologic characterization of tissues, standardization of the postprocessing algorithm is essential across processing software packages, especially in view of the implementation of vendor-neutral archiving.

The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI)

PubMed Central

Makris, Nikos; Gasic, Gregory P.; Garrido, Leoncio

2014-01-01

Measurements of water molecule diffusion along fiber tracts in CNS by diffusion tensor imaging (DTI) provides a static map of neural connections between brain centers, but does not capture the electrical activity along axons for these fiber tracts. Here, a modification of the DTI method is presented to enable the mapping of active fibers. It is termed dynamic diffusion tensor imaging (dDTI) and is based on a hypothesized “anisotropy reduction due to axonal excitation” (“AREX”). The potential changes in water mobility accompanying the movement of ions during the propagation of action potentials along axonal tracts are taken into account. Specifically, the proposed model, termed “ionic DTI model”, was formulated as follows.•First, based on theoretical calculations, we calculated the molecular water flow accompanying the ionic flow perpendicular to the principal axis of fiber tracts produced by electrical conduction along excited myelinated and non-myelinated axons.•Based on the changes in molecular water flow we estimated the signal changes as well as the changes in fractional anisotropy of axonal tracts while performing a functional task.•The variation of fractional anisotropy in axonal tracts could allow mapping the active fiber tracts during a functional task. Although technological advances are necessary to enable the robust and routine measurement of this electrical activity-dependent movement of water molecules perpendicular to axons, the proposed model of dDTI defines the vectorial parameters that will need to be measured to bring this much needed technique to fruition. PMID:25431757

Concepts of soil mapping as a basis for the assessment of soil functions

NASA Astrophysics Data System (ADS)

Baumgarten, Andreas

2014-05-01

Soil mapping systems in Europe have been designed mainly as a tool for the description of soil characteristics from a morphogenetic viewpoint. Contrasting to the American or FAO system, the soil development has been in the main focus of European systems. Nevertheless , recent developments in soil science stress the importance of the functions of soils with respect to the ecosystems. As soil mapping systems usually offer a sound and extensive database, the deduction of soil functions from "classic" mapping parameters can be used for local and regional assessments. According to the used pedo-transfer functions and mapping systems, tailored approaches can be chosen for different applications. In Austria, a system mainly for spatial planning purposes has been developed that will be presented and illustrated by means of best practice examples.

Mapping the parameter space of a T2-dependent model of water diffusion MR in brain tissue.

PubMed

Hansen, Brian; Vestergaard-Poulsen, Peter

2006-10-01

We present a new model for describing the diffusion-weighted (DW) proton nuclear magnetic resonance signal obtained from normal grey matter. Our model is analytical and, in some respects, is an extension of earlier model schemes. We model tissue as composed of three separate compartments with individual properties of diffusion and transverse relaxation. Our study assumes slow exchange between compartments. We attempt to take cell morphology into account, along with its effect on water diffusion in tissues. Using this model, we simulate diffusion-sensitive MR signals and compare model output to experimental data from human grey matter. In doing this comparison, we perform a global search for good fits in the parameter space of the model. The characteristic nonmonoexponential behavior of the signal as a function of experimental b value is reproduced quite well, along with established values for tissue-specific parameters such as volume fraction, tortuosity and apparent diffusion coefficient. We believe that the presented approach to modeling diffusion in grey matter adds new aspects to the treatment of a longstanding problem.

Brain functional BOLD perturbation modelling for forward fMRI and inverse mapping

PubMed Central

Robinson, Jennifer; Calhoun, Vince

2018-01-01

Purpose To computationally separate dynamic brain functional BOLD responses from static background in a brain functional activity for forward fMRI signal analysis and inverse mapping. Methods A brain functional activity is represented in terms of magnetic source by a perturbation model: χ = χ0 +δχ, with δχ for BOLD magnetic perturbations and χ0 for background. A brain fMRI experiment produces a timeseries of complex-valued images (T2* images), whereby we extract the BOLD phase signals (denoted by δP) by a complex division. By solving an inverse problem, we reconstruct the BOLD δχ dataset from the δP dataset, and the brain χ distribution from a (unwrapped) T2* phase image. Given a 4D dataset of task BOLD fMRI, we implement brain functional mapping by temporal correlation analysis. Results Through a high-field (7T) and high-resolution (0.5mm in plane) task fMRI experiment, we demonstrated in detail the BOLD perturbation model for fMRI phase signal separation (P + δP) and reconstructing intrinsic brain magnetic source (χ and δχ). We also provided to a low-field (3T) and low-resolution (2mm) task fMRI experiment in support of single-subject fMRI study. Our experiments show that the δχ-depicted functional map reveals bidirectional BOLD χ perturbations during the task performance. Conclusions The BOLD perturbation model allows us to separate fMRI phase signal (by complex division) and to perform inverse mapping for pure BOLD δχ reconstruction for intrinsic functional χ mapping. The full brain χ reconstruction (from unwrapped fMRI phase) provides a new brain tissue image that allows to scrutinize the brain tissue idiosyncrasy for the pure BOLD δχ response through an automatic function/structure co-localization. PMID:29351339

Adaptive mapping functions to the azimuthal anisotropy of the neutral atmosphere

NASA Astrophysics Data System (ADS)

Gegout, P.; Biancale, R.; Soudarin, L.

2011-10-01

The anisotropy of propagation of radio waves used by global navigation satellite systems is investigated using high-resolution observational data assimilations produced by the European Centre for Medium-range Weather Forecast. The geometry and the refractivity of the neutral atmosphere are built introducing accurate geodetic heights and continuous formulations of the refractivity and its gradient. Hence the realistic ellipsoidal shape of the refractivity field above the topography is properly represented. Atmospheric delays are obtained by ray-tracing through the refractivity field, integrating the eikonal differential system. Ray-traced delays reveal the anisotropy of the atmosphere. With the aim to preserve the classical mapping function strategy, mapping functions can evolve to adapt to high-frequency atmospheric fluctuations and to account for the anisotropy of propagation by fitting at each site and time the zenith delays and the mapping functions coefficients. Adaptive mapping functions (AMF) are designed with coefficients of the continued fraction form which depend on azimuth. The basic idea is to expand the azimuthal dependency of the coefficients in Fourier series introducing a multi-scale azimuthal decomposition which slightly changes the elevation functions with the azimuth. AMF are used to approximate thousands of atmospheric ray-traced delays using a few tens of coefficients. Generic recursive definitions of the AMF and their partial derivatives lead to observe that the truncation of the continued fraction form at the third term and the truncation of the azimuthal Fourier series at the fourth term are sufficient in usual meteorological conditions. Delays' and elevations' mapping functions allow to store and to retrieve the ray-tracing results to solve the parallax problem at the observation level. AMF are suitable to fit the time-variable isotropic and anisotropic parts of the ray-traced delays at each site at each time step and to provide GPS range

Density functional calculation of activation energies for lattice and grain boundary diffusion in alumina

NASA Astrophysics Data System (ADS)

Lei, Yinkai; Gong, Yu; Duan, Zhiyao; Wang, Guofeng

2013-06-01

To acquire knowledge on the lattice and grain boundary diffusion processes in alumina, we have determined the activation energies of elementary O and Al diffusive jumps in the bulk crystal, Σ3(0001) grain boundaries, and Σ3(101¯0) grain boundaries of α-Al2O3 using the first-principles density functional theory method. Specifically, we calculated the activation energies for four elementary jumps of both O and Al lattice diffusion in alumina. It was predicted that the activation energy of O lattice diffusion varied from 3.58 to 5.03 eV, while the activation energy of Al lattice diffusion ranged from 1.80 to 3.17 eV. As compared with experimental measurements, the theoretical predictions of the activation energy for lattice diffusion were lower and thus implied that there might be other high-energy diffusive jumps in the experimental alumina samples. Moreover, our results suggested that the Al lattice diffusion was faster than the O lattice diffusion in alumina, in agreement with experiment observations. Furthermore, it was found from our calculations for α-Al2O3 that the activation energies of O and Al grain boundary diffusion in the high-energy Σ3(0001) grain boundaries were significantly lower than those of the lattice diffusion. In contrast, the activation energies of O and Al grain boundary diffusion in the low-energy Σ3(101¯0) grain boundaries could be even higher than those of the lattice diffusion.

Functional organization of glomerular maps in the mouse accessory olfactory bulb

PubMed Central

Hammen, Gary F.; Turaga, Diwakar; Holy, Timothy E.; Meeks, Julian P.

2014-01-01

Summary The mammalian accessory olfactory system (AOS) extracts information about species, sex, and individual identity from social odors, but its functional organization remains unclear. We imaged presynaptic Ca2+ signals in vomeronasal inputs to the accessory olfactory bulb (AOB) during peripheral stimulation using light sheet microscopy. Urine- and steroid-responsive glomeruli densely innervated the anterior AOB. Glomerular activity maps for sexually mature female mouse urine overlapped maps for juvenile and/or gonadectomized urine of both sexes, whereas maps for sexually mature male urine were highly distinct. Further spatial analysis revealed a complicated organization involving selective juxtaposition and dispersal of functionally-grouped glomerular classes. Glomeruli that were similarly tuned to urines were often closely associated, whereas more disparately tuned glomeruli were selectively dispersed. Maps to a panel of sulfated steroid odorants identified tightly-juxtaposed groups that were disparately tuned and dispersed groups that were similarly tuned. These results reveal a modular, non-chemotopic spatial organization in the AOB. PMID:24880215

Structural and functional connectivity mapping of the vestibular circuitry from human brainstem to cortex.

PubMed

Kirsch, V; Keeser, D; Hergenroeder, T; Erat, O; Ertl-Wagner, B; Brandt, T; Dieterich, M

2016-04-01

Structural and functional interconnections of the bilateral central vestibular network have not yet been completely delineated. This includes both ipsilateral and contralateral pathways and crossing sites on the way from the vestibular nuclei via the thalamic relay stations to multiple "vestibular cortex" areas. This study investigated "vestibular" connectivity in the living human brain in between the vestibular nuclei and the parieto-insular vestibular cortex (PIVC) by combined structural and functional connectivity mapping using diffusion tensor imaging and functional connectivity magnetic resonance imaging in 24 healthy right-handed volunteers. We observed a congruent functional and structural link between the vestibular nuclei and the ipsilateral and contralateral PIVC. Five separate and distinct vestibular pathways were identified: three run ipsilaterally, while the two others cross either in the pons or the midbrain. Two of the ipsilateral projections run through the posterolateral or paramedian thalamic subnuclei, while the third bypasses the thalamus to reach the inferior part of the insular cortex directly. Both contralateral pathways travel through the posterolateral thalamus. At the cortical level, the PIVC regions of both hemispheres with a right hemispherical dominance are interconnected transcallosally through the antero-caudal splenium. The above-described bilateral vestibular circuitry in its entirety takes the form of a structure of a rope ladder extending from the brainstem to the cortex with three crossings in the brainstem (vestibular nuclei, pons, midbrain), none at thalamic level and a fourth cortical crossing through the splenium of the corpus callosum.

Functional-Based Resection Does Not Worsen Quality of Life in Patients with a Diffuse Low-Grade Glioma Involving Eloquent Brain Regions: A Prospective Cohort Study.

PubMed

Muto, Jun; Dezamis, Edouard; Rigaux-Viode, Odile; Peeters, Sophie; Roux, Alexandre; Zanello, Marc; Mellerio, Charles; Sauvageon, Xavier; Varlet, Pascale; Oppenheim, Catherine; Pallud, Johan

2018-05-01

We assessed the impact of surgery on postoperative cognitive function and ability to work in adult patients with a diffuse low-grade glioma involving eloquent brain regions and having a functional-based maximal surgical resection using intraoperative corticosubcortical mapping under awake conditions. We prospectively included 39 consecutive patients with diffuse isocitrate dehydrogenase-mutant low-grade glioma without preoperative and adjuvant oncologic treatment and assessed preoperative (mean, 24.1 ± 21.2 days before surgery) and postoperative (mean, 14.6 ± 13.2 months after surgery) cognitive evaluations and ability to work together with clinical, imaging, therapeutic, and follow-up characteristics before tumor progression. None of the 3 patients without preoperative cognitive deficit had postoperative worsening. We observed a significant inverse interaction between worsened postoperative cognitive function and extent of resection: 80.0%, 18.8%, and 16.7% of worsening after partial, subtotal, and total resection, respectively (P = 0.020). We observed an independent interaction between improved postoperative cognitive function and extent of resection: 20.0%, 43.7%, and 44.4% of improvement after partial, subtotal, and total resection, respectively (P = 0.022). Of the employed patients, 61.8% were unable to work preoperatively and 82.4% resumed their employment postoperatively (mean, 6.9 ± 5.5 months). We observed an independent interaction between postoperative ability to work, similar or superior to preoperative work capacity and extent of resection (P < 0.001): 20.0%, 87.5%, and 100% ability to work after partial, subtotal resection, and total resection. The extent of the functional-based surgical resection and the residual tumor for diffuse low-grade gliomas involving eloquent brain regions correlate with postoperative cognitive outcomes and return to work rates. Copyright © 2018 Elsevier Inc. All rights reserved.

Diffusion and ADC-map images detect ongoing demyelination on subcortical white matter in an adult metachromatic leukodystrophy patient with autoimmune Hashimoto thyroiditis

PubMed Central

Miura, Akiko; Kumabe, Yuri; Kimura, En; Yamashita, Satoshi; Ueda, Akihiko; Hirano, Teruyuki; Uchino, Makoto

2010-01-01

Adult-onset metachromatic leukodystrophy (MLD) often shows schizophrenia- or encephalopathy-like symptoms at an early stage, such as behavioural abnormalities, cognitive impairment, mood disorders and hallucinations. The authors report the case of an adult woman with MLD who had been given antipsychotic medication for schizophrenia. In the differential diagnosis, screening of auto-antibodies was important for ruling out other encephalopathies as she had a euthyroid Hashimoto thyroiditis. Diagnosis was based the results of MRI, nerve conduction velocity, sensory evoked potential, motor evoked potential, lysosomal enzyme activity and gene analysis studies. Brain MRI showed diffuse demyelination spreading from the deep white matter to subcortical area as high signals at the edges of these lesions in diffusion and apparent diffusion coefficient-map images with the U-fibres conserved. The authors diagnosed adult-onset MLD coexisting with euthyroid autoimmune Hashimoto thyroiditis. PMID:22798296

Mapping Resource Selection Functions in Wildlife Studies: Concerns and Recommendations

PubMed Central

Morris, Lillian R.; Proffitt, Kelly M.; Blackburn, Jason K.

2018-01-01

Predicting the spatial distribution of animals is an important and widely used tool with applications in wildlife management, conservation, and population health. Wildlife telemetry technology coupled with the availability of spatial data and GIS software have facilitated advancements in species distribution modeling. There are also challenges related to these advancements including the accurate and appropriate implementation of species distribution modeling methodology. Resource Selection Function (RSF) modeling is a commonly used approach for understanding species distributions and habitat usage, and mapping the RSF results can enhance study findings and make them more accessible to researchers and wildlife managers. Currently, there is no consensus in the literature on the most appropriate method for mapping RSF results, methods are frequently not described, and mapping approaches are not always related to accuracy metrics. We conducted a systematic review of the RSF literature to summarize the methods used to map RSF outputs, discuss the relationship between mapping approaches and accuracy metrics, performed a case study on the implications of employing different mapping methods, and provide recommendations as to appropriate mapping techniques for RSF studies. We found extensive variability in methodology for mapping RSF results. Our case study revealed that the most commonly used approaches for mapping RSF results led to notable differences in the visual interpretation of RSF results, and there is a concerning disconnect between accuracy metrics and mapping methods. We make 5 recommendations for researchers mapping the results of RSF studies, which are focused on carefully selecting and describing the method used to map RSF studies, and relating mapping approaches to accuracy metrics. PMID:29887652

In vivo inflammation mapping of periodontal disease based on diffuse reflectance spectral imaging: a clinical study

NASA Astrophysics Data System (ADS)

Prasanth, Chandra Sekhar; Betsy, Joseph; Jayanthi, Jayaraj L.; Nisha, Unni G.; Prasantila, Janam; Subhash, Narayanan

2013-02-01

Since conventional techniques using periodontal probes have inherent drawbacks in the diagnosis of different grades of gingival inflammation, development of noninvasive screening devices becomes significant. Diffuse reflectance (DR) spectra recorded with white light illumination is utilized to detect periodontal inflammation from the oxygenated hemoglobin absorption ratio R620/R575. A multispectral imaging system is utilized to record narrow-band DR images at 575 and 620 nm from the anterior sextant of the gingivia of 15 healthy volunteers and 25 patients (N=40). An experienced periodontist assesses the level of gingival inflammation at each site through periodontal probing and assigns diagnosis as healthy, mild, moderate, or severe inflammation. The DR image ratio R620/R575 computed for each pixel (8-μm resolution) from the monochrome images is pseudo-color-mapped to identify gingival inflammation sites. The DR image ratio values at each site are compared with clinical diagnosis to estimate the specificity and sensitivity of the DR imaging technique in inflammation mapping. The high diagnostic accuracy is utilized to detect underlying inflammation in six patients with a previous history of periodontitis.

Molecules in motion: influences of diffusion on metabolic structure and function in skeletal muscle.

PubMed

Kinsey, Stephen T; Locke, Bruce R; Dillaman, Richard M

2011-01-15

Metabolic processes are often represented as a group of metabolites that interact through enzymatic reactions, thus forming a network of linked biochemical pathways. Implicit in this view is that diffusion of metabolites to and from enzymes is very fast compared with reaction rates, and metabolic fluxes are therefore almost exclusively dictated by catalytic properties. However, diffusion may exert greater control over the rates of reactions through: (1) an increase in reaction rates; (2) an increase in diffusion distances; or (3) a decrease in the relevant diffusion coefficients. It is therefore not surprising that skeletal muscle fibers have long been the focus of reaction-diffusion analyses because they have high and variable rates of ATP turnover, long diffusion distances, and hindered metabolite diffusion due to an abundance of intracellular barriers. Examination of the diversity of skeletal muscle fiber designs found in animals provides insights into the role that diffusion plays in governing both rates of metabolic fluxes and cellular organization. Experimental measurements of metabolic fluxes, diffusion distances and diffusion coefficients, coupled with reaction-diffusion mathematical models in a range of muscle types has started to reveal some general principles guiding muscle structure and metabolic function. Foremost among these is that metabolic processes in muscles do, in fact, appear to be largely reaction controlled and are not greatly limited by diffusion. However, the influence of diffusion is apparent in patterns of fiber growth and metabolic organization that appear to result from selective pressure to maintain reaction control of metabolism in muscle.

Molecules in motion: influences of diffusion on metabolic structure and function in skeletal muscle

PubMed Central

Kinsey, Stephen T.; Locke, Bruce R.; Dillaman, Richard M.

2011-01-01

Metabolic processes are often represented as a group of metabolites that interact through enzymatic reactions, thus forming a network of linked biochemical pathways. Implicit in this view is that diffusion of metabolites to and from enzymes is very fast compared with reaction rates, and metabolic fluxes are therefore almost exclusively dictated by catalytic properties. However, diffusion may exert greater control over the rates of reactions through: (1) an increase in reaction rates; (2) an increase in diffusion distances; or (3) a decrease in the relevant diffusion coefficients. It is therefore not surprising that skeletal muscle fibers have long been the focus of reaction–diffusion analyses because they have high and variable rates of ATP turnover, long diffusion distances, and hindered metabolite diffusion due to an abundance of intracellular barriers. Examination of the diversity of skeletal muscle fiber designs found in animals provides insights into the role that diffusion plays in governing both rates of metabolic fluxes and cellular organization. Experimental measurements of metabolic fluxes, diffusion distances and diffusion coefficients, coupled with reaction–diffusion mathematical models in a range of muscle types has started to reveal some general principles guiding muscle structure and metabolic function. Foremost among these is that metabolic processes in muscles do, in fact, appear to be largely reaction controlled and are not greatly limited by diffusion. However, the influence of diffusion is apparent in patterns of fiber growth and metabolic organization that appear to result from selective pressure to maintain reaction control of metabolism in muscle. PMID:21177946

Moho map of South America from receiver functions and surface waves

NASA Astrophysics Data System (ADS)

Lloyd, Simon; van der Lee, Suzan; FrançA, George Sand; AssumpçãO, Marcelo; Feng, Mei

2010-11-01

We estimate crustal structure and thickness of South America north of roughly 40°S. To this end, we analyzed receiver functions from 20 relatively new temporary broadband seismic stations deployed across eastern Brazil. In the analysis we include teleseismic and some regional events, particularly for stations that recorded few suitable earthquakes. We first estimate crustal thickness and average Poisson's ratio using two different stacking methods. We then combine the new crustal constraints with results from previous receiver function studies. To interpolate the crustal thickness between the station locations, we jointly invert these Moho point constraints, Rayleigh wave group velocities, and regional S and Rayleigh waveforms for a continuous map of Moho depth. The new tomographic Moho map suggests that Moho depth and Moho relief vary slightly with age within the Precambrian crust. Whether or not a positive correlation between crustal thickness and geologic age is derived from the pre-interpolation point constraints depends strongly on the selected subset of receiver functions. This implies that using only pre-interpolation point constraints (receiver functions) inadequately samples the spatial variation in geologic age. The new Moho map also reveals an anomalously deep Moho beneath the oldest core of the Amazonian Craton.

Catchment Models and Management Tools for diffuse Contaminants (Sediment, Phosphorus and Pesticides): DIFFUSE Project

NASA Astrophysics Data System (ADS)

Mockler, Eva; Reaney, Simeon; Mellander, Per-Erik; Wade, Andrew; Collins, Adrian; Arheimer, Berit; Bruen, Michael

2017-04-01

The agricultural sector is the most common suspected source of nutrient pollution in Irish rivers. However, it is also often the most difficult source to characterise due to its predominantly diffuse nature. Particulate phosphorus in surface water and dissolved phosphorus in groundwater are of particular concern in Irish water bodies. Hence the further development of models and indices to assess diffuse sources of contaminants are required for use by the Irish Environmental Protection Agency (EPA) to provide support for river basin planning. Understanding connectivity in the landscape is a vital component of characterising the source-pathway-receptor relationships for water-borne contaminants, and hence is a priority in this research. The DIFFUSE Project will focus on connectivity modelling and incorporation of connectivity into sediment, nutrient and pesticide risk mapping. The Irish approach to understanding and managing natural water bodies has developed substantially in recent years assisted by outputs from multiple research projects, including modelling and analysis tools developed during the Pathways and CatchmentTools projects. These include the Pollution Impact Potential (PIP) maps, which are an example of research output that is used by the EPA to support catchment management. The PIP maps integrate an understanding of the pollution pressures and mobilisation pathways and, using the source-pathways-receptor model, provide a scientific basis for evaluation of mitigation measures. These maps indicate the potential risk posed by nitrate and phosphate from diffuse agricultural sources to surface and groundwater receptors and delineate critical source areas (CSAs) as a means of facilitating the targeting of mitigation measures. Building on this previous research, the DIFFUSE Project will develop revised and new catchment managements tools focused on connectivity, sediment, phosphorus and pesticides. The DIFFUSE project will strive to identify the state

The Transition from Diffuse to Dense Gas in Herschel Dust Emission Maps

NASA Astrophysics Data System (ADS)

Goldsmith, Paul

Dense cores in dark clouds are the sites where young stars form. These regions manifest as relatively small (<0.1pc) pockets of cold and dense gas. If we wish to understand the star formation process, we have to understand the physical conditions in dense cores. This has been a main aim of star formation research in the past decade. Today, we do indeed possess a good knowledge of the density and velocity structure of cores, as well as their chemical evolution and physical lifetime. However, we do not understand well how dense cores form out of the diffuse gas clouds surrounding them. It is crucial that we constrain the relationship between dense cores and their environment: if we only understand dense cores, we may be able to understand how individual stars form --- but we would not know how the star forming dense cores themselves come into existence. We therefore propose to obtain data sets that reveal both dense cores and the clouds containing them in the same map. Based on these maps, we will study how dense cores form out of their natal clouds. Since cores form stars, this knowledge is crucial for the development of a complete theoretical and observational understanding of the formation of stars and their planets, as envisioned in NASA's Strategic Science Plan. Fortunately, existing archival data allow to derive exactly the sort of maps we need for our analysis. Here, we describe a program that exclusively builds on PACS and SPIRE dust emission imaging data from the NASA-supported Herschel mission. The degree-sized wide-field Herschel maps of the nearby (<260pc) Polaris Flare and Aquila Rift clouds are ideal for our work. They permit to resolve dense cores (<0.1pc), while the maps also reveal large-scale cloud structure (5pc and larger). We will generate column density maps from these dust emission maps and then run a tree-based hierarchical multi-scale structure analysis on them. Only this procedure permits to exploit the full potential of the maps: we will

Light source distribution and scattering phase function influence light transport in diffuse multi-layered media

NASA Astrophysics Data System (ADS)

Vaudelle, Fabrice; L'Huillier, Jean-Pierre; Askoura, Mohamed Lamine

2017-06-01

Red and near-Infrared light is often used as a useful diagnostic and imaging probe for highly scattering media such as biological tissues, fruits and vegetables. Part of diffusively reflected light gives interesting information related to the tissue subsurface, whereas light recorded at further distances may probe deeper into the interrogated turbid tissues. However, modelling diffusive events occurring at short source-detector distances requires to consider both the distribution of the light sources and the scattering phase functions. In this report, a modified Monte Carlo model is used to compute light transport in curved and multi-layered tissue samples which are covered with a thin and highly diffusing tissue layer. Different light source distributions (ballistic, diffuse or Lambertian) are tested with specific scattering phase functions (modified or not modified Henyey-Greenstein, Gegenbauer and Mie) to compute the amount of backscattered and transmitted light in apple and human skin structures. Comparisons between simulation results and experiments carried out with a multispectral imaging setup confirm the soundness of the theoretical strategy and may explain the role of the skin on light transport in whole and half-cut apples. Other computational results show that a Lambertian source distribution combined with a Henyey-Greenstein phase function provides a higher photon density in the stratum corneum than in the upper dermis layer. Furthermore, it is also shown that the scattering phase function may affect the shape and the magnitude of the Bidirectional Reflectance Distribution (BRDF) exhibited at the skin surface.

Diffusion Tensor Imaging of Frontal White Matter and Executive Functioning in Cocaine-Exposed Children

PubMed Central

Warner, Tamara Duckworth; Behnke, Marylou; Eyler, Fonda Davis; Padgett, Kyle; Leonard, Christiana; Hou, Wei; Garvan, Cynthia Wilson; Schmalfuss, Ilona M.; Blackband, Stephen J.

2011-01-01

BACKGROUND Although animal studies have demonstrated frontal white matter and behavioral changes resulting from prenatal cocaine exposure, no human studies have associated neuropsychological deficits in attention and inhibition with brain structure. We used diffusion tensor imaging to investigate frontal white matter integrity and executive functioning in cocaine-exposed children. METHODS Six direction diffusion tensor images were acquired using a Siemens 3T scanner with a spin-echo echo-planar imaging pulse sequence on right-handed cocaine-exposed (n = 28) and sociodemographically similar non-exposed children (n = 25; mean age: 10.6 years) drawn from a prospective, longitudinal study. Average diffusion and fractional anisotropy were measured in the left and right frontal callosal and frontal projection fibers. Executive functioning was assessed using two well-validated neuropsychological tests (Stroop color-word test and Trail Making Test). RESULTS Cocaine-exposed children showed significantly higher average diffusion in the left frontal callosal and right frontal projection fibers. Cocaine-exposed children were also significantly slower on a visual-motor set-shifting task with a trend toward lower scores on a verbal inhibition task. Controlling for gender and intelligence, average diffusion in the left frontal callosal fibers was related to prenatal exposure to alcohol and marijuana and an interaction between cocaine and marijuana exposure. Performance on the visual-motor set-shifting task was related to prenatal cocaine exposure and an interaction between cocaine and tobacco exposure. Significant correlations were found between test performance and fractional anisotropy in areas of the frontal white matter. CONCLUSIONS Prenatal cocaine exposure, alone and in combination with exposure to other drugs, is associated with slightly poorer executive functioning and subtle microstructural changes suggesting less mature development of frontal white matter pathways. The

Diffusion tensor imaging of frontal white matter and executive functioning in cocaine-exposed children.

PubMed

Warner, Tamara Duckworth; Behnke, Marylou; Eyler, Fonda Davis; Padgett, Kyle; Leonard, Christiana; Hou, Wei; Garvan, Cynthia Wilson; Schmalfuss, Ilona M; Blackband, Stephen J

2006-11-01

Although animal studies have demonstrated frontal white matter and behavioral changes resulting from prenatal cocaine exposure, no human studies have associated neuropsychological deficits in attention and inhibition with brain structure. We used diffusion tensor imaging to investigate frontal white matter integrity and executive functioning in cocaine-exposed children. Six direction diffusion tensor images were acquired using a Siemens 3T scanner with a spin-echo echo-planar imaging pulse sequence on right-handed cocaine-exposed (n = 28) and sociodemographically similar non-exposed children (n = 25; mean age: 10.6 years) drawn from a prospective, longitudinal study. Average diffusion and fractional anisotropy were measured in the left and right frontal callosal and frontal projection fibers. Executive functioning was assessed using two well-validated neuropsychological tests (Stroop color-word test and Trail Making Test). Cocaine-exposed children showed significantly higher average diffusion in the left frontal callosal and right frontal projection fibers. Cocaine-exposed children were also significantly slower on a visual-motor set-shifting task with a trend toward lower scores on a verbal inhibition task. Controlling for gender and intelligence, average diffusion in the left frontal callosal fibers was related to prenatal exposure to alcohol and marijuana and an interaction between cocaine and marijuana exposure. Performance on the visual-motor set-shifting task was related to prenatal cocaine exposure and an interaction between cocaine and tobacco exposure. Significant correlations were found between test performance and fractional anisotropy in areas of the frontal white matter. Prenatal cocaine exposure, alone and in combination with exposure to other drugs, is associated with slightly poorer executive functioning and subtle microstructural changes suggesting less mature development of frontal white matter pathways. The relative contribution of postnatal

Phonon Mapping in Flowing Equilibrium

NASA Astrophysics Data System (ADS)

Ruff, J. P. C.

2015-03-01

When a material conducts heat, a modification of the phonon population occurs. The equilibrium Bose-Einstein distribution is perturbed towards flowing-equilibrium, for which the distribution function is not analytically known. Here I argue that the altered phonon population can be efficiently mapped over broad regions of reciprocal space, via diffuse x-ray scattering or time-of-flight neutron scattering, while a thermal gradient is applied across a single crystal sample. When compared to traditional transport measurements, this technique offers a superior, information-rich new perspective on lattice thermal conductivity, wherein the band and momentum dependences of the phonon thermal current are directly resolved. The proposed method is benchmarked using x-ray thermal diffuse scattering measurements of single crystal diamond under transport conditions. CHESS is supported by the NSF & NIH/NIGMS via NSF Award DMR-1332208.

Carbon diffusion in solid iron as function of pressure and temperature

NASA Astrophysics Data System (ADS)

Stagno, V.; Crispin, K. L.; Fei, Y.

2012-12-01

pressure is required to affect the mobility of carbon through metallic iron by almost the same order of magnitude as cooling. The variation of the diffusion coefficient as function of temperature and pressure will be used to determine the activation energy and volume. It is known that the stability of carbide phases in the Earth's interior is mainly governed by the local Fe/C ratios. In the case of enriched mantle model, for instance, carbon in form of diamond will coexist with Fe7C3 for small amounts of metallic iron. In contrast, this would imply that at low carbon contents (<50 ppm) typical of a depleted mantle source, and at oxygen fugacity conditions lower than EMOD buffer, the transport of carbon will likely occur by diffusion through the coexisting metal phase. Results from this study will improve our understanding on the transport of carbon by diffusion at conditions of the Earth's interior and will provide new thermodynamic data to explain the fractionation of carbon by diffusion in other planetary bodies.

A survey of biofilms on wastewater aeration diffusers suggests bacterial community composition and function vary by substrate type and time.

PubMed

Noble, Peter A; Park, Hee-Deung; Olson, Betty H; Asvapathanagul, Pitiporn; Hunter, M Colby; Garrido-Baserba, Manel; Lee, Sang-Hoon; Rosso, Diego

2016-07-01

Aeration diffusers in wastewater treatment plants generate air bubbles that promote mixing, distribution of dissolved oxygen, and microbial processing of dissolved and suspended matter in bulk solution. Biofouling of diffusers represents a significant problem to wastewater treatment plants because biofilms decrease oxygen transfer efficiency and increase backpressure on the blower. To better understand biofouling, we conducted a pilot study to survey the bacterial community composition and function of biofilms on different diffuser substrates and compare them to those in the bulk solution. DNA was extracted from the surface of ethylene-propylene-diene monomer (EPDM), polyurethane, and silicone diffusers operated for 15 months in a municipal treatment plant and sampled at 3 and 9 months. The bacterial community composition and function of the biofilms and bulk solution were determined by amplifying the 16S rRNA genes and pyrosequencing the amplicons and raw metagenomic DNA. The ordination plots and dendrograms of the 16S rRNA and functional genes showed that while the bacterial community composition and function of the bulk solution was independent of sampling time, the composition and function of the biofilms differed by diffuser type and testing time. For the EPDM and silicone diffusers, the biofilm communities were more similar in composition to the bulk solution at 3 months than 9 months. In contrast, the bacteria on the polyurethane diffusers were more dissimilar to the bulk solution at 3 months than 9 months. Taken together, the survey showed that the community composition and function of bacterial biofilms depend on the diffuser substrate and testing time, which warrants further elucidation.

Evaluation of current tropospheric mapping functions by Deep Space Network very long baseline interferometry

NASA Technical Reports Server (NTRS)

Sovers, O. J.; Lanyi, G. E.

1994-01-01

To compare the validity of current algorithms that map zenith tropospheric delay to arbitrary elevation angles, 10 different tropospheric mapping functions are used to analyze the current data base of Deep Space Network Mark 3 intercontinental very long baseline interferometric (VLBI) data. This analysis serves as a stringent test because of the high proportion of low-elevation observations necessitated by the extremely long baselines. Postfit delay and delay-rate residuals are examined, as well as the scatter of baseline lengths about the time-linear model that characterizes tectonic motion. Among the functions that utilize surface meteorological data as input parameters, the Lanyi 1984 mapping shows the best performance both for residuals and baselines, through the 1985 Davis function is statistically nearly identical. The next best performance is shown by the recent function of Niell, which is based on an examination of global atmospheric characteristics as a function of season and uses no weather data at the time of the measurements. The Niell function shows a slight improvement in residuals relative to Lanyi, but also an increase in baseline scatter that is significant for the California-Spain baseline. Two variants of the Chao mapping function, as well as the Chao tables used with the interpolation algorithm employed in the Orbit Determination Program software, show substandard behavior for both VLBI residuals and baseline scatter. The length of the California-Australia baseline (10,600 km) in the VLBI solution can vary by as much as 5 to 10 cm for the 10 mapping functions.

Clinical feasibility of using mean apparent propagator (MAP) MRI to characterize brain tissue microstructure.

PubMed

Avram, Alexandru V; Sarlls, Joelle E; Barnett, Alan S; Özarslan, Evren; Thomas, Cibu; Irfanoglu, M Okan; Hutchinson, Elizabeth; Pierpaoli, Carlo; Basser, Peter J

2016-02-15

Diffusion tensor imaging (DTI) is the most widely used method for characterizing noninvasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its ability to describe intricate tissue microanatomy. Consequently, the biological interpretation of microstructural parameters, such as fractional anisotropy or mean diffusivity, is often equivocal. We evaluate the clinical feasibility of assessing brain tissue microstructure with mean apparent propagator (MAP) MRI, a powerful analytical framework that efficiently measures the probability density function (PDF) of spin displacements and quantifies useful metrics of this PDF indicative of diffusion in complex microstructure (e.g., restrictions, multiple compartments). Rotation invariant and scalar parameters computed from the MAP show consistent variation across neuroanatomical brain regions and increased ability to differentiate tissues with distinct structural and architectural features compared with DTI-derived parameters. The return-to-origin probability (RTOP) appears to reflect cellularity and restrictions better than MD, while the non-Gaussianity (NG) measures diffusion heterogeneity by comprehensively quantifying the deviation between the spin displacement PDF and its Gaussian approximation. Both RTOP and NG can be decomposed in the local anatomical frame for reference determined by the orientation of the diffusion tensor and reveal additional information complementary to DTI. The propagator anisotropy (PA) shows high tissue contrast even in deep brain nuclei and cortical gray matter and is more uniform in white matter than the FA, which drops significantly in regions containing crossing fibers. Orientational profiles of the propagator computed analytically from the MAP MRI series coefficients allow separation of different fiber populations in regions of crossing white matter pathways, which in turn improves our

Bidirectional reflection functions from surface bump maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cabral, B.; Max, N.; Springmeyer, R.

1987-04-29

The Torrance-Sparrow model for calculating bidirectional reflection functions contains a geometrical attenuation factor to account for shadowing and occlusions in a hypothetical distribution of grooves on a rough surface. Using an efficient table-based method for determining the shadows and occlusions, we calculate the geometric attenuation factor for surfaces defined by a specific table of bump heights. Diffuse and glossy specular reflection of the environment can be handled in a unified manner by using an integral of the bidirectional reflection function times the environmental illumination, over the hemisphere of solid angle above a surface. We present a method of estimating themore » integral, by expanding the bidirectional reflection coefficient in spherical harmonics, and show how the coefficients in this expansion can be determined efficiently by reorganizing our geometric attenuation calculation.« less

A Whole-Tumor Histogram Analysis of Apparent Diffusion Coefficient Maps for Differentiating Thymic Carcinoma from Lymphoma.

PubMed

Zhang, Wei; Zhou, Yue; Xu, Xiao-Quan; Kong, Ling-Yan; Xu, Hai; Yu, Tong-Fu; Shi, Hai-Bin; Feng, Qing

2018-01-01

To assess the performance of a whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating thymic carcinoma from lymphoma, and compare it with that of a commonly used hot-spot region-of-interest (ROI)-based ADC measurement. Diffusion weighted imaging data of 15 patients with thymic carcinoma and 13 patients with lymphoma were retrospectively collected and processed with a mono-exponential model. ADC measurements were performed by using a histogram-based and hot-spot-ROI-based approach. In the histogram-based approach, the following parameters were generated: mean ADC (ADC mean ), median ADC (ADC median ), 10th and 90th percentile of ADC (ADC 10 and ADC 90 ), kurtosis, and skewness. The difference in ADCs between thymic carcinoma and lymphoma was compared using a t test. Receiver operating characteristic analyses were conducted to determine and compare the differentiating performance of ADCs. Lymphoma demonstrated significantly lower ADC mean , ADC median , ADC 10 , ADC 90 , and hot-spot-ROI-based mean ADC than those found in thymic carcinoma (all p values < 0.05). There were no differences found in the kurtosis ( p = 0.412) and skewness ( p = 0.273). The ADC 10 demonstrated optimal differentiating performance (cut-off value, 0.403 × 10 -3 mm 2 /s; area under the receiver operating characteristic curve [AUC], 0.977; sensitivity, 92.3%; specificity, 93.3%), followed by the ADC mean , ADC median , ADC 90 , and hot-spot-ROI-based mean ADC. The AUC of ADC 10 was significantly higher than that of the hot spot ROI based ADC (0.977 vs. 0.797, p = 0.036). Compared with the commonly used hot spot ROI based ADC measurement, a histogram analysis of ADC maps can improve the differentiating performance between thymic carcinoma and lymphoma.

Functional localization of the human color center by decreased water displacement using diffusion-weighted fMRI.

PubMed

Williams, Rebecca J; Reutens, David C; Hocking, Julia

2015-11-01

Decreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear. Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex. At the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1. DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.

Diffusing diffusivity: Rotational diffusion in two and three dimensions

NASA Astrophysics Data System (ADS)

Jain, Rohit; Sebastian, K. L.

2017-06-01

We consider the problem of calculating the probability distribution function (pdf) of angular displacement for rotational diffusion in a crowded, rearranging medium. We use the diffusing diffusivity model and following our previous work on translational diffusion [R. Jain and K. L. Sebastian, J. Phys. Chem. B 120, 3988 (2016)], we show that the problem can be reduced to that of calculating the survival probability of a particle undergoing Brownian motion, in the presence of a sink. We use the approach to calculate the pdf for the rotational motion in two and three dimensions. We also propose new dimensionless, time dependent parameters, αr o t ,2 D and αr o t ,3 D, which can be used to analyze the experimental/simulation data to find the extent of deviation from the normal behavior, i.e., constant diffusivity, and obtain explicit analytical expressions for them, within our model.

Long-term calibration monitoring of Spectralon diffusers BRDF in the air-ultraviolet.

PubMed

Georgiev, Georgi T; Butler, James J

2007-11-10

Long-term calibration monitoring of the bidirectional reflectance distribution function (BRDF) of Spectralon diffusers in the air-ultraviolet is presented. Four Spectralon diffusers were monitored in this study. Three of the diffusers, designated as H1, H2, and H3, were used in the prelaunch radiance calibration of the Solar Backscatter Ultraviolet/2 (SBUV/2) satellite instruments on National Oceanic and Atmospheric Administration (NOAA) 14 and 16. A fourth diffuser, designated as the 400 diffuser, was used in the prelaunch calibration of the Ozone Mapping and Profiler Suite (OMPS) instrument scheduled for initial flight in 2009 on the National Polar Orbiting Environmental Satellite System Preparatory Project. The BRDF data of this study were obtained between 1994 and 2005 using the scatterometer located in the National Aeronautics and Space Administration Goddard Space Flight Center Diffuser Calibration Laboratory. The diffusers were measured at 13 wavelengths between 230 and 425 nm at the incident and scatter angles used in the prelaunch calibrations of SBUV/2 and OMPS. Spectral features in the BRDF of Spectralon are also discussed. The comparison shows how the air-ultraviolet BRDF of these Spectralon samples changed over time under clean room deployment conditions.

Intraoperative mapping of language functions: a longitudinal neurolinguistic analysis.

PubMed

Ilmberger, Josef; Ruge, Maximilian; Kreth, Friedrich-Wilhelm; Briegel, Josef; Reulen, Hans-Juergen; Tonn, Joerg-Christian

2008-10-01

This prospective longitudinally designed study was conducted to evaluate language functions pre- and postoperatively in patients who underwent microsurgical treatment of tumors in close proximity to or within language areas and to detect those patients at risk for a postoperative aphasic disturbance. Between 1991 and 2005, 153 awake craniotomies with subsequent cortical mapping of language functions were performed in 149 patients. Language functions were assessed using a standardized test battery. Risk factors were obtained from multivariate logistic regression models. Language mapping was able to be performed in all patients, and complete tumor resection was achieved in 48.4%. Within 21 days after surgery a new language deficit (aphasic disturbance) was observed in 41 (32%) of the 128 cases without preoperative deficits. There were a total of 60 cases involving postoperative aphasic disturbances, including cases both with and without preoperative disturbances. Risk factors for postoperative aphasic disturbance were preoperative aphasia (p<0.0002), intraoperative complications (p<0.02), language-positive sites within the tumor (p<0.001), and nonfrontal lesion location (p<0.001). In patients without a preoperative deficit, a normal (yet submaximal) naming performance was a powerful predictor for an early postoperative aphasic disturbance (p<0.0003). Seven months after treatment 10.9% of the 128 cases without preoperative aphasic disturbances continued to demonstrate new postoperative language disturbances. A total of 17.6% of all cases demonstrated new postoperative language disturbances after 7 months. Risk factors for persistent aphasic disturbance were increased age (>40 years, p<0.02) and preoperative aphasia (p<0.001). Every attempt should be undertaken to preserve language-relevant areas intraoperatively, even when they are located within the tumor. New postoperative deficits resolve in the majority of patients, which may be a result of cortical mapping as

Multiconfiguration Pair-Density Functional Theory Spectral Calculations Are Stable to Adding Diffuse Basis Functions.

PubMed

Hoyer, Chad E; Gagliardi, Laura; Truhlar, Donald G

2015-11-05

Time-dependent Kohn-Sham density functional theory (TD-KS-DFT) is useful for calculating electronic excitation spectra of large systems, but the low-energy spectra are often complicated by artificially lowered higher-energy states. This affects even the lowest energy excited states. Here, by calculating the lowest energy spin-conserving excited state for atoms from H to K and for formaldehyde, we show that this problem does not occur in multiconfiguration pair-density functional theory (MC-PDFT). We use the tPBE on-top density functional, which is a translation of the PBE exchange-correlation functional. We compare to a robust multireference method, namely, complete active space second-order perturbation theory (CASPT2), and to TD-KS-DFT with two popular exchange-correlation functionals, PBE and PBE0. We find for atoms that the mean unsigned error (MUE) of MC-PDFT with the tPBE functional improves from 0.42 to 0.40 eV with a double set of diffuse functions, whereas the MUEs for PBE and PBE0 drastically increase from 0.74 to 2.49 eV and from 0.45 to 1.47 eV, respectively.

Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps.

PubMed

Zhang, Yujuan; Chen, Jun; Liu, Song; Shi, Hua; Guan, Wenxian; Ji, Changfeng; Guo, Tingting; Zheng, Huanhuan; Guan, Yue; Ge, Yun; He, Jian; Zhou, Zhengyang; Yang, Xiaofeng; Liu, Tian

2017-02-01

To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer. Seventy-eight patients with gastric cancer were enrolled in a retrospective 3.0T magnetic resonance imaging (MRI) study. ADC maps were obtained at two different b values (0 and 1000 sec/mm 2 ) for each patient. Tumors were delineated on each slice of the ADC maps, and a histogram for the entire tumor volume was subsequently generated. A series of histogram parameters (eg, skew and kurtosis) were calculated and correlated with the histological grade of the surgical specimen. The diagnostic performance of each parameter for distinguishing poorly from moderately well-differentiated gastric cancers was assessed by using the area under the receiver operating characteristic curve (AUC). There were significant differences in the 5 th , 10 th , 25 th , and 50 th percentiles, skew, and kurtosis between poorly and well-differentiated gastric cancers (P < 0.05). There were correlations between the degrees of differentiation and histogram parameters, including the 10 th percentile, skew, kurtosis, and max frequency; the correlation coefficients were 0.273, -0.361, -0.339, and -0.370, respectively. Among all the histogram parameters, the max frequency had the largest AUC value, which was 0.675. Histogram analysis of the ADC maps on the basis of the entire tumor volume can be useful in differentiating between histological grades for gastric cancer. 4 J. Magn. Reson. Imaging 2017;45:440-449. © 2016 International Society for Magnetic Resonance in Medicine.

Self-diffusion on iridium (100). A structure investigation by field-ion microscopy

NASA Astrophysics Data System (ADS)

Friedl, A.; Schütz, O.; Müller, K.

1992-04-01

An iridium atom was thermally activated for diffusion on the (100) terrace of an Ir tip. The residence sites of the atom between diffusion cycles were recorded by means of a computer-controlled video system which generates a map of all occupied sites. For a field evaporated tip at low temperature this map is a c(2 × 2) grid indicating that only every other fourfold hollow in every other row of an undistor ted (100) surface can be occupied by a diffusing atom. This extraordinary behaviour was already reported by Chen and Tsong [Phys. Rev. Lett. 64 (1990) 3147]. The authors base their interpretation on an exchange diffusion mechanism. As an alternative explanation we propose a local adsorbate induced (2 × 2) reconstruction of the substrate. After heating the same terrace to temperatures above 500 K the residence map of the Ir atom indicates a (1 × 1) structure which, however, contains residues of a c(2 × 2) diffusion pattern: while the diffusion still takes place mainly on a c(2 × 2) sublattice, the diffusion path changes occasionally from one sublattice to the other. This can also be understood by local adsorbate induced distortions.

Histogram analysis of diffusion kurtosis imaging derived maps may distinguish between low and high grade gliomas before surgery.

PubMed

Qi, Xi-Xun; Shi, Da-Fa; Ren, Si-Xie; Zhang, Su-Ya; Li, Long; Li, Qing-Chang; Guan, Li-Ming

2018-04-01

To investigate the value of histogram analysis of diffusion kurtosis imaging (DKI) maps in the evaluation of glioma grading. A total of 39 glioma patients who underwent preoperative magnetic resonance imaging (MRI) were classified into low-grade (13 cases) and high-grade (26 cases) glioma groups. Parametric DKI maps were derived, and histogram metrics between low- and high-grade gliomas were analysed. The optimum diagnostic thresholds of the parameters, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were achieved using a receiver operating characteristic (ROC). Significant differences were observed not only in 12 metrics of histogram DKI parameters (P<0.05), but also in mean diffusivity (MD) and mean kurtosis (MK) values, including age as a covariate (F=19.127, P<0.001 and F=20.894, P<0.001, respectively), between low- and high-grade gliomas. Mean MK was the best independent predictor of differentiating glioma grades (B=18.934, 22.237 adjusted for age, P<0.05). The partial correlation coefficient between fractional anisotropy (FA) and kurtosis fractional anisotropy (KFA) was 0.675 (P<0.001). The AUC of the mean MK, sensitivity, and specificity were 0.925, 88.5% and 84.6%, respectively. DKI parameters can effectively distinguish between low- and high-grade gliomas. Mean MK is the best independent predictor of differentiating glioma grades. • DKI is a new and important method. • DKI can provide additional information on microstructural architecture. • Histogram analysis of DKI may be more effective in glioma grading.

Maps and Map Learning in Social Studies

ERIC Educational Resources Information Center

Bednarz, Sarah Witham; Acheson, Gillian; Bednarz, Robert S.

2006-01-01

The importance of maps and other graphic representations has become more important to geography and geographers. This is due to the development and widespread diffusion of geographic (spatial) technologies. As computers and silicon chips have become more capable and less expensive, geographic information systems (GIS), global positioning satellite…

Hybrid functional studies of stability and diffusion of hydrogen in Mg-doped GaN

NASA Astrophysics Data System (ADS)

Park, Ji-Sang; Chang, K. J.

2012-02-01

Nitride semiconductors are known to suffer from low p-type doping efficiency due to the high activation energy of Mg acceptors and the compensation of hole carriers. To enhance hole carrier concentration, the hydrogen co-doping method is widely used, in which hydrogen is intentionally doped with Mg dopants and removed by subsequent thermal annealing. In this work, we perform first-principles density functional calculations to study the stability and diffusion of hydrogen in Mg-doped GaN. For the exchange-correlation potential, we employ both the generalized gradient approximation (GGA) proposed by Perdew, Burke, and Ernzerhof and the hybrid density functional of Heyd, Scuseria, and Ernzerhof. We examine the diffusion pathways and dissociation barriers of H from the Mg-H complex using the nudged elastic band and dimer methods. We compare the results of the GGA and hybrid density functional calculations for the stability of various H interstitial configurations and the migration barriers for H diffusion. Finally, using the calculated migration barriers as inputs, we perform kinetic Monte Carlo simulations for the dissociation of the Mg-H complex and find that the Mg acceptors are activated by thermal annealing up to 700-800 ^oC, in good agreement with experiments.

Diffusion Tensor Imaging as a Predictor of Locomotor Function after Experimental Spinal Cord Injury and Recovery

PubMed Central

Kelley, Brian J.; Harel, Noam Y.; Kim, Chang-Yeon; Papademetris, Xenophon; Coman, Daniel; Wang, Xingxing; Hasan, Omar; Kaufman, Adam; Globinsky, Ronen; Staib, Lawrence H.; Cafferty, William B.J.; Hyder, Fahmeed

2014-01-01

Abstract Traumatic spinal cord injury (SCI) causes long-term disability with limited functional recovery linked to the extent of axonal connectivity. Quantitative diffusion tensor imaging (DTI) of axonal integrity has been suggested as a potential biomarker for prognostic and therapeutic evaluation after trauma, but its correlation with functional outcomes has not been clearly defined. To examine this application, female Sprague-Dawley rats underwent midthoracic laminectomy followed by traumatic spinal cord contusion of differing severities or laminectomy without contusion. Locomotor scores and hindlimb kinematic data were collected for 4 weeks post-injury. Ex vivo DTI was then performed to assess axonal integrity using tractography and fractional anisotropy (FA), a numerical measure of relative white matter integrity, at the injury epicenter and at specific intervals rostral and caudal to the injury site. Immunohistochemistry for tissue sparing was also performed. Statistical correlation between imaging data and functional performance was assessed as the primary outcome. All injured animals showed some recovery of locomotor function, while hindlimb kinematics revealed graded deficits consistent with injury severity. Standard T2 magnetic resonance sequences illustrated conventional spinal cord morphology adjacent to contusions while corresponding FA maps indicated graded white matter pathology within these adjacent regions. Positive correlations between locomotor (Basso, Beattie, and Bresnahan score and gait kinematics) and imaging (FA values) parameters were also observed within these adjacent regions, most strongly within caudal segments beyond the lesion. Evaluation of axonal injury by DTI provides a mechanism for functional recovery assessment in a rodent SCI model. These findings suggest that focused DTI analysis of caudal spinal cord should be studied in human cases in relationship to motor outcome to augment outcome biomarkers for clinical cases. PMID

A posteriori model validation for the temporal order of directed functional connectivity maps

PubMed Central

Beltz, Adriene M.; Molenaar, Peter C. M.

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data). PMID:26379489

A posteriori model validation for the temporal order of directed functional connectivity maps.

PubMed

Beltz, Adriene M; Molenaar, Peter C M

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data).

Forecast Vienna Mapping Functions 1 for real-time analysis of space geodetic observations

NASA Astrophysics Data System (ADS)

Boehm, J.; Kouba, J.; Schuh, H.

2009-05-01

The Vienna Mapping Functions 1 (VMF1) as provided by the Institute of Geodesy and Geophysics (IGG) at the Vienna University of Technology are the most accurate mapping functions for the troposphere delays that are available globally and for the entire history of space geodetic observations. So far, the VMF1 coefficients have been released with a time delay of almost two days; however, many scientific applications require their availability in near real-time, e.g. the Ultra Rapid solutions of the International GNSS Service (IGS) or the analysis of the Intensive sessions of the International VLBI Service (IVS). Here we present coefficients of the VMF1 as well as the hydrostatic and wet zenith delays that have been determined from forecasting data of the European Centre for Medium-Range Weather Forecasts (ECMWF) and provided on global grids. The comparison with parameters derived from ECMWF analysis data shows that the agreement is at the 1 mm level in terms of station height, and that the differences are larger for the wet mapping functions than for the hydrostatic mapping functions and the hydrostatic zenith delays. These new products (VMF1-FC and hydrostatic zenith delays from forecast data) can be used in real-time analysis of geodetic data without significant loss of accuracy.

FADTTSter: accelerating hypothesis testing with functional analysis of diffusion tensor tract statistics

NASA Astrophysics Data System (ADS)

Noel, Jean; Prieto, Juan C.; Styner, Martin

2017-03-01

Functional Analysis of Diffusion Tensor Tract Statistics (FADTTS) is a toolbox for analysis of white matter (WM) fiber tracts. It allows associating diffusion properties along major WM bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these WM tract properties. However, to use this toolbox, a user must have an intermediate knowledge in scripting languages (MATLAB). FADTTSter was created to overcome this issue and make the statistical analysis accessible to any non-technical researcher. FADTTSter is actively being used by researchers at the University of North Carolina. FADTTSter guides non-technical users through a series of steps including quality control of subjects and fibers in order to setup the necessary parameters to run FADTTS. Additionally, FADTTSter implements interactive charts for FADTTS' outputs. This interactive chart enhances the researcher experience and facilitates the analysis of the results. FADTTSter's motivation is to improve usability and provide a new analysis tool to the community that complements FADTTS. Ultimately, by enabling FADTTS to a broader audience, FADTTSter seeks to accelerate hypothesis testing in neuroimaging studies involving heterogeneous clinical data and diffusion tensor imaging. This work is submitted to the Biomedical Applications in Molecular, Structural, and Functional Imaging conference. The source code of this application is available in NITRC.

White Matter Connectivity of the Thalamus Delineates the Functional Architecture of Competing Thalamocortical Systems

PubMed Central

O'Muircheartaigh, Jonathan; Keller, Simon S.; Barker, Gareth J.; Richardson, Mark P.

2015-01-01

There is an increasing awareness of the involvement of thalamic connectivity on higher level cortical functioning in the human brain. This is reflected by the influence of thalamic stimulation on cortical activity and behavior as well as apparently cortical lesion syndromes occurring as a function of small thalamic insults. Here, we attempt to noninvasively test the correspondence of structural and functional connectivity of the human thalamus using diffusion-weighted and resting-state functional MRI. Using a large sample of 102 adults, we apply tensor independent component analysis to diffusion MRI tractography data to blindly parcellate bilateral thalamus according to diffusion tractography-defined structural connectivity. Using resting-state functional MRI collected in the same subjects, we show that the resulting structurally defined thalamic regions map to spatially distinct, and anatomically predictable, whole-brain functional networks in the same subjects. Although there was significant variability in the functional connectivity patterns, the resulting 51 structural and functional patterns could broadly be reduced to a subset of 7 similar core network types. These networks were distinct from typical cortical resting-state networks. Importantly, these networks were distributed across the brain and, in a subset, map extremely well to known thalamocortico-basal-ganglial loops. PMID:25899706

Whole-body diffusion kurtosis imaging: initial experience on non-Gaussian diffusion in various organs.

PubMed

Filli, Lukas; Wurnig, Moritz; Nanz, Daniel; Luechinger, Roger; Kenkel, David; Boss, Andreas

2014-12-01

Diffusion kurtosis imaging (DKI) is based on a non-Gaussian diffusion model that should inherently better account for restricted water diffusion within the complex microstructure of most tissues than the conventional diffusion-weighted imaging (DWI), which presumes Gaussian distributed water molecule displacement probability. The aim of this investigation was to test the technical feasibility of in vivo whole-body DKI, probe for organ-specific differences, and compare whole-body DKI and DWI results. Eight healthy subjects underwent whole-body DWI on a clinical 3.0 T magnetic resonance imaging system. Echo-planar images in the axial orientation were acquired at b-values of 0, 150, 300, 500, and 800 mm²/s. Parametrical whole-body maps of the diffusion coefficient (D), the kurtosis (K), and the traditional apparent diffusion coefficient (ADC) were generated. Goodness of fit was compared between DKI and DWI fits using the sums of squared residuals. Data groups were tested for significant differences of the mean by paired Student t tests. Good-quality parametrical whole-body maps of D, K, and ADC could be computed. Compared with ADC values, D values were significantly higher in the cerebral gray matter (by 30%) and white matter (27%), renal cortex (23%) and medulla (21%), spleen (101%), as well as erector spinae muscle (34%) (each P value <0.001). No significant differences between D and ADC were found in the cerebrospinal fluid (P = 0.08) and in the liver (P = 0.13). Curves of DKI fitted the measurement points significantly better than DWI curves did in most organs. Whole-body DKI is technically feasible and may reflect tissue microstructure more meaningfully than whole-body DWI.

Mapping for the management of diffuse pollution risks related to agricultural plant protection practices: case of the Etang de l'Or catchment area in France.

PubMed

Mghirbi, Oussama; Bord, Jean-Paul; Le Grusse, Philippe; Mandart, Elisabeth; Fabre, Jacques

2018-03-08

Faced with health, environmental, and socio-economic issues related to the heavy use of pesticides, diffuse phytosanitary pollution becomes a major concern shared by all the field actors. These actors, namely the farmers and territorial managers, have expressed the need to implement decision support tools for the territorial management of diffuse pollution resulting from the plant protection practices and their impacts. To meet these steadily increasing requests, a cartographic analysis approach was implemented based on GIS which allows the spatialization of the diffuse pollution impacts related to plant protection practices on the Etang de l'Or catchment area in the South of France. Risk mapping represents a support-decision tool that enables the different field actors to identify and locate vulnerable areas, so as to determine action plans and agri-environmental measures depending on the context of the natural environment. This work shows that mapping is helpful for managing risks related to the use of pesticides in agriculture by employing indicators of pressure (TFI) and risk on the applicator's health (IRSA) and on the environment (IRTE). These indicators were designed to assess the impact of plant protection practices at various spatial scales (field, farm, etc.). The cartographic analysis of risks related to plant protection practices shows that diffuse pollution is unequally located in the North (known for its abundant garrigues and vineyards) and in the South of the Etang de l'Or catchment area (the Mauguio-Lunel agricultural plain known for its diversified cropping systems). This spatial inequity is essentially related to land use and agricultural production system. Indeed, the agricultural lands cover about 60% of the total catchment area. Consequently, this cartographic analysis helps the territorial actors with the implementation of strategies for managing risks of diffuse pollution related to pesticides use in agriculture, based on environmental and

Myocardial function and perfusion in the CREST syndrome variant of progressive systemic sclerosis. Exercise radionuclide evaluation and comparison with diffuse scleroderma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Follansbee, W.P.; Curtiss, E.I.; Medsger, T.A. Jr.

1984-09-01

Myocardial function and perfusion were evaluated in 22 patients with progressive systemic sclerosis with the CREST syndrome using exercise and radionuclide techniques, pulmonary function testing, and chest roentgenography. The results were compared with a similar study of 26 patients with progressive systemic sclerosis with diffuse scleroderma. The prevalence of thallium perfusion abnormalities was similar in the groups with CREST syndrome and diffuse scleroderma, (64 percent versus 77 percent), but the defects were significantly smaller in the CREST syndrome (p less than 0.01). Reperfusion thallium defects in the absence of extramural coronary artery disease were seen in 38 percent of patientsmore » with diffuse scleroderma. This finding was not seen in any of the patients with the CREST syndrome. In diffuse scleroderma, abnormalities of both right and left ventricular function were related to larger thallium perfusion defects. In the CREST syndrome, abnormalities of left ventricular function were minor, were seen only during exercise, and were unrelated to thallium perfusion defects. Abnormal resting right ventricular function was seen in 36 percent of the patients with the CREST syndrome and was associated with an isolated decrease in diffusing capacity of carbon monoxide. It is concluded that the cardiac manifestations of the CREST syndrome are distinct from those found in diffuse scleroderma. Unlike diffuse scleroderma, abnormalities of left ventricular function in the CREST syndrome are minor and are unrelated to abnormalities of coronary perfusion. Right ventricular dysfunction in the CREST syndrome appears to be primarily related to pulmonary vascular disease.« less

3He Diffusion MRI of the Lung

PubMed Central

Conradi, Mark S.; Yablonskiy, Dmitriy A.; Woods, Jason C.; Gierada, David S.; Jacob, Richard E.; Chang, Yulin V.; Choong, Cliff K.; Sukstanskii, Alex L.; Tanoli, Tariq; Lefrak, Stephen S.; Cooper, Joel D.

2007-01-01

Rationale and Objectives MR imaging of the restricted diffusion of laser-polarized 3He gas provides unique insights into the changes in lung microstructure in emphysema. Results We discuss measurements of ventilation (spin density), mean diffusivity, and the anisotropy of diffusion, which yields the mean acinar airway radius. In addition, the use of spatially modulated longitudinal magnetization allows diffusion to be measured over longer distances and times, with sensitivity to collateral ventilation paths. Early results are also presented for spin density and diffusivity maps made with a perfluorinated inert gas, C3F8. Methods Techniques for purging and imaging excised lungs are discussed. PMID:16253852

Optimizing Filter-Probe Diffusion Weighting in the Rat Spinal Cord for Human Translation

PubMed Central

Budde, Matthew D.; Skinner, Nathan P.; Muftuler, L. Tugan; Schmit, Brian D.; Kurpad, Shekar N.

2017-01-01

Diffusion tensor imaging (DTI) is a promising biomarker of spinal cord injury (SCI). In the acute aftermath, DTI in SCI animal models consistently demonstrates high sensitivity and prognostic performance, yet translation of DTI to acute human SCI has been limited. In addition to technical challenges, interpretation of the resulting metrics is ambiguous, with contributions in the acute setting from both axonal injury and edema. Novel diffusion MRI acquisition strategies such as double diffusion encoding (DDE) have recently enabled detection of features not available with DTI or similar methods. In this work, we perform a systematic optimization of DDE using simulations and an in vivo rat model of SCI and subsequently implement the protocol to the healthy human spinal cord. First, two complementary DDE approaches were evaluated using an orientationally invariant or a filter-probe diffusion encoding approach. While the two methods were similar in their ability to detect acute SCI, the filter-probe DDE approach had greater predictive power for functional outcomes. Next, the filter-probe DDE was compared to an analogous single diffusion encoding (SDE) approach, with the results indicating that in the spinal cord, SDE provides similar contrast with improved signal to noise. In the SCI rat model, the filter-probe SDE scheme was coupled with a reduced field of view (rFOV) excitation, and the results demonstrate high quality maps of the spinal cord without contamination from edema and cerebrospinal fluid, thereby providing high sensitivity to injury severity. The optimized protocol was demonstrated in the healthy human spinal cord using the commercially-available diffusion MRI sequence with modifications only to the diffusion encoding directions. Maps of axial diffusivity devoid of CSF partial volume effects were obtained in a clinically feasible imaging time with a straightforward analysis and variability comparable to axial diffusivity derived from DTI. Overall, the

In Situ Three-Dimensional Reciprocal-Space Mapping of Diffuse Scattering Intensity Distribution and Data Analysis for Precursor Phenomenon in Shape-Memory Alloy

NASA Astrophysics Data System (ADS)

Cheng, Tian-Le; Ma, Fengde D.; Zhou, Jie E.; Jennings, Guy; Ren, Yang; Jin, Yongmei M.; Wang, Yu U.

2012-01-01

Diffuse scattering contains rich information on various structural disorders, thus providing a useful means to study the nanoscale structural deviations from the average crystal structures determined by Bragg peak analysis. Extraction of maximal information from diffuse scattering requires concerted efforts in high-quality three-dimensional (3D) data measurement, quantitative data analysis and visualization, theoretical interpretation, and computer simulations. Such an endeavor is undertaken to study the correlated dynamic atomic position fluctuations caused by thermal vibrations (phonons) in precursor state of shape-memory alloys. High-quality 3D diffuse scattering intensity data around representative Bragg peaks are collected by using in situ high-energy synchrotron x-ray diffraction and two-dimensional digital x-ray detector (image plate). Computational algorithms and codes are developed to construct the 3D reciprocal-space map of diffuse scattering intensity distribution from the measured data, which are further visualized and quantitatively analyzed to reveal in situ physical behaviors. Diffuse scattering intensity distribution is explicitly formulated in terms of atomic position fluctuations to interpret the experimental observations and identify the most relevant physical mechanisms, which help set up reduced structural models with minimal parameters to be efficiently determined by computer simulations. Such combined procedures are demonstrated by a study of phonon softening phenomenon in precursor state and premartensitic transformation of Ni-Mn-Ga shape-memory alloy.

From chemotaxis to the cognitive map: The function of olfaction

PubMed Central

Jacobs, Lucia F.

2012-01-01

A paradox of vertebrate brain evolution is the unexplained variability in the size of the olfactory bulb (OB), in contrast to other brain regions, which scale predictably with brain size. Such variability appears to be the result of selection for olfactory function, yet there is no obvious concordance that would predict the causal relationship between OB size and behavior. This discordance may derive from assuming the primary function of olfaction is odorant discrimination and acuity. If instead the primary function of olfaction is navigation, i.e., predicting odorant distributions in time and space, variability in absolute OB size could be ascribed and explained by variability in navigational demand. This olfactory spatial hypothesis offers a single functional explanation to account for patterns of olfactory system scaling in vertebrates, the primacy of olfaction in spatial navigation, even in visual specialists, and proposes an evolutionary scenario to account for the convergence in olfactory structure and function across protostomes and deuterostomes. In addition, the unique percepts of olfaction may organize odorant information in a parallel map structure. This could have served as a scaffold for the evolution of the parallel map structure of the mammalian hippocampus, and possibly the arthropod mushroom body, and offers an explanation for similar flexible spatial navigation strategies in arthropods and vertebrates. PMID:22723365

Clinical team functioning and IT innovation: a study of the diffusion of a point-of-care online evidence system.

PubMed

Gosling, A Sophie; Westbrook, Johanna I; Braithwaite, Jeffrey

2003-01-01

To investigate the association between clinical team functioning and diffusion (awareness, use, and impact) of a 24-hour online evidence retrieval system. To examine the relationships between clinical team characteristics and the adoption of the online evidence system. 18 clinical teams, consisting of 180 clinicians from three Australian hospitals, were identified and studied. Teams were categorized as small ( 15). Clinical team functioning was assessed using the Team Climate Inventory (TCI). Awareness, use, and impact of an online evidence retrieval system were measured using a self-administered questionnaire. The relationships between TCI scores and awareness, use, and impact were examined using t-tests and one-way ANOVAs. Chi square analyses were used to examine differences between small and large teams. RESULTS were interpreted within a diffusion of innovations framework. Clinical team functioning was not related to awareness or use of the online evidence retrieval system. However, clinical team functioning was significantly associated with the impact of online evidence in terms of reported experience of improved patient care following system use. Clinicians in small teams ( 15) teams. Team functioning had the greatest impact on the fourth stage of innovation diffusion, the effective use of online evidence for clinical care. This supports Rogers' diffusion of innovation theory, to the effect that different types of communication about an innovation are important at different stages in the diffusion process. Members of small teams were more aware of the system than members of large teams. Team functioning is amenable to improvement through interventions. The findings suggest that the role of team climate in the diffusion of information systems is a promising area for future research.

Generalized quantum Fokker-Planck, diffusion, and Smoluchowski equations with true probability distribution functions.

PubMed

Banik, Suman Kumar; Bag, Bidhan Chandra; Ray, Deb Shankar

2002-05-01

Traditionally, quantum Brownian motion is described by Fokker-Planck or diffusion equations in terms of quasiprobability distribution functions, e.g., Wigner functions. These often become singular or negative in the full quantum regime. In this paper a simple approach to non-Markovian theory of quantum Brownian motion using true probability distribution functions is presented. Based on an initial coherent state representation of the bath oscillators and an equilibrium canonical distribution of the quantum mechanical mean values of their coordinates and momenta, we derive a generalized quantum Langevin equation in c numbers and show that the latter is amenable to a theoretical analysis in terms of the classical theory of non-Markovian dynamics. The corresponding Fokker-Planck, diffusion, and Smoluchowski equations are the exact quantum analogs of their classical counterparts. The present work is independent of path integral techniques. The theory as developed here is a natural extension of its classical version and is valid for arbitrary temperature and friction (the Smoluchowski equation being considered in the overdamped limit).

Mapping the Mayo-Portland adaptability inventory to the international classification of functioning, disability and health.

PubMed

Lexell, Jan; Malec, James F; Jacobsson, Lars J

2012-01-01

To examine the contents of the Mayo-Portland Adaptability Inventory (MPAI-4) by mapping it to the International Classification of Functioning, Disability and Health (ICF). Each of the 30 scoreable items in the MPAI-4 was mapped to the most precise ICF categories. All 30 items could be mapped to components and categories in the ICF. A total of 88 meaningful concepts were identified. There were, on average, 2.9 meaningful concepts per item, and 65% of all concepts could be mapped. Items in the Ability and Adjustment subscales mapped to categories in both the Body Functions and Activity/Participation components of the ICF, whereas all except 1 in the Participation subscale were to categories in the Activity/Participation component. The items could also be mapped to 34 (13%) of the 258 Environmental Factors in the ICF. This mapping provides better definition through more concrete examples (as listed in the ICF) of the types of body functions, activities, and participation indicators that are represented by the 30 scoreable MPAI-4 items. This may assist users throughout the world in understanding the intent of each item, and support further development and the possibility to report results in the form of an ICF categorical profile, making it universally interpretable.

Seamless Warping of Diffusion Tensor Fields

PubMed Central

Hao, Xuejun; Bansal, Ravi; Plessen, Kerstin J.; Peterson, Bradley S.

2008-01-01

To warp diffusion tensor fields accurately, tensors must be reoriented in the space to which the tensors are warped based on both the local deformation field and the orientation of the underlying fibers in the original image. Existing algorithms for warping tensors typically use forward mapping deformations in an attempt to ensure that the local deformations in the warped image remains true to the orientation of the underlying fibers; forward mapping, however, can also create “seams” or gaps and consequently artifacts in the warped image by failing to define accurately the voxels in the template space where the magnitude of the deformation is large (e.g., |Jacobian| > 1). Backward mapping, in contrast, defines voxels in the template space by mapping them back to locations in the original imaging space. Backward mapping allows every voxel in the template space to be defined without the creation of seams, including voxels in which the deformation is extensive. Backward mapping, however, cannot reorient tensors in the template space because information about the directional orientation of fiber tracts is contained in the original, unwarped imaging space only, and backward mapping alone cannot transfer that information to the template space. To combine the advantages of forward and backward mapping, we propose a novel method for the spatial normalization of diffusion tensor (DT) fields that uses a bijection (a bidirectional mapping with one-to-one correspondences between image spaces) to warp DT datasets seamlessly from one imaging space to another. Once the bijection has been achieved and tensors have been correctly relocated to the template space, we can appropriately reorient tensors in the template space using a warping method based on Procrustean estimation. PMID:18334425

Assessment of myocardial fibrosis with T1 mapping MRI.

PubMed

Everett, R J; Stirrat, C G; Semple, S I R; Newby, D E; Dweck, M R; Mirsadraee, S

2016-08-01

Myocardial fibrosis can arise from a range of pathological processes and its presence correlates with adverse clinical outcomes. Cardiac magnetic resonance (CMR) can provide a non-invasive assessment of cardiac structure, function, and tissue characteristics, which includes late gadolinium enhancement (LGE) techniques to identify focal irreversible replacement fibrosis with a high degree of accuracy and reproducibility. Importantly the presence of LGE is consistently associated with adverse outcomes in a range of common cardiac conditions; however, LGE techniques are qualitative and unable to detect diffuse myocardial fibrosis, which is an earlier form of fibrosis preceding replacement fibrosis that may be reversible. Novel T1 mapping techniques allow quantitative CMR assessment of diffuse myocardial fibrosis with the two most common measures being native T1 and extracellular volume (ECV) fraction. Native T1 differentiates normal from infarcted myocardium, is abnormal in hypertrophic cardiomyopathy, and may be particularly useful in the diagnosis of Anderson-Fabry disease and amyloidosis. ECV is a surrogate measure of the extracellular space and is equivalent to the myocardial volume of distribution of the gadolinium-based contrast medium. It is reproducible and correlates well with fibrosis on histology. ECV is abnormal in patients with cardiac failure and aortic stenosis, and is associated with functional impairment in these groups. T1 mapping techniques promise to allow earlier detection of disease, monitor disease progression, and inform prognosis; however, limitations remain. In particular, reference ranges are lacking for T1 mapping values as these are influenced by specific CMR techniques and magnetic field strength. In addition, there is significant overlap between T1 mapping values in healthy controls and most disease states, particularly using native T1, limiting the clinical application of these techniques at present. Copyright © 2016 The Royal College

Relationship between regional cerebral metabolism and consciousness disturbance in traumatic diffuse brain injury without large focal lesions: an FDG-PET study with statistical parametric mapping analysis.

PubMed

Nakayama, N; Okumura, A; Shinoda, J; Nakashima, T; Iwama, T

2006-07-01

The cerebral metabolism of patients in the chronic stage of traumatic diffuse brain injury (TDBI) has not been fully investigated. To study the relationship between regional cerebral metabolism (rCM) and consciousness disturbance in patients with TDBI. 52 patients with TDBI in the chronic stage without large focal lesions were enrolled, and rCM was evaluated by fluorine-18-fluorodeoxyglucose positron emission tomography (FDG-PET) with statistical parametric mapping (SPM). All the patients were found to have disturbed consciousness or cognitive function and were divided into the following three groups: group A (n = 22), patients in a state with higher brain dysfunction; group B (n = 13), patients in a minimally conscious state; and group C (n = 17), patients in a vegetative state. rCM patterns on FDG-PET among these groups were evaluated and compared with those of normal control subjects on statistical parametric maps. Hypometabolism was consistently indicated bilaterally in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus. Hypometabolism in these regions was the most widespread and prominent in group C, and that in group B was more widespread and prominent than that in group A. Bilateral hypometabolism in the medial prefrontal regions, the medial frontobasal regions, the cingulate gyrus and the thalamus may reflect the clinical deterioration of TDBI, which is due to functional and structural disconnections of neural networks rather than due to direct cerebral focal contusion.

Chronic Diffuse Pain and Functional Gastrointestinal Disorders After Traumatic Stress: Pathophysiology Through a Polyvagal Perspective

PubMed Central

Kolacz, Jacek; Porges, Stephen W.

2018-01-01

Chronic diffuse pain disorders, such as fibromyalgia, and functional gastrointestinal disorders (FGIDs), such as irritable bowel syndrome, place substantial burden on those affected and on the medical system. Despite their sizable impact, their pathophysiology is poorly understood. In contrast to an approach that focuses on the correlation between heart rate variability (HRV) and a specific organ or symptom, we propose that a bio-evolutionary threat-related autonomic response—as outlined in the Polyvagal Theory—may serve as a plausible explanation of how HRV, particularly respiratory sinus arrhythmia (RSA), would index the pathophysiology of these disorders. Evidence comes from: (1) the well-documented atypical autonomic regulation of the heart common to fibromyalgia and irritable bowel syndrome reflected in dampened RSA, (2) the neural architecture that integrates the heart, pain pathways, and the gastrointestinal tract, (3) the common physical co-morbidities shared by chronic diffuse pain and FGIDs, many of which are functionally regulated by the autonomic nervous system, (4) the elevated risk of chronic diffuse pain and FGIDs following traumatic stress or abuse, (5) and the elevated risk of chronic diffuse pain and FGIDs in individuals with anxiety and panic disorders. This novel conceptualization points to a pathogenesis rooted in changes to brain-body autonomic feedback loops in response to evolutionarily-salient threat cues, providing an integrated biopsychosocial model of chronic diffuse pain and FGIDs and suggesting new, non-pharmacological treatment strategies. PMID:29904631

On testing for spatial correspondence between maps of human brain structure and function.

PubMed

Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D; Glahn, David C; Shinohara, Russell T; Vandekar, Simon N; Raznahan, Armin

2018-06-01

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data. Copyright © 2018 Elsevier Inc. All rights reserved.

Histogram analysis of apparent diffusion coefficient maps for differentiating primary CNS lymphomas from tumefactive demyelinating lesions.

PubMed

Lu, Shan Shan; Kim, Sang Joon; Kim, Namkug; Kim, Ho Sung; Choi, Choong Gon; Lim, Young Min

2015-04-01

This study intended to investigate the usefulness of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating primary CNS lymphomas (PCNSLs), especially atypical PCNSLs, from tumefactive demyelinating lesions (TDLs). Forty-seven patients with PCNSLs and 18 with TDLs were enrolled in our study. Hyperintense lesions seen on T2-weighted images were defined as ROIs after ADC maps were registered to the corresponding T2-weighted image. ADC histograms were calculated from the ROIs containing the entire lesion on every section and on a voxel-by-voxel basis. The ADC histogram parameters were compared among all PCNSLs and TDLs as well as between the subgroup of atypical PCNSLs and TDLs. ROC curves were constructed to evaluate the diagnostic performance of the histogram parameters and to determine the optimum thresholds. The differences between the PCNSLs and TDLs were found in the minimum ADC values (ADCmin) and in the 5th and 10th percentiles (ADC5% and ADC10%) of the cumulative ADC histograms. However, no statistical significance was found in the mean ADC value or in the ADC value concerning the mode, kurtosis, and skewness. The ADCmin, ADC5%, and ADC10% were also lower in atypical PCNSLs than in TDLs. ADCmin was the best indicator for discriminating atypical PCNSLs from TDLs, with a threshold of 556×10(-6) mm2/s (sensitivity, 81.3 %; specificity, 88.9%). Histogram analysis of ADC maps may help to discriminate PCNSLs from TDLs and may be particularly useful in differentiating atypical PCNSLs from TDLs.

Mapping remodeling of thalamocortical projections in the living reeler mouse brain by diffusion tractography

PubMed Central

Harsan, Laura-Adela; Dávid, Csaba; Reisert, Marco; Schnell, Susanne; Hennig, Jürgen; von Elverfeldt, Dominik; Staiger, Jochen F.

2013-01-01

A major challenge in neuroscience is to accurately decipher in vivo the entire brain circuitry (connectome) at a microscopic level. Currently, the only methodology providing a global noninvasive window into structural brain connectivity is diffusion tractography. The extent to which the reconstructed pathways reflect realistic neuronal networks depends, however, on data acquisition and postprocessing factors. Through a unique combination of approaches, we designed and evaluated herein a framework for reliable fiber tracking and mapping of the living mouse brain connectome. One important wiring scheme, connecting gray matter regions and passing fiber-crossing areas, was closely examined: the lemniscal thalamocortical (TC) pathway. We quantitatively validated the TC projections inferred from in vivo tractography with correlative histological axonal tracing in the same wild-type and reeler mutant mice. We demonstrated noninvasively that changes in patterning of the cortical sheet, such as highly disorganized cortical lamination in reeler, led to spectacular compensatory remodeling of the TC pathway. PMID:23610438

Multimodal Diffuse Optical Imaging

NASA Astrophysics Data System (ADS)

Intes, Xavier; Venugopal, Vivek; Chen, Jin; Azar, Fred S.

Diffuse optical imaging, particularly diffuse optical tomography (DOT), is an emerging clinical modality capable of providing unique functional information, at a relatively low cost, and with nonionizing radiation. Multimodal diffuse optical imaging has enabled a synergistic combination of functional and anatomical information: the quality of DOT reconstructions has been significantly improved by incorporating the structural information derived by the combined anatomical modality. In this chapter, we will review the basic principles of diffuse optical imaging, including instrumentation and reconstruction algorithm design. We will also discuss the approaches for multimodal imaging strategies that integrate DOI with clinically established modalities. The merit of the multimodal imaging approaches is demonstrated in the context of optical mammography, but the techniques described herein can be translated to other clinical scenarios such as brain functional imaging or muscle functional imaging.

Resting state functional connectivity magnetic resonance imaging integrated with intraoperative neuronavigation for functional mapping after aborted awake craniotomy

PubMed Central

Batra, Prag; Bandt, S. Kathleen; Leuthardt, Eric C.

2016-01-01

Background: Awake craniotomy is currently the gold standard for aggressive tumor resections in eloquent cortex. However, a significant subset of patients is unable to tolerate this procedure, particularly the very young or old or those with psychiatric comorbidities, cardiopulmonary comorbidities, or obesity, among other conditions. In these cases, typical alternative procedures include biopsy alone or subtotal resection, both of which are associated with diminished surgical outcomes. Case Description: Here, we report the successful use of a preoperatively obtained resting state functional connectivity magnetic resonance imaging (MRI) integrated with intraoperative neuronavigation software in order to perform functional cortical mapping in the setting of an aborted awake craniotomy due to loss of airway. Conclusion: Resting state functional connectivity MRI integrated with intraoperative neuronavigation software can provide an alternative option for functional cortical mapping in the setting of an aborted awake craniotomy. PMID:26958419

The Time Dependent Propensity Function for Acceleration of Spatial Stochastic Simulation of Reaction-Diffusion Systems

PubMed Central

Wu, Sheng; Li, Hong; Petzold, Linda R.

2015-01-01

The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy. PMID:26609185

Predicting postnatal renal function of prenatally detected posterior urethral valves using fetal diffusion-weighted magnetic resonance imaging with apparent diffusion coefficient determination.

PubMed

Faure, Alice; Panait, Nicoleta; Panuel, Michel; Alessandrini, Pierre; D'Ercole, Claude; Chaumoitre, Kathia; Merrot, Thierry

2017-07-01

The objective of this study was to evaluate the accuracy of fetal diffusion-weighted magnetic resonance imaging with apparent diffusion coefficient (ADC) determination to predict postnatal renal function (nadir creatinine at 1 year and eGFR) of men with posterior urethral valves (PUV). Between 2003 and 2014, 11 MRI were performed on fetuses (between 28 and 32 weeks) in whom second trimester sonography suggested severe bilateral urinary tract anomalies, suspected of PUV. The ADC of the 11 fetuses ranged from 1.3 to 2.86 mm 2  s -1 (median = 1.79 mm 2  s -1 , normal range for fetal kidney: 1.1-1.8). Two pregnancies with ADC > 2.6 mm 2  s -1 were interrupted; the autopsy confirmed PUV and Potter syndrome. For the remaining nine babies, the follow-up was 5.4 years (0.8-10). Four children with abnormal ADC (1.8-2.3) had chronic kidney disease. The remaining five cases with normal nadir creatinine and eGFR had normal ADC. One case with unilateral elevated ADC had a poor ipsilateral renal function on dimercaptosuccinic acid scan. Here, it seems that diffusion-weighted magnetic resonance imaging with ADC determination could be useful in accurately evaluating fetal kidneys in PUV and predicting renal function. It may be an additional, non-invasive method when biologic and sonographic findings are inconclusive, especially in the case of oligohydramnios. Further studies are needed to confirm our data. © 2017 John Wiley & Sons, Ltd. © 2017 John Wiley & Sons, Ltd.

Mapping cell-specific functional connections in the mouse brain using ChR2-evoked hemodynamics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bauer, Adam Q.; Kraft, Andrew; Baxter, Grant A.; Bruchas, Michael; Lee, Jin-Moo; Culver, Joseph P.

2017-02-01

Functional magnetic resonance imaging (fMRI) has transformed our understanding of the brain's functional organization. However, mapping subunits of a functional network using hemoglobin alone presents several disadvantages. Evoked and spontaneous hemodynamic fluctuations reflect ensemble activity from several populations of neurons making it difficult to discern excitatory vs inhibitory network activity. Still, blood-based methods of brain mapping remain powerful because hemoglobin provides endogenous contrast in all mammalian brains. To add greater specificity to hemoglobin assays, we integrated optical intrinsic signal(OIS) imaging with optogenetic stimulation to create an Opto-OIS mapping tool that combines the cell-specificity of optogenetics with label-free, hemoglobin imaging. Before mapping, titrated photostimuli determined which stimulus parameters elicited linear hemodynamic responses in the cortex. Optimized stimuli were then scanned over the left hemisphere to create a set of optogenetically-defined effective connectivity (Opto-EC) maps. For many sites investigated, Opto-EC maps exhibited higher spatial specificity than those determined using spontaneous hemodynamic fluctuations. For example, resting-state functional connectivity (RS-FC) patterns exhibited widespread ipsilateral connectivity while Opto-EC maps contained distinct short- and long-range constellations of ipsilateral connectivity. Further, RS-FC maps were usually symmetric about midline while Opto-EC maps displayed more heterogeneous contralateral homotopic connectivity. Both Opto-EC and RS-FC patterns were compared to mouse connectivity data from the Allen Institute. Unlike RS-FC maps, Thy1-based maps collected in awake, behaving mice closely recapitulated the connectivity structure derived using ex vivo anatomical tracer methods. Opto-OIS mapping could be a powerful tool for understanding cellular and molecular contributions to network dynamics and processing in the mouse brain.

Functional mapping of reaction norms to multiple environmental signals through nonparametric covariance estimation

PubMed Central

2011-01-01

Background The identification of genes or quantitative trait loci that are expressed in response to different environmental factors such as temperature and light, through functional mapping, critically relies on precise modeling of the covariance structure. Previous work used separable parametric covariance structures, such as a Kronecker product of autoregressive one [AR(1)] matrices, that do not account for interaction effects of different environmental factors. Results We implement a more robust nonparametric covariance estimator to model these interactions within the framework of functional mapping of reaction norms to two signals. Our results from Monte Carlo simulations show that this estimator can be useful in modeling interactions that exist between two environmental signals. The interactions are simulated using nonseparable covariance models with spatio-temporal structural forms that mimic interaction effects. Conclusions The nonparametric covariance estimator has an advantage over separable parametric covariance estimators in the detection of QTL location, thus extending the breadth of use of functional mapping in practical settings. PMID:21269481

Physiologic abnormalities of cardiac function in progressive systemic sclerosis with diffuse scleroderma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Follansbee, W.P.; Curtiss, E.I.; Medsger, T.A. Jr.

1984-01-19

To investigate cardiopulmonary function in progressive systemic sclerosis with diffuse scleroderma, we studied 26 patients with maximal exercise and redistribution thallium scans, rest and exercise radionuclide ventriculography, pulmonary-function testing, and chest roentgenography. Although only 6 patients had clinical evidence of cardiac involvement, 20 had abnormal thallium scans, including 10 with reversible exercise-induced defects and 18 with fixed defects (8 had both). Seven of the 10 patients who had exercise-induced defects and underwent cardiac catheterization had normal coronary angiograms. Mean resting left ventricular ejection fraction and mean resting right ventricular ejection fraction were lower in patients with post-exercise left ventricular thalliummore » defect scores above the median (59 +/- 13 per cent vs. 69 +/- 6 per cent, and 36 +/- 12 per cent vs. 47 +/- 7 per cent, respectively). The authors conclude that in progressive systemic sclerosis with diffuse scleroderma, abnormalities of myocardial perfusion are common and appear to be due to a disturbance of the myocardial microcirculation. Both right and left ventricular dysfunction appear to be related to this circulatory disturbance, suggesting ischemically mediated injury.« less

Functional genomics platform for pooled screening and mammalian genetic interaction maps

PubMed Central

Kampmann, Martin; Bassik, Michael C.; Weissman, Jonathan S.

2014-01-01

Systematic genetic interaction maps in microorganisms are powerful tools for identifying functional relationships between genes and defining the function of uncharacterized genes. We have recently implemented this strategy in mammalian cells as a two-stage approach. First, genes of interest are robustly identified in a pooled genome-wide screen using complex shRNA libraries. Second, phenotypes for all pairwise combinations of hit genes are measured in a double-shRNA screen and used to construct a genetic interaction map. Our protocol allows for rapid pooled screening under various conditions without a requirement for robotics, in contrast to arrayed approaches. Each stage of the protocol can be implemented in ~2 weeks, with additional time for analysis and generation of reagents. We discuss considerations for screen design, and present complete experimental procedures as well as a full computational analysis suite for identification of hits in pooled screens and generation of genetic interaction maps. While the protocols outlined here were developed for our original shRNA-based approach, they can be applied more generally, including to CRISPR-based approaches. PMID:24992097

Sharp rates of decay of solutions to the nonlinear fast diffusion equation via functional inequalities

PubMed Central

Vázquez, J. L.

2010-01-01

The goal of this paper is to state the optimal decay rate for solutions of the nonlinear fast diffusion equation and, in self-similar variables, the optimal convergence rates to Barenblatt self-similar profiles and their generalizations. It relies on the identification of the optimal constants in some related Hardy–Poincaré inequalities and concludes a long series of papers devoted to generalized entropies, functional inequalities, and rates for nonlinear diffusion equations. PMID:20823259

Technique for examining biological materials using diffuse reflectance spectroscopy and the kubelka-munk function

DOEpatents

Alfano, Robert R.; Yang, Yuanlong

2003-09-02

Method and apparatus for examining biological materials using diffuse reflectance spectroscopy and the Kubelka-Munk function. In one aspect, the method is used to determine whether a tissue sample is cancerous or not and comprises the steps of (a) measuring the diffuse reflectance from the tissue sample at a first wavelength and at a second wavelength, wherein the first wavelength is a wavelength selected from the group consisting of 255-265 nm and wherein the second wavelength is a wavelength selected from the group consisting of 275-285 nm; (b) using the Kubelka-Munk function to transform the diffuse reflectance measurement obtained at the first and second wavelengths; and (c) comparing a ratio or a difference of the transformed Kubelka-Munk measurements at the first and second wavelengths to appropriate standards determine whether or not the tissue sample is cancerous. One can use the spectral profile of KMF between 250 nm to 300 nm to determine whether or not the tissue sample is cancerous or precancerous. According to the value at the first and second wavelengths determine whether or not the malignant tissue is invasive or mixed invasive and in situ or carcinoma in situ.

Glucose Sensing with Phenylboronic Acid Functionalized Hydrogel-Based Optical Diffusers

PubMed Central

2018-01-01

Phenylboronic acids have emerged as synthetic receptors that can reversibly bind to cis-diols of glucose molecules. The incorporation of phenylboronic acids in hydrogels offers exclusive attributes; for example, the binding process with glucose induces Donnan osmotic pressure resulting in volumetric changes in the matrix. However, their practical applications are hindered because of complex readout approaches and their time-consuming fabrication processes. Here, we demonstrate a microimprinting method to fabricate densely packed concavities in phenylboronic acid functionalized hydrogel films. A microengineered optical diffuser structure was imprinted on a phenylboronic acid based cis-diol recognizing motif prepositioned in a hydrogel film. The diffuser structure engineered on the hydrogel was based on laser-inscribed arrays of imperfect microlenses that focused the incoming light at different focal lengths and direction resulting in a diffused profile of light in transmission and reflection readout modes. The signature of the dimensional modulation was detected in terms of changing focal lengths of the microlenses due to the volumetric expansion of the hydrogel that altered the diffusion spectra and transmitted beam profile. The transmitted optical light spread and intensity through the sensor was measured to determine variation in glucose concentrations at physiological conditions. The sensor was integrated in a contact lens and placed over an artificial eye. Artificial stimulation of variation in glucose concentration allowed quantitative measurements using a smartphone’s photodiode. A smartphone app was utilized to convert the received light intensity to quantitative glucose concentration values. The developed sensing platform offers low cost, rapid fabrication, and easy detection scheme as compared to other optical sensing counterparts. The presented detection scheme may have applications in wearable real-time biomarker monitoring devices at point

Angular Distributions of Discrete Mesoscale Mapping Functions

NASA Astrophysics Data System (ADS)

Kroszczyński, Krzysztof

2015-08-01

The paper presents the results of analyses of numerical experiments concerning GPS signal propagation delays in the atmosphere and the discrete mapping functions defined on their basis. The delays were determined using data from the mesoscale non-hydrostatic weather model operated in the Centre of Applied Geomatics, Military University of Technology. A special attention was paid to investigating angular characteristics of GPS slant delays for low angles of elevation. The investigation proved that the temporal and spatial variability of the slant delays depends to a large extent on current weather conditions.

Diffusion of hydrogen into and through γ-iron by density functional theory

NASA Astrophysics Data System (ADS)

Chohan, Urslaan K.; Koehler, Sven P. K.; Jimenez-Melero, Enrique

2018-06-01

This study is concerned with the early stages of hydrogen embrittlement on an atomistic scale. We employed density functional theory to investigate hydrogen diffusion through the (100), (110) and (111) surfaces of γ-Fe. The preferred adsorption sites and respective energies for hydrogen adsorption were established for each plane, as well as a minimum energy pathway for diffusion. The H atoms adsorb on the (100), (110) and (111) surfaces with energies of ∼4.06 eV, ∼3.92 eV and ∼4.05 eV, respectively. The barriers for bulk-like diffusion for the (100), (110) and (111) surfaces are ∼0.6 eV, ∼0.5 eV and ∼0.7 eV, respectively. We compared these calculated barriers with previously obtained experimental data in an Arrhenius plot, which indicates good agreement between experimentally measured and theoretically predicted activation energies. Texturing austenitic steels such that the (111) surfaces of grains are preferentially exposed at the cleavage planes may be a possibility to reduce hydrogen embrittlement.

Functional magnetic resonance imaging.

PubMed

Buchbinder, Bradley R

2016-01-01

Functional magnetic resonance imaging (fMRI) maps the spatiotemporal distribution of neural activity in the brain under varying cognitive conditions. Since its inception in 1991, blood oxygen level-dependent (BOLD) fMRI has rapidly become a vital methodology in basic and applied neuroscience research. In the clinical realm, it has become an established tool for presurgical functional brain mapping. This chapter has three principal aims. First, we review key physiologic, biophysical, and methodologic principles that underlie BOLD fMRI, regardless of its particular area of application. These principles inform a nuanced interpretation of the BOLD fMRI signal, along with its neurophysiologic significance and pitfalls. Second, we illustrate the clinical application of task-based fMRI to presurgical motor, language, and memory mapping in patients with lesions near eloquent brain areas. Integration of BOLD fMRI and diffusion tensor white-matter tractography provides a road map for presurgical planning and intraoperative navigation that helps to maximize the extent of lesion resection while minimizing the risk of postoperative neurologic deficits. Finally, we highlight several basic principles of resting-state fMRI and its emerging translational clinical applications. Resting-state fMRI represents an important paradigm shift, focusing attention on functional connectivity within intrinsic cognitive networks. © 2016 Elsevier B.V. All rights reserved.

An Intracranial Electroencephalography (iEEG) Brain Function Mapping Tool with an Application to Epilepsy Surgery Evaluation.

PubMed

Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli

2016-01-01

Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications.

An Intracranial Electroencephalography (iEEG) Brain Function Mapping Tool with an Application to Epilepsy Surgery Evaluation

PubMed Central

Wang, Yinghua; Yan, Jiaqing; Wen, Jianbin; Yu, Tao; Li, Xiaoli

2016-01-01

Objects: Before epilepsy surgeries, intracranial electroencephalography (iEEG) is often employed in function mapping and epileptogenic foci localization. Although the implanted electrodes provide crucial information for epileptogenic zone resection, a convenient clinical tool for electrode position registration and Brain Function Mapping (BFM) visualization is still lacking. In this study, we developed a BFM Tool, which facilitates electrode position registration and BFM visualization, with an application to epilepsy surgeries. Methods: The BFM Tool mainly utilizes electrode location registration and function mapping based on pre-defined brain models from other software. In addition, the electrode node and mapping properties, such as the node size/color, edge color/thickness, mapping method, can be adjusted easily using the setting panel. Moreover, users may manually import/export location and connectivity data to generate figures for further application. The role of this software is demonstrated by a clinical study of language area localization. Results: The BFM Tool helps clinical doctors and researchers visualize implanted electrodes and brain functions in an easy, quick and flexible manner. Conclusions: Our tool provides convenient electrode registration, easy brain function visualization, and has good performance. It is clinical-oriented and is easy to deploy and use. The BFM tool is suitable for epilepsy and other clinical iEEG applications. PMID:27199729

Preliminary Results of BTDF Calibration of Transmissive Solar Diffusers for Remote Sensing

NASA Technical Reports Server (NTRS)

Georgiev, Georgi T.; Butler, James J.; Thome, Kurt; Cooksey, Catherine; Ding, Leibo

2016-01-01

Satellite instruments operating in the reflected solar wavelength region require accurate and precise determination of the optical properties of their diffusers used in pre-flight and post-flight calibrations. The majority of recent and current space instruments use reflective diffusers. As a result, numerous Bidirectional Reflectance Distribution Function (BRDF) calibration comparisons have been conducted between the National Institute of Standards and Technology (NIST) and other industry and university-based metrology laboratories. However, based on literature searches and communications with NIST and other laboratories, no Bidirectional Transmittance Distribution Function (BTDF) measurement comparisons have been conducted between National Measurement Laboratories (NMLs) and other metrology laboratories. On the other hand, there is a growing interest in the use of transmissive diffusers in the calibration of satellite, air-borne, and ground-based remote sensing instruments. Current remote sensing instruments employing transmissive diffusers include the Ozone Mapping and Profiler Suite instrument (OMPS) Limb instrument on the Suomi-National Polar-orbiting Partnership (S-NPP) platform,, the Geostationary Ocean Color Imager (GOCI) on the Korea Aerospace Research Institute's (KARI) Communication, Ocean, and Meteorological Satellite (COMS), the Ozone Monitoring Instrument (OMI) on NASA's Earth Observing System (EOS) Aura platform, the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument and the Geostationary Environmental Monitoring Spectrometer (GEMS).. This ensemble of instruments requires validated BTDF measurements of their on-board transmissive diffusers from the ultraviolet through the near infrared. This paper presents the preliminary results of a BTDF comparison between the NASA Diffuser Calibration Laboratory (DCL) and NIST on quartz and thin Spectralon samples.

PRELIMINARY RESULTS OF BTDF CALIBRATION OF TRANSMISSIVE SOLAR DIFFUSERS FOR REMOTE SENSING

PubMed Central

Georgiev, Georgi T.; Butler, James J.; Thome, Kurt; Cooksey, Catherine; Ding, Leibo

2016-01-01

Satellite instruments operating in the reflected solar wavelength region require accurate and precise determination of the optical properties of their diffusers used in pre-flight and post-flight calibrations. The majority of recent and current space instruments use reflective diffusers. As a result, numerous Bidirectional Reflectance Distribution Function (BRDF) calibration comparisons have been conducted between the National Institute of Standards and Technology (NIST) and other industry and university-based metrology laboratories. However, based on literature searches and communications with NIST and other laboratories, no Bidirectional Transmittance Distribution Function (BTDF) measurement comparisons have been conducted between National Measurement Laboratories (NMLs) and other metrology laboratories. On the other hand, there is a growing interest in the use of transmissive diffusers in the calibration of satellite, air-borne, and ground-based remote sensing instruments. Current remote sensing instruments employing transmissive diffusers include the Ozone Mapping and Profiler Suite instrument (OMPS) Limb instrument on the Suomi-National Polar-orbiting Partnership (S-NPP) platform,, the Geostationary Ocean Color Imager (GOCI) on the Korea Aerospace Research Institute’s (KARI) Communication, Ocean, and Meteorological Satellite (COMS), the Ozone Monitoring Instrument (OMI) on NASA’s Earth Observing System (EOS) Aura platform, the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument and the Geostationary Environmental Monitoring Spectrometer (GEMS).. This ensemble of instruments requires validated BTDF measurements of their on-board transmissive diffusers from the ultraviolet through the near infrared. This paper presents the preliminary results of a BTDF comparison between the NASA Diffuser Calibration Laboratory (DCL) and NIST on quartz and thin Spectralon samples. PMID:28003712

Preliminary results of BTDF calibration of transmissive solar diffusers for remote sensing

NASA Astrophysics Data System (ADS)

Georgiev, Georgi T.; Butler, James J.; Thome, Kurt; Cooksey, Catherine; Ding, Leibo

2016-09-01

Satellite instruments operating in the reflected solar wavelength region require accurate and precise determination of the optical properties of their diffusers used in pre-flight and post-flight calibrations. The majority of recent and current space instruments use reflective diffusers. As a result, numerous Bidirectional Reflectance Distribution Function (BRDF) calibration comparisons have been conducted between the National Institute of Standards and Technology (NIST) and other industry and university-based metrology laboratories. However, based on literature searches and communications with NIST and other laboratories, no Bidirectional Transmittance Distribution Function (BTDF) measurement comparisons have been conducted between National Measurement Laboratories (NMLs) and other metrology laboratories. On the other hand, there is a growing interest in the use of transmissive diffusers in the calibration of satellite, air-borne, and ground-based remote sensing instruments. Current remote sensing instruments employing transmissive diffusers include the Ozone Mapping and Profiler Suite instrument (OMPS) Limb instrument on the Suomi-National Polar-orbiting Partnership (S-NPP) platform,, the Geostationary Ocean Color Imager (GOCI) on the Korea Aerospace Research Institute's (KARI) Communication, Ocean, and Meteorological Satellite (COMS), the Ozone Monitoring Instrument (OMI) on NASA's Earth Observing System (EOS) Aura platform, the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument and the Geostationary Environmental Monitoring Spectrometer (GEMS).. This ensemble of instruments requires validated BTDF measurements of their onboard transmissive diffusers from the ultraviolet through the near infrared. This paper presents the preliminary results of a BTDF comparison between the NASA Diffuser Calibration Laboratory (DCL) and NIST on quartz and thin Spectralon samples.

PRELIMINARY RESULTS OF BTDF CALIBRATION OF TRANSMISSIVE SOLAR DIFFUSERS FOR REMOTE SENSING.

PubMed

Georgiev, Georgi T; Butler, James J; Thome, Kurt; Cooksey, Catherine; Ding, Leibo

2016-01-01

Satellite instruments operating in the reflected solar wavelength region require accurate and precise determination of the optical properties of their diffusers used in pre-flight and post-flight calibrations. The majority of recent and current space instruments use reflective diffusers. As a result, numerous Bidirectional Reflectance Distribution Function (BRDF) calibration comparisons have been conducted between the National Institute of Standards and Technology (NIST) and other industry and university-based metrology laboratories. However, based on literature searches and communications with NIST and other laboratories, no Bidirectional Transmittance Distribution Function (BTDF) measurement comparisons have been conducted between National Measurement Laboratories (NMLs) and other metrology laboratories. On the other hand, there is a growing interest in the use of transmissive diffusers in the calibration of satellite, air-borne, and ground-based remote sensing instruments. Current remote sensing instruments employing transmissive diffusers include the Ozone Mapping and Profiler Suite instrument (OMPS) Limb instrument on the Suomi-National Polar-orbiting Partnership (S-NPP) platform,, the Geostationary Ocean Color Imager (GOCI) on the Korea Aerospace Research Institute's (KARI) Communication, Ocean, and Meteorological Satellite (COMS), the Ozone Monitoring Instrument (OMI) on NASA's Earth Observing System (EOS) Aura platform, the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument and the Geostationary Environmental Monitoring Spectrometer (GEMS).. This ensemble of instruments requires validated BTDF measurements of their on-board transmissive diffusers from the ultraviolet through the near infrared. This paper presents the preliminary results of a BTDF comparison between the NASA Diffuser Calibration Laboratory (DCL) and NIST on quartz and thin Spectralon samples.

Bound Pool Fractions Complement Diffusion Measures to Describe White Matter Micro and Macrostructure

PubMed Central

Stikov, Nikola; Perry, Lee M.; Mezer, Aviv; Rykhlevskaia, Elena; Wandell, Brian A.; Pauly, John M.; Dougherty, Robert F.

2010-01-01

Diffusion imaging and bound pool fraction (BPF) mapping are two quantitative magnetic resonance imaging techniques that measure microstructural features of the white matter of the brain. Diffusion imaging provides a quantitative measure of the diffusivity of water in tissue. BPF mapping is a quantitative magnetization transfer (qMT) technique that estimates the proportion of exchanging protons bound to macromolecules, such as those found in myelin, and is thus a more direct measure of myelin content than diffusion. In this work, we combine BPF estimates of macromolecular content with measurements of diffusivity within human white matter tracts. Within the white matter, the correlation between BPFs and diffusivity measures such as fractional anisotropy and radial diffusivity was modest, suggesting that diffusion tensor imaging and bound pool fractions are complementary techniques. We found that several major tracts have high BPF, suggesting a higher density of myelin in these tracts. We interpret these results in the context of a quantitative tissue model. PMID:20828622

Diffusion of innovations dynamics, biological growth and catenary function

NASA Astrophysics Data System (ADS)

Guseo, Renato

2016-12-01

The catenary function has a well-known role in determining the shape of chains and cables supported at their ends under the force of gravity. This enables design using a specific static equilibrium over space. Its reflected version, the catenary arch, allows the construction of bridges and arches exploiting the dual equilibrium property under uniform compression. In this paper, we emphasize a further connection with well-known aggregate biological growth models over time and the related diffusion of innovation key paradigms (e.g., logistic and Bass distributions over time) that determine self-sustaining evolutionary growth dynamics in naturalistic and socio-economic contexts. Moreover, we prove that the 'local entropy function', related to a logistic distribution, is a catenary and vice versa. This special invariance may be explained, at a deeper level, through the Verlinde's conjecture on the origin of gravity as an effect of the entropic force.

Detecting Buried Archaeological Remains by the Use of Geophysical Data Processing with 'Diffusion Maps' Methodology

NASA Astrophysics Data System (ADS)

Eppelbaum, Lev

2015-04-01

Geophysical methods are prompt, non-invasive and low-cost tool for quantitative delineation of buried archaeological targets. However, taking into account the complexity of geological-archaeological media, some unfavourable environments and known ambiguity of geophysical data analysis, a single geophysical method examination might be insufficient (Khesin and Eppelbaum, 1997). Besides this, it is well-known that the majority of inverse-problem solutions in geophysics are ill-posed (e.g., Zhdanov, 2002), which means, according to Hadamard (1902), that the solution does not exist, or is not unique, or is not a continuous function of observed geophysical data (when small perturbations in the observations will cause arbitrary mistakes in the solution). This fact has a wide application for informational, probabilistic and wavelet methodologies in archaeological geophysics (Eppelbaum, 2014a). The goal of the modern geophysical data examination is to detect the geophysical signatures of buried targets at noisy areas via the analysis of some physical parameters with a minimal number of false alarms and miss-detections (Eppelbaum et al., 2011; Eppelbaum, 2014b). The proposed wavelet approach to recognition of archaeological targets (AT) by the examination of geophysical method integration consists of advanced processing of each geophysical method and nonconventional integration of different geophysical methods between themselves. The recently developed technique of diffusion clustering combined with the abovementioned wavelet methods was utilized to integrate the geophysical data and detect existing irregularities. The approach is based on the wavelet packet techniques applied as to the geophysical images (or graphs) versus coordinates. For such an analysis may be utilized practically all geophysical methods (magnetic, gravity, seismic, GPR, ERT, self-potential, etc.). On the first stage of the proposed investigation a few tens of typical physical-archaeological models (PAM

White matter tractography using diffusion tensor deflection.

PubMed

Lazar, Mariana; Weinstein, David M; Tsuruda, Jay S; Hasan, Khader M; Arfanakis, Konstantinos; Meyerand, M Elizabeth; Badie, Benham; Rowley, Howard A; Haughton, Victor; Field, Aaron; Alexander, Andrew L

2003-04-01

Diffusion tensor MRI provides unique directional diffusion information that can be used to estimate the patterns of white matter connectivity in the human brain. In this study, the behavior of an algorithm for white matter tractography is examined. The algorithm, called TEND, uses the entire diffusion tensor to deflect the estimated fiber trajectory. Simulations and imaging experiments on in vivo human brains were performed to investigate the behavior of the tractography algorithm. The simulations show that the deflection term is less sensitive than the major eigenvector to image noise. In the human brain imaging experiments, estimated tracts were generated in corpus callosum, corticospinal tract, internal capsule, corona radiata, superior longitudinal fasciculus, inferior longitudinal fasciculus, fronto-occipital fasciculus, and uncinate fasciculus. This approach is promising for mapping the organizational patterns of white matter in the human brain as well as mapping the relationship between major fiber trajectories and the location and extent of brain lesions. Copyright 2003 Wiley-Liss, Inc.

Imaging diffuse clouds: bright and dark gas mapped in CO

NASA Astrophysics Data System (ADS)

Liszt, H. S.; Pety, J.

2012-05-01

Aims: We wish to relate the degree scale structure of galactic diffuse clouds to sub-arcsecond atomic and molecular absorption spectra obtained against extragalactic continuum background sources. Methods: We used the ARO 12 m telescope to map J = 1-0 CO emission at 1' resolution over 30' fields around the positions of 11 background sources occulted by 20 molecular absorption line components, of which 11 had CO emission counterparts. We compared maps of CO emission to sub-arcsec atomic and molecular absorption spectra and to the large-scale distribution of interstellar reddening. Results: 1) The same clouds, identified by their velocity, were seen in absorption and emission and atomic and molecular phases, not necessarily in the same direction. Sub-arcsecond absorption spectra are a preview of what is seen in CO emission away from the continuum. 2) The CO emission structure was amorphous in 9 cases, quasi-periodic or wave-like around B0528+134 and tangled and filamentary around BL Lac. 3) Strong emission, typically 4-5 K at EB - V ≤ 0.15 mag and up to 10-12 K at EB - V ≲ 0.3 mag was found, much brighter than toward the background targets. Typical covering factors of individual features at the 1 K km s-1 level were 20%. 4) CO-H2 conversion factors as much as 4-5 times below the mean value N(H2)/WCO = 2 × 1020 H2 cm-2 (K km s-1)-1 are required to explain the luminosity of CO emission at/above the level of 1 K km s-1. Small conversion factors and sharp variability of the conversion factor on arcminute scales are due primarily to CO chemistry and need not represent unresolved variations in reddening or total column density. Conclusions: Like Fermi and Planck we see some gas that is dark in CO and other gas in which CO is overluminous per H2. A standard CO-H2 conversion factor applies overall owing to balance between the luminosities per H2 and surface covering factors of bright and dark CO, but with wide variations between sightlines and across the faces of

Major Pathways to Electron Distribution Function Formation in Regions of Diffuse Aurora

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Sibeck, David G.; Zesta, Eftyhia

2017-01-01

This paper discusses the major pathways of electron distribution function formation in the region of diffuse aurora. The diffuse aurora accounts for about of 75% of the auroral energy precipitating into the upper atmosphere, and its origin has been the subject of much discussion. We show that an earthward stream of precipitating electrons initially injected from the Earth's plasma sheet via wave-particle interactions degrades in the atmosphere toward lower energies and produces secondary electrons via impact ionization of the neutral atmosphere. These electrons of magnetospheric origin are then reflected back into the magnetosphere along closed dipolar magnetic field lines, leading to a series of reflections and consequent magnetospheric interactions that greatly augment the initially precipitating flux at the upper ionospheric boundary (700-800 km). To date this, systematic magnetosphere-ionosphere coupling element has not been included in auroral research models, and, as we demonstrate in this article, has a dramatic effect (200-300%) on the formation of the precipitating fluxes that result in the diffuse aurora. It is shown that wave-particle interaction processes that drive precipitating fluxes in the region of diffuse aurora from the magnetospheric altitudes are only the first step in the formation of electron precipitation at ionospheric altitudes, and they cannot be separated from the atmospheric collisional machine that redistributes and transfers their energy inside the magnetosphere-ionosphere-atmosphere coupling system.

Major pathways to electron distribution function formation in regions of diffuse aurora

NASA Astrophysics Data System (ADS)

Khazanov, George V.; Sibeck, David G.; Zesta, Eftyhia

2017-04-01

This paper discusses the major pathways of electron distribution function formation in the region of diffuse aurora. The diffuse aurora accounts for about of 75% of the auroral energy precipitating into the upper atmosphere, and its origin has been the subject of much discussion. We show that an earthward stream of precipitating electrons initially injected from the Earth's plasma sheet via wave-particle interactions degrades in the atmosphere toward lower energies and produces secondary electrons via impact ionization of the neutral atmosphere. These electrons of magnetospheric origin are then reflected back into the magnetosphere along closed dipolar magnetic field lines, leading to a series of reflections and consequent magnetospheric interactions that greatly augment the initially precipitating flux at the upper ionospheric boundary (700-800 km). To date this, systematic magnetosphere-ionosphere coupling element has not been included in auroral research models, and, as we demonstrate in this article, has a dramatic effect (200-300%) on the formation of the precipitating fluxes that result in the diffuse aurora. It is shown that wave-particle interaction processes that drive precipitating fluxes in the region of diffuse aurora from the magnetospheric altitudes are only the first step in the formation of electron precipitation at ionospheric altitudes, and they cannot be separated from the atmospheric "collisional machine" that redistributes and transfers their energy inside the magnetosphere-ionosphere-atmosphere coupling system.

Noninvasive Localization of Prostate Cancer via Diffusion Sensitive MRI

DTIC Science & Technology

2008-03-01

sequence, Haker et al and Roebuck et al using a line-scan diffusion sequence, and Vigneron et al using a fast spin-echo diffusion sequence (33,35-37...Mulkern RV, Haker S, Zhang J, Zou KH, Maier SE, Tempany CM. Detection of prostate cancer by integration of line-scan diffusion, T2-mapping and T2-weighted...36. Haker SJ, Szot Barnes A, Maier SE, Tempany CM, Mulkern RV. Diffusion Tensor Imaging for Prostate Cancer Detection: Preliminary Results from a

Grid adaption based on modified anisotropic diffusion equations formulated in the parametic domain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagmeijer, R.

1994-11-01

A new grid-adaption algorithm for problems in computational fluid dynamics is presented. The basic equations are derived from a variational problem formulated in the parametric domain of the mapping that defines the existing grid. Modification of the basic equations provides desirable properties in boundary layers. The resulting modified anisotropic diffusion equations are solved for the computational coordinates as functions of the parametric coordinates and these functions are numerically inverted. Numerical examples show that the algorithm is robust, that shocks and boundary layers are well-resolved on the adapted grid, and that the flow solution becomes a globally smooth function of themore » computational coordinates.« less

Mapping Language Function in the Brain: A Review of the Recent Literature.

ERIC Educational Resources Information Center

Crafton, Robert E.; Kido, Elissa

2000-01-01

Considers the potential importance of brain study for composition instruction, briefly describes functional imaging techniques, and reviews the findings of recent brain-mapping studies investigating the neurocognitive systems involved in language function. Presents a review of the recent literature and considers the possible implications of this…

Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics

PubMed Central

Rodriguez Gutierrez, Daniel; Manita, Muftah; Jaspan, Tim; Dineen, Robert A.; Grundy, Richard G.; Auer, Dorothee P.

2013-01-01

Background Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response. Methods Eighteen patients (age range, 1.9–20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1–16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM). Results Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η2 = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis. Conclusions We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols. PMID:23585630

Rapid and minimum invasive functional brain mapping by real-time visualization of high gamma activity during awake craniotomy.

PubMed

Ogawa, Hiroshi; Kamada, Kyousuke; Kapeller, Christoph; Hiroshima, Satoru; Prueckl, Robert; Guger, Christoph

2014-11-01

Electrocortical stimulation (ECS) is the gold standard for functional brain mapping during an awake craniotomy. The critical issue is to set aside enough time to identify eloquent cortices by ECS. High gamma activity (HGA) ranging between 80 and 120 Hz on electrocorticogram is assumed to reflect localized cortical processing. In this report, we used real-time HGA mapping and functional neuronavigation integrated with functional magnetic resonance imaging (fMRI) for rapid and reliable identification of motor and language functions. Four patients with intra-axial tumors in their dominant hemisphere underwent preoperative fMRI and lesion resection with an awake craniotomy. All patients showed significant fMRI activation evoked by motor and language tasks. During the craniotomy, we recorded electrocorticogram activity by placing subdural grids directly on the exposed brain surface. Each patient performed motor and language tasks and demonstrated real-time HGA dynamics in hand motor areas and parts of the inferior frontal gyrus. Sensitivity and specificity of HGA mapping were 100% compared with ECS mapping in the frontal lobe, which suggested HGA mapping precisely indicated eloquent cortices. We found different HGA dynamics of language tasks in frontal and temporal regions. Specificities of the motor and language-fMRI did not reach 85%. The results of HGA mapping was mostly consistent with those of ECS mapping, although fMRI tended to overestimate functional areas. This novel technique enables rapid and accurate identification of motor and frontal language areas. Furthermore, real-time HGA mapping sheds light on underlying physiological mechanisms related to human brain functions. Copyright © 2014 Elsevier Inc. All rights reserved.

Anatomo-clinical overlapping maps (AnaCOM): a new method to create anatomo-functional maps from neuropsychological tests and structural MRI scan of subjects with brain lesions

NASA Astrophysics Data System (ADS)

Kinkingnehun, Serge R. J.; du Boisgueheneuc, Foucaud; Golmard, Jean-Louis; Zhang, Sandy X.; Levy, Richard; Dubois, Bruno

2004-04-01

We have developed a new technique to analyze correlations between brain anatomy and its neurological functions. The technique is based on the anatomic MRI of patients with brain lesions who are administered neuropsychological tests. Brain lesions of the MRI scans are first manually segmented. The MRI volumes are then normalized to a reference map, using the segmented area as a mask. After normalization, the brain lesions of the MRI are segmented again in order to redefine the border of the lesions in the context of the normalized brain. Once the MRI is segmented, the patient's score on the neuropsychological test is assigned to each voxel in the lesioned area, while the rest of the voxels of the image are set to 0. Subsequently, the individual patient's MRI images are superimposed, and each voxel is reassigned the average score of the patients who have a lesion at that voxel. A threshold is applied to remove regions having less than three overlaps. This process leads to an anatomo-functional map that links brain areas to functional loss. Other maps can be created to aid in analyzing the functional maps, such as one that indicates the 95% confidence interval of the averaged scores for each area. This anatomo-clinical overlapping map (AnaCOM) method was used to obtain functional maps from patients with lesions in the superior frontal gyrus. By finding particular subregions more responsible for a particular deficit, this method can generate new hypotheses to be tested by conventional group methods.

RF-Based Location Using Interpolation Functions to Reduce Fingerprint Mapping

PubMed Central

Ezpeleta, Santiago; Claver, José M.; Pérez-Solano, Juan J.; Martí, José V.

2015-01-01

Indoor RF-based localization using fingerprint mapping requires an initial training step, which represents a time consuming process. This location methodology needs a database conformed with RSSI (Radio Signal Strength Indicator) measures from the communication transceivers taken at specific locations within the localization area. But, the real world localization environment is dynamic and it is necessary to rebuild the fingerprint database when some environmental changes are made. This paper explores the use of different interpolation functions to complete the fingerprint mapping needed to achieve the sought accuracy, thereby reducing the effort in the training step. Also, different distributions of test maps and reference points have been evaluated, showing the validity of this proposal and necessary trade-offs. Results reported show that the same or similar localization accuracy can be achieved even when only 50% of the initial fingerprint reference points are taken. PMID:26516862

Non-Gaussian diffusion in static disordered media

NASA Astrophysics Data System (ADS)

Luo, Liang; Yi, Ming

2018-04-01

Non-Gaussian diffusion is commonly considered as a result of fluctuating diffusivity, which is correlated in time or in space or both. In this work, we investigate the non-Gaussian diffusion in static disordered media via a quenched trap model, where the diffusivity is spatially correlated. Several unique effects due to quenched disorder are reported. We analytically estimate the diffusion coefficient Ddis and its fluctuation over samples of finite size. We show a mechanism of population splitting in the non-Gaussian diffusion. It results in a sharp peak in the distribution of displacement P (x ,t ) around x =0 , that has frequently been observed in experiments. We examine the fidelity of the coarse-grained diffusion map, which is reconstructed from particle trajectories. Finally, we propose a procedure to estimate the correlation length in static disordered environments, where the information stored in the sample-to-sample fluctuation has been utilized.

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

NASA Astrophysics Data System (ADS)

Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

2018-05-01

Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

Chaotic diffusion in the Gliese-876 planetary system

NASA Astrophysics Data System (ADS)

Martí, J. G.; Cincotta, P. M.; Beaugé, C.

2016-07-01

Chaotic diffusion is supposed to be responsible for orbital instabilities in planetary systems after the dissipation of the protoplanetary disc, and a natural consequence of irregular motion. In this paper, we show that resonant multiplanetary systems, despite being highly chaotic, not necessarily exhibit significant diffusion in phase space, and may still survive virtually unchanged over time-scales comparable to their age. Using the GJ-876 system as an example, we analyse the chaotic diffusion of the outermost (and less massive) planet. We construct a set of stability maps in the surrounding regions of the Laplace resonance. We numerically integrate ensembles of close initial conditions, compute Poincaré maps and estimate the chaotic diffusion present in this system. Our results show that, the Laplace resonance contains two different regions: an inner domain characterized by low chaoticity and slow diffusion, and an outer one displaying larger values of dynamical indicators. In the outer resonant domain, the stochastic borders of the Laplace resonance seem to prevent the complete destruction of the system. We characterize the diffusion for small ensembles along the parameters of the outermost planet. Finally, we perform a stability analysis of the inherent chaotic, albeit stable Laplace resonance, by linking the behaviour of the resonant variables of the configurations to the different sub-structures inside the three-body resonance.

High-density diffuse optical tomography of term infant visual cortex in the nursery

NASA Astrophysics Data System (ADS)

Liao, Steve M.; Ferradal, Silvina L.; White, Brian R.; Gregg, Nicholas; Inder, Terrie E.; Culver, Joseph P.

2012-08-01

Advancements in antenatal and neonatal medicine over the last few decades have led to significant improvement in the survival rates of sick newborn infants. However, this improvement in survival has not been matched by a reduction in neurodevelopmental morbidities with increasing recognition of the diverse cognitive and behavioral challenges that preterm infants face in childhood. Conventional neuroimaging modalities, such as cranial ultrasound and magnetic resonance imaging, provide an important definition of neuroanatomy with recognition of brain injury. However, they fail to define the functional integrity of the immature brain, particularly during this critical developmental period. Diffuse optical tomography methods have established success in imaging adult brain function; however, few studies exist to demonstrate their feasibility in the neonatal population. We demonstrate the feasibility of using recently developed high-density diffuse optical tomography (HD-DOT) to map functional activation of the visual cortex in healthy term-born infants. The functional images show high contrast-to-noise ratio obtained in seven neonates. These results illustrate the potential for HD-DOT and provide a foundation for investigations of brain function in more vulnerable newborns, such as preterm infants.

Robust reconstruction of B1 (+) maps by projection into a spherical functions space.

PubMed

Sbrizzi, Alessandro; Hoogduin, Hans; Lagendijk, Jan J; Luijten, Peter; van den Berg, Cornelis A T

2014-01-01

Several parallel transmit MRI techniques require knowledge of the transmit radiofrequency field profiles (B1 (+) ). During the past years, various methods have been developed to acquire this information. Often, these methods suffer from long measurement times and produce maps exhibiting regions with poor signal-to-noise ratio and artifacts. In this article, a model-based reconstruction procedure is introduced that improves the robustness of B1 (+) mapping. The missing information from undersampled B1 (+) maps and the regions of poor signal to noise ratio are reconstructed through projection into the space of spherical functions that arise naturally from the solution of the Helmholtz equations in the spherical coordinate system. As a result, B1 (+) data over a limited range of the field of view/volume is sufficient to reconstruct the B1 (+) over the full spatial domain in a fast and robust way. The same model is exploited to filter the noise of the measured maps. Results from simulations and in vivo measurements confirm the validity of the proposed method. A spherical functions model can well approximate the magnetic fields inside the body with few basis terms. Exploiting this compression capability, B1 (+) maps are reconstructed in regions of unknown or corrupted values. Copyright © 2013 Wiley Periodicals, Inc.

Intra-operative multi-site stimulation: Expanding methodology for cortical brain mapping of language functions.

PubMed

Gonen, Tal; Gazit, Tomer; Korn, Akiva; Kirschner, Adi; Perry, Daniella; Hendler, Talma; Ram, Zvi

2017-01-01

Direct cortical stimulation (DCS) is considered the gold-standard for functional cortical mapping during awake surgery for brain tumor resection. DCS is performed by stimulating one local cortical area at a time. We present a feasibility study using an intra-operative technique aimed at improving our ability to map brain functions which rely on activity in distributed cortical regions. Following standard DCS, Multi-Site Stimulation (MSS) was performed in 15 patients by applying simultaneous cortical stimulations at multiple locations. Language functioning was chosen as a case-cognitive domain due to its relatively well-known cortical organization. MSS, performed at sites that did not produce disruption when applied in a single stimulation point, revealed additional language dysfunction in 73% of the patients. Functional regions identified by this technique were presumed to be significant to language circuitry and were spared during surgery. No new neurological deficits were observed in any of the patients following surgery. Though the neuro-electrical effects of MSS need further investigation, this feasibility study may provide a first step towards sophistication of intra-operative cortical mapping.

Intra-operative multi-site stimulation: Expanding methodology for cortical brain mapping of language functions

PubMed Central

Korn, Akiva; Kirschner, Adi; Perry, Daniella; Hendler, Talma; Ram, Zvi

2017-01-01

Direct cortical stimulation (DCS) is considered the gold-standard for functional cortical mapping during awake surgery for brain tumor resection. DCS is performed by stimulating one local cortical area at a time. We present a feasibility study using an intra-operative technique aimed at improving our ability to map brain functions which rely on activity in distributed cortical regions. Following standard DCS, Multi-Site Stimulation (MSS) was performed in 15 patients by applying simultaneous cortical stimulations at multiple locations. Language functioning was chosen as a case-cognitive domain due to its relatively well-known cortical organization. MSS, performed at sites that did not produce disruption when applied in a single stimulation point, revealed additional language dysfunction in 73% of the patients. Functional regions identified by this technique were presumed to be significant to language circuitry and were spared during surgery. No new neurological deficits were observed in any of the patients following surgery. Though the neuro-electrical effects of MSS need further investigation, this feasibility study may provide a first step towards sophistication of intra-operative cortical mapping. PMID:28700619

Parallel changes in serum proteins and diffusion tensor imaging in methamphetamine-associated psychosis.

PubMed

Breen, Michael S; Uhlmann, Anne; Ozcan, Sureyya; Chan, Man; Pinto, Dalila; Bahn, Sabine; Stein, Dan J

2017-03-02

Methamphetamine-associated psychosis (MAP) involves widespread neurocognitive and molecular deficits, however accurate diagnosis remains challenging. Integrating relationships between biological markers, brain imaging and clinical parameters may provide an improved mechanistic understanding of MAP, that could in turn drive the development of better diagnostics and treatment approaches. We applied selected reaction monitoring (SRM)-based proteomics, profiling 43 proteins in serum previously implicated in the etiology of major psychiatric disorders, and integrated these data with diffusion tensor imaging (DTI) and psychometric measurements from patients diagnosed with MAP (N = 12), methamphetamine dependence without psychosis (MA; N = 14) and healthy controls (N = 16). Protein analysis identified changes in APOC2 and APOH, which differed significantly in MAP compared to MA and controls. DTI analysis indicated widespread increases in mean diffusivity and radial diffusivity delineating extensive loss of white matter integrity and axon demyelination in MAP. Upon integration, several co-linear relationships between serum proteins and DTI measures reported in healthy controls were disrupted in MA and MAP groups; these involved areas of the brain critical for memory and social emotional processing. These findings suggest that serum proteomics and DTI are sensitive measures for detecting pathophysiological changes in MAP and describe a potential diagnostic fingerprint of the disorder.

The functional cancer map: a systems-level synopsis of genetic deregulation in cancer.

PubMed

Krupp, Markus; Maass, Thorsten; Marquardt, Jens U; Staib, Frank; Bauer, Tobias; König, Rainer; Biesterfeld, Stefan; Galle, Peter R; Tresch, Achim; Teufel, Andreas

2011-06-30

Cancer cells are characterized by massive dysegulation of physiological cell functions with considerable disruption of transcriptional regulation. Genome-wide transcriptome profiling can be utilized for early detection and molecular classification of cancers. Accurate discrimination of functionally different tumor types may help to guide selection of targeted therapy in translational research. Concise grouping of tumor types in cancer maps according to their molecular profile may further be helpful for the development of new therapeutic modalities or open new avenues for already established therapies. Complete available human tumor data of the Stanford Microarray Database was downloaded and filtered for relevance, adequacy and reliability. A total of 649 tumor samples from more than 1400 experiments and 58 different tissues were analyzed. Next, a method to score deregulation of KEGG pathway maps in different tumor entities was established, which was then used to convert hundreds of gene expression profiles into corresponding tumor-specific pathway activity profiles. Based on the latter, we defined a measure for functional similarity between tumor entities, which yielded to phylogeny of tumors. We provide a comprehensive, easy-to-interpret functional cancer map that characterizes tumor types with respect to their biological and functional behavior. Consistently, multiple pathways commonly associated with tumor progression were revealed as common features in the majority of the tumors. However, several pathways previously not linked to carcinogenesis were identified in multiple cancers suggesting an essential role of these pathways in cancer biology. Among these pathways were 'ECM-receptor interaction', 'Complement and Coagulation cascades', and 'PPAR signaling pathway'. The functional cancer map provides a systematic view on molecular similarities across different cancers by comparing tumors on the level of pathway activity. This work resulted in identification of

Beyond the usual mapping functions in GPS, VLBI and Deep Space tracking.

NASA Astrophysics Data System (ADS)

Barriot, Jean-Pierre; Serafini, Jonathan; Sichoix, Lydie

2014-05-01

We describe here a new algorithm to model the water contents of the atmosphere (including ZWD) from GPS slant wet delays relative to a single receiver. We first make the assumption that the water vapor contents are mainly governed by a scale height (exponential law), and secondly that the departures from this decaying exponential can be mapped as a set of low degree 3D Zernike functions (w.r.t. space) and Tchebyshev polynomials (w.r.t. time.) We compare this new algorithm with previous algorithms known as mapping functions in GPS, VLBI and Deep Space tracking and give an example with data acquired over a one day time span at the Geodesy Observatory of Tahiti.

Mapping SAGE questionnaire to the International Classification of Functioning, Disability and Health (ICF).

PubMed

Raggi, Alberto; Quintas, Rui; Russo, Emanuela; Martinuzzi, Andrea; Costardi, Daniela; Frisoni, Giovanni Battista; Franco, Maria Grazia; Andreotti, Alessandra; Ojala, Matti; Peña, Sebastián; Perales, Jaime; Chatterji, Somnath; Miret, Marta; Tobiasz-Adamczyk, Beata; Koskinen, Seppo; Frattura, Lucilla; Leonardi, Matilde

2014-01-01

The collaborative research on ageing in Europe protocol was based on that of the World Health Organization Study on global AGEing and adult health (SAGE) project that investigated the relationship between health and well-being and provided a set of instruments that can be used across countries to monitor health and health-related outcomes of older populations as well as the strategies for addressing issues concerning the ageing process. To evaluate the degree to which SAGE protocol covered the spectrum of disability given the scope of the World Health Organization International Classification of Functioning, Disability and Health (ICF), a mapping exercise was performed with SAGE protocol. Results show that the SAGE protocol covers ICF domains in a non-uniform way, with environmental factors categories being underrepresented, whereas mental, cardiovascular, sensory functions and mobility were overrepresented. To overcome this partial coverage of ICF functioning categories, new assessment instruments have been developed. PRACTITIONER MESSAGE: Mapping exercises are valid procedures to understand the extent to which a survey protocol covers the spectrum of functioning. The mapping exercise with SAGE protocol shows that it provides only a partial representation of body functions and activities and participation domains, and the coverage of environmental factors is poor. New instruments are therefore needed for researchers to properly understand the health and disability of ageing populations. Copyright © 2013 John Wiley & Sons, Ltd.

Diffusion tensor magnetic resonance imaging of the pancreas.

PubMed

Nissan, Noam; Golan, Talia; Furman-Haran, Edna; Apter, Sara; Inbar, Yael; Ariche, Arie; Bar-Zakay, Barak; Goldes, Yuri; Schvimer, Michael; Grobgeld, Dov; Degani, Hadassa

2014-01-01

To develop a diffusion-tensor-imaging (DTI) protocol that is sensitive to the complex diffusion and perfusion properties of the healthy and malignant pancreas tissues. Twenty-eight healthy volunteers and nine patients with pancreatic-ductal-adenocacinoma (PDAC), were scanned at 3T with T2-weighted and DTI sequences. Healthy volunteers were also scanned with multi-b diffusion-weighted-imaging (DWI), whereas a standard clinical protocol complemented the PDAC patients' scans. Image processing at pixel resolution yielded parametric maps of three directional diffusion coefficients λ1, λ2, λ3, apparent diffusion coefficient (ADC), and fractional anisotropy (FA), as well as a λ1-vector map, and a main diffusion-direction map. DTI measurements of healthy pancreatic tissue at b-values 0,500 s/mm² yielded: λ1 = (2.65±0.35)×10⁻³, λ2 = (1.87±0.22)×10⁻³, λ3 = (1.20±0.18)×10⁻³, ADC = (1.91±0.22)×10⁻³ (all in mm²/s units) and FA = 0.38±0.06. Using b-values of 100,500 s/mm² led to a significant reduction in λ1, λ2, λ3 and ADC (p<.0001) and a significant increase (p<0.0001) in FA. The reduction in the diffusion coefficients suggested a contribution of a fast intra-voxel-incoherent-motion (IVIM) component at b≤100 s/mm², which was confirmed by the multi-b DWI results. In PDACs, λ1, λ2, λ3 and ADC in both 0,500 s/mm² and 100,500 s/mm² b-values sets, as well as the reduction in these diffusion coefficients between the two sets, were significantly lower in comparison to the distal normal pancreatic tissue, suggesting higher cellularity and diminution of the fast-IVIM component in the cancer tissue. DTI using two reference b-values 0 and 100 s/mm² enabled characterization of the water diffusion and anisotropy of the healthy pancreas, taking into account a contribution of IVIM. The reduction in the diffusion coefficients of PDAC, as compared to normal pancreatic tissue, and the smaller change in these coefficients in PDAC

Diffusion Tensor Magnetic Resonance Imaging of the Pancreas

PubMed Central

Nissan, Noam; Golan, Talia; Furman-Haran, Edna; Apter, Sara; Inbar, Yael; Ariche, Arie; Bar-Zakay, Barak; Goldes, Yuri; Schvimer, Michael; Grobgeld, Dov; Degani, Hadassa

2014-01-01

Purpose To develop a diffusion-tensor-imaging (DTI) protocol that is sensitive to the complex diffusion and perfusion properties of the healthy and malignant pancreas tissues. Materials and Methods Twenty-eight healthy volunteers and nine patients with pancreatic-ductal-adenocacinoma (PDAC), were scanned at 3T with T2-weighted and DTI sequences. Healthy volunteers were also scanned with multi-b diffusion-weighted-imaging (DWI), whereas a standard clinical protocol complemented the PDAC patients’ scans. Image processing at pixel resolution yielded parametric maps of three directional diffusion coefficients λ1, λ2, λ3, apparent diffusion coefficient (ADC), and fractional anisotropy (FA), as well as a λ1-vector map, and a main diffusion-direction map. Results DTI measurements of healthy pancreatic tissue at b-values 0,500 s/mm2yielded: λ1 = (2.65±0.35)×10−3, λ2 = (1.87±0.22)×10−3, λ3 = (1.20±0.18)×10−3, ADC = (1.91±0.22)×10−3 (all in mm2/s units) and FA = 0.38±0.06. Using b-values of 100,500 s/mm2 led to a significant reduction in λ1, λ2, λ3 and ADC (p<.0001) and a significant increase (p<0.0001) in FA. The reduction in the diffusion coefficients suggested a contribution of a fast intra-voxel-incoherent-motion (IVIM) component at b≤100 s/mm2, which was confirmed by the multi-b DWI results. In PDACs, λ1, λ2, λ3 and ADC in both 0,500 s/mm2 and 100,500 s/mm2 b-values sets, as well as the reduction in these diffusion coefficients between the two sets, were significantly lower in comparison to the distal normal pancreatic tissue, suggesting higher cellularity and diminution of the fast-IVIM component in the cancer tissue. Conclusion DTI using two reference b-values 0 and 100 s/mm2 enabled characterization of the water diffusion and anisotropy of the healthy pancreas, taking into account a contribution of IVIM. The reduction in the diffusion coefficients of PDAC, as compared to normal pancreatic tissue, and the smaller

Chronic kidney disease: Pathological and functional evaluation with intravoxel incoherent motion diffusion-weighted imaging.

PubMed

Mao, Wei; Zhou, Jianjun; Zeng, Mengsu; Ding, Yuqin; Qu, Lijie; Chen, Caizhong; Ding, Xiaoqiang; Wang, Yaqiong; Fu, Caixia

2018-05-01

Because chronic kidney disease (CKD) is a worldwide problem, accurate pathological and functional evaluation is required for planning treatment and follow-up. Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) can assess both capillary perfusion and tissue diffusion and may be helpful in evaluating renal function and pathology. To evaluate functional and pathological alterations in CKD by applying IVIM-DWI. Prospective study. In all, 72 CKD patients who required renal biopsy and 20 healthy volunteers. 1.5T. All subjects underwent IVIM-DWI of the kidneys, and image analysis was performed by two radiologists. The mean values of true diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) were acquired from renal parenchyma. Correlation between IVIM-DWI parameters and estimated glomerular filtration rate (eGFR), as well as pathological damage, were assessed. One-way analysis of variance (ANOVA), paired sample t-test and Spearman correlation analysis. The paired sample t-test revealed that IVIM-DWI parameters were significantly lower in medulla than cortex for both patients and controls (P < 0.01). Regardless of whether eGFR was reduced, ANOVA revealed that f values of renal parenchyma were significantly lower in patients than controls (P < 0.05). Spearman correlation analysis revealed that there were positive correlations between eGFR and D (cortex, r = 0.466, P < 0.001; medulla, r = 0.491, P < 0.001), and between eGFR and f (cortex, r = 0.713, P < 0.001; medulla, r = 0.512, P < 0.001). Negative correlations were found between f and glomerular injury (cortex, r = -0.773, P < 0.001; medulla, r = -0.629, P < 0.001), and between f and tubulointerstitial lesion (cortex, r = -0.728, P < 0.001; medulla, r = -0.547, P < 0.001). IVIM-DWI might be feasible for noninvasive evaluation of renal function and pathology of CKD, especially in detection of renal insufficiency at an early stage. 1

A two-layered diffusion model traces the dynamics of information processing in the valuation-and-choice circuit of decision making.

PubMed

Piu, Pietro; Fargnoli, Francesco; Innocenti, Alessandro; Rufa, Alessandra

2014-01-01

A circuit of evaluation and selection of the alternatives is considered a reliable model in neurobiology. The prominent contributions of the literature to this topic are reported. In this study, valuation and choice of a decisional process during Two-Alternative Forced-Choice (TAFC) task are represented as a two-layered network of computational cells, where information accrual and processing progress in nonlinear diffusion dynamics. The evolution of the response-to-stimulus map is thus modeled by two linked diffusive modules (2LDM) representing the neuronal populations involved in the valuation-and-decision circuit of decision making. Diffusion models are naturally appropriate for describing accumulation of evidence over the time. This allows the computation of the response times (RTs) in valuation and choice, under the hypothesis of ex-Wald distribution. A nonlinear transfer function integrates the activities of the two layers. The input-output map based on the infomax principle makes the 2LDM consistent with the reinforcement learning approach. Results from simulated likelihood time series indicate that 2LDM may account for the activity-dependent modulatory component of effective connectivity between the neuronal populations. Rhythmic fluctuations of the estimate gain functions in the delta-beta bands also support the compatibility of 2LDM with the neurobiology of DM.

Diffuse traumatic brain injury affects chronic corticosterone function in the rat.

PubMed

Rowe, Rachel K; Rumney, Benjamin M; May, Hazel G; Permana, Paska; Adelson, P David; Harman, S Mitchell; Lifshitz, Jonathan; Thomas, Theresa C

2016-07-01

As many as 20-55% of patients with a history of traumatic brain injury (TBI) experience chronic endocrine dysfunction, leading to impaired quality of life, impaired rehabilitation efforts and lowered life expectancy. Endocrine dysfunction after TBI is thought to result from acceleration-deceleration forces to the brain within the skull, creating enduring hypothalamic and pituitary neuropathology, and subsequent hypothalamic-pituitary endocrine (HPE) dysfunction. These experiments were designed to test the hypothesis that a single diffuse TBI results in chronic dysfunction of corticosterone (CORT), a glucocorticoid released in response to stress and testosterone. We used a rodent model of diffuse TBI induced by midline fluid percussion injury (mFPI). At 2months postinjury compared with uninjured control animals, circulating levels of CORT were evaluated at rest, under restraint stress and in response to dexamethasone, a synthetic glucocorticoid commonly used to test HPE axis regulation. Testosterone was evaluated at rest. Further, we assessed changes in injury-induced neuron morphology (Golgi stain), neuropathology (silver stain) and activated astrocytes (GFAP) in the paraventricular nucleus (PVN) of the hypothalamus. Resting plasma CORT levels were decreased at 2months postinjury and there was a blunted CORT increase in response to restraint induced stress. No changes in testosterone were measured. These changes in CORT were observed concomitantly with altered complexity of neuron processes in the PVN over time, devoid of neuropathology or astrocytosis. Results provide evidence that a single moderate diffuse TBI leads to changes in CORT function, which can contribute to the persistence of symptoms related to endocrine dysfunction. Future experiments aim to evaluate additional HP-related hormones and endocrine circuit pathology following diffuse TBI. © 2016 The authors.

Diffuse traumatic brain injury affects chronic corticosterone function in the rat

PubMed Central

Rowe, Rachel K; Rumney, Benjamin M; May, Hazel G; Permana, Paska; Adelson, P David; Harman, S Mitchell; Lifshitz, Jonathan

2016-01-01

As many as 20–55% of patients with a history of traumatic brain injury (TBI) experience chronic endocrine dysfunction, leading to impaired quality of life, impaired rehabilitation efforts and lowered life expectancy. Endocrine dysfunction after TBI is thought to result from acceleration–deceleration forces to the brain within the skull, creating enduring hypothalamic and pituitary neuropathology, and subsequent hypothalamic–pituitary endocrine (HPE) dysfunction. These experiments were designed to test the hypothesis that a single diffuse TBI results in chronic dysfunction of corticosterone (CORT), a glucocorticoid released in response to stress and testosterone. We used a rodent model of diffuse TBI induced by midline fluid percussion injury (mFPI). At 2months postinjury compared with uninjured control animals, circulating levels of CORT were evaluated at rest, under restraint stress and in response to dexamethasone, a synthetic glucocorticoid commonly used to test HPE axis regulation. Testosterone was evaluated at rest. Further, we assessed changes in injury-induced neuron morphology (Golgi stain), neuropathology (silver stain) and activated astrocytes (GFAP) in the paraventricular nucleus (PVN) of the hypothalamus. Resting plasma CORT levels were decreased at 2months postinjury and there was a blunted CORT increase in response to restraint induced stress. No changes in testosterone were measured. These changes in CORT were observed concomitantly with altered complexity of neuron processes in the PVN over time, devoid of neuropathology or astrocytosis. Results provide evidence that a single moderate diffuse TBI leads to changes in CORT function, which can contribute to the persistence of symptoms related to endocrine dysfunction. Future experiments aim to evaluate additional HP-related hormones and endocrine circuit pathology following diffuse TBI. PMID:27317610

Pyridine adsorption and diffusion on Pt(111) investigated with density functional theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolsbjerg, Esben L.; Groves, Michael N.; Hammer, Bjørk, E-mail: hammer@phys.au.dk

2016-04-28

The adsorption, diffusion, and dissociation of pyridine, C{sub 5}H{sub 5}N, on Pt(111) are investigated with van der Waals-corrected density functional theory. An elaborate search for local minima in the adsorption potential energy landscape reveals that the intact pyridine adsorbs with the aromatic ring parallel to the surface. Piecewise interconnections of the local minima in the energy landscape reveal that the most favourable diffusion path for pyridine has a barrier of 0.53 eV. In the preferred path, the pyridine remains parallel to the surface while performing small single rotational steps with a carbon-carbon double bond hinged above a single Pt atom.more » The origin of the diffusion pathway is discussed in terms of the C{sub 2}–Pt π-bond being stronger than the corresponding CN–Pt π-bond. The energy barrier and reaction enthalpy for dehydrogenation of adsorbed pyridine into an adsorbed, upright bound α-pyridyl species are calculated to 0.71 eV and 0.18 eV, respectively (both zero-point energy corrected). The calculations are used to rationalize previous experimental observations from the literature for pyridine on Pt(111).« less

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI.

PubMed

Jones, D K; Alexander, D C; Bowtell, R; Cercignani, M; Dell'Acqua, F; McHugh, D J; Miller, K L; Palombo, M; Parker, G J M; Rudrapatna, U S; Tax, C M W

2018-05-22

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging. Specifically, we will discuss how the increase of the accessible measurement space compared to a lower-gradient systems (in terms of Δ, b-value, and TE) can accelerate developments in the areas of 1) axon diameter distribution mapping; 2) microstructural parameter estimation; 3) mapping micro-vs macroscopic anisotropy features with gradient waveforms beyond a single pair of pulsed-gradients; 4) multi-contrast experiments, e.g. diffusion-relaxometry; 5) tractography and high-resolution imaging in vivo and 6) post mortem; 7) diffusion-weighted spectroscopy of metabolites other than water; 8) tumour characterisation; 9) functional diffusion MRI; and 10) quality enhancement of images acquired on lower-gradient systems. We finally discuss practical barriers in the use of ultra-strong gradients, and provide an outlook on the next generation of 'super-scanners'. Copyright © 2018. Published by Elsevier Inc.

Planck 2015 results. IX. Diffuse component separation: CMB maps

NASA Astrophysics Data System (ADS)

Planck Collaboration; Adam, R.; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Basak, S.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Casaponsa, B.; Castex, G.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fantaye, Y.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Helou, G.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Krachmalnicoff, N.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Le Jeune, M.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Molinari, D.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Racine, B.; Reach, W. T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Trombetti, T.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, F.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present foreground-reduced cosmic microwave background (CMB) maps derived from the full Planck data set in both temperature and polarization. Compared to the corresponding Planck 2013 temperature sky maps, the total data volume is larger by a factor of 3.2 for frequencies between 30 and 70 GHz, and by 1.9 for frequencies between 100 and 857 GHz. In addition, systematic errors in the forms of temperature-to-polarization leakage, analogue-to-digital conversion uncertainties, and very long time constant errors have been dramatically reduced, to the extent that the cosmological polarization signal may now be robustly recovered on angular scales ℓ ≳ 40. On the very largest scales, instrumental systematic residuals are still non-negligible compared to the expected cosmological signal, and modes with ℓ< 20 are accordingly suppressed in the current polarization maps by high-pass filtering. As in 2013, four different CMB component separation algorithms are applied to these observations, providing a measure of stability with respect to algorithmic and modelling choices. The resulting polarization maps have rms instrumental noise ranging between 0.21 and 0.27μK averaged over 55' pixels, and between 4.5 and 6.1μK averaged over 3.4 parcm pixels. The cosmological parameters derived from the analysis of temperature power spectra are in agreement at the 1σ level with the Planck 2015 likelihood. Unresolved mismatches between the noise properties of the data and simulations prevent a satisfactory description of the higher-order statistical properties of the polarization maps. Thus, the primary applications of these polarization maps are those that do not require massive simulations for accurate estimation of uncertainties, for instance estimation of cross-spectra and cross-correlations, or stacking analyses. However, the amplitude of primordial non-Gaussianity is consistent with zero within 2σ for all local, equilateral, and orthogonal configurations of the bispectrum

Planck 2015 results: IX. Diffuse component separation: CMB maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adam, R.; Ade, P. A. R.; Aghanim, N.

In this paper, we present foreground-reduced cosmic microwave background (CMB) maps derived from the full Planck data set in both temperature and polarization. Compared to the corresponding Planck 2013 temperature sky maps, the total data volume is larger by a factor of 3.2 for frequencies between 30 and 70 GHz, and by 1.9 for frequencies between 100 and 857 GHz. In addition, systematic errors in the forms of temperature-to-polarization leakage, analogue-to-digital conversion uncertainties, and very long time constant errors have been dramatically reduced, to the extent that the cosmological polarization signal may now be robustly recovered on angular scales ℓ ≳ 40. On the very largest scales, instrumental systematic residuals are still non-negligible compared to the expected cosmological signal, and modes with ℓ< 20 are accordingly suppressed in the current polarization maps by high-pass filtering. As in 2013, four different CMB component separation algorithms are applied to these observations, providing a measure of stability with respect to algorithmic and modelling choices. Additionally, the resulting polarization maps have rms instrumental noise ranging between 0.21 and 0.27μK averaged over 55' pixels, and between 4.5 and 6.1μK averaged over 3more » $$'\\atop{.}$$4 pixels. The cosmological parameters derived from the analysis of temperature power spectra are in agreement at the 1σ level with the Planck 2015 likelihood. Unresolved mismatches between the noise properties of the data and simulations prevent a satisfactory description of the higher-order statistical properties of the polarization maps. Thus, the primary applications of these polarization maps are those that do not require massive simulations for accurate estimation of uncertainties, for instance estimation of cross-spectra and cross-correlations, or stacking analyses. However, the amplitude of primordial non-Gaussianity is consistent with zero within 2σ for all local, equilateral, and

Planck 2015 results: IX. Diffuse component separation: CMB maps

DOE PAGES

Adam, R.; Ade, P. A. R.; Aghanim, N.; ...

2016-09-20

In this paper, we present foreground-reduced cosmic microwave background (CMB) maps derived from the full Planck data set in both temperature and polarization. Compared to the corresponding Planck 2013 temperature sky maps, the total data volume is larger by a factor of 3.2 for frequencies between 30 and 70 GHz, and by 1.9 for frequencies between 100 and 857 GHz. In addition, systematic errors in the forms of temperature-to-polarization leakage, analogue-to-digital conversion uncertainties, and very long time constant errors have been dramatically reduced, to the extent that the cosmological polarization signal may now be robustly recovered on angular scales ℓ ≳ 40. On the very largest scales, instrumental systematic residuals are still non-negligible compared to the expected cosmological signal, and modes with ℓ< 20 are accordingly suppressed in the current polarization maps by high-pass filtering. As in 2013, four different CMB component separation algorithms are applied to these observations, providing a measure of stability with respect to algorithmic and modelling choices. Additionally, the resulting polarization maps have rms instrumental noise ranging between 0.21 and 0.27μK averaged over 55' pixels, and between 4.5 and 6.1μK averaged over 3more » $$'\\atop{.}$$4 pixels. The cosmological parameters derived from the analysis of temperature power spectra are in agreement at the 1σ level with the Planck 2015 likelihood. Unresolved mismatches between the noise properties of the data and simulations prevent a satisfactory description of the higher-order statistical properties of the polarization maps. Thus, the primary applications of these polarization maps are those that do not require massive simulations for accurate estimation of uncertainties, for instance estimation of cross-spectra and cross-correlations, or stacking analyses. However, the amplitude of primordial non-Gaussianity is consistent with zero within 2σ for all local, equilateral, and

Jigsaw puzzle metasurface for multiple functions: polarization conversion, anomalous reflection and diffusion.

PubMed

Zhao, Yi; Cao, Xiangyu; Gao, Jun; Liu, Xiao; Li, Sijia

2016-05-16

We demonstrate a simple reconfigurable metasurface with multiple functions. Anisotropic tiles are investigated and manufactured as fundamental elements. Then, the tiles are combined in a certain sequence to construct a metasurface. Each of the tiles can be adjusted independently which is like a jigsaw puzzle and the whole metasurface can achieve diverse functions by different layouts. For demonstration purposes, we realize polarization conversion, anomalous reflection and diffusion by a jigsaw puzzle metasurface with 6 × 6 pieces of anisotropic tile. Simulated and measured results prove that our method offers a simple and effective strategy for metasurface design.

Diffusion Properties and 3D Architecture of Human Lower Leg Muscles Assessed with Ultra-High-Field-Strength Diffusion-Tensor MR Imaging and Tractography: Reproducibility and Sensitivity to Sex Difference and Intramuscular Variability.

PubMed

Fouré, Alexandre; Ogier, Augustin C; Le Troter, Arnaud; Vilmen, Christophe; Feiweier, Thorsten; Guye, Maxime; Gondin, Julien; Besson, Pierre; Bendahan, David

2018-05-01

Purpose To demonstrate the reproducibility of the diffusion properties and three-dimensional structural organization measurements of the lower leg muscles by using diffusion-tensor imaging (DTI) assessed with ultra-high-field-strength (7.0-T) magnetic resonance (MR) imaging and tractography of skeletal muscle fibers. On the basis of robust statistical mapping analyses, this study also aimed at determining the sensitivity of the measurements to sex difference and intramuscular variability. Materials and Methods All examinations were performed with ethical review board approval; written informed consent was obtained from all volunteers. Reproducibility of diffusion tensor indexes assessment including eigenvalues, mean diffusivity, and fractional anisotropy (FA) as well as muscle volume and architecture (ie, fiber length and pennation angle) were characterized in lower leg muscles (n = 8). Intramuscular variability and sex differences were characterized in young healthy men and women (n = 10 in each group). Student t test, statistical parametric mapping, correlation coefficients (Spearman rho and Pearson product-moment) and coefficient of variation (CV) were used for statistical data analysis. Results High reproducibility of measurements (mean CV ± standard deviation, 4.6% ± 3.8) was determined in diffusion properties and architectural parameters. Significant sex differences were detected in FA (4.2% in women for the entire lower leg; P = .001) and muscle volume (21.7% in men for the entire lower leg; P = .008), whereas architecture parameters were almost identical across sex. Additional differences were found independently of sex in diffusion properties and architecture along several muscles of the lower leg. Conclusion The high-spatial-resolution DTI assessed with 7.0-T MR imaging allows a reproducible assessment of structural organization of superficial and deep muscles, giving indirect information on muscle function. © RSNA, 2018 Online supplemental material is

Green functions and Langevin equations for nonlinear diffusion equations: A comment on ‘Markov processes, Hurst exponents, and nonlinear diffusion equations’ by Bassler et al.

NASA Astrophysics Data System (ADS)

Frank, T. D.

2008-02-01

We discuss two central claims made in the study by Bassler et al. [K.E. Bassler, G.H. Gunaratne, J.L. McCauley, Physica A 369 (2006) 343]. Bassler et al. claimed that Green functions and Langevin equations cannot be defined for nonlinear diffusion equations. In addition, they claimed that nonlinear diffusion equations are linear partial differential equations disguised as nonlinear ones. We review bottom-up and top-down approaches that have been used in the literature to derive Green functions for nonlinear diffusion equations and, in doing so, show that the first claim needs to be revised. We show that the second claim as well needs to be revised. To this end, we point out similarities and differences between non-autonomous linear Fokker-Planck equations and autonomous nonlinear Fokker-Planck equations. In this context, we raise the question whether Bassler et al.’s approach to financial markets is physically plausible because it necessitates the introduction of external traders and causes. Such external entities can easily be eliminated when taking self-organization principles and concepts of nonextensive thermostatistics into account and modeling financial processes by means of nonlinear Fokker-Planck equations.

Ordering process in the diffusively coupled logistic lattice

NASA Astrophysics Data System (ADS)

Conrado, Claudine V.; Bohr, Tomas

1991-08-01

We study the ordering process in a lattice of diffusively coupled logistic maps for increasing lattice size. Within a window of parameters, the system goes into a weakly chaotic state with long range "antiferromagnetic" order. This happens for arbitrary lattice size L and the ordering time behaves as t ~ L2 as we would expect from a picture of diffusing defects.

Comparison of block and event-related experimental designs in diffusion-weighted functional MRI.

PubMed

Williams, Rebecca J; McMahon, Katie L; Hocking, Julia; Reutens, David C

2014-08-01

To compare diffusion-weighted functional magnetic resonance imaging (DfMRI), a novel alternative to the blood oxygenation level-dependent (BOLD) contrast, in a functional MRI experiment. Nine participants viewed contrast reversing (7.5 Hz) black-and-white checkerboard stimuli using block and event-related paradigms. DfMRI (b = 1800 mm/s(2)) and BOLD sequences were acquired. Four parameters describing the observed signal were assessed: percent signal change, spatial extent of the activation, the Euclidean distance between peak voxel locations, and the time-to-peak of the best fitting impulse response for different paradigms and sequences. The BOLD conditions showed a higher percent signal change relative to DfMRI; however, event-related DfMRI showed the strongest group activation (t = 21.23, P < 0.0005). Activation was more diffuse and spatially closer to the BOLD response for DfMRI when the block design was used. DfMRIevent showed the shortest TTP (4.4 ± 0.88 sec). The hemodynamic contribution to DfMRI may increase with the use of block designs. © 2013 Wiley Periodicals, Inc.

Multiparametric or practical quantitative liver MRI: towards millisecond, fat fraction, kilopascal and function era.

PubMed

Unal, Emre; Idilman, Ilkay Sedakat; Karçaaltıncaba, Muşturay

2017-02-01

New advances in liver magnetic resonance imaging (MRI) may enable diagnosis of unseen pathologies by conventional techniques. Normal T1 (550-620 ms for 1.5 T and 700-850 ms for 3 T), T2, T2* (>20 ms), T1rho (40-50 ms) mapping, proton density fat fraction (PDFF) (≤5%) and stiffness (2-3kPa) values can enable differentiation of a normal liver from chronic liver and diffuse diseases. Gd-EOB-DTPA can enable assessment of liver function by using postcontrast hepatobiliary phase or T1 reduction rate (normally above 60%). T1 mapping can be important for the assessment of fibrosis, amyloidosis and copper overload. T1rho mapping is promising for the assessment of liver collagen deposition. PDFF can allow objective treatment assessment in NAFLD and NASH patients. T2 and T2* are used for iron overload determination. MR fingerprinting may enable single slice acquisition and easy implementation of multiparametric MRI and follow-up of patients. Areas covered: T1, T2, T2*, PDFF and stiffness, diffusion weighted imaging, intravoxel incoherent motion imaging (ADC, D, D* and f values) and function analysis are reviewed. Expert commentary: Multiparametric MRI can enable biopsyless diagnosis and more objective staging of diffuse liver disease, cirrhosis and predisposing diseases. A comprehensive approach is needed to understand and overcome the effects of iron, fat, fibrosis, edema, inflammation and copper on MR relaxometry values in diffuse liver disease.

Optimization of Scan Parameters to Reduce Acquisition Time for Diffusion Kurtosis Imaging at 1.5T.

PubMed

Yokosawa, Suguru; Sasaki, Makoto; Bito, Yoshitaka; Ito, Kenji; Yamashita, Fumio; Goodwin, Jonathan; Higuchi, Satomi; Kudo, Kohsuke

2016-01-01

To shorten acquisition of diffusion kurtosis imaging (DKI) in 1.5-tesla magnetic resonance (MR) imaging, we investigated the effects of the number of b-values, diffusion direction, and number of signal averages (NSA) on the accuracy of DKI metrics. We obtained 2 image datasets with 30 gradient directions, 6 b-values up to 2500 s/mm(2), and 2 signal averages from 5 healthy volunteers and generated DKI metrics, i.e., mean, axial, and radial kurtosis (MK, K∥, and K⊥) maps, from various combinations of the datasets. These maps were estimated by using the intraclass correlation coefficient (ICC) with those from the full datasets. The MK and K⊥ maps generated from the datasets including only the b-value of 2500 s/mm(2) showed excellent agreement (ICC, 0.96 to 0.99). Under the same acquisition time and diffusion directions, agreement was better of MK, K∥, and K⊥ maps obtained with 3 b-values (0, 1000, and 2500 s/mm(2)) and 4 signal averages than maps obtained with any other combination of numbers of b-value and varied NSA. Good agreement (ICC > 0.6) required at least 20 diffusion directions in all the metrics. MK and K⊥ maps with ICC greater than 0.95 can be obtained at 1.5T within 10 min (b-value = 0, 1000, and 2500 s/mm(2); 20 diffusion directions; 4 signal averages; slice thickness, 6 mm with no interslice gap; number of slices, 12).

Stable learning of functional maps in self-organizing spiking neural networks with continuous synaptic plasticity

PubMed Central

Srinivasa, Narayan; Jiang, Qin

2013-01-01

This study describes a spiking model that self-organizes for stable formation and maintenance of orientation and ocular dominance maps in the visual cortex (V1). This self-organization process simulates three development phases: an early experience-independent phase, a late experience-independent phase and a subsequent refinement phase during which experience acts to shape the map properties. The ocular dominance maps that emerge accommodate the two sets of monocular inputs that arise from the lateral geniculate nucleus (LGN) to layer 4 of V1. The orientation selectivity maps that emerge feature well-developed iso-orientation domains and fractures. During the last two phases of development the orientation preferences at some locations appear to rotate continuously through ±180° along circular paths and referred to as pinwheel-like patterns but without any corresponding point discontinuities in the orientation gradient maps. The formation of these functional maps is driven by balanced excitatory and inhibitory currents that are established via synaptic plasticity based on spike timing for both excitatory and inhibitory synapses. The stability and maintenance of the formed maps with continuous synaptic plasticity is enabled by homeostasis caused by inhibitory plasticity. However, a prolonged exposure to repeated stimuli does alter the formed maps over time due to plasticity. The results from this study suggest that continuous synaptic plasticity in both excitatory neurons and interneurons could play a critical role in the formation, stability, and maintenance of functional maps in the cortex. PMID:23450808

Scaling results for the magnetic field line trajectories in the stochastic layer near the separatrix in divertor tokamaks with high magnetic shear using the higher shear map

NASA Astrophysics Data System (ADS)

Punjabi, Alkesh; Ali, Halima; Farhat, Hamidullah

2009-07-01

Extra terms are added to the generating function of the simple map (Punjabi et al 1992 Phys. Rev. Lett. 69 3322) to adjust shear of magnetic field lines in divertor tokamaks. From this new generating function, a higher shear map is derived from a canonical transformation. A continuous analog of the higher shear map is also derived. The method of maps (Punjabi et al 1994 J. Plasma Phys. 52 91) is used to calculate the average shear, stochastic broadening of the ideal separatrix near the X-point in the principal plane of the tokamak, loss of poloidal magnetic flux from inside the ideal separatrix, magnetic footprint on the collector plate, and its area, and the radial diffusion coefficient of magnetic field lines near the X-point. It is found that the width of the stochastic layer near the X-point and the loss of poloidal flux from inside the ideal separatrix scale linearly with average shear. The area of magnetic footprints scales roughly linearly with average shear. Linear scaling of the area is quite good when the average shear is greater than or equal to 1.25. When the average shear is in the range 1.1-1.25, the area of the footprint fluctuates (as a function of average shear) and scales faster than linear scaling. Radial diffusion of field lines near the X-point increases very rapidly by about four orders of magnitude as average shear increases from about 1.15 to 1.5. For higher values of average shear, diffusion increases linearly, and comparatively very slowly. The very slow scaling of the radial diffusion of the field can flatten the plasma pressure gradient near the separatrix, and lead to the elimination of type-I edge localized modes.

Diffusion tensor imaging in evaluation of human skeletal muscle injury.

PubMed

Zaraiskaya, Tatiana; Kumbhare, Dinesh; Noseworthy, Michael D

2006-08-01

To explore the capability and reliability of diffusion tensor magnetic resonance imaging (DTI) in the evaluation of human skeletal muscle injury. DTI of four patients with gastrocnemius and soleus muscles injuries was compared to eight healthy controls. Imaging was performed using a GE 3.0T short-bore scanner. A diffusion-weighted 2D spin echo echo-planar imaging (EPI) pulse sequence optimized for skeletal muscle was used. From a series of axially acquired diffusion tensor images the diffusion tensor eigenparameters (eigenvalues and eigenvectors), fractional anisotropy (FA), and apparent diffusion coefficient (ADC) were calculated and compared for injured and healthy calf muscles. Two dimensional (2D) projection maps of the principal eigenvectors were plotted to visualize the healthy and pathologic muscle fiber architectures. Clear differences in FA and ADC were observed in injured skeletal muscle, compared to healthy controls. Mean control FA was 0.23 +/- 0.02 for medial and lateral gastrocnemius (mg and lg) muscles, and 0.20 +/- 0.02 for soleus (sol) muscles. In all patients FA values were reduced compared to controls, to as low as 0.08 +/- 0.02. The ADC in controls ranged from 1.41 to 1.31 x 10(-9) m(2)/second, while in patients this was consistently higher. The 2D projection maps revealed muscle fiber disorder in injured calves, while in healthy controls the 2D projection maps show a well organized (ordered) fiber structure. DTI is a suitable method to assess human calf muscle injury.

Functional mapping of cell surface proteins with localized stimulation of single cells

NASA Astrophysics Data System (ADS)

Sun, Bingyun; Chiu, Daniel T.

2003-11-01

This paper describes the development of using individual micro and nano meter-sized vesicles as delivery vessels to functionally map the distribution of cell surface proteins at the level of single cells. The formation of different sizes of vesicles from tens of nanometers to a few micrometers in diameter that contain the desired molecules is addressed. An optical trap is used to manipulate the loaded vesicle to specific cell morphology of interest, and a pulsed UV laser is used to photo-release the stimuli onto the cell membrane. Carbachol activated cellular calcium flux, upon binding to muscarinic acetylcholine receptors, is studied by this method, and the potential of using this method for the functional mapping of localized proteins on the cell surface membrane is discussed.

Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach.

PubMed

Rajan, Jeny; Kannan, K; Kesavadas, C; Thomas, Bejoy

2009-10-01

Identification of Focal Cortical Dysplasia (FCD) can be difficult due to the subtle MRI changes. Though sequences like FLAIR (fluid attenuated inversion recovery) can detect a large majority of these lesions, there are smaller lesions without signal changes that can easily go unnoticed by the naked eye. The aim of this study is to improve the visibility of focal cortical dysplasia lesions in the T1 weighted brain MRI images. In the proposed method, we used a complex diffusion based approach for calculating the FCD affected areas. Based on the diffused image and thickness map, a complex map is created. From this complex map; FCD areas can be easily identified. MRI brains of 48 subjects selected by neuroradiologists were given to computer scientists who developed the complex map for identifying the cortical dysplasia. The scientists were blinded to the MRI interpretation result of the neuroradiologist. The FCD could be identified in all the patients in whom surgery was done, however three patients had false positive lesions. More lesions were identified in patients in whom surgery was not performed and lesions were seen in few of the controls. These were considered as false positive. This computer aided detection technique using complex diffusion approach can help detect focal cortical dysplasia in patients with epilepsy.

An Efficient Algorithm for Mapping Imaging Data to 3D Unstructured Grids in Computational Biomechanics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Einstein, Daniel R.; Kuprat, Andrew P.; Jiao, Xiangmin

2013-01-01

Geometries for organ scale and multiscale simulations of organ function are now routinely derived from imaging data. However, medical images may also contain spatially heterogeneous information other than geometry that are relevant to such simulations either as initial conditions or in the form of model parameters. In this manuscript, we present an algorithm for the efficient and robust mapping of such data to imaging based unstructured polyhedral grids in parallel. We then illustrate the application of our mapping algorithm to three different mapping problems: 1) the mapping of MRI diffusion tensor data to an unstuctured ventricular grid; 2) the mappingmore » of serial cyro-section histology data to an unstructured mouse brain grid; and 3) the mapping of CT-derived volumetric strain data to an unstructured multiscale lung grid. Execution times and parallel performance are reported for each case.« less

The development and mapping of functional markers in Fragaria and their transferability and potential for mapping in other genera.

PubMed

Sargent, D J; Rys, A; Nier, S; Simpson, D W; Tobutt, K R

2007-01-01

We have developed 46 primer pairs from exon sequences flanking polymorphic introns of 23 Fragaria gene sequences and one Malus sequence deposited in the EMBL database. Sequencing of a set of the PCR products amplified with the novel primer pairs in diploid Fragaria showed the products to be homologous to the sequences from which the primers were originally designed. By scoring the segregation of the 24 genes in two diploid Fragaria progenies FV x FN (F. vesca x F. nubicola F(2)) and 815 x 903BC (F. vesca x F. viridis BC(1)) 29 genetic loci at discrete positions on the seven linkage groups previously characterised could be mapped, bringing to 35 the total number of known function genes mapped in Fragaria. Twenty primer pairs, representing 14 genes, amplified a product of the expected size in both Malus and Prunus. To demonstrate the applicability of these gene-specific loci to comparative mapping in Rosaceae, five markers that displayed clear polymorphism between the parents of a Malus and a Prunus mapping population were selected. The markers were then scored and mapped in at least one of the two additional progenies.

Dissipative particle dynamics study of velocity autocorrelation function and self-diffusion coefficient in terms of interaction potential strength

NASA Astrophysics Data System (ADS)

Zohravi, Elnaz; Shirani, Ebrahim; Pishevar, Ahmadreza; Karimpour, Hossein

2018-07-01

This research focuses on numerically investigating the self-diffusion coefficient and velocity autocorrelation function (VACF) of a dissipative particle dynamics (DPD) fluid as a function of the conservative interaction strength. Analytic solutions to VACF and self-diffusion coefficients in DPD were obtained by many researchers in some restricted cases including ideal gases, without the account of conservative force. As departure from the ideal gas conditions are accentuated with increasing the relative proportion of conservative force, it is anticipated that the VACF should gradually deviate from its normally expected exponentially decay. This trend is confirmed through numerical simulations and an expression in terms of the conservative force parameter, density and temperature is proposed for the self-diffusion coefficient. As it concerned the VACF, the equivalent Langevin equation describing Brownian motion of particles with a harmonic potential is adapted to the problem and reveals an exponentially decaying oscillatory pattern influenced by the conservative force parameter, dissipative parameter and temperature. Although the proposed model for obtaining the self-diffusion coefficient with consideration of the conservative force could not be verified due to computational complexities, nonetheless the Arrhenius dependency of the self-diffusion coefficient to temperature and pressure permits to certify our model over a definite range of DPD parameters.

Functional and structural mapping of human cerebral cortex: Solutions are in the surfaces

PubMed Central

Van Essen, David C.; Drury, Heather A.; Joshi, Sarang; Miller, Michael I.

1998-01-01

The human cerebral cortex is notorious for the depth and irregularity of its convolutions and for its variability from one individual to the next. These complexities of cortical geography have been a chronic impediment to studies of functional specialization in the cortex. In this report, we discuss ways to compensate for the convolutions by using a combination of strategies whose common denominator involves explicit reconstructions of the cortical surface. Surface-based visualization involves reconstructing cortical surfaces and displaying them, along with associated experimental data, in various complementary formats (including three-dimensional native configurations, two-dimensional slices, extensively smoothed surfaces, ellipsoidal representations, and cortical flat maps). Generating these representations for the cortex of the Visible Man leads to a surface-based atlas that has important advantages over conventional stereotaxic atlases as a substrate for displaying and analyzing large amounts of experimental data. We illustrate this by showing the relationship between functionally specialized regions and topographically organized areas in human visual cortex. Surface-based warping allows data to be mapped from individual hemispheres to a surface-based atlas while respecting surface topology, improving registration of identifiable landmarks, and minimizing unwanted distortions. Surface-based warping also can aid in comparisons between species, which we illustrate by warping a macaque flat map to match the shape of a human flat map. Collectively, these approaches will allow more refined analyses of commonalities as well as individual differences in the functional organization of primate cerebral cortex. PMID:9448242

Functional and structural mapping of human cerebral cortex: solutions are in the surfaces

NASA Technical Reports Server (NTRS)

Van Essen, D. C.; Drury, H. A.; Joshi, S.; Miller, M. I.

1998-01-01

The human cerebral cortex is notorious for the depth and irregularity of its convolutions and for its variability from one individual to the next. These complexities of cortical geography have been a chronic impediment to studies of functional specialization in the cortex. In this report, we discuss ways to compensate for the convolutions by using a combination of strategies whose common denominator involves explicit reconstructions of the cortical surface. Surface-based visualization involves reconstructing cortical surfaces and displaying them, along with associated experimental data, in various complementary formats (including three-dimensional native configurations, two-dimensional slices, extensively smoothed surfaces, ellipsoidal representations, and cortical flat maps). Generating these representations for the cortex of the Visible Man leads to a surface-based atlas that has important advantages over conventional stereotaxic atlases as a substrate for displaying and analyzing large amounts of experimental data. We illustrate this by showing the relationship between functionally specialized regions and topographically organized areas in human visual cortex. Surface-based warping allows data to be mapped from individual hemispheres to a surface-based atlas while respecting surface topology, improving registration of identifiable landmarks, and minimizing unwanted distortions. Surface-based warping also can aid in comparisons between species, which we illustrate by warping a macaque flat map to match the shape of a human flat map. Collectively, these approaches will allow more refined analyses of commonalities as well as individual differences in the functional organization of primate cerebral cortex.

A Non-parametric Approach to Constrain the Transfer Function in Reverberation Mapping

NASA Astrophysics Data System (ADS)

Li, Yan-Rong; Wang, Jian-Min; Bai, Jin-Ming

2016-11-01

Broad emission lines of active galactic nuclei stem from a spatially extended region (broad-line region, BLR) that is composed of discrete clouds and photoionized by the central ionizing continuum. The temporal behaviors of these emission lines are blurred echoes of continuum variations (I.e., reverberation mapping, RM) and directly reflect the structures and kinematic information of BLRs through the so-called transfer function (also known as the velocity-delay map). Based on the previous works of Rybicki and Press and Zu et al., we develop an extended, non-parametric approach to determine the transfer function for RM data, in which the transfer function is expressed as a sum of a family of relatively displaced Gaussian response functions. Therefore, arbitrary shapes of transfer functions associated with complicated BLR geometry can be seamlessly included, enabling us to relax the presumption of a specified transfer function frequently adopted in previous studies and to let it be determined by observation data. We formulate our approach in a previously well-established framework that incorporates the statistical modeling of continuum variations as a damped random walk process and takes into account long-term secular variations which are irrelevant to RM signals. The application to RM data shows the fidelity of our approach.

Correlation Structure of Fractional Pearson Diffusions.

PubMed

Leonenko, Nikolai N; Meerschaert, Mark M; Sikorskii, Alla

2013-09-01

The stochastic solution to a diffusion equations with polynomial coefficients is called a Pearson diffusion. If the first time derivative is replaced by a Caputo fractional derivative of order less than one, the stochastic solution is called a fractional Pearson diffusion. This paper develops an explicit formula for the covariance function of a fractional Pearson diffusion in steady state, in terms of Mittag-Leffler functions. That formula shows that fractional Pearson diffusions are long range dependent, with a correlation that falls off like a power law, whose exponent equals the order of the fractional derivative.

Diffusion tensor imaging and T2 mapping in early denervated skeletal muscle in rats.

PubMed

Ha, Dong-Ho; Choi, Sunseob; Kang, Eun-Ju; Park, Hwan Tae

2015-09-01

To evaluate the temporal changes of diffusion tensor imaging (DTI) indices, T2 values, and visual signal intensity on various fat suppression techniques in the early state of denervated skeletal muscle in a rat model. Institutional Animal Care and Use Committee approval was obtained. Sciatic nerves of eight rats were transected for irreversible neurotmesis model. We examined normal lower leg and denervated muscles at 3 days, 1 week, and 2 weeks on a 3 Tesla MR. fractional anisotropy (FA), mean apparent diffusion coefficient (mADC), and T2 values were measured by using DTI and T2 mapping scan. We subjectively classified the signal intensity change on various fat suppression images into the following three grades: negative, suspicious, and definite change. Wilcoxon-sign rank test and Kruskal-Wallis test were used for the comparison of FA, mADC, T2 values. McNemar's test was used for comparing signal intensity change among fat suppression techniques. FA values of denervated muscles at 3 days (0.35 ± 0.06), 1 week (0.29 ± 0.04), and 2 weeks (0.34 ± 0.05) were significantly (P < 0.05) lower than that in the control group (0.54 ± 0.17). mADC of denervated muscles decreased without statistically significant (P > 0.05) change. T2 values were significantly increased at 1 week (38.11 ± 6.42 ms, P = 0.017) and markedly increased at 2 weeks (46.53 ± 5.17 ms, P = 0.012). The grade of visual signal intensity change on chemical shift selective fat saturation, STIR and IDEAL images were identical in all cases (P = 1.000). FA and T2 values can demonstrate the early temporal changes in denervated rat skeletal muscle. © 2014 Wiley Periodicals, Inc.

Innovation-diffusion: a geographical study of the transition of family limitation practice in Taiwan.

PubMed

Ting, T Y

1984-09-01

This paper uses map analysis to study the transition of family limitation practice in Taiwan between 1961-80. The innovation-diffusion perspective emphasizes that birth control, particularly contraception, is a recent innovation and is essentially new in human culture. The innovation-diffusion theory assumes that the decline of fertility began in a setting where there was no, or at most very limited, previous practice of birth control. The theory emphasizes the importance of the spread of information. It also assumes that innovation starts in metropolitan centers, diffuses to other urban places with some delay, and penetrates to rural areas still later. Innovation behavior also diffuses from 1 area to another which is culturally and linguistically similar. Although there was some urban to rural diffusion from the Taiwan family planning program, the government supported program provided services more evenly between urban and rural areas, thus somewhat limiting the diffusion effect from the program. For the diffusion of family practice in Taiwan, it is expected that the availability of of information about and means of family limitation practice may effect the rate of the increase of small m values -- an index of family limitation -- in an area. The case study of Pingtung county shows that the demand-side diffusion from urban to rural areas was important in the earlier decade of the transition of family plimitation practice, but distance from urban center was less important as practice became more uniform through diffusion. Ethnicity, whether or not the township was dominated by Hakka or Fukienese, also seems to have played an important role in determining the pace at which the local residents adopted family practice limitation. Hakka townships seem to have adopted family limitation practice more slowly than Fukienese townships about the same distance from the urban center. The map analysis of Pingtung county provides descriptive evidence to support the diffusion of

Functional Maps of Neocortical Local Circuitry

PubMed Central

Thomson, Alex M.; Lamy, Christophe

2007-01-01

This review aims to summarize data obtained with different techniques to provide a functional map of the local circuit connections made by neocortical neurones, a reference for those interested in cortical circuitry and the numerical information required by those wishing to model the circuit. A brief description of the main techniques used to study circuitry is followed by outline descriptions of the major classes of neocortical excitatory and inhibitory neurones and the connections that each layer makes with other cortical and subcortical regions. Maps summarizing the projection patterns of each class of neurone within the local circuit and tables of the properties of these local circuit connections are provided. This review relies primarily on anatomical studies that have identified the classes of neurones and their local and long distance connections and on paired intracellular and whole-cell recordings which have documented the properties of the connections between them. A large number of different types of synaptic connections have been described, but for some there are only a few published examples and for others the details that can only be obtained with paired recordings and dye-filling are lacking. A further complication is provided by the range of species, technical approaches and age groups used in these studies. Wherever possible the range of available data are summarised and compared. To fill some of the more obvious gaps for the less well-documented cases, data obtained with other methods are also summarized. PMID:18982117

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

PubMed

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

Physics, Techniques and Review of Neuroradiological Applications of Diffusion Kurtosis Imaging (DKI).

PubMed

Marrale, M; Collura, G; Brai, M; Toschi, N; Midiri, F; La Tona, G; Lo Casto, A; Gagliardo, C

2016-12-01

In recent years many papers about diagnostic applications of diffusion tensor imaging (DTI) have been published. This is because DTI allows to evaluate in vivo and in a non-invasive way the process of diffusion of water molecules in biological tissues. However, the simplified description of the diffusion process assumed in DTI does not permit to completely map the complex underlying cellular components and structures, which hinder and restrict the diffusion of water molecules. These limitations can be partially overcome by means of diffusion kurtosis imaging (DKI). The aim of this paper is the description of the theory of DKI, a new topic of growing interest in radiology. DKI is a higher order diffusion model that is a straightforward extension of the DTI model. Here, we analyze the physics underlying this method, we report our MRI acquisition protocol with the preprocessing pipeline used and the DKI parametric maps obtained on a 1.5 T scanner, and we review the most relevant clinical applications of this technique in various neurological diseases.

Diffusion properties of molecules at the blood-brain interface: potential contributions of astrocyte endfeet to diffusion barrier functions.

PubMed

Nuriya, Mutsuo; Shinotsuka, Takanori; Yasui, Masato

2013-09-01

Molecular diffusion in the extracellular space (ECS) plays a key role in determining tissue physiology and pharmacology. The blood-brain barrier regulates the exchange of substances between the brain and the blood, but the diffusion properties of molecules at this blood-brain interface, particularly around the astrocyte endfeet, are poorly characterized. In this study, we used 2-photon microscopy and acute brain slices of mouse neocortex and directly assessed the diffusion patterns of fluorescent molecules. By observing the diffusion of unconjugated and 10-kDa dextran-conjugated Alexa Fluor 488 from the ECS of the brain parenchyma to the blood vessels, we find various degrees of diffusion barriers at the endfeet: Some allow the invasion of dye inside the endfoot network while others completely block it. Detailed analyses of the time course for dye clearance support the existence of a tight endfoot network capable of acting as a diffusion barrier. Finally, we show that this diffusion pattern collapses under pathological conditions. These data demonstrate the heterogeneous nature of molecular diffusion dynamics around the endfeet and suggest that these structures can serve as the diffusion barrier. Therefore, astrocyte endfeet may add another layer of regulation to the exchange of molecules between blood vessels and brain parenchyma.

Associations of electrocardiographic P-wave characteristics with left atrial function, and diffuse left ventricular fibrosis defined by cardiac magnetic resonance: The PRIMERI Study.

PubMed

Tiffany Win, Theingi; Ambale Venkatesh, Bharath; Volpe, Gustavo J; Mewton, Nathan; Rizzi, Patricia; Sharma, Ravi K; Strauss, David G; Lima, Joao A; Tereshchenko, Larisa G

2015-01-01

Abnormal P-terminal force in lead V1 (PTFV1) is associated with an increased risk of heart failure, stroke, atrial fibrillation, and death. Our goal was to explore associations of left ventricular (LV) diffuse fibrosis with left atrial (LA) function and electrocardiographic (ECG) measures of LA electrical activity. Patients without atrial fibrillation (n = 91; mean age 59.5 years; 61.5% men; 65.9% white) with structural heart disease (spatial QRS-T angle ≥105° and/or Selvester QRS score ≥5 on ECG) but LV ejection fraction >35% underwent clinical evaluation, cardiac magnetic resonance, and resting ECG. LA function indices were obtained by multimodality tissue tracking using 2- and 4-chamber long-axis images. T1 mapping and late gadolinium enhancement were used to assess diffuse LV fibrosis and presence of scar. P-prime in V1 amplitude (PPaV1) and duration (PPdV1), averaged P-wave-duration, PR interval, and P-wave axis were automatically measured using 12 SLTM algorithm. PTFV1 was calculated as a product of PPaV1 and PPdV1. In linear regression after adjustment for demographic characteristics, body mass index, maximum LA volume index, presence of scar, and LV mass index, each decile increase in LV interstitial fibrosis was associated with 0.76 mV*ms increase in negative abnormal PTFV1 (95% confidence interval [CI] -1.42 to -0.09; P = .025), 15.3 ms prolongation of PPdV1 (95% CI 6.9 to 23.8; P = .001) and 5.4 ms prolongation of averaged P-duration (95% CI 0.9-10.0; P = .020). LV fibrosis did not affect LA function. PPaV1 and PTFV1 were associated with an increase in LA volumes and decrease in LA emptying fraction and LA reservoir function. LV interstitial fibrosis is associated with abnormal PTFV1, prolonged PPdV1, and P-duration, but does not affect LA function. Copyright © 2015 Heart Rhythm Society. All rights reserved.

Effect of different tropospheric mapping functions on the TRF, CRF and position time-series estimated from VLBI

NASA Astrophysics Data System (ADS)

Tesmer, Volker; Boehm, Johannes; Heinkelmann, Robert; Schuh, Harald

2007-06-01

This paper compares estimated terrestrial reference frames (TRF) and celestial reference frames (CRF) as well as position time-series in terms of systematic differences, scale, annual signals and station position repeatabilities using four different tropospheric mapping functions (MF): The NMF (Niell Mapping Function) and the recently developed GMF (Global Mapping Function) consist of easy-to-handle stand-alone formulae, whereas the IMF (Isobaric Mapping Function) and the VMF1 (Vienna Mapping Function 1) are determined from numerical weather models. All computations were performed at the Deutsches Geodätisches Forschungsinstitut (DGFI) using the OCCAM 6.1 and DOGS-CS software packages for Very Long Baseline Interferometry (VLBI) data from 1984 until 2005. While it turned out that CRF estimates only slightly depend on the MF used, showing small systematic effects up to 0.025 mas, some station heights of the computed TRF change by up to 13 mm. The best agreement was achieved for the VMF1 and GMF results concerning the TRFs, and for the VMF1 and IMF results concerning scale variations and position time-series. The amplitudes of the annual periodical signals in the time-series of estimated heights differ by up to 5 mm. The best precision in terms of station height repeatability is found for the VMF1, which is 5 7% better than for the other MFs.

The role of long-range connectivity for the characterization of the functional-anatomical organization of the cortex.

PubMed

Knösche, Thomas R; Tittgemeyer, Marc

2011-01-01

This review focuses on the role of long-range connectivity as one element of brain structure that is of key importance for the functional-anatomical organization of the cortex. In this context, we discuss the putative guiding principles for mapping brain function and structure onto the cortical surface. Such mappings reveal a high degree of functional-anatomical segregation. Given that brain regions frequently maintain characteristic connectivity profiles and the functional repertoire of a cortical area is closely related to its anatomical connections, long-range connectivity may be used to define segregated cortical areas. This methodology is called connectivity-based parcellation. Within this framework, we investigate different techniques to estimate connectivity profiles with emphasis given to non-invasive methods based on diffusion magnetic resonance imaging (dMRI) and diffusion tractography. Cortical parcellation is then defined based on similarity between diffusion tractograms, and different clustering approaches are discussed. We conclude that the use of non-invasively acquired connectivity estimates to characterize the functional-anatomical organization of the brain is a valid, relevant, and necessary endeavor. Current and future developments in dMRI technology, tractography algorithms, and models of the similarity structure hold great potential for a substantial improvement and enrichment of the results of the technique.

Diffusion Kurtosis Imaging of Acute Infarction: Comparison with Routine Diffusion and Follow-up MR Imaging.

PubMed

Yin, Jianzhong; Sun, Haizhen; Wang, Zhiyun; Ni, Hongyan; Shen, Wen; Sun, Phillip Zhe

2018-05-01

Purpose To determine the relationship between diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in patients with acute stroke at admission and the tissue outcome 1 month after onset of stroke. Materials and Methods Patients with stroke underwent DWI (b values = 0, 1000 sec/mm 2 along three directions) and DKI (b values = 0, 1000, 2000 sec/mm 2 along 20 directions) within 24 hours after symptom onset and 1 month after symptom onset. For large lesions (diameter ≥ 1 cm), acute lesion volumes at DWI and DKI were compared with those at follow-up T2-weighted imaging by using Spearman correlation analysis. For small lesions (diameter < 1 cm), the number of acute lesions at DWI and DKI and follow-up T2-weighted imaging was counted and compared by using the McNemar test. Results Thirty-seven patients (mean age, 58 years; range, 35-82 years) were included. There were 32 large lesions and 138 small lesions. For large lesions, the volumes of acute lesions on kurtosis maps showed no difference from those on 1-month follow-up T2-weighted images (P = .532), with a higher correlation coefficient than those on the apparent diffusion coefficient and mean diffusivity maps (R 2 = 0.730 vs 0.479 and 0.429). For small lesions, the number of acute lesions on DKI, but not on DWI, images was consistent with that on the follow-up T2-weighted images (P = .125). Conclusion DKI complements DWI for improved prediction of outcome of acute ischemic stroke. © RSNA, 2018.

Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm.

PubMed

Witwer, Brian P; Moftakhar, Roham; Hasan, Khader M; Deshmukh, Praveen; Haughton, Victor; Field, Aaron; Arfanakis, Konstantinos; Noyes, Jane; Moritz, Chad H; Meyerand, M Elizabeth; Rowley, Howard A; Alexander, Andrew L; Badie, Behnam

2002-09-01

Preserving vital cerebral function while maximizing tumor resection is a principal goal in surgical neurooncology. Although functional magnetic resonance imaging has been useful in the localization of eloquent cerebral cortex, this method does not provide information about the white matter tracts that may be involved in invasive, intrinsic brain tumors. Recently, diffusion-tensor (DT) imaging techniques have been used to map white matter tracts in the normal brain. The aim of this study was to demonstrate the role of DT imaging in preoperative mapping of white matter tracts in relation to cerebral neoplasms. Nine patients with brain malignancies (one pilocytic astrocytoma, five oligodendrogliomas, one low-grade oligoastrocytoma, one Grade 4 astrocytoma, and one metastatic adenocarcinoma) underwent DT imaging examinations prior to tumor excision. Anatomical information about white matter tract location, orientation, and projections was obtained in every patient. Depending on the tumor type and location, evidence of white matter tract edema (two patients), infiltration (two patients), displacement (five patients), and disruption (two patients) could be assessed with the aid of DT imaging in each case. Diffusion-tensor imaging allowed for visualization of white matter tracts and was found to be beneficial in the surgical planning for patients with intrinsic brain tumors. The authors' experience with DT imaging indicates that anatomically intact fibers may be present in abnormal-appearing areas of the brain. Whether resection of these involved fibers results in subtle postoperative neurological deficits requires further systematic study.

Intermolecular correlations are necessary to explain diffuse scattering from protein crystals

DOE PAGES

Peck, Ariana; Poitevin, Frederic; Lane, Thomas Joseph

2018-02-21

Conformational changes drive protein function, including catalysis, allostery, and signaling. X-ray diffuse scattering from protein crystals has frequently been cited as a probe of these correlated motions, with significant potential to advance our understanding of biological dynamics. However, recent work challenged this prevailing view, suggesting instead that diffuse scattering primarily originates from rigid body motions and could therefore be applied to improve structure determination. To investigate the nature of the disorder giving rise to diffuse scattering, and thus the potential applications of this signal, a diverse repertoire of disorder models was assessed for its ability to reproduce the diffuse signalmore » reconstructed from three protein crystals. This comparison revealed that multiple models of intramolecular conformational dynamics, including ensemble models inferred from the Bragg data, could not explain the signal. Models of rigid body or short-range liquid-like motions, in which dynamics are confined to the biological unit, showed modest agreement with the diffuse maps, but were unable to reproduce experimental features indicative of long-range correlations. Extending a model of liquid-like motions to include disorder across neighboring proteins in the crystal significantly improved agreement with all three systems and highlighted the contribution of intermolecular correlations to the observed signal. These findings anticipate a need to account for intermolecular disorder in order to advance the interpretation of diffuse scattering to either extract biological motions or aid structural inference.« less

Intermolecular correlations are necessary to explain diffuse scattering from protein crystals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peck, Ariana; Poitevin, Frederic; Lane, Thomas Joseph

Conformational changes drive protein function, including catalysis, allostery, and signaling. X-ray diffuse scattering from protein crystals has frequently been cited as a probe of these correlated motions, with significant potential to advance our understanding of biological dynamics. However, recent work challenged this prevailing view, suggesting instead that diffuse scattering primarily originates from rigid body motions and could therefore be applied to improve structure determination. To investigate the nature of the disorder giving rise to diffuse scattering, and thus the potential applications of this signal, a diverse repertoire of disorder models was assessed for its ability to reproduce the diffuse signalmore » reconstructed from three protein crystals. This comparison revealed that multiple models of intramolecular conformational dynamics, including ensemble models inferred from the Bragg data, could not explain the signal. Models of rigid body or short-range liquid-like motions, in which dynamics are confined to the biological unit, showed modest agreement with the diffuse maps, but were unable to reproduce experimental features indicative of long-range correlations. Extending a model of liquid-like motions to include disorder across neighboring proteins in the crystal significantly improved agreement with all three systems and highlighted the contribution of intermolecular correlations to the observed signal. These findings anticipate a need to account for intermolecular disorder in order to advance the interpretation of diffuse scattering to either extract biological motions or aid structural inference.« less

Tissue signature characterisation of diffusion tensor abnormalities in cerebral gliomas.

PubMed

Price, Stephen J; Peña, Alonso; Burnet, Neil G; Jena, Raj; Green, Hadrian A L; Carpenter, T Adrian; Pickard, John D; Gillard, Jonathan H

2004-10-01

The inherent invasiveness of malignant cells is a major determinant of the poor prognosis of cerebral gliomas. Diffusion tensor MRI (DTI) can identify white matter abnormalities in gliomas that are not seen on conventional imaging. By breaking down DTI into its isotropic (p) and anisotropic (q) components, we can determine tissue diffusion "signatures". In this study we have characterised these abnormalities in peritumoural white matter tracts. Thirty-five patients with cerebral gliomas and seven normal volunteers were imaged with DTI and T2-weighted sequences at 3 T. Displaced, infiltrated and disrupted white matter tracts were identified using fractional anisotropy (FA) maps and directionally encoded colour maps and characterised using tissue signatures. The diffusion tissue signatures were normal in ROIs where the white matter was displaced. Infiltrated white matter was characterised by an increase in the isotropic component of the tensor (p) and a less marked reduction of the anisotropic component (q). In disrupted white matter tracts, there was a marked reduction in q and increase in p. The direction of water diffusion was grossly abnormal in these cases. Diffusion tissue signatures may be a useful method of assessing occult white matter infiltration. Copyright 2004 Springer-Verlag

[Effect of exercise load on apparent diffusion coefficient and fractional anisotropy of normal lumbar intervertebral discs in diffusion tensor imaging].

PubMed

Zhong, Xiu; Qiu, Shijun

2015-06-01

To investigate the effect of exercise load on apparent diffusion coefficient (ADC) and fractional anisotropy (FA) of normal lumbar intervertebral discs in magnetic resonance (MR) diffusion tensor imaging (DTI). Thirty healthy volunteers (24 males and 6 females, aged 19 to 25 years) underwent examinations with MR T2WI and DTI of the lumbar intervertebral discs before and after exercise load. Pfirrmann grading was evaluated with T2WI, and the B0 map, ADC map and FA map were reconstructed based on the DTI data to investigate the changes in ADC and FA after exercise. Of the 30 volunteers (150 intervertebral discs) receiving the examination, 27 with discs of Pfirrminn grade II were included for analysis. In these 27 volunteers, the average ADC and FA before exercise were (1.99 ± 0.18)×10⁻³ mm²/s and 0.155∓0.059, respectively. After exercise, ADC was lowered significantly to (1.93 ± 0.17)×10⁻³ mm²/s (P<0.05) and FA increased slightly to 0.1623 ± 0.017 (P>0.05). DTI allows quantitatively analysis of the changes in water molecular diffusion and anisotropy of the lumbar intervertebral discs after exercise load, which can cause a decreased ADC and a increased FA value, and the change of ADC is more sensitive to exercise load.

Step-by-Step Simulation of Radiation Chemistry Using Green Functions for Diffusion-Influenced Reactions

NASA Technical Reports Server (NTRS)

Plante, Ianik; Cucinotta, Francis A.

2011-01-01

Radiolytic species are formed approximately 1 ps after the passage of ionizing radiation through matter. After their formation, they diffuse and chemically react with other radiolytic species and neighboring biological molecules, leading to various oxidative damage. Therefore, the simulation of radiation chemistry is of considerable importance to understand how radiolytic species damage biological molecules [1]. The step-by-step simulation of chemical reactions is difficult, because the radiolytic species are distributed non-homogeneously in the medium. Consequently, computational approaches based on Green functions for diffusion-influenced reactions should be used [2]. Recently, Green functions for more complex type of reactions have been published [3-4]. We have developed exact random variate generators of these Green functions [5], which will allow us to use them in radiation chemistry codes. Moreover, simulating chemistry using the Green functions is which is computationally very demanding, because the probabilities of reactions between each pair of particles should be evaluated at each timestep [2]. This kind of problem is well adapted for General Purpose Graphic Processing Units (GPGPU), which can handle a large number of similar calculations simultaneously. These new developments will allow us to include more complex reactions in chemistry codes, and to improve the calculation time. This code should be of importance to link radiation track structure simulations and DNA damage models.

Functional Multi-Locus QTL Mapping of Temporal Trends in Scots Pine Wood Traits

PubMed Central

Li, Zitong; Hallingbäck, Henrik R.; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J.; García-Gil, M. Rosario

2014-01-01

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. PMID:25305041

How MAP kinase modules function as robust, yet adaptable, circuits.

PubMed

Tian, Tianhai; Harding, Angus

2014-01-01

Genetic and biochemical studies have revealed that the diversity of cell types and developmental patterns evident within the animal kingdom is generated by a handful of conserved, core modules. Core biological modules must be robust, able to maintain functionality despite perturbations, and yet sufficiently adaptable for random mutations to generate phenotypic variation during evolution. Understanding how robust, adaptable modules have influenced the evolution of eukaryotes will inform both evolutionary and synthetic biology. One such system is the MAP kinase module, which consists of a 3-tiered kinase circuit configuration that has been evolutionarily conserved from yeast to man. MAP kinase signal transduction pathways are used across eukaryotic phyla to drive biological functions that are crucial for life. Here we ask the fundamental question, why do MAPK modules follow a conserved 3-tiered topology rather than some other number? Using computational simulations, we identify a fundamental 2-tiered circuit topology that can be readily reconfigured by feedback loops and scaffolds to generate diverse signal outputs. When this 2-kinase circuit is connected to proximal input kinases, a 3-tiered modular configuration is created that is both robust and adaptable, providing a biological circuit that can regulate multiple phenotypes and maintain functionality in an uncertain world. We propose that the 3-tiered signal transduction module has been conserved through positive selection, because it facilitated the generation of phenotypic variation during eukaryotic evolution.

Correspondence between retinotopic cortical mapping and conventional functional and morphological assessment of retinal disease.

PubMed

Ritter, Markus; Hummer, Allan; Ledolter, Anna A; Holder, Graham E; Windischberger, Christian; Schmidt-Erfurth, Ursula M

2018-04-26

The present study describes retinotopic mapping of the primary visual cortex using functional MRI (fMRI) in patients with retinal disease. It addresses the relationship between fMRI data and data obtained by conventional assessment including microperimetry (MP) and structural imaging. Initial testing involved eight patients with central retinal disease (Stargardt disease, STGD) and eight with peripheral retinal disease (retinitis pigmentosa, RP), who were examined using fMRI and MP (Nidek MP-1). All had a secure clinical diagnosis supported by electrophysiological data. fMRI used population-receptive field (pRF) mapping to provide retinotopic data that were then compared with the results of MP, optical coherence tomography and fundus autofluorescence imaging. Full analysis, following assessment of fMRI data reliability criteria, was performed in five patients with STGD and seven patients with RP; unstable fixation was responsible for unreliable pRF measurements in three patients excluded from final analysis. The macular regions in patients with STGD with central visual field defects and outer retinal atrophy (ORA) at the macula correlated well with pRF coverage maps showing reduced density of activated voxels at the occipital pole. Patients with RP exhibited peripheral ORA and concentric visual field defects both on MP and pRF mapping. Anterior V1 voxels, corresponding to peripheral regions, showed no significant activation. Correspondence between MP and pRF mapping was quantified by calculating the simple matching coefficient. Retinotopic maps acquired by fMRI provide a valuable adjunct in the assessment of retinal dysfunction. The addition of microperimetric data to pRF maps allowed better assessment of macular function than MP alone. Unlike MP, pRF mapping provides objective data independent of psychophysical perception from the patient. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No

Multi-mode Li diffusion in natural zircons: Evidence for diffusion in the presence of step-function concentration boundaries

NASA Astrophysics Data System (ADS)

Tang, Ming; Rudnick, Roberta L.; McDonough, William F.; Bose, Maitrayee; Goreva, Yulia

2017-09-01

Micron- to submicron-scale observations of Li distribution and Li isotope composition profiles can be used to infer the mechanisms of Li diffusion in natural zircon. Extreme fractionation (20-30‰) within each single crystal studied here confirms that Li diffusion commonly occurs in zircon. Sharp Li concentration gradients frequently seen in zircons suggest that the effective diffusivity of Li is significantly slower than experimentally determined (Cherniak and Watson, 2010; Trail et al., 2016), otherwise the crystallization/metamorphic heating of these zircons would have to be unrealistically fast (years to tens of years). Charge coupling with REE and Y has been suggested as a mechanism that may considerably reduce Li diffusivity in zircon (Ushikubo et al., 2008; Bouvier et al., 2012). We show that Li diffused in the direction of decreasing Li/Y ratio and increasing Li concentration (uphill diffusion) in one of the zircons, demonstrating charge coupling with REE and Y. Quantitative modeling reveals that Li may diffuse in at least two modes in natural zircons: one being slow and possibly coupled with REE+Y, and the other one being fast and not coupled with REE+Y. The partitioning of Li between these two modes during its diffusion may depend on the pre-diffusion substitution mechanism of REE and Y in the zircon lattice. Based on our results, sharp Li concentration gradients are not indicative of limited diffusion, and can be preserved at temperatures >700 °C on geologic timescales. Finally, large δ7 Li variations observed in the Hadean Jack Hills zircons may record kinetic fractionation, rather than a record of ancient intense weathering in the granite source materials.

Diffusion in silicate melts: III. Empirical models for multicomponent diffusion

NASA Astrophysics Data System (ADS)

Yan, Liang; Richter, Frank M.; Chamberlin, Laurinda

1997-12-01

Empirical models for multicomponent diffusion in an isotropic fluid were derived by splitting the component's dispersion velocity into two parts: (a) an intrinsic velocity which is proportional to each component's electrochemical potential gradient and independent of reference frame and (b) a net interaction velocity which is both model and reference frame dependent. Simple molecules (e.g., M pO q) were chosen as endmember components. The interaction velocity is assumed to be either the same for each component (leading to a common relaxation velocity U) or proportional to a common interaction force ( F). U or F is constrained by requiring no local buildup in either volume or charge. The most general form of the model-derived diffusion matrix [ D] can be written as a product of a model-dependent kinetic matrix [ L] and a model independent thermodynamic matrix [ G], [ D] = [ L] · [ G]. The elements of [ G] are functions of derivatives of chemical potential with respect to concentration. The elements of [ L] are functions of concentration and partial molar volume of the endmember components, Cio and Vio, and self diffusivity Di, and charge number zi of individual diffusing species. When component n is taken as the dependent variable they can be written in a common form L ij = D jδ ij + C io[V noD n - V joD j)A i + (p nz nD n - p jz jD j)B i] where the functional forms of the scaling factors Ai and Bi depend on the model considered. The off-diagonal element Lij ( i ≠ j) is directly proportional to the concentration of component i, and thus negligible when i is a dilute component. The salient feature of kinetic interaction or relaxation is to slow down larger (volume or charge) and faster diffusing components and to speed up smaller (volume or charge) and slower moving species, in order to prevent local volume or charge buildup. Empirical models for multicomponent diffusion were tested in the ternary system CaOAl 2O 3SiO 2 at 1500°C and 1 GPa over a large

Novel techniques of real-time blood flow and functional mapping: technical note.

PubMed

Kamada, Kyousuke; Ogawa, Hiroshi; Saito, Masato; Tamura, Yukie; Anei, Ryogo; Kapeller, Christoph; Hayashi, Hideaki; Prueckl, Robert; Guger, Christoph

2014-01-01

There are two main approaches to intraoperative monitoring in neurosurgery. One approach is related to fluorescent phenomena and the other is related to oscillatory neuronal activity. We developed novel techniques to visualize blood flow (BF) conditions in real time, based on indocyanine green videography (ICG-VG) and the electrophysiological phenomenon of high gamma activity (HGA). We investigated the use of ICG-VG in four patients with moyamoya disease and two with arteriovenous malformation (AVM), and we investigated the use of real-time HGA mapping in four patients with brain tumors who underwent lesion resection with awake craniotomy. Real-time data processing of ICG-VG was based on perfusion imaging, which generated parameters including arrival time (AT), mean transit time (MTT), and BF of brain surface vessels. During awake craniotomy, we analyzed the frequency components of brain oscillation and performed real-time HGA mapping to identify functional areas. Processed results were projected on a wireless monitor linked to the operating microscope. After revascularization for moyamoya disease, AT and BF were significantly shortened and increased, respectively, suggesting hyperperfusion. Real-time fusion images on the wireless monitor provided anatomical, BF, and functional information simultaneously, and allowed the resection of AVMs under the microscope. Real-time HGA mapping during awake craniotomy rapidly indicated the eloquent areas of motor and language function and significantly shortened the operation time. These novel techniques, which we introduced might improve the reliability of intraoperative monitoring and enable the development of rational and objective surgical strategies.

Connection between encounter volume and diffusivity in geophysical flows

NASA Astrophysics Data System (ADS)

Rypina, Irina I.; Smith, Stefan G. Llewellyn; Pratt, Larry J.

2018-04-01

Trajectory encounter volume - the volume of fluid that passes close to a reference fluid parcel over some time interval - has been recently introduced as a measure of mixing potential of a flow. Diffusivity is the most commonly used characteristic of turbulent diffusion. We derive the analytical relationship between the encounter volume and diffusivity under the assumption of an isotropic random walk, i.e., diffusive motion, in one and two dimensions. We apply the derived formulas to produce maps of encounter volume and the corresponding diffusivity in the Gulf Stream region of the North Atlantic based on satellite altimetry, and discuss the mixing properties of Gulf Stream rings. Advantages offered by the derived formula for estimating diffusivity from oceanographic data are discussed, as well as applications to other disciplines.

Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma.

PubMed

Reddy, Anupama; Zhang, Jenny; Davis, Nicholas S; Moffitt, Andrea B; Love, Cassandra L; Waldrop, Alexander; Leppa, Sirpa; Pasanen, Annika; Meriranta, Leo; Karjalainen-Lindsberg, Marja-Liisa; Nørgaard, Peter; Pedersen, Mette; Gang, Anne O; Høgdall, Estrid; Heavican, Tayla B; Lone, Waseem; Iqbal, Javeed; Qin, Qiu; Li, Guojie; Kim, So Young; Healy, Jane; Richards, Kristy L; Fedoriw, Yuri; Bernal-Mizrachi, Leon; Koff, Jean L; Staton, Ashley D; Flowers, Christopher R; Paltiel, Ora; Goldschmidt, Neta; Calaminici, Maria; Clear, Andrew; Gribben, John; Nguyen, Evelyn; Czader, Magdalena B; Ondrejka, Sarah L; Collie, Angela; Hsi, Eric D; Tse, Eric; Au-Yeung, Rex K H; Kwong, Yok-Lam; Srivastava, Gopesh; Choi, William W L; Evens, Andrew M; Pilichowska, Monika; Sengar, Manju; Reddy, Nishitha; Li, Shaoying; Chadburn, Amy; Gordon, Leo I; Jaffe, Elaine S; Levy, Shawn; Rempel, Rachel; Tzeng, Tiffany; Happ, Lanie E; Dave, Tushar; Rajagopalan, Deepthi; Datta, Jyotishka; Dunson, David B; Dave, Sandeep S

2017-10-05

Diffuse large B cell lymphoma (DLBCL) is the most common form of blood cancer and is characterized by a striking degree of genetic and clinical heterogeneity. This heterogeneity poses a major barrier to understanding the genetic basis of the disease and its response to therapy. Here, we performed an integrative analysis of whole-exome sequencing and transcriptome sequencing in a cohort of 1,001 DLBCL patients to comprehensively define the landscape of 150 genetic drivers of the disease. We characterized the functional impact of these genes using an unbiased CRISPR screen of DLBCL cell lines to define oncogenes that promote cell growth. A prognostic model comprising these genetic alterations outperformed current established methods: cell of origin, the International Prognostic Index comprising clinical variables, and dual MYC and BCL2 expression. These results comprehensively define the genetic drivers and their functional roles in DLBCL to identify new therapeutic opportunities in the disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Far-Infrared sources and diffuse emission in M31

NASA Technical Reports Server (NTRS)

Xu, Cong; Helou, George

1994-01-01

A study on the far-infrared (FIR) emission of M31 has been carried out with the High Resolution (HiRes) maps (approx. 1 min) derived from IRAS data. Sixty-eight FIR sources are detected in M31, which in general coincide with optical HII regions, and contribute 15, 23, 29, and 23 percent to the fluxes in 12, 25, 60, and 100 micron bands, respectively. The remaining diffuse emission, which dominates the FIR emission of M31, is studied using a dust heating model which utilizes the UV and optical photometry maps and the HI maps available in the literature. It is found that the global dust-to-gas ratio in M31 disk is 6.5 10(exp -3), very close to the dust-to-gas ratio in the solar neighborhood. There is a significant galactocentric gradient of the dust-to-HI-gas ratio, with an e-folding scale length of 9 kpc. The diffuse dust correlates tightly with the HI gas. The model indicates that the non-ionizing UV (913-4000A) radiation from massive and intermediate massive stars contributes only about 30 percent of the heating of the diffuse dust, while the optical-NIR (4000-9000A) radiation from the old stellar population is responsible for the most of the heating.

Joint brain connectivity estimation from diffusion and functional MRI data

NASA Astrophysics Data System (ADS)

Chu, Shu-Hsien; Lenglet, Christophe; Parhi, Keshab K.

2015-03-01

Estimating brain wiring patterns is critical to better understand the brain organization and function. Anatomical brain connectivity models axonal pathways, while the functional brain connectivity characterizes the statistical dependencies and correlation between the activities of various brain regions. The synchronization of brain activity can be inferred through the variation of blood-oxygen-level dependent (BOLD) signal from functional MRI (fMRI) and the neural connections can be estimated using tractography from diffusion MRI (dMRI). Functional connections between brain regions are supported by anatomical connections, and the synchronization of brain activities arises through sharing of information in the form of electro-chemical signals on axon pathways. Jointly modeling fMRI and dMRI data may improve the accuracy in constructing anatomical connectivity as well as functional connectivity. Such an approach may lead to novel multimodal biomarkers potentially able to better capture functional and anatomical connectivity variations. We present a novel brain network model which jointly models the dMRI and fMRI data to improve the anatomical connectivity estimation and extract the anatomical subnetworks associated with specific functional modes by constraining the anatomical connections as structural supports to the functional connections. The key idea is similar to a multi-commodity flow optimization problem that minimizes the cost or maximizes the efficiency for flow configuration and simultaneously fulfills the supply-demand constraint for each commodity. In the proposed network, the nodes represent the grey matter (GM) regions providing brain functionality, and the links represent white matter (WM) fiber bundles connecting those regions and delivering information. The commodities can be thought of as the information corresponding to brain activity patterns as obtained for instance by independent component analysis (ICA) of fMRI data. The concept of information

Pressure transfer function and absorption cross section from the diffuse field to the human infant ear canal.

PubMed

Keefe, D H; Bulen, J C; Campbell, S L; Burns, E M

1994-01-01

The diffuse-field pressure transfer function from a reverberant field to the ear canal of human infants, ages 1, 3, 6, 12, and 24 months, has been measured from 125-10700 Hz. The source was a loudspeaker using pink noise, and the diffuse-field pressure and the ear-canal pressure were simultaneously measured using a spatial averaging technique in a reverberant room. The results in most subjects show a two-peak structure in the 2-6-kHz range, corresponding to the ear-canal and concha resonances. The ear-canal resonance frequency decreases from 4.4 kHz at age 1 month to 2.9 kHz at age 24 months. The concha resonance frequency decreases from 5.5 kHz at age 1 month to 4.5 kHz at age 24 months. Below 2 kHz, the diffuse-field transfer function shows effects due to the torsos of the infant and parent, and varies with how the infant is held. Comparisons are reported of the diffuse-field absorption cross section for infants relative to adults. This quantity is a measure of power absorbed by the middle ear from a diffuse sound field, and large differences are observed in infants relative to adults. The radiation efficiencies of the infant and the adult ear are small at low frequencies, near unity at midfrequencies, and decrease at higher frequencies. The process of ear-canal development is not yet complete at age 24 months. The results have implications for experiments on hearing in infants.

Diffuse scattering in relaxor ferroelectrics: true three-dimensional mapping, experimental artefacts and modelling.

PubMed

Bosak, A; Chernyshov, D; Vakhrushev, Sergey; Krisch, M

2012-01-01

The available body of experimental data in terms of the relaxor-specific component of diffuse scattering is critically analysed and a collection of related models is reviewed; the sources of experimental artefacts and consequent failures of modelling efforts are enumerated. Furthermore, it is shown that the widely used concept of polar nanoregions as individual static entities is incompatible with the experimental diffuse scattering results. Based on the synchrotron diffuse scattering three-dimensional data set taken for the prototypical ferroelectric relaxor lead magnesium niobate-lead titanate (PMN-PT), a new parameterization of diffuse scattering in relaxors is presented and a simple phenomenological picture is proposed to explain the unusual properties of the relaxor behaviour. The model assumes a specific slowly changing displacement pattern, which is indirectly controlled by the low-energy acoustic phonons of the system. The model provides a qualitative but rather detailed explanation of temperature, pressure and electric-field dependence of diffuse neutron and X-ray scattering, as well as of the existence of a hierarchy in the relaxation times of these materials.

Mapping Multiplex Hubs in Human Functional Brain Networks

PubMed Central

De Domenico, Manlio; Sasai, Shuntaro; Arenas, Alex

2016-01-01

Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches. PMID:27471443

Mapping the current–current correlation function near a quantum critical point

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prodan, Emil, E-mail: prodan@yu.edu; Bellissard, Jean

2016-05-15

The current–current correlation function is a useful concept in the theory of electron transport in homogeneous solids. The finite-temperature conductivity tensor as well as Anderson’s localization length can be computed entirely from this correlation function. Based on the critical behavior of these two physical quantities near the plateau–insulator or plateau–plateau transitions in the integer quantum Hall effect, we derive an asymptotic formula for the current–current correlation function, which enables us to make several theoretical predictions about its generic behavior. For the disordered Hofstadter model, we employ numerical simulations to map the current–current correlation function, obtain its asymptotic form near amore » critical point and confirm the theoretical predictions.« less

Automatic transfer function design for medical visualization using visibility distributions and projective color mapping.

PubMed

Cai, Lile; Tay, Wei-Liang; Nguyen, Binh P; Chui, Chee-Kong; Ong, Sim-Heng

2013-01-01

Transfer functions play a key role in volume rendering of medical data, but transfer function manipulation is unintuitive and can be time-consuming; achieving an optimal visualization of patient anatomy or pathology is difficult. To overcome this problem, we present a system for automatic transfer function design based on visibility distribution and projective color mapping. Instead of assigning opacity directly based on voxel intensity and gradient magnitude, the opacity transfer function is automatically derived by matching the observed visibility distribution to a target visibility distribution. An automatic color assignment scheme based on projective mapping is proposed to assign colors that allow for the visual discrimination of different structures, while also reflecting the degree of similarity between them. When our method was tested on several medical volumetric datasets, the key structures within the volume were clearly visualized with minimal user intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging

NASA Astrophysics Data System (ADS)

Reisman, Matthew David

As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using

Condition Number as a Measure of Noise Performance of Diffusion Tensor Data Acquisition Schemes with MRI

NASA Astrophysics Data System (ADS)

Skare, Stefan; Hedehus, Maj; Moseley, Michael E.; Li, Tie-Qiang

2000-12-01

Diffusion tensor mapping with MRI can noninvasively track neural connectivity and has great potential for neural scientific research and clinical applications. For each diffusion tensor imaging (DTI) data acquisition scheme, the diffusion tensor is related to the measured apparent diffusion coefficients (ADC) by a transformation matrix. With theoretical analysis we demonstrate that the noise performance of a DTI scheme is dependent on the condition number of the transformation matrix. To test the theoretical framework, we compared the noise performances of different DTI schemes using Monte-Carlo computer simulations and experimental DTI measurements. Both the simulation and the experimental results confirmed that the noise performances of different DTI schemes are significantly correlated with the condition number of the associated transformation matrices. We therefore applied numerical algorithms to optimize a DTI scheme by minimizing the condition number, hence improving the robustness to experimental noise. In the determination of anisotropic diffusion tensors with different orientations, MRI data acquisitions using a single optimum b value based on the mean diffusivity can produce ADC maps with regional differences in noise level. This will give rise to rotational variances of eigenvalues and anisotropy when diffusion tensor mapping is performed using a DTI scheme with a limited number of diffusion-weighting gradient directions. To reduce this type of artifact, a DTI scheme with not only a small condition number but also a large number of evenly distributed diffusion-weighting gradients in 3D is preferable.

Current Trends in Intraoperative Optical Imaging for Functional Brain Mapping and Delineation of Lesions of Language Cortex

PubMed Central

Prakash, Neal; Uhleman, Falk; Sheth, Sameer A.; Bookheimer, Susan; Martin, Neil; Toga, Arthur W.

2009-01-01

Resection of a cerebral arteriovenous malformation (AVM), epileptic focus, or glioma, ideally has a prerequisite of microscopic delineation of the lesion borders in relation to the normal gray and white matter that mediate critical functions. Currently, Wada testing and functional magnetic resonance imaging (fMRI) are used for preoperative mapping of critical function, whereas electrical stimulation mapping (ESM) is used for intraoperative mapping. For lesion delineation, MRI and positron emission tomography (PET) are used preoperatively, whereas microscopy and histological sectioning are used intraoperatively. However, for lesions near eloquent cortex, these imaging techniques may lack sufficient resolution to define the relationship between the lesion and language function, and thus not accurately determine which patients will benefit from neurosurgical resection of the lesion without iatrogenic aphasia. Optical techniques such as intraoperative optical imaging of intrinsic signals (iOIS) show great promise for the precise functional mapping of cortices, as well as delineation of the borders of AVMs, epileptic foci, and gliomas. Here we first review the physiology of neuroimaging, and then progress towards the validation and justification of using intraoperative optical techniques, especially in relation to neurosurgical planning of resection AVMs, epileptic foci, and gliomas near or in eloquent cortex. We conclude with a short description of potential novel intraoperative optical techniques. PMID:18786643

Diffusion via space discretization method to study the concentration dependence of self-diffusivity under confinement

NASA Astrophysics Data System (ADS)

Sant, Marco; Papadopoulos, George K.; Theodorou, Doros N.

2010-04-01

The concentration dependence of self-diffusivity is investigated by means of a novel method, extending our previously developed second-order Markov process model to periodic media. Introducing the concept of minimum-crossing surface, we obtain a unique decomposition of the self-diffusion coefficient into two parameters with specific physical meanings. Two case studies showing a maximum in self-diffusivity as a function of concentration are investigated, along with two cases where such a maximum cannot be present. Subsequently, the method is applied to the large cavity pore network of the ITQ-1 (Mobil tWenty tWo, MWW) zeolite for methane (displaying a maximum in self-diffusivity) and carbon dioxide (no maximum), explaining the diffusivity trend on the basis of the evolution of the model parameters as a function of concentration.

Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

PubMed

Li, Zitong; Hallingbäck, Henrik R; Abrahamsson, Sara; Fries, Anders; Gull, Bengt Andersson; Sillanpää, Mikko J; García-Gil, M Rosario

2014-10-09

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals. Copyright © 2014 Li et al.

Model-independent analyses of non-Gaussianity in Planck CMB maps using Minkowski functionals

NASA Astrophysics Data System (ADS)

Buchert, Thomas; France, Martin J.; Steiner, Frank

2017-05-01

Despite the wealth of Planck results, there are difficulties in disentangling the primordial non-Gaussianity of the Cosmic Microwave Background (CMB) from the secondary and the foreground non-Gaussianity (NG). For each of these forms of NG the lack of complete data introduces model-dependences. Aiming at detecting the NGs of the CMB temperature anisotropy δ T , while paying particular attention to a model-independent quantification of NGs, our analysis is based upon statistical and morphological univariate descriptors, respectively: the probability density function P(δ T) , related to v0, the first Minkowski Functional (MF), and the two other MFs, v1 and v2. From their analytical Gaussian predictions we build the discrepancy functions {{ Δ }k} (k  =  P, 0, 1, 2) which are applied to an ensemble of 105 CMB realization maps of the Λ CDM model and to the Planck CMB maps. In our analysis we use general Hermite expansions of the {{ Δ }k} up to the 12th order, where the coefficients are explicitly given in terms of cumulants. Assuming hierarchical ordering of the cumulants, we obtain the perturbative expansions generalizing the second order expansions of Matsubara to arbitrary order in the standard deviation {σ0} for P(δ T) and v0, where the perturbative expansion coefficients are explicitly given in terms of complete Bell polynomials. The comparison of the Hermite expansions and the perturbative expansions is performed for the Λ CDM map sample and the Planck data. We confirm the weak level of non-Gaussianity (1-2)σ of the foreground corrected masked Planck 2015 maps.

Structural disorder in the decagonal Al-Co-Ni. I. Patterson analysis of diffuse x-ray scattering data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kobas, Miroslav; Weber, Thomas; Steurer, Walter

The three-dimensional (3D) difference Patterson (autocorrelation) function of a disordered quasicrystal (Edagawa phase) has been analyzed. 3D diffuse x-ray diffraction data were collected in situ at 300, 1070, and 1120 K. A method, the punch-and-fill technique, has been developed for separating diffuse scattering and Bragg reflections. Its potential and limits are discussed in detail. The different Patterson maps are interpreted in terms of intercluster correlations as a function of temperature. Both at high and low temperatures, the clusters decorate the vertices of the same quasiperiodic covering. At low temperatures, for the disordered part of the structure, short-range intercluster correlations aremore » present, whereas at higher temperatures, medium-range intercluster correlations are formed. This indicates disorder mainly inside clusters at low temperatures, whereas at higher temperatures disorder takes place inside larger superclusters. Qualitatively, the Patterson maps may be interpreted by intercluster correlations mainly inside pentagonal superclusters below 1120 K, and inside the larger decagonal superclusters at 1120 K. The results of our diffraction study are published in two parts. Part I focuses on the 3D Patterson analysis based on experimental data, Part II reports modeling of structural disorder in decagonal Al-Co-Ni.« less

Apoplastic Diffusion Barriers in Arabidopsis

PubMed Central

Schreiber, Lukas; Franke, Rochus Benni; Geldner, Niko; Reina-Pinto, José J.; Kunst, Ljerka

2013-01-01

During the development of Arabidopsis and other land plants, diffusion barriers are formed in the apoplast of specialized tissues within a variety of plant organs. While the cuticle of the epidermis is the primary diffusion barrier in the shoot, the Casparian strips and suberin lamellae of the endodermis and the periderm represent the diffusion barriers in the root. Different classes of molecules contribute to the formation of extracellular diffusion barriers in an organ- and tissue-specific manner. Cutin and wax are the major components of the cuticle, lignin forms the early Casparian strip, and suberin is deposited in the stage II endodermis and the periderm. The current status of our understanding of the relationships between the chemical structure, ultrastructure and physiological functions of plant diffusion barriers is discussed. Specific aspects of the synthesis of diffusion barrier components and protocols that can be used for the assessment of barrier function and important barrier properties are also presented. PMID:24465172

MAPS of Cancer

NASA Technical Reports Server (NTRS)

Gray, Lincoln

1998-01-01

Our goal was to produce an interactive visualization from a mathematical model that successfully predicts metastases from head and neck cancer. We met this goal early in the project. The visualization is available for the public to view. Our work appears to fill a need for more information about this deadly disease. The idea of this project was to make an easily interpretable visualization based on what we call "functional maps" of disease. A functional map is a graphic summary of medical data, where distances between parts of the body are determined by the probability of disease, not by anatomical distances. Functional maps often beat little resemblance to anatomical maps, but they can be used to predict the spread of disease. The idea of modeling the spread of disease in an abstract multidimensional space is difficult for many people. Our goal was to make the important predictions easy to see. NASA must face this problem frequently: how to help laypersons and professionals see important trends in abstract, complex data. We took advantage of concepts perfected in NASA's graphics libraries. As an analogy, consider a functional map of early America. Suppose we choose travel times, rather than miles, as our measures of inter-city distances. For Abraham Lincoln, travel times would have been the more meaningful measure of separation between cities. In such a map New Orleans would be close to Memphis because of the Mississippi River. St. Louis would be close to Portland because of the Oregon Trail. Oklahoma City would be far from Little Rock because of the Cheyenne. Such a map would look puzzling to those of us who have always seen physical maps, but the functional map would be more useful in predicting the probabilities of inter-site transit. Continuing the analogy, we could predict the spread of social diseases such as gambling along the rivers and cattle rustling along the trails. We could simply print the functional map of America, but it would be more interesting

Stimulated echo diffusion tensor imaging (STEAM-DTI) with varying diffusion times as a probe of breast tissue.

PubMed

Teruel, Jose R; Cho, Gene Y; Moccaldi Rt, Melanie; Goa, Pål E; Bathen, Tone F; Feiweier, Thorsten; Kim, Sungheon G; Moy, Linda; Sigmund, Eric E

2017-01-01

To explore the application of diffusion tensor imaging (DTI) for breast tissue and breast pathologies using a stimulated-echo acquisition mode (STEAM) with variable diffusion times. In this Health Insurance Portability and Accountability Act-compliant study, approved by the local institutional review board, eight patients and six healthy volunteers underwent an MRI examination at 3 Tesla including STEAM-DTI with several diffusion times ranging from 68.5 to 902.5 ms. A DTI model was fitted to the data for each diffusion time, and parametric maps of mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for healthy fibroglandular tissue (FGT) and lesions. The median value of radial diffusivity for FGT was fitted to a linear decay to obtain an estimation of the surface-to-volume ratio, from which the radial diameter was calculated. For healthy FGT, radial diffusivity presented a linear decay with the square root of the diffusion time resulting in a range of estimated radial diameters from 202 to 496 µm, while axial diffusivity presented a nearly time-independent diffusion. Residual fat signal was reduced at longer diffusion times due to the shorter T1 of fat. Residual fat signal to the overall signal in the healthy volunteers' FGT was found to range from 2.39% to 2.55% (shortest mixing time), and from 0.40% to 0.51% (longest mixing time) for the b500 images. The use of variable diffusion times may provide an in vivo noninvasive tool to probe diffusion lengths in breast tissue and breast pathology, and might aid by improving fat suppression at longer diffusion times. 2 J. Magn. Reson. Imaging 2017;45:84-93. © 2016 International Society for Magnetic Resonance in Medicine.

Novel cardiac magnetic resonance biomarkers: native T1 and extracellular volume myocardial mapping.

PubMed

Cannaò, Paola Maria; Altabella, Luisa; Petrini, Marcello; Alì, Marco; Secchi, Francesco; Sardanelli, Francesco

2016-04-28

Cardiac magnetic resonance (CMR) is a non-invasive diagnostic tool playing a key role in the assessment of cardiac morphology and function as well as in tissue characterization. Late gadolinium enhancement is a fundamental CMR technique for detecting focal or regional abnormalities such as scar tissue, replacement fibrosis, or inflammation using qualitative, semi-quantitative, or quantitative methods, but not allowing for evaluating the whole myocardium in the presence of diffuse disease. The novel T1 mapping approach permits a quantitative assessment of the entire myocardium providing a voxel-by-voxel map of native T1 relaxation time, obtained before the intravenous administration of gadolinium-based contrast material. Combining T1 data obtained before and after contrast injection, it is also possible to calculate the voxel-by-voxel extracellular volume (ECV), resulting in another myocardial parametric map. This article describes technical challenges and clinical perspectives of these two novel CMR biomarkers: myocardial native T1 and ECV mapping.

How MAP kinase modules function as robust, yet adaptable, circuits

PubMed Central

Tian, Tianhai; Harding, Angus

2014-01-01

Genetic and biochemical studies have revealed that the diversity of cell types and developmental patterns evident within the animal kingdom is generated by a handful of conserved, core modules. Core biological modules must be robust, able to maintain functionality despite perturbations, and yet sufficiently adaptable for random mutations to generate phenotypic variation during evolution. Understanding how robust, adaptable modules have influenced the evolution of eukaryotes will inform both evolutionary and synthetic biology. One such system is the MAP kinase module, which consists of a 3-tiered kinase circuit configuration that has been evolutionarily conserved from yeast to man. MAP kinase signal transduction pathways are used across eukaryotic phyla to drive biological functions that are crucial for life. Here we ask the fundamental question, why do MAPK modules follow a conserved 3-tiered topology rather than some other number? Using computational simulations, we identify a fundamental 2-tiered circuit topology that can be readily reconfigured by feedback loops and scaffolds to generate diverse signal outputs. When this 2-kinase circuit is connected to proximal input kinases, a 3-tiered modular configuration is created that is both robust and adaptable, providing a biological circuit that can regulate multiple phenotypes and maintain functionality in an uncertain world. We propose that the 3-tiered signal transduction module has been conserved through positive selection, because it facilitated the generation of phenotypic variation during eukaryotic evolution. PMID:25483189

Stochastic chaos induced by diffusion processes with identical spectral density but different probability density functions.

PubMed

Lei, Youming; Zheng, Fan

2016-12-01

Stochastic chaos induced by diffusion processes, with identical spectral density but different probability density functions (PDFs), is investigated in selected lightly damped Hamiltonian systems. The threshold amplitude of diffusion processes for the onset of chaos is derived by using the stochastic Melnikov method together with a mean-square criterion. Two quasi-Hamiltonian systems, namely, a damped single pendulum and damped Duffing oscillator perturbed by stochastic excitations, are used as illustrative examples. Four different cases of stochastic processes are taking as the driving excitations. It is shown that in such two systems the spectral density of diffusion processes completely determines the threshold amplitude for chaos, regardless of the shape of their PDFs, Gaussian or otherwise. Furthermore, the mean top Lyapunov exponent is employed to verify analytical results. The results obtained by numerical simulations are in accordance with the analytical results. This demonstrates that the stochastic Melnikov method is effective in predicting the onset of chaos in the quasi-Hamiltonian systems.

Corticostriatal connectivity fingerprints: Probability maps based on resting-state functional connectivity.

PubMed

Jaspers, Ellen; Balsters, Joshua H; Kassraian Fard, Pegah; Mantini, Dante; Wenderoth, Nicole

2017-03-01

Over the last decade, structure-function relationships have begun to encompass networks of brain areas rather than individual structures. For example, corticostriatal circuits have been associated with sensorimotor, limbic, and cognitive information processing, and damage to these circuits has been shown to produce unique behavioral outcomes in Autism, Parkinson's Disease, Schizophrenia and healthy ageing. However, it remains an open question how abnormal or absent connectivity can be detected at the individual level. Here, we provide a method for clustering gross morphological structures into subregions with unique functional connectivity fingerprints, and generate network probability maps usable as a baseline to compare individual cases against. We used connectivity metrics derived from resting-state fMRI (N = 100), in conjunction with hierarchical clustering methods, to parcellate the striatum into functionally distinct clusters. We identified three highly reproducible striatal subregions, across both hemispheres and in an independent replication dataset (N = 100) (dice-similarity values 0.40-1.00). Each striatal seed region resulted in a highly reproducible distinct connectivity fingerprint: the putamen showed predominant connectivity with cortical and cerebellar sensorimotor and language processing areas; the ventromedial striatum cluster had a distinct limbic connectivity pattern; the caudate showed predominant connectivity with the thalamus, frontal and occipital areas, and the cerebellum. Our corticostriatal probability maps agree with existing connectivity data in humans and non-human primates, and showed a high degree of replication. We believe that these maps offer an efficient tool to further advance hypothesis driven research and provide important guidance when investigating deviant connectivity in neurological patient populations suffering from e.g., stroke or cerebral palsy. Hum Brain Mapp 38:1478-1491, 2017. © 2016 Wiley Periodicals, Inc. �

Methodology and apparatus for diffuse photon imaging

DOEpatents

Feng, S.C.; Zeng, F.; Zhao, H.L.

1997-12-09

Non-invasive near infrared optical medical imaging devices for both hematoma detection in the brain and early tumor detection in the breast is achieved using image reconstruction which allows a mapping of the position dependent contrast diffusive propagation constants, which are related to the optical absorption coefficient and scattering coefficient in the tissue, at near infrared wavelengths. Spatial resolutions in the range of 5 mm for adult brain sizes and breast sizes can be achieved. The image reconstruction utilizes WKB approximation on most probable diffusion paths which has as lowest order approximation the straight line-of-sight between the plurality of sources and the plurality of detectors. The WKB approximation yields a set of linear equations in which the contrast optical absorption coefficients are the unknowns and for which signals can be generated to produce a pixel map of the contrast optical resolution of the scanned tissue. 58 figs.

Methodology and apparatus for diffuse photon mimaging

DOEpatents

Feng, Shechao C.; Zeng, Fanan; Zhao, Hui-Lin

1997-12-09

Non-invasive near infrared optical medical imaging devices for both hematoma detection in the brain and early tumor detection in the breast is achieved using image reconstruction which allows a mapping of the position dependent contrast diffusive propagation constants, which are related to the optical absorption coefficient and scattering coefficient in the tissue, at near infrared wavelengths. Spatial resolutions in the range of 5 mm for adult brain sizes and breast sizes can be achieved. The image reconstruction utilizes WKB approximation on most probable diffusion paths which has as lowest order approximation the straight line-of-sight between the plurality of sources and the plurality of detectors. The WKB approximation yields a set of linear equations in which the contrast optical absorption coefficients are the unknowns and for which signals can be generated to produce a pixel map of the contrast optical resolution of the scanned tissue.

Short Diffusion Time Diffusion-Weighted Imaging With Oscillating Gradient Preparation as an Early Magnetic Resonance Imaging Biomarker for Radiation Therapy Response Monitoring in Glioblastoma: A Preclinical Feasibility Study.

PubMed

Bongers, Andre; Hau, Eric; Shen, Han

2018-01-04

To investigate a novel alternative diffusion-weighted imaging (DWI) approach using oscillating gradients preparation (OGSE) to obtain much shorter effective diffusion times (Δ eff ) for tumor response monitoring by apparent diffusion coefficient (ADC) mapping in a glioblastoma mouse model. Twenty-four BALB/c nude mice inoculated with U87 glioblastoma cells were randomized into a control group and an irradiation group, which underwent a 15-day fractioned radiation therapy (RT) course with 2 Gy/d. Therapy response was assessed by mapping of ADCs at 6 time points using an in-house implementation of a cos-OGSE DWI sequence with Δ eff  = 1.25 ms and compared with a standard pulsed gradient DWI protocol (PGSE) with typical clinical diffusion time Δ eff  = 18 ms. Longitudinal ADC changes in tumor and contralateral white matter (WM) were statistically assessed using repeated-measures analysis of variance and post hoc (Sidak) testing. On short Δ eff OGSE maps tumor ADC was generally 30%-50% higher than in surrounding WM. Areas correlated well with histology. Tumor identification was generally more difficult on PGSE maps owing to nonsignificant WM/tumor contrast. During RT, OGSE maps also showed significant tumor ADC increase (approximately 15%) in response to radiation, consistently seen after 14-Gy RT dose. The clinical reference (PGSE) showed lower sensitivity to radiation changes, and no significant response across the radiation group and time course could be detected. Our short Δ eff DWI method using OGSE better reflected histologically defined tumor areas and enabled more consistent and earlier detection of microstructural radiation changes than conventional methods. Oscillating gradients preparation offers significant potential as a robust microstructural RT response biomarker, potentially helping to shift important therapy decisions to earlier stages in the RT time course. Copyright © 2018 Elsevier Inc. All rights reserved.

Theory of activated penetrant diffusion in viscous fluids and colloidal suspensions

NASA Astrophysics Data System (ADS)

Zhang, Rui; Schweizer, Kenneth S.

2015-10-01

We heuristically formulate a microscopic, force level, self-consistent nonlinear Langevin equation theory for activated barrier hopping and non-hydrodynamic diffusion of a hard sphere penetrant in very dense hard sphere fluid matrices. Penetrant dynamics is controlled by a rich competition between force relaxation due to penetrant self-motion and collective matrix structural (alpha) relaxation. In the absence of penetrant-matrix attraction, three activated dynamical regimes are predicted as a function of penetrant-matrix size ratio which are physically distinguished by penetrant jump distance and the nature of matrix motion required to facilitate its hopping. The penetrant diffusion constant decreases the fastest with size ratio for relatively small penetrants where the matrix effectively acts as a vibrating amorphous solid. Increasing penetrant-matrix attraction strength reduces penetrant diffusivity due to physical bonding. For size ratios approaching unity, a distinct dynamical regime emerges associated with strong slaving of penetrant hopping to matrix structural relaxation. A crossover regime at intermediate penetrant-matrix size ratio connects the two limiting behaviors for hard penetrants, but essentially disappears if there are strong attractions with the matrix. Activated penetrant diffusivity decreases strongly with matrix volume fraction in a manner that intensifies as the size ratio increases. We propose and implement a quasi-universal approach for activated diffusion of a rigid atomic/molecular penetrant in a supercooled liquid based on a mapping between the hard sphere system and thermal liquids. Calculations for specific systems agree reasonably well with experiments over a wide range of temperature, covering more than 10 orders of magnitude of variation of the penetrant diffusion constant.

Wave-function description of conductance mapping for a quantum Hall electron interferometer

NASA Astrophysics Data System (ADS)

Kolasiński, K.; Szafran, B.

2014-04-01

Scanning gate microscopy of quantum point contacts (QPC) in the integer quantum Hall regime is considered in terms of the scattering wave functions with a finite-difference implementation of the quantum transmitting boundary approach. Conductance (G) maps for a clean QPC as well as for a system including an antidot within the QPC constriction are evaluated. The steplike locally flat G maps for clean QPCs turn into circular resonances that are reentrant in an external magnetic field when the antidot is introduced to the constriction. The current circulation around the antidot and the spacing of the resonances at the magnetic field scale react to the probe approaching the QPC. The calculated G maps with a rigid but soft antidot potential reproduce the features detected recently in the electron interferometer [F. Martins et al., Sci. Rep. 3, 1416 (2013), 10.1038/srep01416].

Spatial diffusion of raccoon rabies in Pennsylvania, USA.

PubMed

Moore, D A

1999-05-14

Identification of the geographic pattern of diffusion of a wildlife disease could lead to information regarding its control. The objective of this study was to model raccoon-rabies diffusion in Pennsylvania to identify geographic constraints on the diffusion pattern for potential use in bait-vaccination strategies. A trend-surface analysis (TSA) was used as a spatial filter for month to first report by county location. A cubic polynomial model was fitted (R2 = 0.80). Velocity vectors were calculated from the partial derivatives of the model and mapped to demonstrate the instantaneous speed of diffusion at each location. A main corridor of diffusion through the ridge and valley section of the state was evident early in the outbreak. Once the disease reached the northern counties, the disease moved west toward Ohio. I believe that TSA was useful in identifying the pattern of raccoon-rabies diffusion across the stage from the inherent noise of disease-reporting data.

A Factor Analysis of Functional Independence and Functional Assessment Measure Scores Among Focal and Diffuse Brain Injury Patients: The Importance of Bifactor Models.

PubMed

Gunn, Sarah; Burgess, Gerald H; Maltby, John

2018-04-30

To explore the factor structure of the UK Functional Independence Measure and Functional Assessment Measure (FIM+FAM) among focal and diffuse acquired brain injury patients. Criterion standard. A National Health Service acute acquired brain injury inpatient rehabilitation hospital. Referred sample of N=447 adults admitted for inpatient treatment following an acquired brain injury significant enough to justify intensive inpatient neurorehabilitation INTERVENTION: Not applicable. Functional Independence Measure and Functional Assessment Measure. Exploratory factor analysis suggested a 2-factor structure to FIM+FAM scores, among both focal-proximate and diffuse-proximate acquired brain injury aetiologies. Confirmatory factor analysis suggested a 3-factor bifactor structure presented the best fit of the FIM+FAM score data across both aetiologies. However, across both analyses, a convergence was found towards a general factor, demonstrated by high correlations between factors in the exploratory factor analysis, and by a general factor explaining the majority of the variance in scores on confirmatory factor analysis. Our findings suggested that although factors describing specific functional domains can be derived from FIM+FAM item scores, there is a convergence towards a single factor describing overall functioning. This single factor informs the specific group factors (eg, motor, psychosocial, and communication function) after brain injury. Further research into the comparative value of the general and group factors as evaluative/prognostic measures is indicated. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Novel Techniques of Real-time Blood Flow and Functional Mapping: Technical Note

PubMed Central

KAMADA, Kyousuke; OGAWA, Hiroshi; SAITO, Masato; TAMURA, Yukie; ANEI, Ryogo; KAPELLER, Christoph; HAYASHI, Hideaki; PRUECKL, Robert; GUGER, Christoph

2014-01-01

There are two main approaches to intraoperative monitoring in neurosurgery. One approach is related to fluorescent phenomena and the other is related to oscillatory neuronal activity. We developed novel techniques to visualize blood flow (BF) conditions in real time, based on indocyanine green videography (ICG-VG) and the electrophysiological phenomenon of high gamma activity (HGA). We investigated the use of ICG-VG in four patients with moyamoya disease and two with arteriovenous malformation (AVM), and we investigated the use of real-time HGA mapping in four patients with brain tumors who underwent lesion resection with awake craniotomy. Real-time data processing of ICG-VG was based on perfusion imaging, which generated parameters including arrival time (AT), mean transit time (MTT), and BF of brain surface vessels. During awake craniotomy, we analyzed the frequency components of brain oscillation and performed real-time HGA mapping to identify functional areas. Processed results were projected on a wireless monitor linked to the operating microscope. After revascularization for moyamoya disease, AT and BF were significantly shortened and increased, respectively, suggesting hyperperfusion. Real-time fusion images on the wireless monitor provided anatomical, BF, and functional information simultaneously, and allowed the resection of AVMs under the microscope. Real-time HGA mapping during awake craniotomy rapidly indicated the eloquent areas of motor and language function and significantly shortened the operation time. These novel techniques, which we introduced might improve the reliability of intraoperative monitoring and enable the development of rational and objective surgical strategies. PMID:25263624

Diffuse Optics for Tissue Monitoring and Tomography

PubMed Central

Durduran, T; Choe, R; Baker, W B; Yodh, A G

2015-01-01

This review describes the diffusion model for light transport in tissues and the medical applications of diffuse light. Diffuse optics is particularly useful for measurement of tissue hemodynamics, wherein quantitative assessment of oxy- and deoxy-hemoglobin concentrations and blood flow are desired. The theoretical basis for near-infrared or diffuse optical spectroscopy (NIRS or DOS, respectively) is developed, and the basic elements of diffuse optical tomography (DOT) are outlined. We also discuss diffuse correlation spectroscopy (DCS), a technique whereby temporal correlation functions of diffusing light are transported through tissue and are used to measure blood flow. Essential instrumentation is described, and representative brain and breast functional imaging and monitoring results illustrate the workings of these new tissue diagnostics. PMID:26120204

Structure-function analysis of the extracellular domain of the pneumococcal cell division site positioning protein MapZ

NASA Astrophysics Data System (ADS)

Manuse, Sylvie; Jean, Nicolas L.; Guinot, Mégane; Lavergne, Jean-Pierre; Laguri, Cédric; Bougault, Catherine M.; Vannieuwenhze, Michael S.; Grangeasse, Christophe; Simorre, Jean-Pierre

2016-06-01

Accurate placement of the bacterial division site is a prerequisite for the generation of two viable and identical daughter cells. In Streptococcus pneumoniae, the positive regulatory mechanism involving the membrane protein MapZ positions precisely the conserved cell division protein FtsZ at the cell centre. Here we characterize the structure of the extracellular domain of MapZ and show that it displays a bi-modular structure composed of two subdomains separated by a flexible serine-rich linker. We further demonstrate in vivo that the N-terminal subdomain serves as a pedestal for the C-terminal subdomain, which determines the ability of MapZ to mark the division site. The C-terminal subdomain displays a patch of conserved amino acids and we show that this patch defines a structural motif crucial for MapZ function. Altogether, this structure-function analysis of MapZ provides the first molecular characterization of a positive regulatory process of bacterial cell division.

Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system.

PubMed

Chitnis, Danial; Cooper, Robert J; Dempsey, Laura; Powell, Samuel; Quaggia, Simone; Highton, David; Elwell, Clare; Hebden, Jeremy C; Everdell, Nicholas L

2016-10-01

We present the first three-dimensional, functional images of the human brain to be obtained using a fibre-less, high-density diffuse optical tomography system. Our technology consists of independent, miniaturized, silicone-encapsulated DOT modules that can be placed directly on the scalp. Four of these modules were arranged to provide up to 128, dual-wavelength measurement channels over a scalp area of approximately 60 × 65 mm 2 . Using a series of motor-cortex stimulation experiments, we demonstrate that this system can obtain high-quality, continuous-wave measurements at source-detector separations ranging from 14 to 55 mm in adults, in the presence of hair. We identify robust haemodynamic response functions in 5 out of 5 subjects, and present diffuse optical tomography images that depict functional haemodynamic responses that are well-localized in all three dimensions at both the individual and group levels. This prototype modular system paves the way for a new generation of wearable, wireless, high-density optical neuroimaging technologies.

Tin-phthalocyanine adsorption and diffusion on Cu and Au (111) surfaces: A density functional theory study

NASA Astrophysics Data System (ADS)

Qin, Dan; Ge, Xu-Jin; Lü, Jing-Tao

2018-05-01

Through density functional theory based calculations, we study the adsorption and diffusion of tin phthalocyanine (SnPc) molecule on Au(111) and Cu(111) surfaces. SnPc has two conformers with Sn pointing to the vacuum (Sn-up) and substrate (Sn-down), respectively. The binding energies of the two conformers with different adsorption sites on the two surfaces, including top, bridge, fcc, hcp, are calculated and compared. It is found that the SnPc molecule binds stronger on Cu(111) surface, with binding energy about 1 eV larger than that on Au(111). Only the bridge and top adsorption sites are stable on Cu(111), while all the four adsorption sites are stable on Au(111), with small diffusion barriers between them. Moreover, the flipping barrier from Sn-up to Sn-down conformer is of the same magnitude on the two metal surfaces. These results are consistent with a recent experiment [Zhang, et al., Angew. Chem., 56, 11769 (2017)], which shows that conformation change from Sn-up to Sn-down on Cu(111) surface can be induced by a C60-functionalized STM tip, while similar change is difficult to realize on Au(111), due to smaller diffusion barrier on Au(111).

Numerical Evaluation of Lateral Diffusion Inside Diffusive Gradients in Thin Films Samplers

PubMed Central

2015-01-01

Using numerical simulation of diffusion inside diffusive gradients in thin films (DGT) samplers, we show that the effect of lateral diffusion inside the sampler on the solute flux into the sampler is a nonlinear function of the diffusion layer thickness and the physical sampling window size. In contrast, earlier work concluded that this effect was constant irrespective of parameters of the sampler geometry. The flux increase caused by lateral diffusion inside the sampler was determined to be ∼8.8% for standard samplers, which is considerably lower than the previous estimate of ∼20%. Lateral diffusion is also propagated to the diffusive boundary layer (DBL), where it leads to a slightly stronger decrease in the mass uptake than suggested by the common 1D diffusion model that is applied for evaluating DGT results. We introduce a simple correction procedure for lateral diffusion and demonstrate how the effect of lateral diffusion on diffusion in the DBL can be accounted for. These corrections often result in better estimates of the DBL thickness (δ) and the DGT-measured concentration than earlier approaches and will contribute to more accurate concentration measurements in solute monitoring in waters. PMID:25877251

Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognitive Functions

DTIC Science & Technology

2017-05-14

AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a.  CONTRACT NUMBER 5b.  GRANT...SUPPLEMENTARY NOTES 14. ABSTRACT Brain stress level measurement (non-invasively) in quantitative term is very helpful to correlate with various