Stress concentration factors at saddle and crown positions on the central brace of two-planar welded CHS DKT-connections

NASA Astrophysics Data System (ADS)

Ahmadi, Hamid; Lotfollahi-Yaghin, Mohammad Ali; Aminfar, Mohammad H.

2012-03-01

A set of parametric stress analyses was carried out for two-planar tubular DKT-joints under different axial loading conditions. The analysis results were used to present general remarks on the effects of the geometrical parameters on stress concentration factors (SCFs) at the inner saddle, outer saddle, and crown positions on the central brace. Based on results of finite element (FE) analysis and through nonlinear regression analysis, a new set of SCF parametric equations was established for fatigue design purposes. An assessment study of equations was conducted against the experimental data and original SCF database. The satisfaction of acceptance criteria proposed by the UK Department of Energy (UK DoE) was also checked. Results of parametric study showed that highly remarkable differences exist between the SCF values in a multi-planar DKT-joint and the corresponding SCFs in an equivalent uni-planar KT-joint having the same geometrical properties. It can be clearly concluded from this observation that using the equations proposed for uni-planar KT-connections to compute the SCFs in multi-planar DKT-joints will lead to either considerably under-predicting or over-predicting results. Hence, it is necessary to develop SCF formulae specially designed for multi-planar DKT-joints. Good results of equation assessment according to UK DoE acceptance criteria, high values of correlation coefficients, and the satisfactory agreement between the predictions of the proposed equations and the experimental data guarantee the accuracy of the equations. Therefore, the developed equations can be reliably used for fatigue design of offshore structures.

Advanced joining concepts for passive vibration control

NASA Technical Reports Server (NTRS)

Prucz, Jacky C.; Spyrakos, Constantine

1987-01-01

A comprehensive parametric study was carried out to establish design guidelines for favorable tradeoffs between damping benefits and the associated stiffness, strength and weight penalties in a rhombic joint. The results are compared with the corresponding tradeoffs for a double-lap joint made of the same materials.

Techniques d'inspection par ondes guidees ultrasonores d'assemblages brases dans des reacteurs aeronautiques =

NASA Astrophysics Data System (ADS)

Comot, Pierre

L'industrie aeronautique, cherche a etudier la possibilite d'utiliser de maniere structurelle des joints brases, dans une optique de reduction de poids et de cout. Le developpement d'une methode d'evaluation rapide, fiable et peu couteuse pour evaluer l'integrite structurelle des joints apparait donc indispensable. La resistance mecanique d'un joint brase dependant principalement de la quantite de phase fragile dans sa microstructure. Les ondes guidees ultrasonores permettent de detecter ce type de phase lorsqu'elles sont couplees a une mesure spatio-temporelle. De plus la nature de ce type d'ondes permet l'inspection de joints ayant des formes complexes. Ce memoire se concentre donc sur le developpement d'une technique basee sur l'utilisation d'ondes guidees ultrasonores pour l'inspection de joints brases a recouvrement d'Inconel 625 avec comme metal d'apport du BNi-2. Dans un premiers temps un modele elements finis du joint a ete utilise pour simuler la propagation des ultrasons et optimiser les parametres d'inspection, la simulation a permis egalement de demontrer la faisabilite de la technique pour la detection de la quantite de phase fragile dans ce type de joints. Les parametres optimises sont la forme de signal d'excitation, sa frequence centrale et la direction d'excitation. Les simulations ont montre que l'energie de l'onde ultrasonore transmise a travers le joint aussi bien que celle reflechie, toutes deux extraites des courbes de dispersion, etaient proportionnelles a la quantite de phase fragile presente dans le joint et donc cette methode permet d'identifier la presence ou non d'une phase fragile dans ce type de joint. Ensuite des experimentations ont ete menees sur trois echantillons typiques presentant differentes quantites de phase fragile dans le joint, pour obtenir ce type d'echantillons differents temps de brasage ont ete utilises (1, 60 et 180 min). Pour cela un banc d'essai automatise a ete developpe permettant d'effectuer une analyse similaire a celle utilisee en simulation. Les parametres experimentaux ayant ete choisis en accord avec l'optimisation effectuee lors des simulations et apres une premiere optimisation du procede experimental. Finalement les resultats experimentaux confirment les resultats obtenus en simulation, et demontrent le potentiel de la methode developpee.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

On the apparent insignificance of the randomness of flexible joints on large space truss dynamics

NASA Technical Reports Server (NTRS)

Koch, R. M.; Klosner, J. M.

1993-01-01

Deployable periodic large space structures have been shown to exhibit high dynamic sensitivity to period-breaking imperfections and uncertainties. These can be brought on by manufacturing or assembly errors, structural imperfections, as well as nonlinear and/or nonconservative joint behavior. In addition, the necessity of precise pointing and position capability can require the consideration of these usually negligible and unknown parametric uncertainties and their effect on the overall dynamic response of large space structures. This work describes the use of a new design approach for the global dynamic solution of beam-like periodic space structures possessing parametric uncertainties. Specifically, the effect of random flexible joints on the free vibrations of simply-supported periodic large space trusses is considered. The formulation is a hybrid approach in terms of an extended Timoshenko beam continuum model, Monte Carlo simulation scheme, and first-order perturbation methods. The mean and mean-square response statistics for a variety of free random vibration problems are derived for various input random joint stiffness probability distributions. The results of this effort show that, although joint flexibility has a substantial effect on the modal dynamic response of periodic large space trusses, the effect of any reasonable uncertainty or randomness associated with these joint flexibilities is insignificant.

Parametric fMRI of paced motor responses uncovers novel whole-brain imaging biomarkers in spinocerebellar ataxia type 3.

PubMed

Duarte, João Valente; Faustino, Ricardo; Lobo, Mercês; Cunha, Gil; Nunes, César; Ferreira, Carlos; Januário, Cristina; Castelo-Branco, Miguel

2016-10-01

Machado-Joseph Disease, inherited type 3 spinocerebellar ataxia (SCA3), is the most common form worldwide. Neuroimaging and neuropathology have consistently demonstrated cerebellar alterations. Here we aimed to discover whole-brain functional biomarkers, based on parametric performance-level-dependent signals. We assessed 13 patients with early SCA3 and 14 healthy participants. We used a combined parametric behavioral/functional neuroimaging design to investigate disease fingerprints, as a function of performance levels, coupled with structural MRI and voxel-based morphometry. Functional magnetic resonance imaging (fMRI) was designed to parametrically analyze behavior and neural responses to audio-paced bilateral thumb movements at temporal frequencies of 1, 3, and 5 Hz. Our performance-level-based design probing neuronal correlates of motor coordination enabled the discovery that neural activation and behavior show critical loss of parametric modulation specifically in SCA3, associated with frequency-dependent cortico/subcortical activation/deactivation patterns. Cerebellar/cortical rate-dependent dissociation patterns could clearly differentiate between groups irrespective of grey matter loss. Our findings suggest functional reorganization of the motor network and indicate a possible role of fMRI as a tool to monitor disease progression in SCA3. Accordingly, fMRI patterns proved to be potential biomarkers in early SCA3, as tested by receiver operating characteristic analysis of both behavior and neural activation at different frequencies. Discrimination analysis based on BOLD signal in response to the applied parametric finger-tapping task significantly often reached >80% sensitivity and specificity in single regions-of-interest.Functional fingerprints based on cerebellar and cortical BOLD performance dependent signal modulation can thus be combined as diagnostic and/or therapeutic targets in hereditary ataxia. Hum Brain Mapp 37:3656-3668, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A Non-Parametric Approach for the Activation Detection of Block Design fMRI Simulated Data Using Self-Organizing Maps and Support Vector Machine.

PubMed

Bahrami, Sheyda; Shamsi, Mousa

2017-01-01

Functional magnetic resonance imaging (fMRI) is a popular method to probe the functional organization of the brain using hemodynamic responses. In this method, volume images of the entire brain are obtained with a very good spatial resolution and low temporal resolution. However, they always suffer from high dimensionality in the face of classification algorithms. In this work, we combine a support vector machine (SVM) with a self-organizing map (SOM) for having a feature-based classification by using SVM. Then, a linear kernel SVM is used for detecting the active areas. Here, we use SOM for feature extracting and labeling the datasets. SOM has two major advances: (i) it reduces dimension of data sets for having less computational complexity and (ii) it is useful for identifying brain regions with small onset differences in hemodynamic responses. Our non-parametric model is compared with parametric and non-parametric methods. We use simulated fMRI data sets and block design inputs in this paper and consider the contrast to noise ratio (CNR) value equal to 0.6 for simulated datasets. fMRI simulated dataset has contrast 1-4% in active areas. The accuracy of our proposed method is 93.63% and the error rate is 6.37%.

Non‐parametric combination and related permutation tests for neuroimaging

PubMed Central

Webster, Matthew A.; Brooks, Jonathan C.; Tracey, Irene; Smith, Stephen M.; Nichols, Thomas E.

2016-01-01

Abstract In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well‐known definition of union‐intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of tests, allowing flexibility to integrate imaging data with different spatial resolutions, surface and/or volume‐based representations of the brain, including non‐imaging data. For the problem of joint inference, we propose and evaluate a modification of the recently introduced non‐parametric combination (NPC) methodology, such that instead of a two‐phase algorithm and large data storage requirements, the inference can be performed in a single phase, with reasonable computational demands. The method compares favorably to classical multivariate tests (such as MANCOVA), even when the latter is assessed using permutations. We also evaluate, in the context of permutation tests, various combining methods that have been proposed in the past decades, and identify those that provide the best control over error rate and power across a range of situations. We show that one of these, the method of Tippett, provides a link between correction for the multiplicity of tests and their combination. Finally, we discuss how the correction can solve certain problems of multiple comparisons in one‐way ANOVA designs, and how the combination is distinguished from conjunctions, even though both can be assessed using permutation tests. We also provide a common algorithm that accommodates combination and correction. Hum Brain Mapp 37:1486‐1511, 2016. © 2016 Wiley Periodicals, Inc. PMID:26848101

Effect of brain structure, brain function, and brain connectivity on relapse in alcohol-dependent patients.

PubMed

Beck, Anne; Wüstenberg, Torsten; Genauck, Alexander; Wrase, Jana; Schlagenhauf, Florian; Smolka, Michael N; Mann, Karl; Heinz, Andreas

2012-08-01

In alcohol-dependent patients, brain atrophy and functional brain activation elicited by alcohol-associated stimuli may predict relapse. However, to date, the interaction between both factors has not been studied. To determine whether results from structural and functional magnetic resonance imaging are associated with relapse in detoxified alcohol-dependent patients. A cue-reactivity functional magnetic resonance experiment with alcohol-associated and neutral stimuli. After a follow-up period of 3 months, the group of 46 detoxified alcohol-dependent patients was subdivided into 16 abstainers and 30 relapsers. Faculty for Clinical Medicine Mannheim at the University of Heidelberg, Germany. A total of 46 detoxified alcohol-dependent patients and 46 age- and sex-matched healthy control subjects Local gray matter volume, local stimulus-related functional magnetic resonance imaging activation, joint analyses of structural and functional data with Biological Parametric Mapping, and connectivity analyses adopting the psychophysiological interaction approach. Subsequent relapsers showed pronounced atrophy in the bilateral orbitofrontal cortex and in the right medial prefrontal and anterior cingulate cortex, compared with healthy controls and patients who remained abstinent. The local gray matter volume-corrected brain response elicited by alcohol-associated vs neutral stimuli in the left medial prefrontal cortex was enhanced for subsequent relapsers, whereas abstainers displayed an increased neural response in the midbrain (the ventral tegmental area extending into the subthalamic nucleus) and ventral striatum. For alcohol-associated vs neutral stimuli in abstainers compared with relapsers, the analyses of the psychophysiological interaction showed a stronger functional connectivity between the midbrain and the left amygdala and between the midbrain and the left orbitofrontal cortex. Subsequent relapsers displayed increased brain atrophy in brain areas associated with error monitoring and behavioral control. Correcting for gray matter reductions, we found that, in these patients, alcohol-related cues elicited increased activation in brain areas associated with attentional bias toward these cues and that, in patients who remained abstinent, increased activation and connectivity were observed in brain areas associated with processing of salient or aversive stimuli.

Brain signal variability is parametrically modifiable.

PubMed

Garrett, Douglas D; McIntosh, Anthony R; Grady, Cheryl L

2014-11-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Parametric Method to Define Area of Allowable Configurations while Changing Position of Restricted Zones

NASA Astrophysics Data System (ADS)

Pritykin, F. N.; Nefedov, D. I.; Rogoza, Yu A.; Zinchenko, Yu V.

2018-03-01

The article presents the findings related to the development of the module for automatic collision detection of the manipulator with restricted zones for virtual motion modeling. It proposes the parametric method for specifying the area of allowable joint configurations. The authors study the cases when restricted zones are specified using the horizontal plane or front-projection planes. The joint coordinate space is specified by rectangular axes in the direction of which the angles defining the displacements in turning pairs are laid off. The authors present the results of modeling which enabled to develop a parametric method for specifying a set of cross-sections defining the shape and position of allowable configurations in different positions of a restricted zone. All joint points that define allowable configurations refer to the indicated sections. The area of allowable configurations is specified analytically by using several kinematic surfaces that limit it. A geometric analysis is developed based on the use of the area of allowable configurations characterizing the position of the manipulator and reported restricted zones. The paper presents numerical calculations related to virtual simulation of the manipulator path performed by the mobile robot Varan when using the developed algorithm and restricted zones. The obtained analytical dependencies allow us to define the area of allowable configurations, which is a knowledge pool to ensure the intelligent control of the manipulator path in a predefined environment. The use of the obtained region to synthesize a joint trajectory makes it possible to correct the manipulator path to foresee and eliminate deadlocks when synthesizing motions along the velocity vector.

Neural Mechanisms of Attention

DTIC Science & Technology

1993-05-21

of Attention 39 The Element Superiority Effect : Attention? 46 Animal Models of Attention Deficit 47 Conditioned Attention Theory 50 2 ATTENTION AND...fails to obtain the necessary quantitative information about the effects of parametric manipulations on the dissociation, or the parametric results...neuroscience endeavor as described here. If simultaneously psychologists ignore the brain arid neuroscientists ignore the mind, no effective translation

Simulating the Structural Response of a Preloaded Bolted Joint

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Phillips, Dawn R.; Raju, Ivatury S.

2008-01-01

The present paper describes the structural analyses performed on a preloaded bolted-joint configuration. The joint modeled was comprised of two L-shaped structures connected together using a single bolt. Each L-shaped structure involved a vertical flat segment (or shell wall) welded to a horizontal segment (or flange). Parametric studies were performed using elasto-plastic, large-deformation nonlinear finite element analyses to determine the influence of several factors on the bolted-joint response. The factors considered included bolt preload, washer-surface-bearing size, edge boundary conditions, joint segment length, and loading history. Joint response is reported in terms of displacements, gap opening, and surface strains. Most of the factors studied were determined to have minimal effect on the bolted-joint response; however, the washer-bearing-surface size affected the response significantly.

A semi-parametric within-subject mixture approach to the analyses of responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria; Vermunt, Jeroen K

2018-05-01

In item response theory, modelling the item response times in addition to the item responses may improve the detection of possible between- and within-subject differences in the process that resulted in the responses. For instance, if respondents rely on rapid guessing on some items but not on all, the joint distribution of the responses and response times will be a multivariate within-subject mixture distribution. Suitable parametric methods to detect these within-subject differences have been proposed. In these approaches, a distribution needs to be assumed for the within-class response times. In this paper, it is demonstrated that these parametric within-subject approaches may produce false positives and biased parameter estimates if the assumption concerning the response time distribution is violated. A semi-parametric approach is proposed which resorts to categorized response times. This approach is shown to hardly produce false positives and parameter bias. In addition, the semi-parametric approach results in approximately the same power as the parametric approach. © 2017 The British Psychological Society.

Neurodynamics in the Sensorimotor Loop: Representing Behavior Relevant External Situations

PubMed Central

Pasemann, Frank

2017-01-01

In the context of the dynamical system approach to cognition and supposing that brains or brain-like systems controlling the behavior of autonomous systems are permanently driven by their sensor signals, the paper approaches the question of neurodynamics in the sensorimotor loop in a purely formal way. This is carefully done by addressing the problem in three steps, using the time-discrete dynamics of standard neural networks and a fiber space representation for better clearness. Furthermore, concepts like meta-transients, parametric stability and dynamical forms are introduced, where meta-transients describe the effect of realistic sensor inputs, parametric stability refers to a class of sensor inputs all generating the “same type” of dynamic behavior, and a dynamical form comprises the corresponding class of parametrized dynamical systems. It is argued that dynamical forms are the essential internal representatives of behavior relevant external situations. Consequently, it is suggested that dynamical forms are the basis for a memory of these situations. Finally, based on the observation that not all brain process have a direct effect on the motor activity, a natural splitting of neurodynamics into vertical (internal) and horizontal (effective) parts is introduced. PMID:28217092

Robust biological parametric mapping: an improved technique for multimodal brain image analysis

NASA Astrophysics Data System (ADS)

Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

2011-03-01

Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

[Detection of cerebral hypoperfusion using single photon emission computed tomography image analysis and statistical parametric mapping in patients with Parkinson's disease or progressive supranuclear palsy].

PubMed

Harada, Kengo; Saeki, Hiroshi; Matsuya, Eiji; Okita, Izumi

2013-11-01

We carried out differential diagnosis of brain blood flow images using single-photon emission computed tomography (SPECT) for patients with Parkinson's disease (PD) or progressive supranuclear paralysis (PSP) using statistical parametric mapping (SPM) and to whom we had applied anatomical standardization. We studied two groups and compared brain blood flow images using SPECT (N-isopropyl-4-iodoamphetamine [(123)I] hydrochloride injection, 222 MGq dosage i.v.). A total of 27 patients were studied using SPM: 18 with PD and 9 with PSP; humming bird sign on MRI was from moderate to medium. The decline of brain bloodstream in the PSP group was more notable in the midbrain, near the domain where the humming bird sign was observable, than in the PD group. The observable differences in brain bloodstream decline in the midbrain of PSP and PD patients suggest the potential usefulness of this technique's clinical application to distinction diagnosis.

Ankle Joint Intrinsic Dynamics is More Complex than a Mass-Spring-Damper Model.

PubMed

Sobhani Tehrani, Ehsan; Jalaleddini, Kian; Kearney, Robert E

2017-09-01

This paper describes a new small signal parametric model of ankle joint intrinsic mechanics in normal subjects. We found that intrinsic ankle mechanics is a third-order system and the second-order mass-spring-damper model, referred to as IBK, used by many researchers in the literature cannot adequately represent ankle dynamics at all frequencies in a number of important tasks. This was demonstrated using experimental data from five healthy subjects with no voluntary muscle contraction and at seven ankle positions covering the range of motion. We showed that the difference between the new third-order model and the conventional IBK model increased from dorsi to plantarflexed position. The new model was obtained using a multi-step identification procedure applied to experimental input/output data of the ankle joint. The procedure first identifies a non-parametric model of intrinsic joint stiffness where ankle position is the input and torque is the output. Then, in several steps, the model is converted into a continuous-time transfer function of ankle compliance, which is the inverse of stiffness. Finally, we showed that the third-order model is indeed structurally consistent with agonist-antagonist musculoskeletal structure of human ankle, which is not the case for the IBK model.

Direct reconstruction of parametric images for brain PET with event-by-event motion correction: evaluation in two tracers across count levels

NASA Astrophysics Data System (ADS)

Germino, Mary; Gallezot, Jean-Dominque; Yan, Jianhua; Carson, Richard E.

2017-07-01

Parametric images for dynamic positron emission tomography (PET) are typically generated by an indirect method, i.e. reconstructing a time series of emission images, then fitting a kinetic model to each voxel time activity curve. Alternatively, ‘direct reconstruction’, incorporates the kinetic model into the reconstruction algorithm itself, directly producing parametric images from projection data. Direct reconstruction has been shown to achieve parametric images with lower standard error than the indirect method. Here, we present direct reconstruction for brain PET using event-by-event motion correction of list-mode data, applied to two tracers. Event-by-event motion correction was implemented for direct reconstruction in the Parametric Motion-compensation OSEM List-mode Algorithm for Resolution-recovery reconstruction. The direct implementation was tested on simulated and human datasets with tracers [11C]AFM (serotonin transporter) and [11C]UCB-J (synaptic density), which follow the 1-tissue compartment model. Rigid head motion was tracked with the Vicra system. Parametric images of K 1 and distribution volume (V T  =  K 1/k 2) were compared to those generated by the indirect method by regional coefficient of variation (CoV). Performance across count levels was assessed using sub-sampled datasets. For simulated and real datasets at high counts, the two methods estimated K 1 and V T with comparable accuracy. At lower count levels, the direct method was substantially more robust to outliers than the indirect method. Compared to the indirect method, direct reconstruction reduced regional K 1 CoV by 35-48% (simulated dataset), 39-43% ([11C]AFM dataset) and 30-36% ([11C]UCB-J dataset) across count levels (averaged over regions at matched iteration); V T CoV was reduced by 51-58%, 54-60% and 30-46%, respectively. Motion correction played an important role in the dataset with larger motion: correction increased regional V T by 51% on average in the [11C]UCB-J dataset. Direct reconstruction of dynamic brain PET with event-by-event motion correction is achievable and dramatically more robust to noise in V T images than the indirect method.

Parametric study in weld mismatch of longitudinally welded SSME HPFTP inlet

NASA Technical Reports Server (NTRS)

Min, J. B.; Spanyer, K. L.; Brunair, R. M.

1991-01-01

Welded joints are an essential part of pressure vessels such as the Space Shuttle Main Engine (SSME) Turbopumps. Defects produced in the welding process can be detrimental to weld performance. Recently, review of the SSME high pressure fuel turbopump (HPFTP) titanium inlet x rays revealed several weld discrepancies such as penetrameter density issues, film processing discrepancies, weld width discrepancies, porosity, lack of fusion, and weld offsets. Currently, the sensitivity of welded structures to defects is of concern. From a fatigue standpoint, weld offset may have a serious effect since local yielding, in general, aggravates cyclic stress effects. Therefore, the weld offset issue is considered. Using the finite element method and mathematical formulations, parametric studies were conducted to determine the influence of weld offsets and a variation of weld widths in longitudinally welded cylindrical structures with equal wall thickness on both sides of the joint. From the study, the finite element results and theoretical solutions are presented.

An EM-based semi-parametric mixture model approach to the regression analysis of competing-risks data.

PubMed

Ng, S K; McLachlan, G J

2003-04-15

We consider a mixture model approach to the regression analysis of competing-risks data. Attention is focused on inference concerning the effects of factors on both the probability of occurrence and the hazard rate conditional on each of the failure types. These two quantities are specified in the mixture model using the logistic model and the proportional hazards model, respectively. We propose a semi-parametric mixture method to estimate the logistic and regression coefficients jointly, whereby the component-baseline hazard functions are completely unspecified. Estimation is based on maximum likelihood on the basis of the full likelihood, implemented via an expectation-conditional maximization (ECM) algorithm. Simulation studies are performed to compare the performance of the proposed semi-parametric method with a fully parametric mixture approach. The results show that when the component-baseline hazard is monotonic increasing, the semi-parametric and fully parametric mixture approaches are comparable for mildly and moderately censored samples. When the component-baseline hazard is not monotonic increasing, the semi-parametric method consistently provides less biased estimates than a fully parametric approach and is comparable in efficiency in the estimation of the parameters for all levels of censoring. The methods are illustrated using a real data set of prostate cancer patients treated with different dosages of the drug diethylstilbestrol. Copyright 2003 John Wiley & Sons, Ltd.

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

PubMed

Seo, Seongho; Kim, Su Jin; Lee, Dong Soo; Lee, Jae Sung

2014-10-01

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

Design, Static Analysis And Fabrication Of Composite Joints

NASA Astrophysics Data System (ADS)

Mathiselvan, G.; Gobinath, R.; Yuvaraja, S.; Raja, T.

2017-05-01

The Bonded joints will be having one of the important issues in the composite technology is the repairing of aging in aircraft applications. In these applications and also for joining various composite material parts together, the composite materials fastened together either using adhesives or mechanical fasteners. In this paper, we have carried out design, static analysis of 3-D models and fabrication of the composite joints (bonded, riveted and hybrid). The 3-D model of the composite structure will be fabricated by using the materials such as epoxy resin, glass fibre material and aluminium rivet for preparing the joints. The static analysis was carried out with different joint by using ANSYS software. After fabrication, parametric study was also conducted to compare the performance of the hybrid joint with varying adherent width, adhesive thickness and overlap length. Different joint and its materials tensile test result have compared.

Integral abutment bridges under thermal loading : numerical simulations and parametric study.

DOT National Transportation Integrated Search

2016-06-01

Integral abutment bridges (IABs) have become of interest due to their decreased construction and maintenance costs in : comparison to conventional jointed bridges. Most prior IAB research was related to substructure behavior, and, as a result, most :...

An approach to trial design and analysis in the era of non-proportional hazards of the treatment effect.

PubMed

Royston, Patrick; Parmar, Mahesh K B

2014-08-07

Most randomized controlled trials with a time-to-event outcome are designed and analysed under the proportional hazards assumption, with a target hazard ratio for the treatment effect in mind. However, the hazards may be non-proportional. We address how to design a trial under such conditions, and how to analyse the results. We propose to extend the usual approach, a logrank test, to also include the Grambsch-Therneau test of proportional hazards. We test the resulting composite null hypothesis using a joint test for the hazard ratio and for time-dependent behaviour of the hazard ratio. We compute the power and sample size for the logrank test under proportional hazards, and from that we compute the power of the joint test. For the estimation of relevant quantities from the trial data, various models could be used; we advocate adopting a pre-specified flexible parametric survival model that supports time-dependent behaviour of the hazard ratio. We present the mathematics for calculating the power and sample size for the joint test. We illustrate the methodology in real data from two randomized trials, one in ovarian cancer and the other in treating cellulitis. We show selected estimates and their uncertainty derived from the advocated flexible parametric model. We demonstrate in a small simulation study that when a treatment effect either increases or decreases over time, the joint test can outperform the logrank test in the presence of both patterns of non-proportional hazards. Those designing and analysing trials in the era of non-proportional hazards need to acknowledge that a more complex type of treatment effect is becoming more common. Our method for the design of the trial retains the tools familiar in the standard methodology based on the logrank test, and extends it to incorporate a joint test of the null hypothesis with power against non-proportional hazards. For the analysis of trial data, we propose the use of a pre-specified flexible parametric model that can represent a time-dependent hazard ratio if one is present.

Brain serotonin transporter density and aggression in abstinent methamphetamine abusers.

PubMed

Sekine, Yoshimoto; Ouchi, Yasuomi; Takei, Nori; Yoshikawa, Etsuji; Nakamura, Kazuhiko; Futatsubashi, Masami; Okada, Hiroyuki; Minabe, Yoshio; Suzuki, Katsuaki; Iwata, Yasuhide; Tsuchiya, Kenji J; Tsukada, Hideo; Iyo, Masaomi; Mori, Norio

2006-01-01

In animals, methamphetamine is known to have a neurotoxic effect on serotonin neurons, which have been implicated in the regulation of mood, anxiety, and aggression. It remains unknown whether methamphetamine damages serotonin neurons in humans. To investigate the status of brain serotonin neurons and their possible relationship with clinical characteristics in currently abstinent methamphetamine abusers. Case-control analysis. A hospital research center. Twelve currently abstinent former methamphetamine abusers (5 women and 7 men) and 12 age-, sex-, and education-matched control subjects recruited from the community. The brain regional density of the serotonin transporter, a structural component of serotonin neurons, was estimated using positron emission tomography and trans-1,2,3,5,6,10-beta-hexahydro-6-[4-(methylthio)phenyl]pyrrolo-[2,1-a]isoquinoline ([(11)C](+)McN-5652). Estimates were derived from region-of-interest and statistical parametric mapping methods, followed by within-case analysis using the measures of clinical variables. The duration of methamphetamine use, the magnitude of aggression and depressive symptoms, and changes in serotonin transporter density represented by the [(11)C](+)McN-5652 distribution volume. Methamphetamine abusers showed increased levels of aggression compared with controls. Region-of-interest and statistical parametric mapping analyses revealed that the serotonin transporter density in global brain regions (eg, the midbrain, thalamus, caudate, putamen, cerebral cortex, and cerebellum) was significantly lower in methamphetamine abusers than in control subjects, and this reduction was significantly inversely correlated with the duration of methamphetamine use. Furthermore, statistical parametric mapping analyses indicated that the density in the orbitofrontal, temporal, and anterior cingulate areas was closely associated with the magnitude of aggression in methamphetamine abusers. Protracted abuse of methamphetamine may reduce the density of the serotonin transporter in the brain, leading to elevated aggression, even in currently abstinent abusers.

Comparison of System Identification Techniques for the Hydraulic Manipulator Test Bed (HMTB)

NASA Technical Reports Server (NTRS)

Morris, A. Terry

1996-01-01

In this thesis linear, dynamic, multivariable state-space models for three joints of the ground-based Hydraulic Manipulator Test Bed (HMTB) are identified. HMTB, housed at the NASA Langley Research Center, is a ground-based version of the Dexterous Orbital Servicing System (DOSS), a representative space station manipulator. The dynamic models of the HMTB manipulator will first be estimated by applying nonparametric identification methods to determine each joint's response characteristics using various input excitations. These excitations include sum of sinusoids, pseudorandom binary sequences (PRBS), bipolar ramping pulses, and chirp input signals. Next, two different parametric system identification techniques will be applied to identify the best dynamical description of the joints. The manipulator is localized about a representative space station orbital replacement unit (ORU) task allowing the use of linear system identification methods. Comparisons, observations, and results of both parametric system identification techniques are discussed. The thesis concludes by proposing a model reference control system to aid in astronaut ground tests. This approach would allow the identified models to mimic on-orbit dynamic characteristics of the actual flight manipulator thus providing astronauts with realistic on-orbit responses to perform space station tasks in a ground-based environment.

Assessment of Biomarkers Associated with Joint Injury and Subsequent Post-Traumatic Arthritis

DTIC Science & Technology

2014-10-01

synovitis score with semi-quantitative scales, and osteophyte score6-10. Parametric analyses were performed for bone morphological measures and...histological assessment. Subchondral bone thickening was significantly increased in the C57BL/6 mice compared to the MRL/MpJ mice in the medial femur (p...biochemical and metabolic data. J Bone Joint Surg Am. 53:523-537. 10. Gelse K, Soder S, Eger W, Diemtar T, Aigner T. Feb 2003. Osteophyte development

Sensitivity of the Halstead and Wechsler Test Batteries to brain damage: Evidence from Reitan's original validation sample.

PubMed

Loring, David W; Larrabee, Glenn J

2006-06-01

The Halstead-Reitan Battery has been instrumental in the development of neuropsychological practice in the United States. Although Reitan administered both the Wechsler-Bellevue Intelligence Scale and Halstead's test battery when evaluating Halstead's theory of biologic intelligence, the relative sensitivity of each test battery to brain damage continues to be an area of controversy. Because Reitan did not perform direct parametric analysis to contrast group performances, we reanalyze Reitan's original validation data from both Halstead (Reitan, 1955) and Wechsler batteries (Reitan, 1959a) and calculate effect sizes and probability levels using traditional parametric approaches. Eight of the 10 tests comprising Halstead's original Impairment Index, as well as the Impairment Index itself, statistically differentiated patients with unequivocal brain damage from controls. In addition, 13 of 14 Wechsler measures including Full-Scale IQ also differed statistically between groups (Brain Damage Full-Scale IQ = 96.2; Control Group Full Scale IQ = 112.6). We suggest that differences in the statistical properties of each battery (e.g., raw scores vs. standardized scores) likely contribute to classification characteristics including test sensitivity and specificity.

Refining patterns of joint hypermobility, habitus, and orthopedic traits in joint hypermobility syndrome and Ehlers-Danlos syndrome, hypermobility type.

PubMed

Morlino, Silvia; Dordoni, Chiara; Sperduti, Isabella; Venturini, Marina; Celletti, Claudia; Camerota, Filippo; Colombi, Marina; Castori, Marco

2017-04-01

Joint hypermobility syndrome (JHS) and Ehlers-Danlos syndrome, hypermobility type (EDS-HT) are two overlapping heritable disorders (JHS/EDS-HT) recognized by separated sets of diagnostic criteria and still lack a confirmatory test. This descriptive research was aimed at better characterizing the clinical phenotype of JHS/EDS-HT with focus on available diagnostic criteria, and in order to propose novel features and assessment strategies. One hundred and eighty-nine (163 females, 26 males; age: 2-73 years) patients from two Italian reference centers were investigated for Beighton score, range of motion in 21 additional joints, rate and sites of dislocations and sprains, recurrent soft-tissue injuries, tendon and muscle ruptures, body mass index, arm span/height ratio, wrist and thumb signs, and 12 additional orthopedic features. Rough rates were compared by age, sex, and handedness with a series of parametric and non-parametric tools. Multiple correspondence analysis was carried out for possible co-segregations of features. Beighton score and hypermobility at other joints were influenced by age at diagnosis. Rate and sites of joint instability complications did not vary according to age at diagnosis except for soft-tissue injuries. No major difference was registered by sex and dominant versus non-dominant body side. At multiple correspondence analysis, selected features tend to co-segregate in a dichotomous distribution. Dolichostenomelia and arachnodactyly segregated independently. This study pointed out a more protean musculoskeletal phenotype than previously considered according to available diagnostic criteria for JHS/EDS-HT. Our findings corroborated the need for a re-thinking of JHS/EDS-HT on clinical grounds in order to find better therapeutic and research strategies. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Axisymmetric shell analysis of the Space Shuttle solid rocket booster field joint

NASA Technical Reports Server (NTRS)

Nemeth, Michael P.; Anderson, Melvin S.

1989-01-01

The Space Shuttle Challenger (STS 51-L) accident led to an intense investigation of the structural behavior of the solid rocket booster (SRB) tang and clevis field joints. The presence of structural deformations between the clevis inner leg and the tang, substantial enough to prevent the O-ring seals from eliminating hot gas flow through the joints, has emerged as a likely cause of the vehicle failure. This paper presents results of axisymmetric shell analyses that parametrically assess the structural behavior of SRB field joints subjected to quasi-steady-state internal pressure loading for both the original joint flown on mission STS 51-L and the redesigned joint recently flown on the Space Shuttle Discovery. Discussion of axisymmetric shell modeling issues and details is presented and a generic method for simulating contact between adjacent shells of revolution is described. Results are presented that identify the performance trends of the joints for a wide range of joint parameters.

Parametric Coding of the Size and Clutter of Natural Scenes in the Human Brain

PubMed Central

Park, Soojin; Konkle, Talia; Oliva, Aude

2015-01-01

Estimating the size of a space and its degree of clutter are effortless and ubiquitous tasks of moving agents in a natural environment. Here, we examine how regions along the occipital–temporal lobe respond to pictures of indoor real-world scenes that parametrically vary in their physical “size” (the spatial extent of a space bounded by walls) and functional “clutter” (the organization and quantity of objects that fill up the space). Using a linear regression model on multivoxel pattern activity across regions of interest, we find evidence that both properties of size and clutter are represented in the patterns of parahippocampal cortex, while the retrosplenial cortex activity patterns are predominantly sensitive to the size of a space, rather than the degree of clutter. Parametric whole-brain analyses confirmed these results. Importantly, this size and clutter information was represented in a way that generalized across different semantic categories. These data provide support for a property-based representation of spaces, distributed across multiple scene-selective regions of the cerebral cortex. PMID:24436318

Whole brain analysis of postmortem density changes of grey and white matter on computed tomography by statistical parametric mapping.

PubMed

Nishiyama, Yuichi; Kanayama, Hidekazu; Mori, Hiroshi; Tada, Keiji; Yamamoto, Yasushi; Katsube, Takashi; Takeshita, Haruo; Kawakami, Kazunori; Kitagaki, Hajime

2017-06-01

This study examined the usefulness of statistical parametric mapping (SPM) for investigating postmortem changes on brain computed tomography (CT). This retrospective study included 128 patients (23 - 100 years old) without cerebral abnormalities who underwent unenhanced brain CT before and after death. The antemortem CT (AMCT) scans and postmortem CT (PMCT) scans were spatially normalized using our original brain CT template, and postmortem changes of CT values (in Hounsfield units; HU) were analysed by the SPM technique. Compared with AMCT scans, 58.6 % and 98.4 % of PMCT scans showed loss of the cerebral sulci and an unclear grey matter (GM)-white matter (WM) interface, respectively. SPM analysis revealed a significant decrease in cortical GM density within 70 min after death on PMCT scans, suggesting cytotoxic brain oedema. Furthermore, there was a significant increase in the density of the WM, lenticular nucleus and thalamus more than 120 min after death. The SPM technique demonstrated typical postmortem changes on brain CT scans, and revealed that the unclear GM-WM interface on early PMCT scans is caused by a rapid decrease in cortical GM density combined with a delayed increase in WM density. SPM may be useful for assessment of whole brain postmortem changes. • The original brain CT template achieved successful normalization of brain morphology. • Postmortem changes in the brain were independent of sex. • Cortical GM density decreased rapidly after death. • WM and deep GM densities increased following cortical GM density change. • SPM could be useful for assessment of whole brain postmortem changes.

Modeling and stochastic analysis of dynamic mechanisms of the perception

NASA Astrophysics Data System (ADS)

Pisarchik, A.; Bashkirtseva, I.; Ryashko, L.

2017-10-01

Modern studies in physiology and cognitive neuroscience consider a noise as an important constructive factor of the brain functionality. Under the adequate noise, the brain can rapidly access different ordered states, and provide decision-making by preventing deadlocks. Bistable dynamic models are often used for the study of the underlying mechanisms of the visual perception. In the present paper, we consider a bistable energy model subject to both additive and parametric noise. Using the catastrophe theory formalism and stochastic sensitivity functions technique, we analyze a response of the equilibria to noise, and study noise-induced transitions between equilibria. We demonstrate and analyse the effect of hysteresis squeezing when the intensity of noise is increased. Stochastic bifurcations connected with the suppression of oscillations by parametric noises are discussed.

A Computer-Aided Analysis Method of SPECT Brain Images for Quantitative Treatment Monitoring: Performance Evaluations and Clinical Applications.

PubMed

Zheng, Xiujuan; Wei, Wentao; Huang, Qiu; Song, Shaoli; Wan, Jieqing; Huang, Gang

2017-01-01

The objective and quantitative analysis of longitudinal single photon emission computed tomography (SPECT) images are significant for the treatment monitoring of brain disorders. Therefore, a computer aided analysis (CAA) method is introduced to extract a change-rate map (CRM) as a parametric image for quantifying the changes of regional cerebral blood flow (rCBF) in longitudinal SPECT brain images. The performances of the CAA-CRM approach in treatment monitoring are evaluated by the computer simulations and clinical applications. The results of computer simulations show that the derived CRMs have high similarities with their ground truths when the lesion size is larger than system spatial resolution and the change rate is higher than 20%. In clinical applications, the CAA-CRM approach is used to assess the treatment of 50 patients with brain ischemia. The results demonstrate that CAA-CRM approach has a 93.4% accuracy of recovered region's localization. Moreover, the quantitative indexes of recovered regions derived from CRM are all significantly different among the groups and highly correlated with the experienced clinical diagnosis. In conclusion, the proposed CAA-CRM approach provides a convenient solution to generate a parametric image and derive the quantitative indexes from the longitudinal SPECT brain images for treatment monitoring.

A Parametric Approach to Numerical Modeling of TKR Contact Forces

PubMed Central

Lundberg, Hannah J.; Foucher, Kharma C.; Wimmer, Markus A.

2009-01-01

In vivo knee contact forces are difficult to determine using numerical methods because there are more unknown forces than equilibrium equations available. We developed parametric methods for computing contact forces across the knee joint during the stance phase of level walking. Three-dimensional contact forces were calculated at two points of contact between the tibia and the femur, one on the lateral aspect of the tibial plateau, and one on the medial side. Muscle activations were parametrically varied over their physiologic range resulting in a solution space of contact forces. The obtained solution space was reasonably small and the resulting force pattern compared well to a previous model from the literature for kinematics and external kinetics from the same patient. Peak forces of the parametric model and the previous model were similar for the first half of the stance phase, but differed for the second half. The previous model did not take into account the transverse external moment about the knee and could not calculate muscle activation levels. Ultimately, the parametric model will result in more accurate contact force inputs for total knee simulators, as current inputs are not generally based on kinematics and kinetics inputs from TKR patients. PMID:19155015

Brain metabolism in patients with vegetative state after post-resuscitated hypoxic-ischemic brain injury: statistical parametric mapping analysis of F-18 fluorodeoxyglucose positron emission tomography.

PubMed

Kim, Yong Wook; Kim, Hyoung Seop; An, Young-sil

2013-03-01

Hypoxic-ischemic brain injury (HIBI) after cardiopulmonary resuscitation is one of the most devastating neurological conditions that causing the impaired consciousness. However, there were few studies investigated the changes of brain metabolism in patients with vegetative state (VS) after post-resuscitated HIBI. This study aimed to analyze the change of overall brain metabolism and elucidated the brain area correlated with the level of consciousness (LOC) in patients with VS after post-resuscitated HIBI. We consecutively enrolled 17 patients with VS after HIBI, who experienced cardiopulmonary resuscitation. Overall brain metabolism was measured by F-18 fluorodeoxyglucose positron emission tomography (F-18 FDG PET) and we compared regional brain metabolic patterns from 17 patients with those from 15 normal controls using voxel-by-voxel based statistical parametric mapping analysis. Additionally, we correlated the LOC measured by the JFK-coma recovery scale-revised of each patient with brain metabolism by covariance analysis. Compared with normal controls, the patients with VS after post-resuscitated HIBI revealed significantly decreased brain metabolism in bilateral precuneus, bilateral posterior cingulate gyrus, bilateral middle frontal gyri, bilateral superior parietal gyri, bilateral middle occipital gyri, bilateral precentral gyri (PFEW correctecd < 0.0001), and increased brain metabolism in bilateral insula, bilateral cerebella, and the brainstem (PFEW correctecd < 0.0001). In covariance analysis, the LOC was significantly correlated with brain metabolism in bilateral fusiform and superior temporal gyri (Puncorrected < 0.005). Our study demonstrated that the precuneus, the posterior cingulate area and the frontoparietal cortex, which is a component of neural correlate for consciousness, may be relevant structure for impaired consciousness in patient with VS after post-resuscitated HIBI. In post-resuscitated HIBI, measurement of brain metabolism using PET images may be helpful for investigating the brain function that cannot be obtained by morphological imaging and can be used to assess the brain area responsible for consciousness.

Brain connectivity study of joint attention using frequency-domain optical imaging technique

NASA Astrophysics Data System (ADS)

Chaudhary, Ujwal; Zhu, Banghe; Godavarty, Anuradha

2010-02-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic populations. In this study, diffuse optical imaging is being used to study brain connectivity for the first time in response to joint attention experience in normal adults. The prefrontal region of the brain was non-invasively imaged using a frequency-domain based optical imager. The imaging studies were performed on 11 normal right-handed adults and optical measurements were acquired in response to joint-attention based video clips. While the intensity-based optical data provides information about the hemodynamic response of the underlying neural process, the time-dependent phase-based optical data has the potential to explicate the directional information on the activation of the brain. Thus brain connectivity studies are performed by computing covariance/correlations between spatial units using this frequency-domain based optical measurements. The preliminary results indicate that the extent of synchrony and directional variation in the pattern of activation varies in the left and right frontal cortex. The results have significant implication for research in neural pathways associated with autism that can be mapped using diffuse optical imaging tools in the future.

Ultrasonic guided wave inspection of Inconel 625 brazed lap joints

NASA Astrophysics Data System (ADS)

Comot, Pierre; Bocher, Philippe; Belanger, Pierre

2016-04-01

The aerospace industry has been investigating the use of brazing for structural joints, as a mean of reducing cost and weight. There therefore is a need for a rapid, robust, and cost-effective non-destructive testing method for evaluating the structural integrity of the joints. The mechanical strength of brazed joints depends mainly on the amount of brittle phases in their microstructure. Ultrasonic guided waves offer the possibility of detecting brittle phases in joints using spatio-temporal measurements. Moreover, they offer the opportunity to inspect complex shape joints. This study focused on the development of a technique based on ultrasonic guided waves for the inspection of Inconel 625 lap joints brazed with BNi-2 filler metal. A finite element model of a lap joint was used to optimize the inspection parameters and assess the feasibility of detecting the amount of brittle phases in the joint. A finite element parametric study simulating the input signal shape, the center frequency, and the excitation direction was performed. The simulations showed that the ultrasonic guided wave energy transmitted through, and reflected from, the joints was proportional to the amount of brittle phases in the joint.

Structural design of an in-line bolted joint for the space shuttle solid rocket motor case segments

NASA Technical Reports Server (NTRS)

Dorsey, John T.; Stein, Peter A.; Bush, Harold G.

1987-01-01

Results of a structural design study of an in-line bolted joint concept which can be used to assemble Space Shuttle Solid Rocket Motor (SRM) case segments are presented. Numerous parametric studies are performed to characterize the in-line bolted joint behavior as major design variables are altered, with the primary objective always being to keep the inside of the joint (where the O-rings are located) closed during the SRM firing. The resulting design has 180 1-inch studs, an eccentricity of -0.5 inch, a flange thickness of 3/4 inch, a bearing plate thickness of 1/4 inch, and the studs are subjected to a preload which is 70% of ultimate. The mass penalty per case segment joint for the in-line design is 346 lbm more than the weight penalty for the proposed capture tang fix.

Joint source based analysis of multiple brain structures in studying major depressive disorder

NASA Astrophysics Data System (ADS)

Ramezani, Mahdi; Rasoulian, Abtin; Hollenstein, Tom; Harkness, Kate; Johnsrude, Ingrid; Abolmaesumi, Purang

2014-03-01

We propose a joint Source-Based Analysis (jSBA) framework to identify brain structural variations in patients with Major Depressive Disorder (MDD). In this framework, features representing position, orientation and size (i.e. pose), shape, and local tissue composition are extracted. Subsequently, simultaneous analysis of these features within a joint analysis method is performed to generate the basis sources that show signi cant di erences between subjects with MDD and those in healthy control. Moreover, in a cross-validation leave- one-out experiment, we use a Fisher Linear Discriminant (FLD) classi er to identify individuals within the MDD group. Results show that we can classify the MDD subjects with an accuracy of 76% solely based on the information gathered from the joint analysis of pose, shape, and tissue composition in multiple brain structures.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography.

PubMed

Packham, B; Barnes, G; Dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-06-01

Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography

PubMed Central

Packham, B; Barnes, G; dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-01-01

Abstract Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity. PMID:27203477

Brain tissues volume measurements from 2D MRI using parametric approach

NASA Astrophysics Data System (ADS)

L'vov, A. A.; Toropova, O. A.; Litovka, Yu. V.

2018-04-01

The purpose of the paper is to propose a fully automated method of volume assessment of structures within human brain. Our statistical approach uses maximum interdependency principle for decision making process of measurements consistency and unequal observations. Detecting outliers performed using maximum normalized residual test. We propose a statistical model which utilizes knowledge of tissues distribution in human brain and applies partial data restoration for precision improvement. The approach proposes completed computationally efficient and independent from segmentation algorithm used in the application.

Modulation of experimental arthritis by vagal sensory and central brain stimulation.

PubMed

Bassi, Gabriel Shimizu; Dias, Daniel Penteado Martins; Franchin, Marcelo; Talbot, Jhimmy; Reis, Daniel Gustavo; Menezes, Gustavo Batista; Castania, Jaci Airton; Garcia-Cairasco, Norberto; Resstel, Leonardo Barbosa Moraes; Salgado, Helio Cesar; Cunha, Fernando Queiróz; Cunha, Thiago Mattar; Ulloa, Luis; Kanashiro, Alexandre

2017-08-01

Articular inflammation is a major clinical burden in multiple inflammatory diseases, especially in rheumatoid arthritis. Biological anti-rheumatic drug therapies are expensive and increase the risk of systemic immunosuppression, infections, and malignancies. Here, we report that vagus nerve stimulation controls arthritic joint inflammation by inducing local regulation of innate immune response. Most of the previous studies of neuromodulation focused on vagal regulation of inflammation via the efferent peripheral pathway toward the viscera. Here, we report that vagal stimulation modulates arthritic joint inflammation through a novel "afferent" pathway mediated by the locus coeruleus (LC) of the central nervous system. Afferent vagal stimulation activates two sympatho-excitatory brain areas: the paraventricular hypothalamic nucleus (PVN) and the LC. The integrity of the LC, but not that of the PVN, is critical for vagal control of arthritic joint inflammation. Afferent vagal stimulation suppresses articular inflammation in the ipsilateral, but not in the contralateral knee to the hemispheric LC lesion. Central stimulation is followed by subsequent activation of joint sympathetic nerve terminals inducing articular norepinephrine release. Selective adrenergic beta-blockers prevent the effects of articular norepinephrine and thereby abrogate vagal control of arthritic joint inflammation. These results reveals a novel neuro-immune brain map with afferent vagal signals controlling side-specific articular inflammation through specific inflammatory-processing brain centers and joint sympathetic innervations. Copyright © 2017 Elsevier Inc. All rights reserved.

Constructing a simple parametric model of shoulder from medical images

NASA Astrophysics Data System (ADS)

Atmani, H.; Fofi, D.; Merienne, F.; Trouilloud, P.

2006-02-01

The modelling of the shoulder joint is an important step to set a Computer-Aided Surgery System for shoulder prosthesis placement. Our approach mainly concerns the bones structures of the scapulo-humeral joint. Our goal is to develop a tool that allows the surgeon to extract morphological data from medical images in order to interpret the biomechanical behaviour of a prosthesised shoulder for preoperative and peroperative virtual surgery. To provide a light and easy-handling representation of the shoulder, a geometrical model composed of quadrics, planes and other simple forms is proposed.

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.

Adaptive plasticity in mammalian masticatory joints

NASA Astrophysics Data System (ADS)

Ravosa, Matthew J.; Kunwar, Ravinder; Nicholson, Elisabeth K.; Klopp, Emily B.; Pinchoff, Jessie; Stock, Stuart R.; Stack, M. Sharon; Hamrick, Mark W.

2006-08-01

Genetically similar white rabbits raised on diets of different mechanical properties, as well as wild-type and myostatin-deficient mice raised on similar diets, were compared to assess the postweaning effects of elevated masticatory loads due to increased jaw-adductor muscle and bite forces on the proportions and properties of the mandibular symphysis and temporomandibular joint (TMJ). Microcomputed tomography (microCT) was used to quantify bone structure at a series of equidistant external and internal sites in coronal sections for a series of joint locations. Discriminant function analyses and non-parametric ANOVAs were used to characterize variation in biomineralization within and between loading cohorts. In both species, long-term excessive loading results in larger joint proportions, thicker articular and cortical bone, and increased biomineralization of hard tissues. Such adaptive plasticity appears designed to maintain the postnatal integrity of masticatory joint systems for a primary loading environment(s). This behavioral signal may be increasingly mitigated in older organisms by the interplay between adaptive and degradative joint tissue responses.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Functional brain connectivity when cooperation fails.

PubMed

Balconi, Michela; Vanutelli, Maria Elide; Gatti, Laura

2018-06-01

Functional connectivity during cooperative actions is an important topic in social neuroscience that has yet to be answered. Here, we examined the effects of administration of (fictitious) negative social feedback in relation to cooperative capabilities. Cognitive performance and neural activation underlying the execution of joint actions was recorded with functional near-infrared spectroscopy (fNIRS) on prefrontal regions during a task where pairs of participants received negative feedback after their joint action. Performance (error rates (ERs) and response times (RTs)) and intra- and inter-brain connectivity indices were computed, along with the ConIndex (inter-brain/intra-brain connectivity). Finally, correlational measures were considered to assess the relation between these different measures. Results showed that the negative feedback was able to modulate participants' responses for both behavioral and neural components. Cognitive performance was decreased after the feedback. Moreover, decreased inter-brain connectivity and increased intra-brain connectivity was induced by the feedback, whereas the cooperative task pre-feedback condition was able to increase the brain-to-brain coupling, mainly localized within the dorsolateral prefrontal cortex (DLPFC). Finally, the presence of significant correlations between RTs and inter-brain connectivity revealed that ineffective joint action produces the worst cognitive performance and a more 'individual strategy' for brain activity, limiting the inter-brain connectivity. The present study provides a significant contribution to the identification of patterns of intra- and inter-brain functional connectivity when negative social reinforcement is provided in relation to cooperative actions. Copyright © 2018 Elsevier Inc. All rights reserved.

Within-subject joint independent component analysis of simultaneous fMRI/ERP in an auditory oddball paradigm

PubMed Central

MANGALATHU-ARUMANA, J.; BEARDSLEY, S. A.; LIEBENTHAL, E.

2012-01-01

The integration of event-related potential (ERP) and functional magnetic resonance imaging (fMRI) can contribute to characterizing neural networks with high temporal and spatial resolution. This research aimed to determine the sensitivity and limitations of applying joint independent component analysis (jICA) within-subjects, for ERP and fMRI data collected simultaneously in a parametric auditory frequency oddball paradigm. In a group of 20 subjects, an increase in ERP peak amplitude ranging 1–8 μV in the time window of the P300 (350–700ms), and a correlated increase in fMRI signal in a network of regions including the right superior temporal and supramarginal gyri, was observed with the increase in deviant frequency difference. JICA of the same ERP and fMRI group data revealed activity in a similar network, albeit with stronger amplitude and larger extent. In addition, activity in the left pre- and post- central gyri, likely associated with right hand somato-motor response, was observed only with the jICA approach. Within-subject, the jICA approach revealed significantly stronger and more extensive activity in the brain regions associated with the auditory P300 than the P300 linear regression analysis. The results suggest that with the incorporation of spatial and temporal information from both imaging modalities, jICA may be a more sensitive method for extracting common sources of activity between ERP and fMRI. PMID:22377443

Joint Analysis of Band-Specific Functional Connectivity and Signal Complexity in Autism

ERIC Educational Resources Information Center

Ghanbari, Yasser; Bloy, Luke; Edgar, J. Christopher; Blaskey, Lisa; Verma, Ragini; Roberts, Timothy P. L.

2015-01-01

Examination of resting state brain activity using electrophysiological measures like complexity as well as functional connectivity is of growing interest in the study of autism spectrum disorders (ASD). The present paper jointly examined complexity and connectivity to obtain a more detailed characterization of resting state brain activity in ASD.…

Pig brain stereotaxic standard space: mapping of cerebral blood flow normative values and effect of MPTP-lesioning.

PubMed

Andersen, Flemming; Watanabe, Hideaki; Bjarkam, Carsten; Danielsen, Erik H; Cumming, Paul

2005-07-15

The analysis of physiological processes in brain by position emission tomography (PET) is facilitated when images are spatially normalized to a standard coordinate system. Thus, PET activation studies of human brain frequently employ the common stereotaxic coordinates of Talairach. We have developed an analogous stereotaxic coordinate system for the brain of the Gottingen miniature pig, based on automatic co-registration of magnetic resonance (MR) images obtained in 22 male pigs. The origin of the pig brain stereotaxic space (0, 0, 0) was arbitrarily placed in the centroid of the pineal gland as identified on the average MRI template. The orthogonal planes were imposed using the line between stereotaxic zero and the optic chiasm. A series of mean MR images in the coronal, sagittal and horizontal planes were generated. To test the utility of the common coordinate system for functional imaging studies of minipig brain, we calculated cerebral blood flow (CBF) maps from normal minipigs and from minipigs with a syndrome of parkisonism induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-poisoning. These maps were transformed from the native space into the common stereotaxic space. After global normalization of these maps, an undirected search for differences between the groups was then performed using statistical parametric mapping. Using this method, we detected a statistically significant focal increase in CBF in the left cerebellum of the MPTP-lesioned group. We expect the present approach to be of general use in the statistical parametric mapping of CBF and other physiological parameters in living pig brain.

Lightweight structural design of a bolted case joint for the space shuttle solid rocket motor

NASA Technical Reports Server (NTRS)

Dorsey, John T.; Stein, Peter A.; Bush, Harold G.

1988-01-01

The structural design of a bolted joint with a static face seal which can be used to join Space Shuttle Solid Rocket Motor (SRM) case segments is given. Results from numerous finite element parametric studies indicate that the bolted joint meets the design requirement of preventing joint opening at the O-ring locations during SRM pressurization. A final design recommended for further development has the following parameters: 180 one-in.-diam. studs, stud centerline offset of 0.5 in radially inward from the shell wall center line, flange thickness of 0.75 in, bearing plate thickness of 0.25 in, studs prestressed to 70 percent of ultimate load, and the intermediate alcove. The design has a mass penalty of 1096 lbm, which is 164 lbm greater than the currently proposed capture tang redesign.

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.

Joint penalized-likelihood reconstruction of time-activity curves and regions-of-interest from projection data in brain PET

NASA Astrophysics Data System (ADS)

Krestyannikov, E.; Tohka, J.; Ruotsalainen, U.

2008-06-01

This paper presents a novel statistical approach for joint estimation of regions-of-interest (ROIs) and the corresponding time-activity curves (TACs) from dynamic positron emission tomography (PET) brain projection data. It is based on optimizing the joint objective function that consists of a data log-likelihood term and two penalty terms reflecting the available a priori information about the human brain anatomy. The developed local optimization strategy iteratively updates both the ROI and TAC parameters and is guaranteed to monotonically increase the objective function. The quantitative evaluation of the algorithm is performed with numerically and Monte Carlo-simulated dynamic PET brain data of the 11C-Raclopride and 18F-FDG tracers. The results demonstrate that the method outperforms the existing sequential ROI quantification approaches in terms of accuracy, and can noticeably reduce the errors in TACs arising due to the finite spatial resolution and ROI delineation.

Parameter identification and optimization of slide guide joint of CNC machine tools

NASA Astrophysics Data System (ADS)

Zhou, S.; Sun, B. B.

2017-11-01

The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

Exploration of Parametric Integrals Related to a Question of Soil Mechanics

ERIC Educational Resources Information Center

Dana-Picard, Thierry; Zeitoun, David

2017-01-01

We study a 1-parameter family of trigonometric definite integrals, showing how the joint usage of Information and Communication Technologies and paper-and-pencil work lead to different outputs, revealing different mathematical meanings and different concrete meanings. This family of integrals is useful for describing a phenomenon in soil…

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Joint temporal density measurements for two-photon state characterization.

PubMed

Kuzucu, Onur; Wong, Franco N C; Kurimura, Sunao; Tovstonog, Sergey

2008-10-10

We demonstrate a technique for characterizing two-photon quantum states based on joint temporal correlation measurements using time-resolved single-photon detection by femtosecond up-conversion. We measure for the first time the joint temporal density of a two-photon entangled state, showing clearly the time anticorrelation of the coincident-frequency entangled photon pair generated by ultrafast spontaneous parametric down-conversion under extended phase-matching conditions. The new technique enables us to manipulate the frequency entanglement by varying the down-conversion pump bandwidth to produce a nearly unentangled two-photon state that is expected to yield a heralded single-photon state with a purity of 0.88. The time-domain correlation technique complements existing frequency-domain measurement methods for a more complete characterization of photonic entanglement.

Effects of Breast Cancer Chemotherapy Agents on Brain Activity in Rats: Functional Imaging Studies

DTIC Science & Technology

2011-04-29

and in a small region of the striatum. Visual stimulation produced bilateral activation of the superior colliculus, lateral geniculate and a small...pattern was seen in the lateral geniculate . These results demonstrate the feasibility of using brain activation by parametric sensory stimulation as...both the right and left lateral geniculate functional ROIs (25% and 29%, respectively). There were smaller but not statistically significant decreases

Connecting long distance: semantic distance in analogical reasoning modulates frontopolar cortex activity.

PubMed

Green, Adam E; Kraemer, David J M; Fugelsang, Jonathan A; Gray, Jeremy R; Dunbar, Kevin N

2010-01-01

Solving problems often requires seeing new connections between concepts or events that seemed unrelated at first. Innovative solutions of this kind depend on analogical reasoning, a relational reasoning process that involves mapping similarities between concepts. Brain-based evidence has implicated the frontal pole of the brain as important for analogical mapping. Separately, cognitive research has identified semantic distance as a key characteristic of the kind of analogical mapping that can support innovation (i.e., identifying similarities across greater semantic distance reveals connections that support more innovative solutions and models). However, the neural substrates of semantically distant analogical mapping are not well understood. Here, we used functional magnetic resonance imaging (fMRI) to measure brain activity during an analogical reasoning task, in which we parametrically varied the semantic distance between the items in the analogies. Semantic distance was derived quantitatively from latent semantic analysis. Across 23 participants, activity in an a priori region of interest (ROI) in left frontopolar cortex covaried parametrically with increasing semantic distance, even after removing effects of task difficulty. This ROI was centered on a functional peak that we previously associated with analogical mapping. To our knowledge, these data represent a first empirical characterization of how the brain mediates semantically distant analogical mapping.

Structure of the alexithymic brain: A parametric coordinate-based meta-analysis.

PubMed

Xu, Pengfei; Opmeer, Esther M; van Tol, Marie-José; Goerlich, Katharina S; Aleman, André

2018-04-01

Alexithymia refers to deficiencies in identifying and expressing emotions. This might be related to changes in structural brain volumes, but its neuroanatomical basis remains uncertain as studies have shown heterogeneous findings. Therefore, we conducted a parametric coordinate-based meta-analysis. We identified seventeen structural neuroimaging studies (including a total of 2586 individuals with different levels of alexithymia) investigating the association between gray matter volume and alexithymia. Volumes of the left insula, left amygdala, orbital frontal cortex and striatum were consistently smaller in people with high levels of alexithymia. These areas are important for emotion perception and emotional experience. Smaller volumes in these areas might lead to deficiencies in appropriately identifying and expressing emotions. These findings provide the first quantitative integration of results pertaining to the structural neuroanatomical basis of alexithymia. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Joint explorative analysis of neuroreceptor subsystems in the human brain: application to receptor-transporter correlation using PET data.

PubMed

Cselényi, Zsolt; Lundberg, Johan; Halldin, Christer; Farde, Lars; Gulyás, Balázs

2004-10-01

Positron emission tomography (PET) has proved to be a highly successful technique in the qualitative and quantitative exploration of the human brain's neurotransmitter-receptor systems. In recent years, the number of PET radioligands, targeted to different neuroreceptor systems of the human brain, has increased considerably. This development paves the way for a simultaneous analysis of different receptor systems and subsystems in the same individual. The detailed exploration of the versatility of neuroreceptor systems requires novel technical approaches, capable of operating on huge parametric image datasets. An initial step of such explorative data processing and analysis should be the development of novel exploratory data-mining tools to gain insight into the "structure" of complex multi-individual, multi-receptor data sets. For practical reasons, a possible and feasible starting point of multi-receptor research can be the analysis of the pre- and post-synaptic binding sites of the same neurotransmitter. In the present study, we propose an unsupervised, unbiased data-mining tool for this task and demonstrate its usefulness by using quantitative receptor maps, obtained with positron emission tomography, from five healthy subjects on (pre-synaptic) serotonin transporters (5-HTT or SERT) and (post-synaptic) 5-HT(1A) receptors. Major components of the proposed technique include the projection of the input receptor maps to a feature space, the quasi-clustering and classification of projected data (neighbourhood formation), trans-individual analysis of neighbourhood properties (trajectory analysis), and the back-projection of the results of trajectory analysis to normal space (creation of multi-receptor maps). The resulting multi-receptor maps suggest that complex relationships and tendencies in the relationship between pre- and post-synaptic transporter-receptor systems can be revealed and classified by using this method. As an example, we demonstrate the regional correlation of the serotonin transporter-receptor systems. These parameter-specific multi-receptor maps can usefully guide the researchers in their endeavour to formulate models of multi-receptor interactions and changes in the human brain.

Progressive Damage Analysis of Bonded Composite Joints

NASA Technical Reports Server (NTRS)

Leone, Frank A., Jr.; Girolamo, Donato; Davila, Carlos G.

2012-01-01

The present work is related to the development and application of progressive damage modeling techniques to bonded joint technology. The joint designs studied in this work include a conventional composite splice joint and a NASA-patented durable redundant joint. Both designs involve honeycomb sandwich structures with carbon/epoxy facesheets joined using adhesively bonded doublers.Progressive damage modeling allows for the prediction of the initiation and evolution of damage within a structure. For structures that include multiple material systems, such as the joint designs under consideration, the number of potential failure mechanisms that must be accounted for drastically increases the complexity of the analyses. Potential failure mechanisms include fiber fracture, intraply matrix cracking, delamination, core crushing, adhesive failure, and their interactions. The bonded joints were modeled using highly parametric, explicitly solved finite element models, with damage modeling implemented via custom user-written subroutines. Each ply was discretely meshed using three-dimensional solid elements. Layers of cohesive elements were included between each ply to account for the possibility of delaminations and were used to model the adhesive layers forming the joint. Good correlation with experimental results was achieved both in terms of load-displacement history and the predicted failure mechanism(s).

Reusable Launch Vehicle Tank/Intertank Sizing Trade Study

NASA Technical Reports Server (NTRS)

Dorsey, John T.; Myers, David E.; Martin, Carl J.

2000-01-01

A tank and intertank sizing tool that includes effects of major design drivers, and which allows parametric studies to be performed, has been developed and calibrated against independent representative results. Although additional design features, such as bulkheads and field joints, are not currently included in the process, the improved level of fidelity has allowed parametric studies to be performed which have resulted in understanding of key tank and intertank design drivers, design sensitivities, and definition of preferred design spaces. The sizing results demonstrated that there were many interactions between the configuration parameters of internal/external payload, vehicle fineness ratio (half body angle), fuel arrangement (LOX-forward/LOX-aft), number of tanks, and tank shape/arrangement (number of lobes).

Optimization of two-photon wave function in parametric down conversion by adaptive optics control of the pump radiation.

PubMed

Minozzi, M; Bonora, S; Sergienko, A V; Vallone, G; Villoresi, P

2013-02-15

We present an efficient method for optimizing the spatial profile of entangled-photon wave function produced in a spontaneous parametric down conversion process. A deformable mirror that modifies a wavefront of a 404 nm CW diode laser pump interacting with a nonlinear β-barium borate type-I crystal effectively controls the profile of the joint biphoton function. The use of a feedback signal extracted from the biphoton coincidence rate is used to achieve the optimal wavefront shape. The optimization of the two-photon coupling into two, single spatial modes for correlated detection is used for a practical demonstration of this physical principle.

A critical examination of stresses in an elastic single lap joint

NASA Technical Reports Server (NTRS)

Cooper, P. A.; Sawyer, J. W.

1979-01-01

The results of an approximate nonlinear finite-element analysis of a single lap joint are presented and compared with the results of a linear finite-element analysis, and the geometric nonlinear effects caused by the load-path eccentricity on the adhesive stress distributions are determined. The results from finite-element, Goland-Reissner, and photoelastic analyses show that for a single lap joint the effect of the geometric nonlinear behavior of the joint has a sizable effect on the stresses in the adhesive. The Goland-Reissner analysis is sufficiently accurate in the prediction of stresses along the midsurface of the adhesive bond to be used for qualitative evaluation of the influence of geometric or material parametric variations. Detailed stress distributions in both the adherend and adhesive obtained from the finite-element analysis are presented to provide a basis for comparison with other solution techniques.

Joint Attention and Brain Functional Connectivity in Infants and Toddlers.

PubMed

Eggebrecht, Adam T; Elison, Jed T; Feczko, Eric; Todorov, Alexandre; Wolff, Jason J; Kandala, Sridhar; Adams, Chloe M; Snyder, Abraham Z; Lewis, John D; Estes, Annette M; Zwaigenbaum, Lonnie; Botteron, Kelly N; McKinstry, Robert C; Constantino, John N; Evans, Alan; Hazlett, Heather C; Dager, Stephen; Paterson, Sarah J; Schultz, Robert T; Styner, Martin A; Gerig, Guido; Das, Samir; Kostopoulos, Penelope; Schlaggar, Bradley L; Petersen, Steven E; Piven, Joseph; Pruett, John R

2017-03-01

Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development. © The Author 2017. Published by Oxford University Press.

Joint Attention and Brain Functional Connectivity in Infants and Toddlers

PubMed Central

Eggebrecht, Adam T.; Elison, Jed T.; Feczko, Eric; Todorov, Alexandre; Wolff, Jason J.; Kandala, Sridhar; Adams, Chloe M.; Snyder, Abraham Z.; Lewis, John D.; Estes, Annette M.; Zwaigenbaum, Lonnie; Botteron, Kelly N.; McKinstry, Robert C.; Constantino, John N.; Evans, Alan; Hazlett, Heather C.; Dager, Stephen; Paterson, Sarah J.; Schultz, Robert T.; Styner, Martin A.; Gerig, Guido; Das, Samir; Kostopoulos, Penelope; Schlaggar, Bradley L.; Petersen, Steven E.; Piven, Joseph; Pruett, John R.

2017-01-01

Abstract Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development. PMID:28062515

Motor impairments related to brain injury timing in early hemiparesis. Part II: abnormal upper extremity joint torque synergies.

PubMed

Sukal-Moulton, Theresa; Krosschell, Kristin J; Gaebler-Spira, Deborah J; Dewald, Julius P A

2014-01-01

Extensive neuromotor development occurs early in human life, and the timing of brain injury may affect the resulting motor impairment. In Part I of this series, it was demonstrated that the distribution of weakness in the upper extremity depended on the timing of brain injury in individuals with childhood-onset hemiparesis. The goal of this study was to characterize how timing of brain injury affects joint torque synergies, or losses of independent joint control. Twenty-four individuals with hemiparesis were divided into 3 groups based on the timing of their injury: before birth (PRE-natal, n = 8), around the time of birth (PERI-natal, n = 8), and after 6 months of age (POST-natal, n = 8). Individuals with hemiparesis and 8 typically developing peers participated in maximal isometric shoulder, elbow, wrist, and finger torque generation tasks while their efforts were recorded by a multiple degree-of-freedom load cell. Motor output in 4 joints of the upper extremity was concurrently measured during 8 primary torque generation tasks to quantify joint torque synergies. There were a number of significant coupling patterns identified in individuals with hemiparesis that differed from the typically developing group. POST-natal differences were most noted in the coupling of shoulder abductors with elbow, wrist, and finger flexors, while the PRE-natal group demonstrated significant distal joint coupling with elbow flexion. The torque synergies measured provide indirect evidence for the use of bulbospinal pathways in the POST-natal group, while those with earlier injury may use relatively preserved ipsilateral corticospinal motor pathways.

Self Diagnostic Adhesive for Bonded Joints in Aircraft Structures

DTIC Science & Technology

2016-10-04

validated under the fatigue/dynamic loading condition. 3) Both SEM (Spectral Element Modeling) and FEM ( Finite Element Modeling) simulation of the...Sensors ..................................................................... 22 Parametric Study of Sensor Performance via Finite Element Simulation...The frequency range that we are interested is around 800 kHz. Conventional linear finite element method (FEM) requires a very fine spatial

A Semiparametric Model for Jointly Analyzing Response Times and Accuracy in Computerized Testing

ERIC Educational Resources Information Center

Wang, Chun; Fan, Zhewen; Chang, Hua-Hua; Douglas, Jeffrey A.

2013-01-01

The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the…

JDINAC: joint density-based non-parametric differential interaction network analysis and classification using high-dimensional sparse omics data.

PubMed

Ji, Jiadong; He, Di; Feng, Yang; He, Yong; Xue, Fuzhong; Xie, Lei

2017-10-01

A complex disease is usually driven by a number of genes interwoven into networks, rather than a single gene product. Network comparison or differential network analysis has become an important means of revealing the underlying mechanism of pathogenesis and identifying clinical biomarkers for disease classification. Most studies, however, are limited to network correlations that mainly capture the linear relationship among genes, or rely on the assumption of a parametric probability distribution of gene measurements. They are restrictive in real application. We propose a new Joint density based non-parametric Differential Interaction Network Analysis and Classification (JDINAC) method to identify differential interaction patterns of network activation between two groups. At the same time, JDINAC uses the network biomarkers to build a classification model. The novelty of JDINAC lies in its potential to capture non-linear relations between molecular interactions using high-dimensional sparse data as well as to adjust confounding factors, without the need of the assumption of a parametric probability distribution of gene measurements. Simulation studies demonstrate that JDINAC provides more accurate differential network estimation and lower classification error than that achieved by other state-of-the-art methods. We apply JDINAC to a Breast Invasive Carcinoma dataset, which includes 114 patients who have both tumor and matched normal samples. The hub genes and differential interaction patterns identified were consistent with existing experimental studies. Furthermore, JDINAC discriminated the tumor and normal sample with high accuracy by virtue of the identified biomarkers. JDINAC provides a general framework for feature selection and classification using high-dimensional sparse omics data. R scripts available at https://github.com/jijiadong/JDINAC. lxie@iscb.org. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Construction of joint confidence regions for the optimal true class fractions of Receiver Operating Characteristic (ROC) surfaces and manifolds.

PubMed

Bantis, Leonidas E; Nakas, Christos T; Reiser, Benjamin; Myall, Daniel; Dalrymple-Alford, John C

2017-06-01

The three-class approach is used for progressive disorders when clinicians and researchers want to diagnose or classify subjects as members of one of three ordered categories based on a continuous diagnostic marker. The decision thresholds or optimal cut-off points required for this classification are often chosen to maximize the generalized Youden index (Nakas et al., Stat Med 2013; 32: 995-1003). The effectiveness of these chosen cut-off points can be evaluated by estimating their corresponding true class fractions and their associated confidence regions. Recently, in the two-class case, parametric and non-parametric methods were investigated for the construction of confidence regions for the pair of the Youden-index-based optimal sensitivity and specificity fractions that can take into account the correlation introduced between sensitivity and specificity when the optimal cut-off point is estimated from the data (Bantis et al., Biomet 2014; 70: 212-223). A parametric approach based on the Box-Cox transformation to normality often works well while for markers having more complex distributions a non-parametric procedure using logspline density estimation can be used instead. The true class fractions that correspond to the optimal cut-off points estimated by the generalized Youden index are correlated similarly to the two-class case. In this article, we generalize these methods to the three- and to the general k-class case which involves the classification of subjects into three or more ordered categories, where ROC surface or ROC manifold methodology, respectively, is typically employed for the evaluation of the discriminatory capacity of a diagnostic marker. We obtain three- and multi-dimensional joint confidence regions for the optimal true class fractions. We illustrate this with an application to the Trail Making Test Part A that has been used to characterize cognitive impairment in patients with Parkinson's disease.

Parametric motion control of robotic arms: A biologically based approach using neural networks

NASA Technical Reports Server (NTRS)

Bock, O.; D'Eleuterio, G. M. T.; Lipitkas, J.; Grodski, J. J.

1993-01-01

A neural network based system is presented which is able to generate point-to-point movements of robotic manipulators. The foundation of this approach is the use of prototypical control torque signals which are defined by a set of parameters. The parameter set is used for scaling and shaping of these prototypical torque signals to effect a desired outcome of the system. This approach is based on neurophysiological findings that the central nervous system stores generalized cognitive representations of movements called synergies, schemas, or motor programs. It has been proposed that these motor programs may be stored as torque-time functions in central pattern generators which can be scaled with appropriate time and magnitude parameters. The central pattern generators use these parameters to generate stereotypical torque-time profiles, which are then sent to the joint actuators. Hence, only a small number of parameters need to be determined for each point-to-point movement instead of the entire torque-time trajectory. This same principle is implemented for controlling the joint torques of robotic manipulators where a neural network is used to identify the relationship between the task requirements and the torque parameters. Movements are specified by the initial robot position in joint coordinates and the desired final end-effector position in Cartesian coordinates. This information is provided to the neural network which calculates six torque parameters for a two-link system. The prototypical torque profiles (one per joint) are then scaled by those parameters. After appropriate training of the network, our parametric control design allowed the reproduction of a trained set of movements with relatively high accuracy, and the production of previously untrained movements with comparable accuracy. We conclude that our approach was successful in discriminating between trained movements and in generalizing to untrained movements.

Influence of the pump threshold on the single-frequency output power of singly resonant optical parametric oscillators

NASA Astrophysics Data System (ADS)

Sowade, R.; Breunig, I.; Kiessling, J.; Buse, K.

2009-07-01

We demonstrate that for a given pump source, there is an optimum pump threshold to achieve the maximum single-frequency output power in singly resonant optical parametric oscillators. Therefore, cavity losses and parametric amplification have to be adjusted. In particular, continuous-wave output powers of 1.5 W were achieved with a 2.5 cm lithium niobate crystal in comparison with 0.5 W by a 5 cm long crystal within the same cavity design. This counter-intuitive result of weaker amplification leading to larger powers can be explained using a model from L.B. Kreuzer (Proc. Joint Conf. Lasers and Opt.-Elect., p. 52, 1969). Kreuzer also states that single-mode operation is possible only up to pump powers which are 4.6 times the threshold value. Additionally, implementing an outcoupling mirror to increase losses, single-frequency waves with powers of 3 W at 3.2 µm and 7 W at 1.5 µm could be generated simultaneously.

A novel ultrasound technique for detection of osteochondral defects in the ankle joint: a parametric and feasibility study.

PubMed

Sarkalkan, Nazli; Loeve, Arjo J; van Dongen, Koen W A; Tuijthof, Gabrielle J M; Zadpoor, Amir A

2014-12-24

(Osteo)chondral defects (OCDs) in the ankle are currently diagnosed with modalities that are not convenient to use in long-term follow-ups. Ultrasound (US) imaging, which is a cost-effective and non-invasive alternative, has limited ability to discriminate OCDs. We aim to develop a new diagnostic technique based on US wave propagation through the ankle joint. The presence of OCDs is identified when a US signal deviates from a reference signal associated with the healthy joint. The feasibility of the proposed technique is studied using experimentally-validated 2D finite-difference time-domain models of the ankle joint. The normalized maximum cross correlation of experiments and simulation was 0.97. Effects of variables relevant to the ankle joint, US transducers and OCDs were evaluated. Variations in joint space width and transducer orientation made noticeable alterations to the reference signal: normalized root mean square error ranged from 6.29% to 65.25% and from 19.59% to 8064.2%, respectively. The results suggest that the new technique could be used for detection of OCDs, if the effects of other parameters (i.e., parameters related to the ankle joint and US transducers) can be reduced.

Progressive Damage Modeling of Durable Bonded Joint Technology

NASA Technical Reports Server (NTRS)

Leone, Frank A.; Davila, Carlos G.; Lin, Shih-Yung; Smeltzer, Stan; Girolamo, Donato; Ghose, Sayata; Guzman, Juan C.; McCarville, Duglas A.

2013-01-01

The development of durable bonded joint technology for assembling composite structures for launch vehicles is being pursued for the U.S. Space Launch System. The present work is related to the development and application of progressive damage modeling techniques to bonded joint technology applicable to a wide range of sandwich structures for a Heavy Lift Launch Vehicle. The joint designs studied in this work include a conventional composite splice joint and a NASA-patented Durable Redundant Joint. Both designs involve a honeycomb sandwich with carbon/epoxy facesheets joined with adhesively bonded doublers. Progressive damage modeling allows for the prediction of the initiation and evolution of damage. For structures that include multiple materials, the number of potential failure mechanisms that must be considered increases the complexity of the analyses. Potential failure mechanisms include fiber fracture, matrix cracking, delamination, core crushing, adhesive failure, and their interactions. The joints were modeled using Abaqus parametric finite element models, in which damage was modeled with user-written subroutines. Each ply was meshed discretely, and layers of cohesive elements were used to account for delaminations and to model the adhesive layers. Good correlation with experimental results was achieved both in terms of load-displacement history and predicted failure mechanisms.

KmL3D: a non-parametric algorithm for clustering joint trajectories.

PubMed

Genolini, C; Pingault, J B; Driss, T; Côté, S; Tremblay, R E; Vitaro, F; Arnaud, C; Falissard, B

2013-01-01

In cohort studies, variables are measured repeatedly and can be considered as trajectories. A classic way to work with trajectories is to cluster them in order to detect the existence of homogeneous patterns of evolution. Since cohort studies usually measure a large number of variables, it might be interesting to study the joint evolution of several variables (also called joint-variable trajectories). To date, the only way to cluster joint-trajectories is to cluster each trajectory independently, then to cross the partitions obtained. This approach is unsatisfactory because it does not take into account a possible co-evolution of variable-trajectories. KmL3D is an R package that implements a version of k-means dedicated to clustering joint-trajectories. It provides facilities for the management of missing values, offers several quality criteria and its graphic interface helps the user to select the best partition. KmL3D can work with any number of joint-variable trajectories. In the restricted case of two joint trajectories, it proposes 3D tools to visualize the partitioning and then export 3D dynamic rotating-graphs to PDF format. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

PubMed Central

Hirayama, Jun-ichiro; Hyvärinen, Aapo; Kiviniemi, Vesa; Kawanabe, Motoaki; Yamashita, Okito

2016-01-01

Characterizing the variability of resting-state functional brain connectivity across subjects and/or over time has recently attracted much attention. Principal component analysis (PCA) serves as a fundamental statistical technique for such analyses. However, performing PCA on high-dimensional connectivity matrices yields complicated “eigenconnectivity” patterns, for which systematic interpretation is a challenging issue. Here, we overcome this issue with a novel constrained PCA method for connectivity matrices by extending the idea of the previously proposed orthogonal connectivity factorization method. Our new method, modular connectivity factorization (MCF), explicitly introduces the modularity of brain networks as a parametric constraint on eigenconnectivity matrices. In particular, MCF analyzes the variability in both intra- and inter-module connectivities, simultaneously finding network modules in a principled, data-driven manner. The parametric constraint provides a compact module-based visualization scheme with which the result can be intuitively interpreted. We develop an optimization algorithm to solve the constrained PCA problem and validate our method in simulation studies and with a resting-state functional connectivity MRI dataset of 986 subjects. The results show that the proposed MCF method successfully reveals the underlying modular eigenconnectivity patterns in more general situations and is a promising alternative to existing methods. PMID:28002474

Joint attention studies in normal and autistic children using NIRS

NASA Astrophysics Data System (ADS)

Chaudhary, Ujwal; Hall, Michael; Gutierrez, Anibal; Messinger, Daniel; Rey, Gustavo; Godavarty, Anuradha

2011-03-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic. In this study Near infrared spectroscopy (NIRS) is being applied for the first time to study the difference in activation and connectivity in the frontal cortex of typically developing (TD) and autistic children between 4-8 years of age in response to joint attention task. The optical measurements are acquired in real time from frontal cortex using Imagent (ISS Inc.) - a frequency domain based NIRS system in response to video clips which engenders a feeling of joint attention experience in the subjects. A block design consisting of 5 blocks of following sequence 30 sec joint attention clip (J), 30 sec non-joint attention clip (NJ) and 30 sec rest condition is used. Preliminary results from TD child shows difference in brain activation (in terms of oxy-hemoglobin, HbO) during joint attention interaction compared to the nonjoint interaction and rest. Similar activation study did not reveal significant differences in HbO across the stimuli in, unlike in an autistic child. Extensive studies are carried out to validate the initial observations from both brain activation as well as connectivity analysis. The result has significant implication for research in neural pathways associated with autism that can be mapped using NIRS.

Joint-specific risk of impaired function in fibrodysplasia ossificans progressiva (FOP).

PubMed

Pignolo, Robert J; Durbin-Johnson, Blythe P; Rocke, David M; Kaplan, Frederick S

2018-04-01

Fibrodysplasia ossificans progressiva (FOP) causes progressive disability due to heterotopic ossification from episodic flare-ups. Using data from 500 FOP patients (representing 63% of all known patients world-wide), age- and joint-specific risks of new joint involvement were estimated using parametric and nonparametric statistical methods. Compared to data from a 1994 survey of 44 individuals with FOP, our current estimates of age- and joint-specific risks of new joint involvement are more accurate (narrower confidence limits), based on a wider range of ages, and have less bias due to its greater comprehensiveness (captures over three-fifths of the known FOP patients worldwide). For the neck, chest, abdomen, and upper back, the estimated hazard decreases over time. For the jaw, lower back, shoulder, elbow, wrist, fingers, hip, knee, ankle, and foot, the estimated hazard increases initially then either plateaus or decreases. At any given time and for any anatomic site, the data indicate which joints are at risk. This study of approximately 63% of the world's known population of FOP patients provides a refined estimate of risk for new involvement at any joint at any age, as well as the proportion of patients with uninvolved joints at any age. Importantly, these joint-specific survival curves can be used to facilitate clinical trial design and to determine if potential treatments can modify the predicted trajectory of progressive joint dysfunction. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of Biomarkers Associated with Joint Injury and Subsequent Post-Traumatic Arthritis

DTIC Science & Technology

2014-10-01

using a modified Mankin score, synovial inflammation using a modified synovitis score with semi-quantitative scales, and osteophyte score6-10...Parametric analyses were performed for bone morphological measures and histological assessment. Subchondral bone thickening was significantly increased in...Soder S, Eger W, Diemtar T, Aigner T. Feb 2003. Osteophyte development-- molecular characterization of differentiation stages. Osteoarthritis

Exploration of parametric integrals related to a question of soil mechanics

NASA Astrophysics Data System (ADS)

Dana-Picard, Thierry; Zeitoun, David

2017-05-01

We study a 1-parameter family of trigonometric definite integrals, showing how the joint usage of Information and Communication Technologies and paper-and-pencil work lead to different outputs, revealing different mathematical meanings and different concrete meanings. This family of integrals is useful for describing a phenomenon in soil mechanics, whence the importance of such integrals in STEM education.

Experimental investigation of the intensity fluctuation joint probability and conditional distributions of the twin-beam quantum state.

PubMed

Zhang, Yun; Kasai, Katsuyuki; Watanabe, Masayoshi

2003-01-13

We give the intensity fluctuation joint probability of the twin-beam quantum state, which was generated with an optical parametric oscillator operating above threshold. Then we present what to our knowledge is the first measurement of the intensity fluctuation conditional probability distributions of twin beams. The measured inference variance of twin beams 0.62+/-0.02, which is less than the standard quantum limit of unity, indicates inference with a precision better than that of separable states. The measured photocurrent variance exhibits a quantum correlation of as much as -4.9+/-0.2 dB between the signal and the idler.

Joint confidence region estimation for area under ROC curve and Youden index.

PubMed

Yin, Jingjing; Tian, Lili

2014-03-15

In the field of diagnostic studies, the area under the ROC curve (AUC) serves as an overall measure of a biomarker/diagnostic test's accuracy. Youden index, defined as the overall correct classification rate minus one at the optimal cut-off point, is another popular index. For continuous biomarkers of binary disease status, although researchers mainly evaluate the diagnostic accuracy using AUC, for the purpose of making diagnosis, Youden index provides an important and direct measure of the diagnostic accuracy at the optimal threshold and hence should be taken into consideration in addition to AUC. Furthermore, AUC and Youden index are generally correlated. In this paper, we initiate the idea of evaluating diagnostic accuracy based on AUC and Youden index simultaneously. As the first step toward this direction, this paper only focuses on the confidence region estimation of AUC and Youden index for a single marker. We present both parametric and non-parametric approaches for estimating joint confidence region of AUC and Youden index. We carry out extensive simulation study to evaluate the performance of the proposed methods. In the end, we apply the proposed methods to a real data set. Copyright © 2013 John Wiley & Sons, Ltd.

Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features.

PubMed

Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara

2017-01-01

In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.

SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods.

PubMed

Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald

2007-05-01

(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal FWERs. Those rejected clusters were outlying values in the distribution of cluster size but cannot be distinguished from true positive findings without further analyses, including assessing whether fMRI signal in those regions correlates with other clinical, behavioral, or cognitive measures. Rejecting the large clusters, however, significantly reduced the statistical power of nonparametric methods in detecting true findings compared with parametric methods, which would have detected most true findings that are essential for making valid biological inferences in MRI data. Parametric analyses, in contrast, detected most true findings while generating relatively few false positives: on average, less than one of those very large clusters would be deemed a true finding in each brain-wide analysis. We therefore recommend the continued use of parametric methods that model nonstationary smoothness for cluster-level, familywise control of false positives, particularly when using a Cluster Defining Threshold of 2.5 or higher, and subsequently assessing rigorously the biological plausibility of the findings, even for large clusters. Finally, because nonparametric methods yielded a large reduction in statistical power to detect true positive findings, we conclude that the modest reduction in false positive findings that nonparametric analyses afford does not warrant a re-analysis of previously published fMRI studies using nonparametric techniques. Copyright © 2018 Elsevier Inc. All rights reserved.

Formation of parametric images using mixed-effects models: a feasibility study.

PubMed

Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh

2016-03-01

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

What can music tell us about social interaction?

PubMed

D'Ausilio, Alessandro; Novembre, Giacomo; Fadiga, Luciano; Keller, Peter E

2015-03-01

Humans are innately social creatures, but cognitive neuroscience, that has traditionally focused on individual brains, is only now beginning to investigate social cognition through realistic interpersonal interaction. Music provides an ideal domain for doing so because it offers a promising solution for balancing the trade-off between ecological validity and experimental control when testing cognitive and brain functions. Musical ensembles constitute a microcosm that provides a platform for parametrically modeling the complexity of human social interaction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Brain activation and connectivity of social cognition using diffuse optical imaging

NASA Astrophysics Data System (ADS)

Zhu, Banghe; Godavarty, Anuradha

2009-02-01

In the current research, diffuse optical imaging (DOI) is used for the first time towards studies related to sociocommunication impairments, which is a characteristic feature of autism. DOI studies were performed on normal adult volunteers to determine the differences in the brain activation (cognitive regions) in terms of the changes in the cerebral blood oxygenation levels in response to joint and non-joint attention based stimulus (i.e. socio-communicative paradigms shown as video clips). Functional connectivity models are employed to assess the extent of synchronization between the left and right pre-frontal regions of the brain in response to the above stimuli.

Brain responses to facial attractiveness induced by facial proportions: evidence from an fMRI study

PubMed Central

Shen, Hui; Chau, Desmond K. P.; Su, Jianpo; Zeng, Ling-Li; Jiang, Weixiong; He, Jufang; Fan, Jintu; Hu, Dewen

2016-01-01

Brain responses to facial attractiveness induced by facial proportions are investigated by using functional magnetic resonance imaging (fMRI), in 41 young adults (22 males and 19 females). The subjects underwent fMRI while they were presented with computer-generated, yet realistic face images, which had varying facial proportions, but the same neutral facial expression, baldhead and skin tone, as stimuli. Statistical parametric mapping with parametric modulation was used to explore the brain regions with the response modulated by facial attractiveness ratings (ARs). The results showed significant linear effects of the ARs in the caudate nucleus and the orbitofrontal cortex for all of the subjects, and a non-linear response profile in the right amygdala for only the male subjects. Furthermore, canonical correlation analysis was used to learn the most relevant facial ratios that were best correlated with facial attractiveness. A regression model on the fMRI-derived facial ratio components demonstrated a strong linear relationship between the visually assessed mean ARs and the predictive ARs. Overall, this study provided, for the first time, direct neurophysiologic evidence of the effects of facial ratios on facial attractiveness and suggested that there are notable gender differences in perceiving facial attractiveness as induced by facial proportions. PMID:27779211

Brain responses to facial attractiveness induced by facial proportions: evidence from an fMRI study.

PubMed

Shen, Hui; Chau, Desmond K P; Su, Jianpo; Zeng, Ling-Li; Jiang, Weixiong; He, Jufang; Fan, Jintu; Hu, Dewen

2016-10-25

Brain responses to facial attractiveness induced by facial proportions are investigated by using functional magnetic resonance imaging (fMRI), in 41 young adults (22 males and 19 females). The subjects underwent fMRI while they were presented with computer-generated, yet realistic face images, which had varying facial proportions, but the same neutral facial expression, baldhead and skin tone, as stimuli. Statistical parametric mapping with parametric modulation was used to explore the brain regions with the response modulated by facial attractiveness ratings (ARs). The results showed significant linear effects of the ARs in the caudate nucleus and the orbitofrontal cortex for all of the subjects, and a non-linear response profile in the right amygdala for only the male subjects. Furthermore, canonical correlation analysis was used to learn the most relevant facial ratios that were best correlated with facial attractiveness. A regression model on the fMRI-derived facial ratio components demonstrated a strong linear relationship between the visually assessed mean ARs and the predictive ARs. Overall, this study provided, for the first time, direct neurophysiologic evidence of the effects of facial ratios on facial attractiveness and suggested that there are notable gender differences in perceiving facial attractiveness as induced by facial proportions.

Modulation of brain activity by multiple lexical and word form variables in visual word recognition: A parametric fMRI study.

PubMed

Hauk, Olaf; Davis, Matthew H; Pulvermüller, Friedemann

2008-09-01

Psycholinguistic research has documented a range of variables that influence visual word recognition performance. Many of these variables are highly intercorrelated. Most previous studies have used factorial designs, which do not exploit the full range of values available for continuous variables, and are prone to skewed stimulus selection as well as to effects of the baseline (e.g. when contrasting words with pseudowords). In our study, we used a parametric approach to study the effects of several psycholinguistic variables on brain activation. We focussed on the variable word frequency, which has been used in numerous previous behavioural, electrophysiological and neuroimaging studies, in order to investigate the neuronal network underlying visual word processing. Furthermore, we investigated the variable orthographic typicality as well as a combined variable for word length and orthographic neighbourhood size (N), for which neuroimaging results are still either scarce or inconsistent. Data were analysed using multiple linear regression analysis of event-related fMRI data acquired from 21 subjects in a silent reading paradigm. The frequency variable correlated negatively with activation in left fusiform gyrus, bilateral inferior frontal gyri and bilateral insulae, indicating that word frequency can affect multiple aspects of word processing. N correlated positively with brain activity in left and right middle temporal gyri as well as right inferior frontal gyrus. Thus, our analysis revealed multiple distinct brain areas involved in visual word processing within one data set.

Quantum illumination with Gaussian states.

PubMed

Tan, Si-Hui; Erkmen, Baris I; Giovannetti, Vittorio; Guha, Saikat; Lloyd, Seth; Maccone, Lorenzo; Pirandola, Stefano; Shapiro, Jeffrey H

2008-12-19

An optical transmitter irradiates a target region containing a bright thermal-noise bath in which a low-reflectivity object might be embedded. The light received from this region is used to decide whether the object is present or absent. The performance achieved using a coherent-state transmitter is compared with that of a quantum-illumination transmitter, i.e., one that employs the signal beam obtained from spontaneous parametric down-conversion. By making the optimum joint measurement on the light received from the target region together with the retained spontaneous parametric down-conversion idler beam, the quantum-illumination system realizes a 6 dB advantage in the error-probability exponent over the optimum reception coherent-state system. This advantage accrues despite there being no entanglement between the light collected from the target region and the retained idler beam.

Intra- and inter-brain synchronization during musical improvisation on the guitar.

PubMed

Müller, Viktor; Sänger, Johanna; Lindenberger, Ulman

2013-01-01

Humans interact with the environment through sensory and motor acts. Some of these interactions require synchronization among two or more individuals. Multiple-trial designs, which we have used in past work to study interbrain synchronization in the course of joint action, constrain the range of observable interactions. To overcome the limitations of multiple-trial designs, we conducted single-trial analyses of electroencephalography (EEG) signals recorded from eight pairs of guitarists engaged in musical improvisation. We identified hyper-brain networks based on a complex interplay of different frequencies. The intra-brain connections primarily involved higher frequencies (e.g., beta), whereas inter-brain connections primarily operated at lower frequencies (e.g., delta and theta). The topology of hyper-brain networks was frequency-dependent, with a tendency to become more regular at higher frequencies. We also found hyper-brain modules that included nodes (i.e., EEG electrodes) from both brains. Some of the observed network properties were related to musical roles during improvisation. Our findings replicate and extend earlier work and point to mechanisms that enable individuals to engage in temporally coordinated joint action.

Intra- and Inter-Brain Synchronization during Musical Improvisation on the Guitar

PubMed Central

Müller, Viktor; Sänger, Johanna; Lindenberger, Ulman

2013-01-01

Humans interact with the environment through sensory and motor acts. Some of these interactions require synchronization among two or more individuals. Multiple-trial designs, which we have used in past work to study interbrain synchronization in the course of joint action, constrain the range of observable interactions. To overcome the limitations of multiple-trial designs, we conducted single-trial analyses of electroencephalography (EEG) signals recorded from eight pairs of guitarists engaged in musical improvisation. We identified hyper-brain networks based on a complex interplay of different frequencies. The intra-brain connections primarily involved higher frequencies (e.g., beta), whereas inter-brain connections primarily operated at lower frequencies (e.g., delta and theta). The topology of hyper-brain networks was frequency-dependent, with a tendency to become more regular at higher frequencies. We also found hyper-brain modules that included nodes (i.e., EEG electrodes) from both brains. Some of the observed network properties were related to musical roles during improvisation. Our findings replicate and extend earlier work and point to mechanisms that enable individuals to engage in temporally coordinated joint action. PMID:24040094

Experimental determination of frequency response function estimates for flexible joint industrial manipulators with serial kinematics

NASA Astrophysics Data System (ADS)

Saupe, Florian; Knoblach, Andreas

2015-02-01

Two different approaches for the determination of frequency response functions (FRFs) are used for the non-parametric closed loop identification of a flexible joint industrial manipulator with serial kinematics. The two applied experiment designs are based on low power multisine and high power chirp excitations. The main challenge is to eliminate disturbances of the FRF estimates caused by the numerous nonlinearities of the robot. For the experiment design based on chirp excitations, a simple iterative procedure is proposed which allows exploiting the good crest factor of chirp signals in a closed loop setup. An interesting synergy of the two approaches, beyond validation purposes, is pointed out.

Rapid Parametric Mapping of the Longitudinal Relaxation Time T1 Using Two-Dimensional Variable Flip Angle Magnetic Resonance Imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla

PubMed Central

Dieringer, Matthias A.; Deimling, Michael; Santoro, Davide; Wuerfel, Jens; Madai, Vince I.; Sobesky, Jan; von Knobelsdorff-Brenkenhoff, Florian; Schulz-Menger, Jeanette; Niendorf, Thoralf

2014-01-01

Introduction Visual but subjective reading of longitudinal relaxation time (T1) weighted magnetic resonance images is commonly used for the detection of brain pathologies. For this non-quantitative measure, diagnostic quality depends on hardware configuration, imaging parameters, radio frequency transmission field (B1+) uniformity, as well as observer experience. Parametric quantification of the tissue T1 relaxation parameter offsets the propensity for these effects, but is typically time consuming. For this reason, this study examines the feasibility of rapid 2D T1 quantification using a variable flip angles (VFA) approach at magnetic field strengths of 1.5 Tesla, 3 Tesla, and 7 Tesla. These efforts include validation in phantom experiments and application for brain T1 mapping. Methods T1 quantification included simulations of the Bloch equations to correct for slice profile imperfections, and a correction for B1+. Fast gradient echo acquisitions were conducted using three adjusted flip angles for the proposed T1 quantification approach that was benchmarked against slice profile uncorrected 2D VFA and an inversion-recovery spin-echo based reference method. Brain T1 mapping was performed in six healthy subjects, one multiple sclerosis patient, and one stroke patient. Results Phantom experiments showed a mean T1 estimation error of (-63±1.5)% for slice profile uncorrected 2D VFA and (0.2±1.4)% for the proposed approach compared to the reference method. Scan time for single slice T1 mapping including B1+ mapping could be reduced to 5 seconds using an in-plane resolution of (2×2) mm2, which equals a scan time reduction of more than 99% compared to the reference method. Conclusion Our results demonstrate that rapid 2D T1 quantification using a variable flip angle approach is feasible at 1.5T/3T/7T. It represents a valuable alternative for rapid T1 mapping due to the gain in speed versus conventional approaches. This progress may serve to enhance the capabilities of parametric MR based lesion detection and brain tissue characterization. PMID:24621588

Rapid parametric mapping of the longitudinal relaxation time T1 using two-dimensional variable flip angle magnetic resonance imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla.

PubMed

Dieringer, Matthias A; Deimling, Michael; Santoro, Davide; Wuerfel, Jens; Madai, Vince I; Sobesky, Jan; von Knobelsdorff-Brenkenhoff, Florian; Schulz-Menger, Jeanette; Niendorf, Thoralf

2014-01-01

Visual but subjective reading of longitudinal relaxation time (T1) weighted magnetic resonance images is commonly used for the detection of brain pathologies. For this non-quantitative measure, diagnostic quality depends on hardware configuration, imaging parameters, radio frequency transmission field (B1+) uniformity, as well as observer experience. Parametric quantification of the tissue T1 relaxation parameter offsets the propensity for these effects, but is typically time consuming. For this reason, this study examines the feasibility of rapid 2D T1 quantification using a variable flip angles (VFA) approach at magnetic field strengths of 1.5 Tesla, 3 Tesla, and 7 Tesla. These efforts include validation in phantom experiments and application for brain T1 mapping. T1 quantification included simulations of the Bloch equations to correct for slice profile imperfections, and a correction for B1+. Fast gradient echo acquisitions were conducted using three adjusted flip angles for the proposed T1 quantification approach that was benchmarked against slice profile uncorrected 2D VFA and an inversion-recovery spin-echo based reference method. Brain T1 mapping was performed in six healthy subjects, one multiple sclerosis patient, and one stroke patient. Phantom experiments showed a mean T1 estimation error of (-63±1.5)% for slice profile uncorrected 2D VFA and (0.2±1.4)% for the proposed approach compared to the reference method. Scan time for single slice T1 mapping including B1+ mapping could be reduced to 5 seconds using an in-plane resolution of (2×2) mm2, which equals a scan time reduction of more than 99% compared to the reference method. Our results demonstrate that rapid 2D T1 quantification using a variable flip angle approach is feasible at 1.5T/3T/7T. It represents a valuable alternative for rapid T1 mapping due to the gain in speed versus conventional approaches. This progress may serve to enhance the capabilities of parametric MR based lesion detection and brain tissue characterization.

The contribution of quasi-joint stiffness of the ankle joint to gait in patients with hemiparesis.

PubMed

Sekiguchi, Yusuke; Muraki, Takayuki; Kuramatsu, Yuko; Furusawa, Yoshihito; Izumi, Shin-Ichi

2012-06-01

The role of ankle joint stiffness during gait in patients with hemiparesis has not been clarified. The purpose of this study was to determine the contribution of quasi-joint stiffness of the ankle joint to spatiotemporal and kinetic parameters regarding gait in patients with hemiparesis due to brain tumor or stroke and healthy individuals. Spatiotemporal and kinetic parameters regarding gait in twelve patients with hemiparesis due to brain tumor or stroke and nine healthy individuals were measured with a 3-dimensional motion analysis system. Quasi-joint stiffness was calculated from the slope of the linear regression of the moment-angle curve of the ankle joint during the second rocker. There was no significant difference in quasi-joint stiffness among both sides of patients and the right side of controls. Quasi-joint stiffness on the paretic side of patients with hemiparesis positively correlated with maximal ankle power (r=0.73, P<0.01) and gait speed (r=0.66, P<0.05). In contrast, quasi-joint stiffness in controls negatively correlated with maximal ankle power (r=-0.73, P<0.05) and gait speed (r=-0.76, P<0.05). Our findings suggested that ankle power during gait might be generated by increasing quasi-joint stiffness in patients with hemiparesis. In contrast, healthy individuals might decrease quasi-joint stiffness to avoid deceleration of forward tilt of the tibia. Our findings might be useful for selecting treatment for increased ankle stiffness due to contracture and spasticity in patients with hemiparesis. Copyright © 2011 Elsevier Ltd. All rights reserved.

Statistical parametric mapping for analyzing interictal magnetoencephalography in patients with left frontal lobe epilepsy.

PubMed

Zhu, Haitao; Zhu, Jinlong; Bao, Forrest Sheng; Liu, Hongyi; Zhu, Xuchuang; Wu, Ting; Yang, Lu; Zou, Yuanjie; Zhang, Rui; Zheng, Gang

2016-01-01

Frontal lobe epilepsy is a common epileptic disorder and is characterized by recurring seizures that arise in the frontal lobes. The purpose of this study is to identify the epileptogenic regions and other abnormal regions in patients with left frontal lobe epilepsy (LFLE) based on the magnetoencephalogram (MEG), and to understand the effects of clinical variables on brain activities in patients with LFLE. Fifteen patients with LFLE (23.20 ± 8.68 years, 6 female and 9 male) and 16 healthy controls (23.13 ± 7.66 years, 6 female and 10 male) were included in resting-stage MEG examinations. Epileptogenic regions of LFLE patients were confirmed by surgery. Regional brain activations were quantified using statistical parametric mapping (SPM). The correlation between the activations of the abnormal brain regions and the clinical seizure parameters were computed for LFLE patients. Brain activations of LFLE patients were significantly elevated in left superior/middle/inferior frontal gyri, postcentral gyrus, inferior temporal gyrus, insula, parahippocampal gyrus and amygdala, including the epileptogenic regions. Remarkable decreased activations were found mainly in the left parietal gyrus and precuneus. There is a positive correlation between the duration of the epilepsy (in month) and activations of the abnormal regions, while no relation was found between age of seizure onset (year), seizure frequency and the regions of the abnormal activity of the epileptic patients. Our findings suggest that the aberrant brain activities of LFLE patients were not restricted to the epileptogenic zones. Long duration of epilepsy might induce further functional damage in patients with LFLE. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Age- and sex-associated changes in cerebral glucose metabolism in normal healthy subjects: statistical parametric mapping analysis of F-18 fluorodeoxyglucose brain positron emission tomography.

PubMed

Kim, In-Ju; Kim, Seong-Jang; Kim, Yong-Ki

2009-12-01

The age- and sex-associated changes of brain development are unclear and controversial. Several previous studies showed conflicting results of a specific pattern of cerebral glucose metabolism or no differences of cerebral glucose metabolism in association with normal aging process and sex. To investigate the effects of age and sex on changes in cerebral glucose metabolism in healthy subjects using fluorine-18 fluorodeoxyglucose (F-18 FDG) brain positron emission tomography (PET) and statistical parametric mapping (SPM) analysis. Seventy-eight healthy subjects (32 males, mean age 46.6+/-18.2 years; 46 females, mean age 40.6+/-19.8 years) underwent F-18 FDG brain PET. Using SPM, age- and sex-associated changes in cerebral glucose metabolism were investigated. In males, a negative correlation existed in several gray matter areas, including the right temporopolar (Brodmann area [BA] 38), right orbitofrontal (BA 47), left orbitofrontal gyrus (BA 10), left dorsolateral frontal gyrus (BA 8), and left insula (BA 13) areas. A positive relationship existed in the left claustrum and left thalamus. In females, negative changes existed in the left caudate body, left temporopolar area (BA 38), right orbitofrontal gyri (BA 47 and BA 10), and right dorsolateral prefrontal cortex (BA 46). A positive association was demonstrated in the left subthalamic nucleus and the left superior frontal gyrus. In white matter, an age-associated decrease in FDG uptake in males was shown in the left insula, and increased FDG uptake was found in the left corpus callosum. The female group had an age-associated negative correlation of FDG uptake only in the right corpus callosum. Using SPM, we found not only similar areas of brain, but also sex-specific cerebral areas of age-associated changes of FDG uptake.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Spatial hydrological drought characteristics in Karkheh River basin, southwest Iran using copulas

NASA Astrophysics Data System (ADS)

Dodangeh, Esmaeel; Shahedi, Kaka; Shiau, Jenq-Tzong; MirAkbari, Maryam

2017-08-01

Investigation on drought characteristics such as severity, duration, and frequency is crucial for water resources planning and management in a river basin. While the methodology for multivariate drought frequency analysis is well established by applying the copulas, the estimation on the associated parameters by various parameter estimation methods and the effects on the obtained results have not yet been investigated. This research aims at conducting a comparative analysis between the maximum likelihood parametric and non-parametric method of the Kendall τ estimation method for copulas parameter estimation. The methods were employed to study joint severity-duration probability and recurrence intervals in Karkheh River basin (southwest Iran) which is facing severe water-deficit problems. Daily streamflow data at three hydrological gauging stations (Tang Sazbon, Huleilan and Polchehr) near the Karkheh dam were used to draw flow duration curves (FDC) of these three stations. The Q_{75} index extracted from the FDC were set as threshold level to abstract drought characteristics such as drought duration and severity on the basis of the run theory. Drought duration and severity were separately modeled using the univariate probabilistic distributions and gamma-GEV, LN2-exponential, and LN2-gamma were selected as the best paired drought severity-duration inputs for copulas according to the Akaike Information Criteria (AIC), Kolmogorov-Smirnov and chi-square tests. Archimedean Clayton, Frank, and extreme value Gumbel copulas were employed to construct joint cumulative distribution functions (JCDF) of droughts for each station. Frank copula at Tang Sazbon and Gumbel at Huleilan and Polchehr stations were identified as the best copulas based on the performance evaluation criteria including AIC, BIC, log-likelihood and root mean square error (RMSE) values. Based on the RMSE values, nonparametric Kendall-τ is preferred to the parametric maximum likelihood estimation method. The results showed greater drought return periods by the parametric ML method in comparison to the nonparametric Kendall τ estimation method. The results also showed that stations located in tributaries (Huleilan and Polchehr) have close return periods, while the station along the main river (Tang Sazbon) has the smaller return periods for the drought events with identical drought duration and severity.

PR01 - The Effects of Total Sleep Deprivation and Recovery Sleep on Cognitive Performance and Brain Function

DTIC Science & Technology

2006-08-01

characterizing brain areas using fMRI activation during parametric variations of attentional load.Neuron, 2001, 32: 737–745. Doran, S . M., Van Dongen...four nouns. Three images collected at the begin- ning of each run were omitted form the analysis. The entire task lasted 300 s . Data Analysis fMRI data...The views, opinions and/or findings contained in this report are those of the author( s ) and should not be construed as an official Department of the

Three-photon states in nonlinear crystal superlattices

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

Antonosyan, D. A.; Kryuchkyan, G. Yu.; Institute for Physical Researches, National Academy of Sciences Ashtarak-2, 0203 Ashtarak

2011-04-15

It has been a longstanding goal in quantum optics to realize controllable sources generating joint multiphoton states, particularly photon triplet with arbitrary spectral characteristics. We demonstrate that such sources can be realized via cascaded parametric down-conversion (PDC) in superlattice structures of nonlinear and linear segments. We consider a scheme that involves two parametric processes--{omega}{sub 0{yields}{omega}1}+{omega}{sub 2}, {omega}{sub 2{yields}{omega}1}+{omega}{sub 1} under pulsed pump--and investigate the spontaneous creation of a photon triplet as well as the generation of high-intensity mode in intracavity three-photon splitting. We show the preparation of Greenberger-Horne-Zeilinger polarization-entangled states in cascaded type-II and type-I PDC in the framework ofmore » considering the dual-grid structure that involves two periodically poled crystals. We demonstrate the method of compensation of the dispersive effects in nonlinear segments by appropriately chosen linear dispersive segments of superlattice for preparation of the heralded joint states of two polarized photons. In the case of intracavity three-photon splitting, we concentrate on the investigation of photon-number distributions, third-order photon-number correlation function, as well as the Wigner functions. These quantities are observed both for short interaction time intervals and the over-transient regime, when dissipative effects are essential.« less

Parametric optimization in virtual prototyping environment of the control device for a robotic system used in thin layers deposition

NASA Astrophysics Data System (ADS)

Enescu (Balaş, M. L.; Alexandru, C.

2016-08-01

The paper deals with the optimal design of the control system for a 6-DOF robot used in thin layers deposition. The optimization is based on parametric technique, by modelling the design objective as a numerical function, and then establishing the optimal values of the design variables so that to minimize the objective function. The robotic system is a mechatronic product, which integrates the mechanical device and the controlled operating device.The mechanical device of the robot was designed in the CAD (Computer Aided Design) software CATIA, the 3D-model being then transferred to the MBS (Multi-Body Systems) environment ADAMS/View. The control system was developed in the concurrent engineering concept, through the integration with the MBS mechanical model, by using the DFC (Design for Control) software solution EASY5. The necessary angular motions in the six joints of the robot, in order to obtain the imposed trajectory of the end-effector, have been established by performing the inverse kinematic analysis. The positioning error in each joint of the robot is used as design objective, the optimization goal being to minimize the root mean square during simulation, which is a measure of the magnitude of the positioning error varying quantity.

Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction.

PubMed

Soleimani, Hossein; Hensman, James; Saria, Suchi

2017-08-21

Missing data and noisy observations pose significant challenges for reliably predicting events from irregularly sampled multivariate time series (longitudinal) data. Imputation methods, which are typically used for completing the data prior to event prediction, lack a principled mechanism to account for the uncertainty due to missingness. Alternatively, state-of-the-art joint modeling techniques can be used for jointly modeling the longitudinal and event data and compute event probabilities conditioned on the longitudinal observations. These approaches, however, make strong parametric assumptions and do not easily scale to multivariate signals with many observations. Our proposed approach consists of several key innovations. First, we develop a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the proposed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, we derive an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model. The derived policy trades-off the cost of a delayed detection versus incorrect assessments and abstains from making decisions when the estimated event probability does not satisfy the derived confidence criteria. Experiments on a large dataset show that the proposed framework significantly outperforms state-of-the-art techniques in event prediction.

Analytical and Experimental Assessment of Seismic Vulnerability of Beam-Column Joints without Transverse Reinforcement in Concrete Buildings

NASA Astrophysics Data System (ADS)

Hassan, Wael Mohammed

Beam-column joints in concrete buildings are key components to ensure structural integrity of building performance under seismic loading. Earthquake reconnaissance has reported the substantial damage that can result from inadequate beam-column joints. In some cases, failure of older-type corner joints appears to have led to building collapse. Since the 1960s, many advances have been made to improve seismic performance of building components, including beam-column joints. New design and detailing approaches are expected to produce new construction that will perform satisfactorily during strong earthquake shaking. Much less attention has been focused on beam-column joints of older construction that may be seismically vulnerable. Concrete buildings constructed prior to developing details for ductility in the 1970s normally lack joint transverse reinforcement. The available literature concerning the performance of such joints is relatively limited, but concerns about performance exist. The current study aimed to improve understanding and assessment of seismic performance of unconfined exterior and corner beam-column joints in existing buildings. An extensive literature survey was performed, leading to development of a database of about a hundred tests. Study of the data enabled identification of the most important parameters and the effect of each parameter on the seismic performance. The available analytical models and guidelines for strength and deformability assessment of unconfined joints were surveyed and evaluated. In particular, The ASCE 41 existing building document proved to be substantially conservative in joint shear strength estimation. Upon identifying deficiencies in these models, two new joint shear strength models, a bond capacity model, and two axial capacity models designed and tailored specifically for unconfined beam-column joints were developed. The proposed models strongly correlated with previous test results. In the laboratory testing phase of the current study, four full-scale corner beam-column joint subassemblies, with slab included, were designed, built, instrumented, tested, and analyzed. The specimens were tested under unidirectional and bidirectional displacement-controlled quasi-static loading that incorporated varying axial loads that simulated overturning seismic moment effects. The axial loads varied between tension and high compression loads reaching about 50% of the column axial capacity. The test parameters were axial load level, loading history, joint aspect ratio, and beam reinforcement ratio. The test results proved that high axial load increases joint shear strength and decreases the deformability of joints failing in pure shear failure mode without beam yielding. On the contrary, high axial load did not affect the strength of joints failing in shear after significant beam yielding; however, it substantially increased their displacement ductility. Joint aspect ratio proved to be instrumental in deciding joint shear strength; that is the deeper the joint the lower the shear strength. Bidirectional loading reduced the apparent strength of the joint in the uniaxial principal axes. However, circular shear strength interaction is an appropriate approximation to predict the biaxial strength. The developed shear strength models predicted successfully the strength of test specimens. Based on the literature database investigation, the shear and axial capacity models developed and the test results of the current study, an analytical finite element component model based on a proposed joint shear stress-rotation backbone constitutive curve was developed to represent the behavior of unconfined beam-column joints in computer numerical simulations of concrete frame buildings. The proposed finite element model included the effect of axial load, mode of joint failure, joint aspect ratio and axial capacity of joint. The proposed backbone curve along with the developed joint element exhibited high accuracy in simulating the test response of the current test specimens as well as previous test joints. Finally, a parametric study was conducted to assess the axial failure vulnerability of unconfined beam-column joints based on the developed shear and axial capacity models. This parametric study compared the axial failure potential of unconfined beam-column joint with that of shear critical columns to provide a preliminary insight into the axial collapse vulnerability of older-type buildings during intense ground shaking.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Visual analytics of brain networks.

PubMed

Li, Kaiming; Guo, Lei; Faraco, Carlos; Zhu, Dajiang; Chen, Hanbo; Yuan, Yixuan; Lv, Jinglei; Deng, Fan; Jiang, Xi; Zhang, Tuo; Hu, Xintao; Zhang, Degang; Miller, L Stephen; Liu, Tianming

2012-05-15

Identification of regions of interest (ROIs) is a fundamental issue in brain network construction and analysis. Recent studies demonstrate that multimodal neuroimaging approaches and joint analysis strategies are crucial for accurate, reliable and individualized identification of brain ROIs. In this paper, we present a novel approach of visual analytics and its open-source software for ROI definition and brain network construction. By combining neuroscience knowledge and computational intelligence capabilities, visual analytics can generate accurate, reliable and individualized ROIs for brain networks via joint modeling of multimodal neuroimaging data and an intuitive and real-time visual analytics interface. Furthermore, it can be used as a functional ROI optimization and prediction solution when fMRI data is unavailable or inadequate. We have applied this approach to an operation span working memory fMRI/DTI dataset, a schizophrenia DTI/resting state fMRI (R-fMRI) dataset, and a mild cognitive impairment DTI/R-fMRI dataset, in order to demonstrate the effectiveness of visual analytics. Our experimental results are encouraging. Copyright © 2012 Elsevier Inc. All rights reserved.

Analytical Time-Domain Solution of Plane Wave Propagation Across a Viscoelastic Rock Joint

NASA Astrophysics Data System (ADS)

Zou, Yang; Li, Jianchun; Laloui, Lyesse; Zhao, Jian

2017-10-01

The effects of viscoelastic filled rock joints on wave propagation are of great significance in rock engineering. The solutions in time domain for plane longitudinal ( P-) and transverse ( S-) waves propagation across a viscoelastic rock joint are derived based on Maxwell and Kelvin models which are, respectively, applied to describe the viscoelastic deformational behaviour of the rock joint and incorporated into the displacement discontinuity model (DDM). The proposed solutions are verified by comparing with the previous studies on harmonic waves, which are simulated by sinusoidal incident P- and S-waves. Comparison between the predicted transmitted waves and the experimental data for P-wave propagation across a joint filled with clay is conducted. The Maxwell is found to be more appropriate to describe the filled joint. The parametric studies show that wave propagation is affected by many factors, such as the stiffness and the viscosity of joints, the incident angle and the duration of incident waves. Furthermore, the dependences of the transmission and reflection coefficients on the specific joint stiffness and viscosity are different for the joints with Maxwell and Kelvin behaviours. The alternation of the reflected and transmitted waveforms is discussed, and the application scope of this study is demonstrated by an illustration of the effects of the joint thickness. The solutions are also extended for multiple parallel joints with the virtual wave source method and the time-domain recursive method. For an incident wave with arbitrary waveform, it is convenient to adopt the present approach to directly calculate wave propagation across a viscoelastic rock joint without additional mathematical methods such as the Fourier and inverse Fourier transforms.

Chromium content in the human hip joint tissues.

PubMed

Brodziak-Dopierała, Barbara; Kwapuliński, Jerzy; Sobczyk, Krzysztof; Wiechuła, Danuta

2015-02-01

Chromium has many important functions in the human body. For the osseous tissue, its role has not been clearly defined. This study was aimed at determining chromium content in hip joint tissues. A total of 91 hip joint samples were taken in this study, including 66 from females and 25 from males. The sample tissues were separated according to their anatomical parts. The chromium content was determined by the AAS method. The statistical analysis was performed with U Mann-Whitney's non-parametric test, P≤0.05. The overall chromium content in tissues of the hip joint in the study subjects was as follows: 5.73 µg/g in the articular cartilage, 5.33 µg/g in the cortical bone, 17.86 µg/g in the cancellous bone, 5.95 µg/g in the fragment of the cancellous bone from the intertrochanteric region, and 1.28 µg/g in the joint capsule. The chromium contents were observed in 2 group patients, it was 7.04 µg/g in people with osteoarthritis and 12.59 µg/g in people with fractures. The observed chromium content was highest in the cancellous bone and the lowest in the joint capsule. Chromium content was significantly different between the people with hip joint osteoarthritis and the people with femoral neck fractures. Copyright © 2015 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

Shape of wear particles found in human knee joints and their relationship to osteoarthritis.

PubMed

Kuster, M S; Podsiadlo, P; Stachowiak, G W

1998-09-01

To analyse and compare the shape of wear particles found in healthy and osteoarthritic human knee joints for monitoring the progress of osteoarthritis, the long-term prognosis and to evaluate therapeutic regimens. Joint particles from seven patients with normal cartilage in all compartments of the knee joint, 12 patients with fibrillation of less than half the cartilage thickness (grade 1), seven patients with fibrillation of more than half the cartilage thickness (grade 2) and four patients with erosions down to bone (grade 3) were analysed. A total of 565 particles were extracted from synovial fluid samples by ferrography and analysed in a scanning electron microscope. A number of numerical descriptors, i.e. boundary fractal dimension, shape factor, convexity and elongation, were calculated for each particle image and correlated to the degree of osteoarthritis using non-parametric tests. Experiments demonstrated that there were significant differences between the numerical descriptors calculated for wear particles from healthy and osteoarthritic knee joints (P < 0.01), suggesting that the particle shape can be used as an indicator of the joint condition. In particular, the fractal dimension of the particle boundary was shown to correlate directly with the degree of osteoarthritis. Numerical analysis of the shape of wear particles found in human knee joints may provide a reliable means for the assessment of cartilage repair after surgical or conservative treatment of osteoarthritis.

Characterization of the Spatial Structure of Local Functional Connectivity Using Multidistance Average Correlation Measures.

PubMed

Macià, Dídac; Pujol, Jesus; Blanco-Hinojo, Laura; Martínez-Vilavella, Gerard; Martín-Santos, Rocío; Deus, Joan

2018-06-01

There is ample evidence from basic research in neuroscience of the importance of local corticocortical networks. Millimetric resolution is achievable with current functional magnetic resonance imaging (fMRI) scanners and sequences, and consequently a number of "local" activity similarity measures have been defined to describe patterns of segregation and integration at this spatial scale. We have introduced the use of IsoDistant Average Correlation (IDAC), easily defined as the average fMRI temporal correlation of a given voxel with other voxels placed at increasingly separated isodistant intervals, to characterize the curve of local fMRI signal similarities. IDAC curves can be statistically compared using parametric multivariate statistics. Furthermore, by using red-green-blue color coding to display jointly IDAC values belonging to three different distance lags, IDAC curves can also be displayed as multidistance IDAC maps. We applied IDAC analysis to a sample of 41 subjects scanned under two different conditions, a resting state and an auditory-visual continuous stimulation. Multidistance IDAC mapping was able to discriminate between gross anatomofunctional cortical areas and, moreover, was sensitive to modulation between the two brain conditions in areas known to activate and deactivate during audiovisual tasks. Unlike previous fMRI local similarity measures already in use, our approach draws special attention to the continuous smooth pattern of local functional connectivity.

Joint Bayesian Component Separation and CMB Power Spectrum Estimation

NASA Technical Reports Server (NTRS)

Eriksen, H. K.; Jewell, J. B.; Dickinson, C.; Banday, A. J.; Gorski, K. M.; Lawrence, C. R.

2008-01-01

We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are (1) conditional sampling of foreground spectral parameters and (2) joint sampling of all amplitude-type degrees of freedom (e.g., CMB, foreground pixel amplitudes, and global template amplitudes) given spectral parameters. Given a parametric model of the foreground signals, we estimate efficiently and accurately the exact joint foreground- CMB posterior distribution and, therefore, all marginal distributions such as the CMB power spectrum or foreground spectral index posteriors. The main limitation of the current implementation is the requirement of identical beam responses at all frequencies, which restricts the analysis to the lowest resolution of a given experiment. We outline a future generalization to multiresolution observations. To verify the method, we analyze simple models and compare the results to analytical predictions. We then analyze a realistic simulation with properties similar to the 3 yr WMAP data, downgraded to a common resolution of 3 deg FWHM. The results from the actual 3 yr WMAP temperature analysis are presented in a companion Letter.

Parametric Study of Single Bolted Composite Bolted Joint Subjected to Static Tensile Loading

NASA Astrophysics Data System (ADS)

Awadhani, L. V.; Bewoor, Anand, Dr.

2017-08-01

The use of composites is increasing in the engineering applications in order to reduce the weight, building energy efficient systems, designing a suitable material according to the requirements of the application. But at the same time, building a structure is possible only by bonding or bolting or combination of them. There are limitations for the bonding methods and problems with the bolting such as stress concentration near the neighborhood of the bolt hole, tensile or shear failure, delamination etc. Hence the design of a composite bolted structure needs a special attention. This paper focuses on the performance of the composite bolted joint under static tensile loading and the effect of variation in the parameters such as the bolt pitch, plate width, thickness, bolt tightening torque, composite material, coefficient of friction between the bolt and plate etc. A simple spring mass model is used to study the single bolted composite bolted joint. The influencing parameters are identified through the developed model and compared with the results from the literature. The best geometric parameters for the applied load are identified for the composite bolted joints.

Lasting impact of regret and gratification on resting brain activity and its relation to depressive traits.

PubMed

Eryilmaz, Hamdi; Van De Ville, Dimitri; Schwartz, Sophie; Vuilleumier, Patrik

2014-06-04

Obtaining lower gains than rejected alternatives during decision making evokes feelings of regret, whereas higher gains elicit gratification. Although decision-related emotions produce lingering effects on mental state, neuroscience research has generally focused on transient brain responses to positive or negative events, but ignored more sustained consequences of emotional episodes on subsequent brain states. We investigated how spontaneous brain activity and functional connectivity at rest are modulated by postdecision regret and gratification in 18 healthy human subjects using a gambling task in fMRI. Differences between obtained and unobtained outcomes were manipulated parametrically to evoke different levels of regret or gratification. We investigated how individual personality traits related to depression and rumination affected these responses. Medial and ventral prefrontal areas differentially responded to favorable and unfavorable outcomes during the gambling period. More critically, during subsequent rest, rostral anterior and posterior cingulate cortex, ventral striatum, and insula showed parametric response to the gratification level of preceding outcomes. Functional coupling of posterior cingulate with striatum and amygdala was also enhanced during rest after high gratification. Regret produced distinct changes in connectivity of subgenual cingulate with orbitofrontal cortex and thalamus. Interestingly, individual differences in depressive traits and ruminations correlated with activity of the striatum after gratification and orbitofrontal cortex after regret, respectively. By revealing lingering effects of decision-related emotions on key nodes of resting state networks, our findings illuminate how such emotions may influence self-reflective processing and subsequent behavioral adjustment, but also highlight the malleability of resting networks in emotional contexts. Copyright © 2014 the authors 0270-6474/14/347825-11$15.00/0.

Gender differences in cerebral metabolism for color processing in mice: A PET/MRI Study.

PubMed

Njemanze, Philip C; Kranz, Mathias; Amend, Mario; Hauser, Jens; Wehrl, Hans; Brust, Peter

2017-01-01

Color processing is a central component of mammalian vision. Gender-related differences of color processing revealed by non-invasive functional transcranial Doppler ultrasound suggested right hemisphere pattern for blue/yellow chromatic opponency by men, and a left hemisphere pattern by women. The present study measured the accumulation of [18F]fluorodeoxyglucose ([18F]FDG) in mouse brain using small animal positron emission tomography and magnetic resonance imaging (PET/MRI) with statistical parametric mapping (SPM) during light stimulation with blue and yellow filters compared to darkness condition. PET revealed a reverse pattern relative to dark condition compared to previous human studies: Male mice presented with left visual cortex dominance for blue through the right eye, while female mice presented with right visual cortex dominance for blue through the left eye. We applied statistical parametric mapping (SPM) to examine gender differences in activated architectonic areas within the orbital and medial prefrontal cortex and related cortical and sub-cortical areas that lead to the striatum, medial thalamus and other brain areas. The metabolic connectivity of the orbital and medial prefrontal cortex evoked by blue stimulation spread through a wide range of brain structures implicated in viscerosensory and visceromotor systems in the left intra-hemispheric regions in male, but in the right-to-left inter-hemispheric regions in female mice. Color functional ocular dominance plasticity was noted in the right eye in male mice but in the left eye in female mice. This study of color processing in an animal model could be applied in the study of the role of gender differences in brain disease.

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.

PubMed

Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P; Frank, Lawrence R

2018-04-13

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Imaging decision about whether to benefit self by harming others: Adolescents with conduct and substance problems, with or without callous-unemotionality, or developing typically.

PubMed

Sakai, Joseph T; Dalwani, Manish S; Mikulich-Gilbertson, Susan K; Raymond, Kristen; McWilliams, Shannon; Tanabe, Jody; Rojas, Don; Regner, Michael; Banich, Marie T; Crowley, Thomas J

2017-05-30

We sought to identify brain activation differences in conduct-problem youth with limited prosocial emotions (LPE) compared to conduct-problem youth without LPE and community adolescents, and to test associations between brain activation and severity of callous-unemotional traits. We utilized a novel task, which asks subjects to repeatedly decide whether to accept offers where they will benefit but a beneficent other will be harmed. Behavior on this task has been previously associated with levels of prosocial emotions and severity of callous-unemotional traits, and is related to empathic concern. During fMRI acquisition, 66 male adolescents (21 conduct-problem patients with LPE, 21 without, and 24 typically-developing controls) played this novel game. Within typically-developing controls, we identified a network engaged during decision involving bilateral insula, and inferior parietal and medial frontal cortices, among other regions. Group comparisons using non-parametric (distribution-free) permutation tests demonstrated LPE patients had lower activation estimates than typically-developing adolescents in right anterior insula. Additional significant group differences emerged with our a priori parametric cluster-wise inference threshold. These results suggest measurable functional brain activation differences in conduct-problem adolescents with LPE compared to typically-developing adolescents. Such differences may underscore differential treatment needs for conduct-problem males with and without LPE. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Statistical parametric mapping of stimuli-evoked changes in quantitative blood flow using extended-focus optical coherence microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Marchand, Paul J.; Bouwens, Arno; Shamaei, Vincent; Nguyen, David; Extermann, Jerome; Bolmont, Tristan; Lasser, Theo

2016-03-01

Magnetic Resonance Imaging has revolutionised our understanding of brain function through its ability to image human cerebral structures non-invasively over the entire brain. By exploiting the different magnetic properties of oxygenated and deoxygenated blood, functional MRI can indirectly map areas undergoing neural activation. Alongside the development of fMRI, powerful statistical tools have been developed in an effort to shed light on the neural pathways involved in processing of sensory and cognitive information. In spite of the major improvements made in fMRI technology, the obtained spatial resolution of hundreds of microns prevents MRI in resolving and monitoring processes occurring at the cellular level. In this regard, Optical Coherence Microscopy is an ideal instrumentation as it can image at high spatio-temporal resolution. Moreover, by measuring the mean and the width of the Doppler spectra of light scattered by moving particles, OCM allows extracting the axial and lateral velocity components of red blood cells. The ability to assess quantitatively total blood velocity, as opposed to classical axial velocity Doppler OCM, is of paramount importance in brain imaging as a large proportion of cortical vascular is oriented perpendicularly to the optical axis. We combine here quantitative blood flow imaging with extended-focus Optical Coherence Microscopy and Statistical Parametric Mapping tools to generate maps of stimuli-evoked cortical hemodynamics at the capillary level.

Multisite EPR oximetry from multiple quadrature harmonics.

PubMed

Ahmad, R; Som, S; Johnson, D H; Zweier, J L; Kuppusamy, P; Potter, L C

2012-01-01

Multisite continuous wave (CW) electron paramagnetic resonance (EPR) oximetry using multiple quadrature field modulation harmonics is presented. First, a recently developed digital receiver is used to extract multiple harmonics of field modulated projection data. Second, a forward model is presented that relates the projection data to unknown parameters, including linewidth at each site. Third, a maximum likelihood estimator of unknown parameters is reported using an iterative algorithm capable of jointly processing multiple quadrature harmonics. The data modeling and processing are applicable for parametric lineshapes under nonsaturating conditions. Joint processing of multiple harmonics leads to 2-3-fold acceleration of EPR data acquisition. For demonstration in two spatial dimensions, both simulations and phantom studies on an L-band system are reported. Copyright © 2011 Elsevier Inc. All rights reserved.

Dynamic stability analysis of torsional vibrations of a shaft system connected by a Hooke's joint through a continuous system model

NASA Astrophysics Data System (ADS)

Bulut, Gökhan

2014-08-01

Stability of parametrically excited torsional vibrations of a shaft system composed of two torsionally elastic shafts interconnected through a Hooke's joint is studied. The shafts are considered to be continuous (distributed-parameter) systems and an approximate discrete model for the torsional vibrations of the shaft system is derived via a finite element scheme. The stability of the solutions of the linearized equations of motion, consisting of a set of Mathieu-Hill type equations, is examined by means of a monodromy matrix method and the results are presented in the form of a Strutt-Ince diagram visualizing the effects of the system parameters on the stability of the shaft system.

Cryogenic Impinging Jets Subjected to High Frequency Transverse Acoustic Forcing in a High Pressure Environment

DTIC Science & Technology

2016-07-27

Transverse Acoustic Forcing in a High Pressure Environment 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Mario ...Acoustic Forcing in a High Pressure Environment Mario Roa, Sierra Lobo, Inc. Alex Schumaker, AFRL Doug Talley, AFRL 24-27 July 2016 Joint Propulsion...Distribution A: Approved for Public Release; Distribution Unlimited. PA# 16333 9 Parametric Sweep Super -Critical Results Differences between

Initialization by measurement of a superconducting quantum bit circuit.

PubMed

Ristè, D; van Leeuwen, J G; Ku, H-S; Lehnert, K W; DiCarlo, L

2012-08-03

We demonstrate initialization by joint measurement of two transmon qubits in 3D circuit quantum electrodynamics. Homodyne detection of cavity transmission is enhanced by Josephson parametric amplification to discriminate the two-qubit ground state from single-qubit excitations nondestructively and with 98.1% fidelity. Measurement and postselection of a steady-state mixture with 4.7% residual excitation per qubit achieve 98.8% fidelity to the ground state, thus outperforming passive initialization.

Training communication partners of people with severe traumatic brain injury improves everyday conversations: a multicenter single blind clinical trial.

PubMed

Togher, Leanne; McDonald, Skye; Tate, Robyn; Power, Emma; Rietdijk, Rachael

2013-07-01

To determine effectiveness of communication training for partners of people with severe traumatic brain injury. Three arm non-randomized controlled trial comparing communication partner training (JOINT) with individual treatment (TBI SOLO) and a waitlist control group with 6 month follow-up. Forty-four outpatients with severe chronic traumatic brain injuries were recruited. Ten-week conversational skills treatment program encompassing weekly group and individual sessions for both treatment groups. The JOINT condition focused on both the partner and the person with traumatic brain injury while the TBI SOLO condition focused on the individual with TBI only. Primary outcomes were blind ratings of the person with traumatic brain injury's level of participation during conversation on the Measure of Participation in Communication Adapted Kagan scales. Communication partner training improved conversational performance relative to training the person with traumatic brain injury alone and a waitlist control group on the primary outcome measures. Results were maintained at six months post-training. Training communication partners of people with chronic severe traumatic brain injury was more efficacious than training the person with traumatic brain injury alone. The Adapted Kagan scales proved to be a robust and sensitive outcome measure for a conversational skills training program.

An fMRI study of joint action–varying levels of cooperation correlates with activity in control networks

PubMed Central

Chaminade, Thierry; Marchant, Jennifer L.; Kilner, James; Frith, Christopher D.

2012-01-01

As social agents, humans continually interact with the people around them. Here, motor cooperation was investigated using a paradigm in which pairs of participants, one being scanned with fMRI, jointly controlled a visually presented object with joystick movements. The object oscillated dynamically along two dimensions, color and width of gratings, corresponding to the two cardinal directions of joystick movements. While the overall control of each participant on the object was kept constant, the amount of cooperation along the two dimensions varied along four levels, from no (each participant controlled one dimension exclusively) to full (each participant controlled half of each dimension) cooperation. Increasing cooperation correlated with BOLD signal in the left parietal operculum and anterior cingulate cortex (ACC), while decreasing cooperation correlated with activity in the right inferior frontal and superior temporal gyri, the intraparietal sulci and inferior temporal gyri bilaterally, and the dorsomedial prefrontal cortex. As joint performance improved with the level of cooperation, we assessed the brain responses correlating with behavior, and found that activity in most of the areas associated with levels of cooperation also correlated with the joint performance. The only brain area found exclusively in the negative correlation with cooperation was in the dorso medial frontal cortex, involved in monitoring action outcome. Given the cluster location and condition-related signal change, we propose that this region monitored actions to extract the level of cooperation in order to optimize the joint response. Our results, therefore, indicate that, in the current experimental paradigm involving joint control of a visually presented object with joystick movements, the level of cooperation affected brain networks involved in action control, but not mentalizing. PMID:22715326

Scalable Joint Segmentation and Registration Framework for Infant Brain Images.

PubMed

Dong, Pei; Wang, Li; Lin, Weili; Shen, Dinggang; Wu, Guorong

2017-03-15

The first year of life is the most dynamic and perhaps the most critical phase of postnatal brain development. The ability to accurately measure structure changes is critical in early brain development study, which highly relies on the performances of image segmentation and registration techniques. However, either infant image segmentation or registration, if deployed independently, encounters much more challenges than segmentation/registration of adult brains due to dynamic appearance change with rapid brain development. In fact, image segmentation and registration of infant images can assists each other to overcome the above challenges by using the growth trajectories (i.e., temporal correspondences) learned from a large set of training subjects with complete longitudinal data. Specifically, a one-year-old image with ground-truth tissue segmentation can be first set as the reference domain. Then, to register the infant image of a new subject at earlier age, we can estimate its tissue probability maps, i.e., with sparse patch-based multi-atlas label fusion technique, where only the training images at the respective age are considered as atlases since they have similar image appearance. Next, these probability maps can be fused as a good initialization to guide the level set segmentation. Thus, image registration between the new infant image and the reference image is free of difficulty of appearance changes, by establishing correspondences upon the reasonably segmented images. Importantly, the segmentation of new infant image can be further enhanced by propagating the much more reliable label fusion heuristics at the reference domain to the corresponding location of the new infant image via the learned growth trajectories, which brings image segmentation and registration to assist each other. It is worth noting that our joint segmentation and registration framework is also flexible to handle the registration of any two infant images even with significant age gap in the first year of life, by linking their joint segmentation and registration through the reference domain. Thus, our proposed joint segmentation and registration method is scalable to various registration tasks in early brain development studies. Promising segmentation and registration results have been achieved for infant brain MR images aged from 2-week-old to 1-year-old, indicating the applicability of our method in early brain development study.

Joint representation of consistent structural and functional profiles for identification of common cortical landmarks.

PubMed

Zhang, Shu; Zhao, Yu; Jiang, Xi; Shen, Dinggang; Liu, Tianming

2018-06-01

In the brain mapping field, there have been significant interests in representation of structural/functional profiles to establish structural/functional landmark correspondences across individuals and populations. For example, from the structural perspective, our previous studies have identified hundreds of consistent DICCCOL (dense individualized and common connectivity-based cortical landmarks) landmarks across individuals and populations, each of which possess consistent DTI-derived fiber connection patterns. From the functional perspective, a large collection of well-characterized HAFNI (holistic atlases of functional networks and interactions) networks based on sparse representation of whole-brain fMRI signals have been identified in our prior studies. However, due to the remarkable variability of structural and functional architectures in the human brain, it is challenging for earlier studies to jointly represent the connectome-scale structural and functional profiles for establishing a common cortical architecture which can comprehensively encode both structural and functional characteristics across individuals. To address this challenge, we propose an effective computational framework to jointly represent the structural and functional profiles for identification of consistent and common cortical landmarks with both structural and functional correspondences across different brains based on DTI and fMRI data. Experimental results demonstrate that 55 structurally and functionally common cortical landmarks can be successfully identified.

Photon Entanglement Through Brain Tissue.

PubMed

Shi, Lingyan; Galvez, Enrique J; Alfano, Robert R

2016-12-20

Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness.

Photon Entanglement Through Brain Tissue

NASA Astrophysics Data System (ADS)

Shi, Lingyan; Galvez, Enrique J.; Alfano, Robert R.

2016-12-01

Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness.

Parametric Modulation of Error-Related ERP Components by the Magnitude of Visuo-Motor Mismatch

ERIC Educational Resources Information Center

Vocat, Roland; Pourtois, Gilles; Vuilleumier, Patrik

2011-01-01

Errors generate typical brain responses, characterized by two successive event-related potentials (ERP) following incorrect action: the error-related negativity (ERN) and the positivity error (Pe). However, it is unclear whether these error-related responses are sensitive to the magnitude of the error, or instead show all-or-none effects. We…

Non-intrusive reduced order modeling of nonlinear problems using neural networks

NASA Astrophysics Data System (ADS)

Hesthaven, J. S.; Ubbiali, S.

2018-06-01

We develop a non-intrusive reduced basis (RB) method for parametrized steady-state partial differential equations (PDEs). The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and employs artificial neural networks (ANNs), particularly multi-layer perceptrons (MLPs), to accurately approximate the coefficients of the reduced model. The search for the optimal number of neurons and the minimum amount of training samples to avoid overfitting is carried out in the offline phase through an automatic routine, relying upon a joint use of the Latin hypercube sampling (LHS) and the Levenberg-Marquardt (LM) training algorithm. This guarantees a complete offline-online decoupling, leading to an efficient RB method - referred to as POD-NN - suitable also for general nonlinear problems with a non-affine parametric dependence. Numerical studies are presented for the nonlinear Poisson equation and for driven cavity viscous flows, modeled through the steady incompressible Navier-Stokes equations. Both physical and geometrical parametrizations are considered. Several results confirm the accuracy of the POD-NN method and show the substantial speed-up enabled at the online stage as compared to a traditional RB strategy.

Joint Pairing and Structured Mapping of Convolutional Brain Morphological Multiplexes for Early Dementia Diagnosis.

PubMed

Lisowska, Anna; Rekik, Islem

2018-06-21

Diagnosis of brain dementia, particularly early mild cognitive impairment (eMCI), is critical for early intervention to prevent the onset of Alzheimer's Disease (AD), where cognitive decline is severe and irreversible. There is a large body of machine-learning based research investigating how dementia alters brain connectivity, mainly using structural (derived from diffusion MRI) and functional (derived from resting-state functional MRI) brain connectomic data. However, how early dementia affects cortical brain connections in morphology remains largely unexplored. To fill this gap, we propose a joint morphological brain multiplexes pairing and mapping strategy for early MCI detection, where a brain multiplex not only encodes the similarity in morphology between pairs of brain regions, but also a pair of brain morphological networks. Experimental results confirm that the proposed framework outperforms in classification accuracy several state-of-the-art methods. More importantly, we unprecedentedly identified most discriminative brain morphological networks between eMCI and NC, which included the paired views derived from maximum principal curvature and the sulcal depth for the left hemisphere and sulcal depth and the average curvature for the right hemisphere. We also identified the most highly correlated morphological brain connections in our cohort, which included the (pericalcarine cortex, insula cortex) on the maximum principal curvature view, (entorhinal cortex, insula cortex) on the mean sulcal depth view, and (entorhinal cortex, pericalcarine cortex) on the mean average curvature view, for both hemispheres. These highly correlated morphological connections might serve as biomarkers for early MCI diagnosis.

Effect of MRI Acoustic Noise on Cerebral FDG Uptake in Simultaneous MR-PET Imaging

PubMed Central

Abolmaali, Nasreddin; Arabasz, Grae; Guimaraes, Alexander R.; Catana, Ciprian

2013-01-01

Integrated scanners capable of simultaneous PET and MRI data acquisition are now available for human use. Although the scanners’ manufacturers have made substantial efforts to understand and minimize the mutual electromagnetic interference between the two modalities, the potential physiological inference has not been evaluated. In this work, we have studied the influence of the acoustic noise produced by the MR gradients on brain FDG uptake in the Siemens MR-BrainPET prototype. While particular attention was paid to the primary auditory cortex (PAC), a brain-wide analysis was also performed. Methods The effects of the MR on the PET count rate and image quantification were first investigated in phantoms. Next, ten healthy volunteers underwent two simultaneous FDG-PET/MR scans in the supine position with the FDG injection occurring inside the MR-BrainPET, alternating between a “quiet” (control) environment in which no MR sequences were run during the FDG uptake phase (the first 40 minutes after radiotracer administration) and a “noisy” (test) case in which MR sequences were run for the entire time. Cortical and subcortical regions of interest (ROIs) were derived from the high-resolution morphological MR data using FreeSurfer. The changes in FDG uptake in the FreeSurfer-derived ROIs between the two conditions were analyzed from parametric and static PET images, and on a voxel-by-voxel basis using SPM8 and FreeSurfer. Results Only minimal to no electromagnetic interference was observed for most of the MR sequences tested, with a maximum drop in count rate of 1.5% and a maximum change in the measured activity of 1.1% in the corresponding images. The ROI-based analysis showed statistically significant increases in the right PAC in both the parametric (9.13±4.73%) and static (4.18±2.87%) images. SPM8 analysis showed no statistically significant clusters in any images when a p<0.05 (corrected) was used; however, a p<0.001 (uncorrected) resolved bilateral statistically significant clusters of increased FDG uptake in the area of the PAC for the parametric image (left: 8.37±1.55%, right: 8.20±1.17%), but only unilateral increase in the static image (left: 8.68±3.89%). Conclusion Although the operation of the BrainPET prototype is virtually unaffected by the MR scanner, the acoustic noise produced by the MR gradients causes a focal increase in FDG uptake in the PAC, which could affect the interpretation of pathological (or brain-activation related) changes in FDG uptake in this region, if the expected effects are of comparable amplitude. PMID:23462677

Effect of MRI acoustic noise on cerebral fludeoxyglucose uptake in simultaneous MR-PET imaging.

PubMed

Chonde, Daniel B; Abolmaali, Nasreddin; Arabasz, Grae; Guimaraes, Alexander R; Catana, Ciprian

2013-05-01

Integrated scanners capable of simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) data acquisition are now available for human use. Although the scanners' manufacturers have made substantial efforts to understand and minimize the mutual electromagnetic interference between the 2 modalities, the potential physiological inference has not been evaluated. In this study, we have studied the influence of the acoustic noise produced by the magnetic resonance (MR) gradients on brain fludeoxyglucose (FDG) uptake in the Siemens MR-BrainPET prototype. Although particular attention was paid to the primary auditory cortex (PAC), a brain-wide analysis was also performed. The effects of the MR on the PET count rate and image quantification were first investigated in phantoms. Next, 10 healthy volunteers underwent 2 simultaneous FDG-PET/MR scans in the supine position with the FDG injection occurring inside the MR-BrainPET, alternating between a "quiet" (control) environment in which no MR sequences were run during the FDG uptake phase (the first 40 minutes after radiotracer administration) and a "noisy" (test) environment in which MR sequences were run for the entire time. Cortical and subcortical regions of interest were derived from the high-resolution morphological MR data using FreeSurfer. The changes in the FDG uptake in the FreeSurfer-derived regions of interest between the 2 conditions were analyzed from parametric and static PET images, and on a voxel-by-voxel basis using SPM8 and FreeSurfer. Only minimal to no electromagnetic interference was observed for most of the MR sequences tested, with a maximum drop in count rate of 1.5% and a maximum change in the measured activity of 1.1% in the corresponding images. The region of interest-based analysis showed statistically significant increases in the right PAC in both the parametric (9.13% [4.73%]) and static (4.18% [2.87%]) images. The SPM8 analysis showed no statistically significant clusters in any images when a P < 0.05 (corrected) was used; however, a P < 0.001 (uncorrected) resolved bilateral statistically significant clusters of increased FDG uptake in the area of the PAC for the parametric image (left, 8.37% [1.55%]; right, 8.20% [1.17%]) but only unilateral increase in the static image (left, 8.68% [3.89%]). Although the operation of the BrainPET prototype is virtually unaffected by the MR scanner, the acoustic noise produced by the MR gradients causes a focal increase in the FDG uptake in the PAC, which could affect the interpretation of pathological (or brain-activation-related) changes in the FDG uptake in this region if the expected effects are of comparable amplitude.

Joint probabilities and quantum cognition

NASA Astrophysics Data System (ADS)

de Barros, J. Acacio

2012-12-01

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Parametrically coupled fermionic oscillators: Correlation functions and phase-space description

NASA Astrophysics Data System (ADS)

Ghosh, Arnab

2015-01-01

A fermionic analog of a parametric amplifier is used to describe the joint quantum state of the two interacting fermionic modes. Based on a two-mode generalization of the time-dependent density operator, time evolution of the fermionic density operator is determined in terms of its two-mode Wigner and P function. It is shown that the equation of motion of the Wigner function corresponds to a fermionic analog of Liouville's equation. The equilibrium density operator for fermionic fields developed by Cahill and Glauber is thus extended to a dynamical context to show that the mathematical structures of both the correlation functions and the weight factors closely resemble their bosonic counterpart. It has been shown that the fermionic correlation functions are marked by a characteristic upper bound due to Fermi statistics, which can be verified in the matter wave counterpart of photon down-conversion experiments.

Quantum teleportation in the spin-orbit variables of photon pairs

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

Khoury, A. Z.; Milman, P.; Laboratoire Materiaux et Phenomenes Quantiques, CNRS UMR 7162, Universite Paris Diderot, F-75013, Paris

2011-06-15

We propose a polarization to orbital angular momentum teleportation scheme using entangled photon pairs generated by spontaneous parametric down-conversion. By making a joint detection of the polarization and angular momentum parity of a single photon, we are able to detect all the Bell states and perform, in principle, perfect teleportation from a discrete to a continuous system using minimal resources. The proposed protocol implementation demands experimental resources that are currently available in quantum optics laboratories.

Parametric weight evaluation of joined wings by structural optimization

NASA Technical Reports Server (NTRS)

Miura, Hirokazu; Shyu, Albert T.; Wolkovitch, Julian

1988-01-01

Joined-wing aircraft employ tandem wings having positive and negative sweep and dihedral, arranged to form diamond shapes in both plan and front views. An optimization method was applied to study the effects of joined-wing geometry parameters on structural weight. The lightest wings were obtained by increasing dihedral and taper ratio, decreasing sweep and span, increasing fraction of airfoil chord occupied by structural box, and locating the joint inboard of the front wing tip.

A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity

PubMed Central

Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837

Joint spectral characterization of photon-pair sources

NASA Astrophysics Data System (ADS)

Zielnicki, Kevin; Garay-Palmett, Karina; Cruz-Delgado, Daniel; Cruz-Ramirez, Hector; O'Boyle, Michael F.; Fang, Bin; Lorenz, Virginia O.; U'Ren, Alfred B.; Kwiat, Paul G.

2018-06-01

The ability to determine the joint spectral properties of photon pairs produced by the processes of spontaneous parametric downconversion (SPDC) and spontaneous four-wave mixing (SFWM) is crucial for guaranteeing the usability of heralded single photons and polarization-entangled pairs for multi-photon protocols. In this paper, we compare six different techniques that yield either a characterization of the joint spectral intensity or of the closely related purity of heralded single photons. These six techniques include: (i) scanning monochromator measurements, (ii) a variant of Fourier transform spectroscopy designed to extract the desired information exploiting a resource-optimized technique, (iii) dispersive fibre spectroscopy, (iv) stimulated-emission-based measurement, (v) measurement of the second-order correlation function ? for one of the two photons, and (vi) two-source Hong-Ou-Mandel interferometry. We discuss the relative performance of these techniques for the specific cases of a SPDC source designed to be factorable and SFWM sources of varying purity, and compare the techniques' relative advantages and disadvantages.

Trajectory planning of free-floating space robot using Particle Swarm Optimization (PSO)

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Walter, Ulrich

2015-07-01

This paper investigates the application of Particle Swarm Optimization (PSO) strategy to trajectory planning of the kinematically redundant space robot in free-floating mode. Due to the path dependent dynamic singularities, the volume of available workspace of the space robot is limited and enormous joint velocities are required when such singularities are met. In order to overcome this effect, the direct kinematics equations in conjunction with PSO are employed for trajectory planning of free-floating space robot. The joint trajectories are parametrized with the Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for trajectory planning of 7 degree-of-freedom (DOF) redundant manipulator mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

Multi-state modelling of repeated hospitalisation and death in patients with heart failure: The use of large administrative databases in clinical epidemiology.

PubMed

Ieva, Francesca; Jackson, Christopher H; Sharples, Linda D

2017-06-01

In chronic diseases like heart failure (HF), the disease course and associated clinical event histories for the patient population vary widely. To improve understanding of the prognosis of patients and enable health care providers to assess and manage resources, we wish to jointly model disease progression, mortality and their relation with patient characteristics. We show how episodes of hospitalisation for disease-related events, obtained from administrative data, can be used as a surrogate for disease status. We propose flexible multi-state models for serial hospital admissions and death in HF patients, that are able to accommodate important features of disease progression, such as multiple ordered events and competing risks. Fully parametric and semi-parametric semi-Markov models are implemented using freely available software in R. The models were applied to a dataset from the administrative data bank of the Lombardia region in Northern Italy, which included 15,298 patients who had a first hospitalisation ending in 2006 and 4 years of follow-up thereafter. This provided estimates of the associations of age and gender with rates of hospital admission and length of stay in hospital, and estimates of the expected total time spent in hospital over five years. For example, older patients and men were readmitted more frequently, though the total time in hospital was roughly constant with age. We also discuss the relative merits of parametric and semi-parametric multi-state models, and model assessment and comparison.

Atypical brain activation patterns during a face-to-face joint attention game in adults with autism spectrum disorder.

PubMed

Redcay, Elizabeth; Dodell-Feder, David; Mavros, Penelope L; Kleiner, Mario; Pearrow, Mark J; Triantafyllou, Christina; Gabrieli, John D; Saxe, Rebecca

2013-10-01

Joint attention behaviors include initiating one's own and responding to another's bid for joint attention to an object, person, or topic. Joint attention abilities in autism are pervasively atypical, correlate with development of language and social abilities, and discriminate children with autism from other developmental disorders. Despite the importance of these behaviors, the neural correlates of joint attention in individuals with autism remain unclear. This paucity of data is likely due to the inherent challenge of acquiring data during a real-time social interaction. We used a novel experimental set-up in which participants engaged with an experimenter in an interactive face-to-face joint attention game during fMRI data acquisition. Both initiating and responding to joint attention behaviors were examined as well as a solo attention (SA) control condition. Participants included adults with autism spectrum disorder (ASD) (n = 13), a mean age- and sex-matched neurotypical group (n = 14), and a separate group of neurotypical adults (n = 22). Significant differences were found between groups within social-cognitive brain regions, including dorsal medial prefrontal cortex (dMPFC) and right posterior superior temporal sulcus (pSTS), during the RJA as compared to SA conditions. Region-of-interest analyses revealed a lack of signal differentiation between joint attention and control conditions within left pSTS and dMPFC in individuals with ASD. Within the pSTS, this lack of differentiation was characterized by reduced activation during joint attention and relative hyper-activation during SA. These findings suggest a possible failure of developmental neural specialization within the STS and dMPFC to joint attention in ASD. Copyright © 2012 Wiley Periodicals, Inc.

A randomised controlled trial of intra-articular corticosteroid injection of the carpometacarpal joint of the thumb in osteoarthritis

PubMed Central

Meenagh, G; Patton, J; Kynes, C; Wright, G

2004-01-01

Objective: To investigate the efficacy of corticosteroid injections into the carpometacarpal joint of the thumb (CMCJ) in patients with osteoarthritis. Design: A double blind, randomised controlled trial using 40 hospital referred patients with CMCJ osteoarthritis who received intra-articular injections of 5 mg triamcinolone hexacetonide (0.25 ml) or sterile 0.9% saline (0.25 ml). Injections were given under imaging control. Main outcome measures: The primary outcome was improvement in a pain visual analogue score (VAS) of 20% at 24 weeks. In addition patients were assessed at 4, 12, and 24 weeks for joint stiffness, joint tenderness, and physician and patient global assessments. Hand radiographs were evaluated for the degree of CMC joint space narrowing and marginal osteophytes according to the OARSI atlas. Results: Baseline clinical variables were not significantly different between the two treatment groups. There was no improvement in the VAS of pain at 24 weeks. At each assessment point there was no significant difference between the steroid and placebo groups in median values for joint stiffness, joint tenderness, or patient and physician global assessments. Non-parametric analysis of each group individually revealed statistically significant improvements in patient and physician global assessments at weeks 4, 12, and 24 in the placebo group and at weeks 4 and 12 in the steroid group. Conclusions: No clinical benefit was gained from intra-articular steroid injection to the CMCJ in moderate to severe osteoarthritis compared with placebo injection. PMID:15361383

An evaluation of the lap-shear test for Sn-rich solder/Cu couples: Experiments and simulation

NASA Astrophysics Data System (ADS)

Chawla, N.; Shen, Y.-L.; Deng, X.; Ege, E. S.

2004-12-01

The lap-shear technique is commonly used to evaluate the shear, creep, and thermal fatigue behavior of solder joints. We have conducted a parametric experimental and modeling study, on the effect of testing and geometrical parameters on solder/copper joint response in lap-shear. It was shown that the farfield applied strain is quite different from the actual solder strain (measured optically). Subtraction of the deformation of the Cu substrate provides a reasonable approximation of the solder strain in the elastic regime, but not in the plastic regime. Solder joint thickness has a profound effect on joint response. The solder response moves progressively closer to “true” shear response with increasing joint thickness. Numerical modeling using finite-element analyses were performed to rationalize the experimental findings. The same lap-shear configuration was used in the simulation. The input response for solder was based on the experimental tensile test result on bulk specimens. The calculated shear response, using both the commonly adopted far-field measure and the actual shear strain in solder, was found to be consistent with the trends observed in the lap-shear experiments. The geometric features were further explored to provide physical insight into the problem. Deformation of the substrate was found to greatly influence the shear behavior of the solder.

A neuro-inspired model-based closed-loop neuroprosthesis for the substitution of a cerebellar learning function in anesthetized rats

NASA Astrophysics Data System (ADS)

Hogri, Roni; Bamford, Simeon A.; Taub, Aryeh H.; Magal, Ari; Giudice, Paolo Del; Mintz, Matti

2015-02-01

Neuroprostheses could potentially recover functions lost due to neural damage. Typical neuroprostheses connect an intact brain with the external environment, thus replacing damaged sensory or motor pathways. Recently, closed-loop neuroprostheses, bidirectionally interfaced with the brain, have begun to emerge, offering an opportunity to substitute malfunctioning brain structures. In this proof-of-concept study, we demonstrate a neuro-inspired model-based approach to neuroprostheses. A VLSI chip was designed to implement essential cerebellar synaptic plasticity rules, and was interfaced with cerebellar input and output nuclei in real time, thus reproducing cerebellum-dependent learning in anesthetized rats. Such a model-based approach does not require prior system identification, allowing for de novo experience-based learning in the brain-chip hybrid, with potential clinical advantages and limitations when compared to existing parametric ``black box'' models.

Evaluating the features of the brain waves to quantify ADHD improvement by neurofeedback.

PubMed

Dehghanpour, Peyman; Einalou, Zahra

2017-10-23

Attention-deficit/hyperactivity disorder (ADHD), as one of the most common neurological disorders in children and adolescents, is characterized by decentralization, slow learning, distraction and hyperactivity. Studies have shown that in addition to medication, neurofeedback training can also be used to partially control the brain activity of these patients. In this study, using the brain signals processing before and after the treatment in 10 children treated by neurofeedback, the changes were evaluated by non-parametric statistical analysis and impact of neurofeedback on brain frequency bands was investigated. Finally, the results were compared with the protocols introduced in this paper and before researches. The results of Kruskal-Wallis test showed an approximately significant increase in the relative power of gamma and an approximately significant reduction in the ratio of relative power of alpha/beta. It represents the emotional response, elicited by the successful learning and diminished ratio of slow learning to active learning respectively.

A review of multivariate methods in brain imaging data fusion

NASA Astrophysics Data System (ADS)

Sui, Jing; Adali, Tülay; Li, Yi-Ou; Yang, Honghui; Calhoun, Vince D.

2010-03-01

On joint analysis of multi-task brain imaging data sets, a variety of multivariate methods have shown their strengths and been applied to achieve different purposes based on their respective assumptions. In this paper, we provide a comprehensive review on optimization assumptions of six data fusion models, including 1) four blind methods: joint independent component analysis (jICA), multimodal canonical correlation analysis (mCCA), CCA on blind source separation (sCCA) and partial least squares (PLS); 2) two semi-blind methods: parallel ICA and coefficient-constrained ICA (CC-ICA). We also propose a novel model for joint blind source separation (BSS) of two datasets using a combination of sCCA and jICA, i.e., 'CCA+ICA', which, compared with other joint BSS methods, can achieve higher decomposition accuracy as well as the correct automatic source link. Applications of the proposed model to real multitask fMRI data are compared to joint ICA and mCCA; CCA+ICA further shows its advantages in capturing both shared and distinct information, differentiating groups, and interpreting duration of illness in schizophrenia patients, hence promising applicability to a wide variety of medical imaging problems.

Effect of Experimental Thyrotoxicosis on Brain Gray Matter: A Voxel-Based Morphometry Study.

PubMed

Göbel, Anna; Heldmann, Marcus; Göttlich, Martin; Dirk, Anna-Luise; Brabant, Georg; Münte, Thomas F

2015-09-01

Hyper-as well hypothyroidism have an effect on behavior and brain function. Moreover, during development thyroid hormones influence brain structure. This study aimed to demonstrate an effect of experimentally induced hyperthyroidism on brain gray matter in healthy adult humans. High-resolution 3D T1-weighted images were acquired in 29 healthy young subjects prior to as well as after receiving 250 µg of T4 per day for 8 weeks. Voxel-based morphometry analysis was performed using Statistical Parametric Mapping 8 (SPM8). Laboratory testing confirmed the induction of hyperthyroidism. In the hyperthyroid condition, gray matter volumes were increased in the right posterior cerebellum (lobule VI) and decreased in the bilateral visual cortex and anterior cerebellum (lobules I-IV) compared to the euthyroid condition. Our study provides evidence that short periods of hyperthyroidism induce distinct alterations in brain structures of cerebellar regions that have been associated with sensorimotor functions as well as working memory in the literature.

Parametric Crowd Generation Software for MS&T Simulations and Training

DTIC Science & Technology

2007-02-20

3 Technology Overview 5 Dynemotion System Components 5 Dynemotion System Architecture 6 Dynemotion-Enabled NPC Brain Cycles 9 Dynemotion API...Contents 10 Development Project Background Information 11 Potential Application and Impact for the DoD 13 Project Objectives, Scope...Methodology 13 Benefits of the Project 13 Project Innovation 14 *l_essons Learned and Open Questions 14 Research and Development Challenges 16

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

PubMed

Sauwen, N; Acou, M; Van Cauter, S; Sima, D M; Veraart, J; Maes, F; Himmelreich, U; Achten, E; Van Huffel, S

2016-01-01

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

Ultrasound-aided Multi-parametric Photoacoustic Microscopy of the Mouse Brain.

PubMed

Ning, Bo; Sun, Naidi; Cao, Rui; Chen, Ruimin; Kirk Shung, K; Hossack, John A; Lee, Jin-Moo; Zhou, Qifa; Hu, Song

2015-12-21

High-resolution quantitative imaging of cerebral oxygen metabolism in mice is crucial for understanding brain functions and formulating new strategies to treat neurological disorders, but remains a challenge. Here, we report on our newly developed ultrasound-aided multi-parametric photoacoustic microscopy (PAM), which enables simultaneous quantification of the total concentration of hemoglobin (CHb), the oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF) at the microscopic level and through the intact mouse skull. The three-dimensional skull and vascular anatomies delineated by the dual-contrast (i.e., ultrasonic and photoacoustic) system provide important guidance for dynamically focused contour scan and vessel orientation-dependent correction of CBF, respectively. Moreover, bi-directional raster scan allows determining the direction of blood flow in individual vessels. Capable of imaging all three hemodynamic parameters at the same spatiotemporal scale, our ultrasound-aided PAM fills a critical gap in preclinical neuroimaging and lays the foundation for high-resolution mapping of the cerebral metabolic rate of oxygen (CMRO2)-a quantitative index of cerebral oxygen metabolism. This technical innovation is expected to shed new light on the mechanism and treatment of a broad spectrum of neurological disorders, including Alzheimer's disease and ischemic stroke.

Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor

NASA Astrophysics Data System (ADS)

Taverniers, Søren; Tartakovsky, Daniel M.

2017-11-01

Predictions of the total energy deposited into a brain tumor through X-ray irradiation are notoriously error-prone. We investigate how this predictive uncertainty is affected by uncertainty in both the location of the region occupied by a dose-enhancing iodinated contrast agent and the agent's concentration. This is done within the probabilistic framework in which these uncertain parameters are modeled as random variables. We employ the stochastic collocation (SC) method to estimate statistical moments of the deposited energy in terms of statistical moments of the random inputs, and the global sensitivity analysis (GSA) to quantify the relative importance of uncertainty in these parameters on the overall predictive uncertainty. A nonlinear radiation-diffusion equation dramatically magnifies the coefficient of variation of the uncertain parameters, yielding a large coefficient of variation for the predicted energy deposition. This demonstrates that accurate prediction of the energy deposition requires a proper treatment of even small parametric uncertainty. Our analysis also reveals that SC outperforms standard Monte Carlo, but its relative efficiency decreases as the number of uncertain parameters increases from one to three. A robust GSA ameliorates this problem by reducing this number.

Photon Entanglement Through Brain Tissue

PubMed Central

Shi, Lingyan; Galvez, Enrique J.; Alfano, Robert R.

2016-01-01

Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness. PMID:27995952

Middle School Students' Learning of the Impact of Methamphetamine Abuse on the Brain through Serious Game Play

ERIC Educational Resources Information Center

Cheng, Meng-Tzu

2009-01-01

In response to the solicitation of the National Institute on Drug Use (NIDA) (NIDA, 2006) for the "Development of a Virtual Reality Environment for Teaching about the Impact of Drug Abuse on the Brain," a virtual brain exhibit was developed by the joint venture of Entertainment Science, Inc. and Virtual Heroes, Inc.. This exhibit included a…

Joint eigenvector estimation from mutually anisotropic tensors improves susceptibility tensor imaging of the brain, kidney, and heart.

PubMed

Dibb, Russell; Liu, Chunlei

2017-06-01

To develop a susceptibility-based MRI technique for probing microstructure and fiber architecture of magnetically anisotropic tissues-such as central nervous system white matter, renal tubules, and myocardial fibers-in three dimensions using susceptibility tensor imaging (STI) tools. STI can probe tissue microstructure, but is limited by reconstruction artifacts because of absent phase information outside the tissue and noise. STI accuracy may be improved by estimating a joint eigenvector from mutually anisotropic susceptibility and relaxation tensors. Gradient-recalled echo image data were simulated using a numerical phantom and acquired from the ex vivo mouse brain, kidney, and heart. Susceptibility tensor data were reconstructed using STI, regularized STI, and the proposed algorithm of mutually anisotropic and joint eigenvector STI (MAJESTI). Fiber map and tractography results from each technique were compared with diffusion tensor data. MAJESTI reduced the estimated susceptibility tensor orientation error by 30% in the phantom, 36% in brain white matter, 40% in the inner medulla of the kidney, and 45% in myocardium. This improved the continuity and consistency of susceptibility-based fiber tractography in each tissue. MAJESTI estimation of the susceptibility tensors yields lower orientation errors for susceptibility-based fiber mapping and tractography in the intact brain, kidney, and heart. Magn Reson Med 77:2331-2346, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Decrease in fMRI brain activation during working memory performed after sleeping under 10 lux light.

PubMed

Kang, Seung-Gul; Yoon, Ho-Kyoung; Cho, Chul-Hyun; Kwon, Soonwook; Kang, June; Park, Young-Min; Lee, Eunil; Kim, Leen; Lee, Heon-Jeong

2016-11-09

The aim of this study was to investigate the effect of exposure to dim light at night (dLAN) when sleeping on functional brain activation during a working-memory tasks. We conducted the brain functional magnetic resonance imaging (fMRI) analysis on 20 healthy male subjects. All participants slept in a polysomnography laboratory without light exposure on the first and second nights and under a dim-light condition of either 5 or 10 lux on the third night. The fMRI scanning was conducted during n-back tasks after second and third nights. Statistical parametric maps revealed less activation in the right inferior frontal gyrus (IFG) after exposure to 10-lux light. The brain activity in the right and left IFG areas decreased more during the 2-back task than during the 1- or 0-back task in the 10-lux group. The exposure to 5-lux light had no significant effect on brain activities. The exposure to dLAN might influence the brain function which is related to the cognition.

Immediate effects of bilateral manipulation of talocrural joints on standing stability in healthy subjects.

PubMed

Alburquerque-Sendín, Francisco; Fernández-de-las-Peñas, César; Santos-del-Rey, Miguel; Martín-Vallejo, Francisco Javier

2009-02-01

The purpose of this study was to investigate the immediate effects of bilateral talocrural joint manipulation on standing stability in healthy subjects. Sixty-two healthy subjects, 16 males and 46 females, aged from 18 to 32 years old (mean: 21+/-3 years old) participated in the study. Subjects were randomly divided into two groups: an intervention group (n=32), who received manipulation of bilateral talocrural joints and a control group (n=30) which did not receive any intervention. Baropodometric and stabilometric evaluations were assessed pre- and 5 min post-intervention by an assessor blinded to the treatment allocation. Intra-group and inter-group comparisons were analysed using appropriate parametric tests. The results indicated that changes on the X coordinate range, length of motion, and mean speed approximated to statistical significance (P=0.06), and changes on the Y coordinate range reached statistical significance (P=0.02). Average X and Y motions, and anterior-posterior or lateral velocities did not show significant differences. Our results showed that bilateral thrust manipulation of the talocrural joint did not modify standing stability, that is, the behavioural pattern of the projection of the centre of pressure, in healthy subjects.

The Gaussian atmospheric transport model and its sensitivity to the joint frequency distribution and parametric variability.

PubMed

Hamby, D M

2002-01-01

Reconstructed meteorological data are often used in some form of long-term wind trajectory models for estimating the historical impacts of atmospheric emissions. Meteorological data for the straight-line Gaussian plume model are put into a joint frequency distribution, a three-dimensional array describing atmospheric wind direction, speed, and stability. Methods using the Gaussian model and joint frequency distribution inputs provide reasonable estimates of downwind concentration and have been shown to be accurate to within a factor of four. We have used multiple joint frequency distributions and probabilistic techniques to assess the Gaussian plume model and determine concentration-estimate uncertainty and model sensitivity. We examine the straight-line Gaussian model while calculating both sector-averaged and annual-averaged relative concentrations at various downwind distances. The sector-average concentration model was found to be most sensitive to wind speed, followed by horizontal dispersion (sigmaZ), the importance of which increases as stability increases. The Gaussian model is not sensitive to stack height uncertainty. Precision of the frequency data appears to be most important to meteorological inputs when calculations are made for near-field receptors, increasing as stack height increases.

Joint scale-change models for recurrent events and failure time.

PubMed

Xu, Gongjun; Chiou, Sy Han; Huang, Chiung-Yu; Wang, Mei-Cheng; Yan, Jun

2017-01-01

Recurrent event data arise frequently in various fields such as biomedical sciences, public health, engineering, and social sciences. In many instances, the observation of the recurrent event process can be stopped by the occurrence of a correlated failure event, such as treatment failure and death. In this article, we propose a joint scale-change model for the recurrent event process and the failure time, where a shared frailty variable is used to model the association between the two types of outcomes. In contrast to the popular Cox-type joint modeling approaches, the regression parameters in the proposed joint scale-change model have marginal interpretations. The proposed approach is robust in the sense that no parametric assumption is imposed on the distribution of the unobserved frailty and that we do not need the strong Poisson-type assumption for the recurrent event process. We establish consistency and asymptotic normality of the proposed semiparametric estimators under suitable regularity conditions. To estimate the corresponding variances of the estimators, we develop a computationally efficient resampling-based procedure. Simulation studies and an analysis of hospitalization data from the Danish Psychiatric Central Register illustrate the performance of the proposed method.

Shape-driven 3D segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2006-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details.

Rhythm in joint action: psychological and neurophysiological mechanisms for real-time interpersonal coordination

PubMed Central

Keller, Peter E.; Novembre, Giacomo; Hove, Michael J.

2014-01-01

Human interaction often requires simultaneous precision and flexibility in the coordination of rhythmic behaviour between individuals engaged in joint activity, for example, playing a musical duet or dancing with a partner. This review article addresses the psychological processes and brain mechanisms that enable such rhythmic interpersonal coordination. First, an overview is given of research on the cognitive-motor processes that enable individuals to represent joint action goals and to anticipate, attend and adapt to other's actions in real time. Second, the neurophysiological mechanisms that underpin rhythmic interpersonal coordination are sought in studies of sensorimotor and cognitive processes that play a role in the representation and integration of self- and other-related actions within and between individuals' brains. Finally, relationships between social–psychological factors and rhythmic interpersonal coordination are considered from two perspectives, one concerning how social-cognitive tendencies (e.g. empathy) affect coordination, and the other concerning how coordination affects interpersonal affiliation, trust and prosocial behaviour. Our review highlights musical ensemble performance as an ecologically valid yet readily controlled domain for investigating rhythm in joint action. PMID:25385772

Evaluation of drug effects on cerebral blood flow and glucose uptake in un-anesthetized and un-stimulated rats: application of free-moving apparatus enabling to keep rats free during PET/SPECT tracer injection and uptake.

PubMed

Sugita, Taku; Kondo, Yusuke; Ishino, Seigo; Mori, Ikuo; Horiguchi, Takashi; Ogawa, Mikako; Magata, Yasuhiro

2018-05-15

The purpose of this study is the development of novel fluorine-18-fluorodeoxyglucose (F-FDG)-PET and Tc-hexamethylpropylene amine oxime (HMPAO) SPECT methods with free-moving apparatus on conscious rats to investigate brain activity without the effects of anesthesia and tactual stimulation. We also assessed the sensitivity of the experimental system by an intervention study using fluoxetine as a reference drug. A catheter was inserted into the femoral vein and connected to a free-moving cannula system. After fluoxetine administration, the rats were given an injection of F-FDG or Tc-HMPAO via the intravenous cannula and released into a free-moving cage. After the tracer was trapped in the brain, the rats were anesthetized and scanned with PET or SPECT scanners. Then a volume of interest analysis and statistical parametric mapping were performed. We could inject the tracer without touching the rats, while keeping them conscious until the tracers were distributed and trapped in the brain using the developed system. The effects of fluoxetine on glucose uptake and cerebral blood flow were perceptively detected by volume of interest and statistical parametric mapping analysis. We successfully developed free-moving F-FDG-PET and Tc-HMPAO-SPECT imaging systems and detected detailed glucose uptake and cerebral blood flow changes in the conscious rat brain with fluoxetine administration. This system is expected to be useful to assess brain activity without the effects of anesthesia and tactual stimulation to evaluate drug effect or animal brain function.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.

Brain Research Focuses on New Assays, Drugs

ERIC Educational Resources Information Center

Chemical and Engineering News, 1977

1977-01-01

Those attending the CIC/ACS (Chemical Institute of Canada /American Chemical Society) joint conference at Montreal heard about recent advances in brain chemistry research, the use of compartmental models for predicting pollution, the presence of carcinogens (N-Nitrosamines) in sidestream tobacco smoke, and the synthesis of sex attractants using…

Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.

PubMed

Citak-Er, Fusun; Firat, Zeynep; Kovanlikaya, Ilhami; Ture, Ugur; Ozturk-Isik, Esin

2018-06-15

The objective of this study was to assess the contribution of multi-parametric (mp) magnetic resonance imaging (MRI) quantitative features in the machine learning-based grading of gliomas with a multi-region-of-interests approach. Forty-three patients who were newly diagnosed as having a glioma were included in this study. The patients were scanned prior to any therapy using a standard brain tumor magnetic resonance (MR) imaging protocol that included T1 and T2-weighted, diffusion-weighted, diffusion tensor, MR perfusion and MR spectroscopic imaging. Three different regions-of-interest were drawn for each subject to encompass tumor, immediate tumor periphery, and distant peritumoral edema/normal. The normalized mp-MRI features were used to build machine-learning models for differentiating low-grade gliomas (WHO grades I and II) from high grades (WHO grades III and IV). In order to assess the contribution of regional mp-MRI quantitative features to the classification models, a support vector machine-based recursive feature elimination method was applied prior to classification. A machine-learning model based on support vector machine algorithm with linear kernel achieved an accuracy of 93.0%, a specificity of 86.7%, and a sensitivity of 96.4% for the grading of gliomas using ten-fold cross validation based on the proposed subset of the mp-MRI features. In this study, machine-learning based on multiregional and multi-parametric MRI data has proven to be an important tool in grading glial tumors accurately even in this limited patient population. Future studies are needed to investigate the use of machine learning algorithms for brain tumor classification in a larger patient cohort. Copyright © 2018. Published by Elsevier Ltd.

Brain Functional Connectivity in Small Cell Lung Cancer Population after Chemotherapy Treatment: an ICA fMRI Study

NASA Astrophysics Data System (ADS)

Bromis, K.; Kakkos, I.; Gkiatis, K.; Karanasiou, I. S.; Matsopoulos, G. K.

2017-11-01

Previous neurocognitive assessments in Small Cell Lung Cancer (SCLC) population, highlight the presence of neurocognitive impairments (mainly in attention processing and executive functioning) in this type of cancer. The majority of these studies, associate these deficits with the Prophylactic Cranial Irradiation (PCI) that patients undergo in order to avoid brain metastasis. However, there is not much evidence exploring cognitive impairments induced by chemotherapy in SCLC patients. For this reason, we aimed to investigate the underlying processes that may potentially affect cognition by examining brain functional connectivity in nineteen SCLC patients after chemotherapy treatment, while additionally including fourteen healthy participants as control group. Independent Component Analysis (ICA) is a functional connectivity measure aiming to unravel the temporal correlation between brain regions, which are called brain networks. We focused on two brain networks related to the aforementioned cognitive functions, the Default Mode Network (DMN) and the Task-Positive Network (TPN). Permutation tests were performed between the two groups to assess the differences and control for familywise errors in the statistical parametric maps. ICA analysis showed functional connectivity disruptions within both of the investigated networks. These results, propose a detrimental effect of chemotherapy on brain functioning in the SCLC population.

Parametric manipulation of the conflict signal and control-state adaptation.

PubMed

Forster, Sarah E; Carter, Cameron S; Cohen, Jonathan D; Cho, Raymond Y

2011-04-01

Mechanisms by which the brain monitors and modulates performance are an important focus of recent research. The conflict-monitoring hypothesis posits that the ACC detects conflict between competing response pathways which, in turn, signals for enhanced control. The N2, an ERP component that has been localized to ACC, has been observed after high conflict stimuli. As a candidate index of the conflict signal, the N2 would be expected to be sensitive to the degree of response conflict present, a factor that depends on both the features of external stimuli and the internal control state. In the present study, we sought to explore the relationship between N2 amplitude and these variables through use of a modified Eriksen flankers task in which target-distracter compatibility was parametrically varied. We hypothesized that greater target-distracter incompatibility would result in higher levels of response conflict, as indexed by both behavior and the N2 component. Consistent with this prediction, there were parametric degradations in behavioral performance and increases in N2 amplitudes with increasing incompatibility. Further, increasingly incompatible stimuli led to the predicted parametric increases in control on subsequent incompatible trials as evidenced by enhanced performance and reduced N2 amplitudes. These findings suggest that the N2 component and associated behavioral performance are finely sensitive to the degree of response conflict present and to the control adjustments that result from modulations in conflict.

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis.

PubMed

Quintela-del-Río, Alejandro; Francisco-Fernández, Mario

2011-02-01

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

Implications of heterogeneous impacts of protected areas on deforestation and poverty

PubMed Central

Hanauer, Merlin M.; Canavire-Bacarreza, Gustavo

2015-01-01

Protected areas are a popular policy instrument in the global fight against loss of biodiversity and ecosystem services. However, the effectiveness of protected areas in preventing deforestation, and their impacts on poverty, are not well understood. Recent studies have found that Bolivia's protected-area system, on average, reduced deforestation and poverty. We implement several non-parametric and semi-parametric econometric estimators to characterize the heterogeneity in Bolivia's protected-area impacts on joint deforestation and poverty outcomes across a number of socioeconomic and biophysical moderators. Like previous studies from Costa Rica and Thailand, we find that Bolivia's protected areas are not associated with poverty traps. Our results also indicate that protection did not have a differential impact on indigenous populations. However, results from new multidimensional non-parametric estimators provide evidence that the biophysical characteristics associated with the greatest avoided deforestation are the characteristics associated with the potential for poverty exacerbation from protection. We demonstrate that these results would not be identified using the methods implemented in previous studies. Thus, this study provides valuable practical information on the impacts of Bolivia's protected areas for conservation practitioners and demonstrates methods that are likely to be valuable to researchers interested in better understanding the heterogeneity in conservation impacts. PMID:26460125

Implications of heterogeneous impacts of protected areas on deforestation and poverty.

PubMed

Hanauer, Merlin M; Canavire-Bacarreza, Gustavo

2015-11-05

Protected areas are a popular policy instrument in the global fight against loss of biodiversity and ecosystem services. However, the effectiveness of protected areas in preventing deforestation, and their impacts on poverty, are not well understood. Recent studies have found that Bolivia's protected-area system, on average, reduced deforestation and poverty. We implement several non-parametric and semi-parametric econometric estimators to characterize the heterogeneity in Bolivia's protected-area impacts on joint deforestation and poverty outcomes across a number of socioeconomic and biophysical moderators. Like previous studies from Costa Rica and Thailand, we find that Bolivia's protected areas are not associated with poverty traps. Our results also indicate that protection did not have a differential impact on indigenous populations. However, results from new multidimensional non-parametric estimators provide evidence that the biophysical characteristics associated with the greatest avoided deforestation are the characteristics associated with the potential for poverty exacerbation from protection. We demonstrate that these results would not be identified using the methods implemented in previous studies. Thus, this study provides valuable practical information on the impacts of Bolivia's protected areas for conservation practitioners and demonstrates methods that are likely to be valuable to researchers interested in better understanding the heterogeneity in conservation impacts. © 2015 The Author(s).

Joint radius-length distribution as a measure of anisotropic pore eccentricity: an experimental and analytical framework.

PubMed

Benjamini, Dan; Basser, Peter J

2014-12-07

In this work, we present an experimental design and analytical framework to measure the nonparametric joint radius-length (R-L) distribution of an ensemble of parallel, finite cylindrical pores, and more generally, the eccentricity distribution of anisotropic pores. Employing a novel 3D double pulsed-field gradient acquisition scheme, we first obtain both the marginal radius and length distributions of a population of cylindrical pores and then use these to constrain and stabilize the estimate of the joint radius-length distribution. Using the marginal distributions as constraints allows the joint R-L distribution to be reconstructed from an underdetermined system (i.e., more variables than equations), which requires a relatively small and feasible number of MR acquisitions. Three simulated representative joint R-L distribution phantoms corrupted by different noise levels were reconstructed to demonstrate the process, using this new framework. As expected, the broader the peaks in the joint distribution, the less stable and more sensitive to noise the estimation of the marginal distributions. Nevertheless, the reconstruction of the joint distribution is remarkably robust to increases in noise level; we attribute this characteristic to the use of the marginal distributions as constraints. Axons are known to exhibit local compartment eccentricity variations upon injury; the extent of the variations depends on the severity of the injury. Nonparametric estimation of the eccentricity distribution of injured axonal tissue is of particular interest since generally one cannot assume a parametric distribution a priori. Reconstructing the eccentricity distribution may provide vital information about changes resulting from injury or that occurred during development.

Mind Operational Semantics and Brain Operational Architectonics: A Putative Correspondence

PubMed Central

Benedetti, Giulio; Marchetti, Giorgio; Fingelkurts, Alexander A; Fingelkurts, Andrew A

2010-01-01

Despite allowing for the unprecedented visualization of brain functional activity, modern neurobiological techniques have not yet been able to provide satisfactory answers to important questions about the relationship between brain and mind. The aim of this paper is to show how two different but complementary approaches, Mind Operational Semantics (OS) and Brain Operational Architectonics (OA), can help bridge the gap between a specific kind of mental activity—the higher-order reflective thought or linguistic thought—and brain. The fundamental notion that allows the two different approaches to be jointly used under a common framework is that of operation. According to OS, which is based on introspection and linguistic data, the meanings of words can be analyzed in terms of elemental mental operations (EOMC), amongst which those of attention play a key role. Linguistic thought is made possible by special kinds of elements, which OS calls “correlators”, which have the function of tying together the other elements of thought, which OS calls “correlata” (a "correlational network” that is, a sentence, is so formed). Therefore, OS conceives of linguistic thought as a hierarchy of operations of increasing complexity. Likewise, according to OA, which is based on the joint analysis of cognitive and electromagnetic data (EEG and MEG), every conscious phenomenon is brought to existence by the joint operations of many functional and transient neuronal assemblies in the brain. According to OA, the functioning of the brain is always operational (made up of operations), and its structure is characterized by a hierarchy of operations of increasing complexity: single neurons, single assemblies of neurons, synchronized neuronal assemblies or Operational Modules (OM), integrated or complex OMs. The authors put forward the hypothesis that the whole level of OS’s description (EOMC, correlators, and correlational networks) corresponds to the level of OMs (or set of them) of different complexity within OA’s theory: EOMC could correspond to simple OMs, correlators to complex OMs and the correlational network to a set of simple and complex OMs. Finally, a set of experiments is proposed to verify the putative correspondence between OS and OA and prove the existence of an integrated continuum between brain and mind. PMID:21113277

Development, Validation and Parametric study of a 3-Year-Old Child Head Finite Element Model

NASA Astrophysics Data System (ADS)

Cui, Shihai; Chen, Yue; Li, Haiyan; Ruan, ShiJie

2015-12-01

Traumatic brain injury caused by drop and traffic accidents is an important reason for children's death and disability. Recently, the computer finite element (FE) head model has been developed to investigate brain injury mechanism and biomechanical responses. Based on CT data of a healthy 3-year-old child head, the FE head model with detailed anatomical structure was developed. The deep brain structures such as white matter, gray matter, cerebral ventricle, hippocampus, were firstly created in this FE model. The FE model was validated by comparing the simulation results with that of cadaver experiments based on reconstructing the child and adult cadaver experiments. In addition, the effects of skull stiffness on the child head dynamic responses were further investigated. All the simulation results confirmed the good biofidelity of the FE model.

The experience of mathematical beauty and its neural correlates

PubMed Central

Zeki, Semir; Romaya, John Paul; Benincasa, Dionigi M. T.; Atiyah, Michael F.

2014-01-01

Many have written of the experience of mathematical beauty as being comparable to that derived from the greatest art. This makes it interesting to learn whether the experience of beauty derived from such a highly intellectual and abstract source as mathematics correlates with activity in the same part of the emotional brain as that derived from more sensory, perceptually based, sources. To determine this, we used functional magnetic resonance imaging (fMRI) to image the activity in the brains of 15 mathematicians when they viewed mathematical formulae which they had individually rated as beautiful, indifferent or ugly. Results showed that the experience of mathematical beauty correlates parametrically with activity in the same part of the emotional brain, namely field A1 of the medial orbito-frontal cortex (mOFC), as the experience of beauty derived from other sources. PMID:24592230

Causes, effects and connectivity changes in MS-related cognitive decline.

PubMed

Rimkus, Carolina de Medeiros; Steenwijk, Martijn D; Barkhof, Frederik

2016-01-01

Cognitive decline is a frequent but undervalued aspect of multiple sclerosis (MS). Currently, it remains unclear what the strongest determinants of cognitive dysfunction are, with grey matter damage most directly related to cognitive impairment. Multi-parametric studies seem to indicate that individual factors of MS-pathology are highly interdependent causes of grey matter atrophy and permanent brain damage. They are associated with intermediate functional effects (e.g. in functional MRI) representing a balance between disconnection and (mal) adaptive connectivity changes. Therefore, a more comprehensive MRI approach is warranted, aiming to link structural changes with functional brain organization. To better understand the disconnection syndromes and cognitive decline in MS, this paper reviews the associations between MRI metrics and cognitive performance, by discussing the interactions between multiple facets of MS pathology as determinants of brain damage and how they affect network efficiency.

Optimizing Muscle Parameters in Musculoskeletal Modeling Using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Hanson, Andrea; Reed, Erik; Cavanagh, Peter

2011-01-01

Astronauts assigned to long-duration missions experience bone and muscle atrophy in the lower limbs. The use of musculoskeletal simulation software has become a useful tool for modeling joint and muscle forces during human activity in reduced gravity as access to direct experimentation is limited. Knowledge of muscle and joint loads can better inform the design of exercise protocols and exercise countermeasure equipment. In this study, the LifeModeler(TM) (San Clemente, CA) biomechanics simulation software was used to model a squat exercise. The initial model using default parameters yielded physiologically reasonable hip-joint forces. However, no activation was predicted in some large muscles such as rectus femoris, which have been shown to be active in 1-g performance of the activity. Parametric testing was conducted using Monte Carlo methods and combinatorial reduction to find a muscle parameter set that more closely matched physiologically observed activation patterns during the squat exercise. Peak hip joint force using the default parameters was 2.96 times body weight (BW) and increased to 3.21 BW in an optimized, feature-selected test case. The rectus femoris was predicted to peak at 60.1% activation following muscle recruitment optimization, compared to 19.2% activation with default parameters. These results indicate the critical role that muscle parameters play in joint force estimation and the need for exploration of the solution space to achieve physiologically realistic muscle activation.

Optimum design of bolted composite lap joints under mechanical and thermal loading

NASA Astrophysics Data System (ADS)

Kradinov, Vladimir Yurievich

A new approach is developed for the analysis and design of mechanically fastened composite lap joints under mechanical and thermal loading. Based on the combined complex potential and variational formulation, the solution method satisfies the equilibrium equations exactly while the boundary conditions are satisfied by minimizing the total potential. This approach is capable of modeling finite laminate planform dimensions, uniform and variable laminate thickness, laminate lay-up, interaction among bolts, bolt torque, bolt flexibility, bolt size, bolt-hole clearance and interference, insert dimensions and insert material properties. Comparing to the finite element analysis, the robustness of the method does not decrease when modeling the interaction of many bolts; also, the method is more suitable for parametric study and design optimization. The Genetic Algorithm (GA), a powerful optimization technique for multiple extrema functions in multiple dimensions search spaces, is applied in conjunction with the complex potential and variational formulation to achieve optimum designs of bolted composite lap joints. The objective of the optimization is to acquire such a design that ensures the highest strength of the joint. The fitness function for the GA optimization is based on the average stress failure criterion predicting net-section, shear-out, and bearing failure modes in bolted lap joints. The criterion accounts for the stress distribution in the thickness direction at the bolt location by applying an approach utilizing a beam on an elastic foundation formulation.

Emotion processing in joint hypermobility: A potential link to the neural bases of anxiety and related somatic symptoms in collagen anomalies.

PubMed

Mallorquí-Bagué, N; Bulbena, A; Roé-Vellvé, N; Hoekzema, E; Carmona, S; Barba-Müller, E; Fauquet, J; Pailhez, G; Vilarroya, O

2015-06-01

Joint hypermobility syndrome (JHS) has repeatedly been associated with anxiety and anxiety disorders, fibromyalgia, irritable bowel syndrome and temporomandibular joint disorder. However, the neural underpinnings of these associations still remain unclear. This study explored brain responses to facial visual stimuli with emotional cues using fMRI techniques in general population with different ranges of hypermobility. Fifty-one non-clinical volunteers (33 women) completed state and trait anxiety questionnaire measures, were assessed with a clinical examination for hypermobility (Beighton system) and performed an emotional face processing paradigm during functional neuroimaging. Trait anxiety scores did significantly correlate with both state anxiety and hypermobility scores. BOLD signals of the hippocampus did positively correlate with hypermobility scores for the crying faces versus neutral faces contrast in ROI analyses. No results were found for any of the other studied ROIs. Additionally, hypermobility scores were also associated with other key affective processing areas (i.e. the middle and anterior cingulate gyrus, fusiform gyrus, parahippocampal region, orbitofrontal cortex and cerebellum) in the whole brain analysis. Hypermobility scores are associated with trait anxiety and higher brain responses to emotional faces in emotion processing brain areas (including hippocampus) described to be linked to anxiety and somatic symptoms. These findings increase our understanding of emotion processing in people bearing this heritable variant of collagen and the mechanisms through which vulnerability to anxiety and somatic symptoms arises in this population. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Individual and Joint Contributions of the Cerebral Hemispheres to Language Comprehension

ERIC Educational Resources Information Center

Wlotko, Edward Wesley

2009-01-01

Normal language comprehension requires contributions from and cooperation of many parts of the brain, ranging from sensory areas that receive the initial physical input, through frontal and temporal areas associated with oft-characterized language subprocesses, to brain areas involved in perspective-taking and social cognition; thus a network of…

Topic Repetitiveness after Traumatic Brain Injury: An Emergent, Jointly Managed Behaviour

ERIC Educational Resources Information Center

Body, Richard; Parker, Mark

2005-01-01

Topic repetitiveness is a common component of pragmatic impairment and a powerful contributor to social exclusion. Despite this, description, characterization and intervention remain underdeveloped. This article explores the nature of repetitiveness in traumatic brain injury (TBI). A case study of one individual after TBI provides the basis for a…

Comparative gut physiology symposium: The microbe-gut-brain axis

USDA-ARS?s Scientific Manuscript database

The Comparative Gut Physiology Symposium titled “The Microbe-Gut-Brain Axis” was held at the Joint Annual Meeting of the American Society of Animal Science and the American Dairy Science Association on Thursday, July 21, 2016, in Salt Lake City Utah. The goal of the symposium was to present basic r...

Interbrains cooperation: Hyperscanning and self-perception in joint actions.

PubMed

Balconi, Michela; Vanutelli, Maria Elide

2017-08-01

The aim of the present study was to investigate the neural bases of cooperative behaviors and social self-perception underlying the execution of joint actions by using a hyperscanning brain paradigm with functional near-infrared spectroscopy (fNIRS). We firstly found that an artificial positive feedback on the cognitive performance was able to affect the self-perception of social position and hierarchy (higher social ranking) for the dyad, as well as the cognitive performance (decreased error rate, ER, and response times, RTs). In addition, the shared cognitive strategy was concurrently improved within the dyad after this social reinforcing. Secondly, fNIRS measures revealed an increased brain activity in the postfeedback condition for the dyad. Moreover, an interbrain similarity was found for the dyads during the task, with higher coherent prefrontal cortex (PFC) activity for the interagents in the postfeedback condition. Finally, a significant prefrontal brain lateralization effect was revealed, with the left hemisphere being more engaged during the postfeedback condition. To summarize, the self-perception, the cognitive performance, and the shared brain activity were all reinforced by the social feedback within the dyad.

Shape-Driven 3D Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2013-01-01

This paper presents a novel active surface segmentation algorithm using a multiscale shape representation and prior. We define a parametric model of a surface using spherical wavelet functions and learn a prior probability distribution over the wavelet coefficients to model shape variations at different scales and spatial locations in a training set. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior in the segmentation framework. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to the segmentation of brain caudate nucleus, of interest in the study of schizophrenia. Our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm by capturing finer shape details. PMID:17354875

Brain-Mind Operational Architectonics Imaging: Technical and Methodological Aspects

PubMed Central

Fingelkurts, Andrew A; Fingelkurts, Alexander A

2008-01-01

This review paper deals with methodological and technical foundations of the Operational Architectonics framework of brain and mind functioning. This theory provides a framework for mapping and understanding important aspects of the brain mechanisms that constitute perception, cognition, and eventually consciousness. The methods utilized within Operational Architectonics framework allow analyzing with an incredible detail the operational behavior of local neuronal assemblies and their joint activity in the form of unified and metastable operational modules, which constitute the whole hierarchy of brain operations, operations of cognition and phenomenal consciousness. PMID:19526071

Computational Psychosomatics and Computational Psychiatry: Toward a Joint Framework for Differential Diagnosis.

PubMed

Petzschner, Frederike H; Weber, Lilian A E; Gard, Tim; Stephan, Klaas E

2017-09-15

This article outlines how a core concept from theories of homeostasis and cybernetics, the inference-control loop, may be used to guide differential diagnosis in computational psychiatry and computational psychosomatics. In particular, we discuss 1) how conceptualizing perception and action as inference-control loops yields a joint computational perspective on brain-world and brain-body interactions and 2) how the concrete formulation of this loop as a hierarchical Bayesian model points to key computational quantities that inform a taxonomy of potential disease mechanisms. We consider the utility of this perspective for differential diagnosis in concrete clinical applications. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

On the stiffness matrix of the intervertebral joint: application to total disk replacement.

PubMed

O'Reilly, Oliver M; Metzger, Melodie F; Buckley, Jenni M; Moody, David A; Lotz, Jeffrey C

2009-08-01

The traditional method of establishing the stiffness matrix associated with an intervertebral joint is valid only for infinitesimal rotations, whereas the rotations featured in spinal motion are often finite. In the present paper, a new formulation of this stiffness matrix is presented, which is valid for finite rotations. This formulation uses Euler angles to parametrize the rotation, an associated basis, which is known as the dual Euler basis, to describe the moments, and it enables a characterization of the nonconservative nature of the joint caused by energy loss in the poroviscoelastic disk and ligamentous support structure. As an application of the formulation, the stiffness matrix of a motion segment is experimentally determined for the case of an intact intervertebral disk and compared with the matrices associated with the same segment after the insertion of a total disk replacement system. In this manner, the matrix is used to quantify the changes in the intervertebral kinetics associated with total disk replacements. As a result, this paper presents the first such characterization of the kinetics of a total disk replacement.

The numerical high cycle fatigue damage model of fillet weld joint under weld-induced residual stresses

NASA Astrophysics Data System (ADS)

Nguyen Van Do, Vuong

2018-04-01

In this study, a development of nonlinear continuum damage mechanics (CDM) model for multiaxial high cycle fatigue is proposed in which the cyclic plasticity constitutive model has been incorporated in the finite element (FE) framework. T-joint FE simulation of fillet welding is implemented to characterize sequentially coupled three-dimensional (3-D) of thermo-mechanical FE formulation and simulate the welding residual stresses. The high cycle fatigue damage model is then taken account into the fillet weld joints under the various cyclic fatigue load types to calculate the fatigue life considering the residual stresses. The fatigue crack initiation and the propagation in the present model estimated for the total fatigue is compared with the experimental results. The FE results illustrated that the proposed high cycle fatigue damage model in this study could become a powerful tool to effectively predict the fatigue life of the welds. Parametric studies in this work are also demonstrated that the welding residual stresses cannot be ignored in the computation of the fatigue life of welded structures.

Numerical assessment of the influence of different joint hysteretic models over the seismic behaviour of Moment Resisting Steel Frames

NASA Astrophysics Data System (ADS)

Giordano, V.; Chisari, C.; Rizzano, G.; Latour, M.

2017-10-01

The main aim of this work is to understand how the prediction of the seismic performance of moment-resisting (MR) steel frames depends on the modelling of their dissipative zones when the structure geometry (number of stories and bays) and seismic excitation source vary. In particular, a parametric analysis involving 4 frames was carried out, and, for each one, the full-strength beam-to-column connections were modelled according to 4 numerical approaches with different degrees of sophistication (Smooth Hysteretic Model, Bouc-Wen, Hysteretic and simple Elastic-Plastic models). Subsequently, Incremental Dynamic Analyses (IDA) were performed by considering two different earthquakes (Spitak and Kobe). The preliminary results collected so far pointed out that the influence of the joint modelling on the overall frame response is negligible up to interstorey drift ratio values equal to those conservatively assumed by the codes to define conventional collapse (0.03 rad). Conversely, if more realistic ultimate interstorey drift values are considered for the q-factor evaluation, the influence of joint modelling can be significant, and thus may require accurate modelling of its cyclic behavior.

Slice-to-Volume Nonrigid Registration of Histological Sections to MR Images of the Human Brain

PubMed Central

Osechinskiy, Sergey; Kruggel, Frithjof

2011-01-01

Registration of histological images to three-dimensional imaging modalities is an important step in quantitative analysis of brain structure, in architectonic mapping of the brain, and in investigation of the pathology of a brain disease. Reconstruction of histology volume from serial sections is a well-established procedure, but it does not address registration of individual slices from sparse sections, which is the aim of the slice-to-volume approach. This study presents a flexible framework for intensity-based slice-to-volume nonrigid registration algorithms with a geometric transformation deformation field parametrized by various classes of spline functions: thin-plate splines (TPS), Gaussian elastic body splines (GEBS), or cubic B-splines. Algorithms are applied to cross-modality registration of histological and magnetic resonance images of the human brain. Registration performance is evaluated across a range of optimization algorithms and intensity-based cost functions. For a particular case of histological data, best results are obtained with a TPS three-dimensional (3D) warp, a new unconstrained optimization algorithm (NEWUOA), and a correlation-coefficient-based cost function. PMID:22567290

Influence of signal intensity non-uniformity on brain volumetry using an atlas-based method.

PubMed

Goto, Masami; Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.

Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method

PubMed Central

Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Objective Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials. PMID:22778560

A global goodness-of-fit test for receiver operating characteristic curve analysis via the bootstrap method.

PubMed

Zou, Kelly H; Resnic, Frederic S; Talos, Ion-Florin; Goldberg-Zimring, Daniel; Bhagwat, Jui G; Haker, Steven J; Kikinis, Ron; Jolesz, Ferenc A; Ohno-Machado, Lucila

2005-10-01

Medical classification accuracy studies often yield continuous data based on predictive models for treatment outcomes. A popular method for evaluating the performance of diagnostic tests is the receiver operating characteristic (ROC) curve analysis. The main objective was to develop a global statistical hypothesis test for assessing the goodness-of-fit (GOF) for parametric ROC curves via the bootstrap. A simple log (or logit) and a more flexible Box-Cox normality transformations were applied to untransformed or transformed data from two clinical studies to predict complications following percutaneous coronary interventions (PCIs) and for image-guided neurosurgical resection results predicted by tumor volume, respectively. We compared a non-parametric with a parametric binormal estimate of the underlying ROC curve. To construct such a GOF test, we used the non-parametric and parametric areas under the curve (AUCs) as the metrics, with a resulting p value reported. In the interventional cardiology example, logit and Box-Cox transformations of the predictive probabilities led to satisfactory AUCs (AUC=0.888; p=0.78, and AUC=0.888; p=0.73, respectively), while in the brain tumor resection example, log and Box-Cox transformations of the tumor size also led to satisfactory AUCs (AUC=0.898; p=0.61, and AUC=0.899; p=0.42, respectively). In contrast, significant departures from GOF were observed without applying any transformation prior to assuming a binormal model (AUC=0.766; p=0.004, and AUC=0.831; p=0.03), respectively. In both studies the p values suggested that transformations were important to consider before applying any binormal model to estimate the AUC. Our analyses also demonstrated and confirmed the predictive values of different classifiers for determining the interventional complications following PCIs and resection outcomes in image-guided neurosurgery.

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

NASA Astrophysics Data System (ADS)

Gutiérrez, David

2008-08-01

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEG data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation.

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

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

Gutierrez, David

2008-08-11

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEGmore » data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation.« less

Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping

PubMed Central

Keith, Lauren; Ross, Brian D.; Galbán, Craig J.; Luker, Gary D.; Galbán, Stefanie; Zhao, Binsheng; Guo, Xiaotao; Chenevert, Thomas L.; Hoff, Benjamin A.

2017-01-01

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice. PMID:28286871

Individualism, conservatism, and radicalism as criteria for processing political beliefs: a parametric fMRI study.

PubMed

Zamboni, Giovanna; Gozzi, Marta; Krueger, Frank; Duhamel, Jean-René; Sirigu, Angela; Grafman, Jordan

2009-01-01

Politics is a manifestation of the uniquely human ability to debate, decide, and reach consensus on decisions affecting large groups over long durations of time. Recent neuroimaging studies on politics have focused on the association between brain regions and specific political behaviors by adopting party or ideological affiliation as a criterion to classify either experimental stimuli or subjects. However, it is unlikely that complex political beliefs (i.e., "the government should protect freedom of speech") are evaluated only on a liberal-to-conservative criterion. Here we used multidimensional scaling and parametric functional magnetic resonance imaging to identify which criteria/dimensions people use to structure complex political beliefs and which brain regions are concurrently activated. We found that three independent dimensions explained the variability of a set of statements expressing political beliefs and that each dimension was reflected in a distinctive pattern of neural activation: individualism (medial prefrontal cortex and temporoparietal junction), conservatism (dorsolateral prefrontal cortex), and radicalism (ventral striatum and posterior cingulate). The structures we identified are also known to be important in self-other processing, social decision-making in ambivalent situations, and reward prediction. Our results extend current knowledge on the neural correlates of the structure of political beliefs, a fundamental aspect of the human ability to coalesce into social entities.

sfDM: Open-Source Software for Temporal Analysis and Visualization of Brain Tumor Diffusion MR Using Serial Functional Diffusion Mapping.

PubMed

Ceschin, Rafael; Panigrahy, Ashok; Gopalakrishnan, Vanathi

2015-01-01

A major challenge in the diagnosis and treatment of brain tumors is tissue heterogeneity leading to mixed treatment response. Additionally, they are often difficult or at very high risk for biopsy, further hindering the clinical management process. To overcome this, novel advanced imaging methods are increasingly being adapted clinically to identify useful noninvasive biomarkers capable of disease stage characterization and treatment response prediction. One promising technique is called functional diffusion mapping (fDM), which uses diffusion-weighted imaging (DWI) to generate parametric maps between two imaging time points in order to identify significant voxel-wise changes in water diffusion within the tumor tissue. Here we introduce serial functional diffusion mapping (sfDM), an extension of existing fDM methods, to analyze the entire tumor diffusion profile along the temporal course of the disease. sfDM provides the tools necessary to analyze a tumor data set in the context of spatiotemporal parametric mapping: the image registration pipeline, biomarker extraction, and visualization tools. We present the general workflow of the pipeline, along with a typical use case for the software. sfDM is written in Python and is freely available as an open-source package under the Berkley Software Distribution (BSD) license to promote transparency and reproducibility.

Curvature, metric and parametrization of origami tessellations: theory and application to the eggbox pattern.

PubMed

Nassar, H; Lebée, A; Monasse, L

2017-01-01

Origami tessellations are particular textured morphing shell structures. Their unique folding and unfolding mechanisms on a local scale aggregate and bring on large changes in shape, curvature and elongation on a global scale. The existence of these global deformation modes allows for origami tessellations to fit non-trivial surfaces thus inspiring applications across a wide range of domains including structural engineering, architectural design and aerospace engineering. The present paper suggests a homogenization-type two-scale asymptotic method which, combined with standard tools from differential geometry of surfaces, yields a macroscopic continuous characterization of the global deformation modes of origami tessellations and other similar periodic pin-jointed trusses. The outcome of the method is a set of nonlinear differential equations governing the parametrization, metric and curvature of surfaces that the initially discrete structure can fit. The theory is presented through a case study of a fairly generic example: the eggbox pattern. The proposed continuous model predicts correctly the existence of various fittings that are subsequently constructed and illustrated.

Curvature, metric and parametrization of origami tessellations: theory and application to the eggbox pattern

NASA Astrophysics Data System (ADS)

Nassar, H.; Lebée, A.; Monasse, L.

2017-01-01

Origami tessellations are particular textured morphing shell structures. Their unique folding and unfolding mechanisms on a local scale aggregate and bring on large changes in shape, curvature and elongation on a global scale. The existence of these global deformation modes allows for origami tessellations to fit non-trivial surfaces thus inspiring applications across a wide range of domains including structural engineering, architectural design and aerospace engineering. The present paper suggests a homogenization-type two-scale asymptotic method which, combined with standard tools from differential geometry of surfaces, yields a macroscopic continuous characterization of the global deformation modes of origami tessellations and other similar periodic pin-jointed trusses. The outcome of the method is a set of nonlinear differential equations governing the parametrization, metric and curvature of surfaces that the initially discrete structure can fit. The theory is presented through a case study of a fairly generic example: the eggbox pattern. The proposed continuous model predicts correctly the existence of various fittings that are subsequently constructed and illustrated.

ACSYNT - A standards-based system for parametric, computer aided conceptual design of aircraft

NASA Technical Reports Server (NTRS)

Jayaram, S.; Myklebust, A.; Gelhausen, P.

1992-01-01

A group of eight US aerospace companies together with several NASA and NAVY centers, led by NASA Ames Systems Analysis Branch, and Virginia Tech's CAD Laboratory agreed, through the assistance of Americal Technology Initiative, in 1990 to form the ACSYNT (Aircraft Synthesis) Institute. The Institute is supported by a Joint Sponsored Research Agreement to continue the research and development in computer aided conceptual design of aircraft initiated by NASA Ames Research Center and Virginia Tech's CAD Laboratory. The result of this collaboration, a feature-based, parametric computer aided aircraft conceptual design code called ACSYNT, is described. The code is based on analysis routines begun at NASA Ames in the early 1970's. ACSYNT's CAD system is based entirely on the ISO standard Programmer's Hierarchical Interactive Graphics System and is graphics-device independent. The code includes a highly interactive graphical user interface, automatically generated Hermite and B-Spline surface models, and shaded image displays. Numerous features to enhance aircraft conceptual design are described.

Non-symbolic numerical distance effect in children with and without developmental dyscalculia: a parametric fMRI study.

PubMed

Kucian, Karin; Loenneker, Thomas; Martin, Ernst; von Aster, Michael

2011-01-01

This study investigated areas of brain activation related to non-symbolic distance effects in children with and without developmental dyscalculia (DD). We examined 15 children with DD (11.3 years) and 15 controls (10.6 years) by means of functional magnetic resonance imaging (fMRI). Both groups displayed similar behavioral performance, but differences in brain activation were observed, particularly in the supplementary motor area and the right fusiform gyrus, where children with DD demonstrated stronger activation. These results suggest that dyscalculic children engage areas attributed to higher difficulty in response selection more than control children, possibly due to a deficient development of a spatial number representation in DD.

A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.

2009-05-01

Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.

Skeletal pattern in subjects with temporomandibular joint disorders

PubMed Central

Almăşan, Oana Cristina; Almăşan, Horea Artimoniu; Bran, Simion; Lascu, Liana; Iancu, Mihaela; Băciuţ, Grigore

2013-01-01

Introduction To establish the skeletal pattern in subjects with malocclusions and temporomandibular disorders (TMD); to assess the relationship between craniofacial skeletal structures and TMD in subjects with malocclusions. Material and methods Sixty-four subjects with malocclusions, over 18 years of age, were included in the study. Temporomandibular disorders were clinically assessed according to the Helkimo Anamnestic Index. Subjects underwent a lateral cephalogram. Subjects were grouped according to the sagittal skeletal pattern (ANB angle) into class I, II and III. Parametric Student tests with equal or unequal variations were used (variations were previously tested with Levene test). Results Twenty-four patients with TMD (experimental sample); 40 patients without TMD (control group); interincisal angle was higher in class I and II (p < 0.05) experimental subjects; overjet was larger in experimental subjects; midline shift and Wits appraisal were broader in the experimental group in all three classes. In class III subjects, the SNB angle was higher in the experimental group (p = 0.01). Joint noises followed by reduced mandible mobility, muscular pain and temporomandibular joint (TMJ) pain were the most frequent symptoms in subjects with TMD and malocclusions. Conclusions Temporomandibular joint status is an important factor to consider when planning orthodontic treatment in patients with severe malocclusions; midline shift, large overjet and deep overbite have been associated with signs and symptoms of TMD. PMID:23515361

Human arm stiffness and equilibrium-point trajectory during multi-joint movement.

PubMed

Gomi, H; Kawato, M

1997-03-01

By using a newly designed high-performance manipulandum and a new estimation algorithm, we measured human multi-joint arm stiffness parameters during multi-joint point-to-point movements on a horizontal plane. This manipulandum allows us to apply a sufficient perturbation to subject's arm within a brief period during movement. Arm stiffness parameters were reliably estimated using a new algorithm, in which all unknown structural parameters could be estimated independent of arm posture (i.e., constant values under any arm posture). Arm stiffness during transverse movement was considerably greater than that during corresponding posture, but not during a longitudinal movement. Although the ratios of elbow, shoulder, and double-joint stiffness were varied in time, the orientation of stiffness ellipses during the movement did not change much. Equilibrium-point trajectories that were predicted from measured stiffness parameters and actual trajectories were slightly sinusoidally curved in Cartesian space and their velocity profiles were quite different from the velocity profiles of actual hand trajectories. This result contradicts the hypothesis that the brain does not take the dynamics into account in movement control depending on the neuromuscular servo mechanism; rather, it implies that the brain needs to acquire some internal models of controlled objects.

Rhythm in joint action: psychological and neurophysiological mechanisms for real-time interpersonal coordination.

PubMed

Keller, Peter E; Novembre, Giacomo; Hove, Michael J

2014-12-19

Human interaction often requires simultaneous precision and flexibility in the coordination of rhythmic behaviour between individuals engaged in joint activity, for example, playing a musical duet or dancing with a partner. This review article addresses the psychological processes and brain mechanisms that enable such rhythmic interpersonal coordination. First, an overview is given of research on the cognitive-motor processes that enable individuals to represent joint action goals and to anticipate, attend and adapt to other's actions in real time. Second, the neurophysiological mechanisms that underpin rhythmic interpersonal coordination are sought in studies of sensorimotor and cognitive processes that play a role in the representation and integration of self- and other-related actions within and between individuals' brains. Finally, relationships between social-psychological factors and rhythmic interpersonal coordination are considered from two perspectives, one concerning how social-cognitive tendencies (e.g. empathy) affect coordination, and the other concerning how coordination affects interpersonal affiliation, trust and prosocial behaviour. Our review highlights musical ensemble performance as an ecologically valid yet readily controlled domain for investigating rhythm in joint action. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Advances in nonlinear optical materials and devices

NASA Technical Reports Server (NTRS)

Byer, Robert L.

1991-01-01

The recent progress in the application of nonlinear techniques to extend the frequency of laser sources has come from the joint progress in laser sources and in nonlinear materials. A brief summary of the progress in diode pumped solid state lasers is followed by an overview of progress in nonlinear frequency extension by harmonic generation and parametric processes. Improved nonlinear materials including bulk crystals, quasiphasematched interactions, guided wave devices, and quantum well intersubband studies are discussed with the idea of identifying areas of future progress in nonlinear materials and devices.

Intrinsic Brain Connectivity in Chronic Pain: A Resting-State fMRI Study in Patients with Rheumatoid Arthritis

PubMed Central

Flodin, Pär; Martinsen, Sofia; Altawil, Reem; Waldheim, Eva; Lampa, Jon; Kosek, Eva; Fransson, Peter

2016-01-01

Background: Rheumatoid arthritis (RA) is commonly accompanied by pain that is discordant with the degree of peripheral pathology. Very little is known about the cerebral processes involved in pain processing in RA. Here we investigated resting-state brain connectivity associated with prolonged pain in RA. Methods: 24 RA subjects and 19 matched controls were compared with regard to both behavioral measures of pain perception and resting-resting state fMRI data acquired subsequently to fMRI sessions involving pain stimuli. The resting-state fMRI brain connectivity was investigated using 159 seed regions located in cardinal pain processing brain regions. Additional principal component based multivariate pattern analysis of the whole brain connectivity pattern was carried out in a data driven analysis to localize group differences in functional connectivity. Results: When RA patients were compared to controls, we observed significantly lower pain resilience for pressure on the affected finger joints (i.e., P50-joint) and an overall heightened level of perceived global pain in RA patients. Relative to controls, RA patients displayed increased brain connectivity predominately for the supplementary motor areas, mid-cingulate cortex, and the primary sensorimotor cortex. Additionally, we observed an increase in brain connectivity between the insula and prefrontal cortex as well as between anterior cingulate cortex and occipital areas for RA patients. None of the group differences in brain connectivity were significantly correlated with behavioral parameters. Conclusion: Our study provides experimental evidence of increased connectivity between frontal midline regions that are implicated in affective pain processing and bilateral sensorimotor regions in RA patients. PMID:27014038

The Event-Related Brain Potential as an Index of Information Processing and Cognitive Activity: A Program of Basic Research.

DTIC Science & Technology

1986-02-20

related brain potential at the Joint EEG Society/ ohp hysioogical Society (ERP) and measures of the electromyogram Meeting. Bristol (England), 1983. and...proving the memory representation of the task ( mem - manipulations of primary-task difficulty attenuated ory data limits). If the P300 amplitude does in

Joint power and kinematics coordination in load carriage running: Implications for performance and injury.

PubMed

Liew, Bernard X W; Morris, Susan; Netto, Kevin

2016-06-01

Investigating the impact of incremental load magnitude on running joint power and kinematics is important for understanding the energy cost burden and potential injury-causative mechanisms associated with load carriage. It was hypothesized that incremental load magnitude would result in phase-specific, joint power and kinematic changes within the stance phase of running, and that these relationships would vary at different running velocities. Thirty-one participants performed running while carrying three load magnitudes (0%, 10%, 20% body weight), at three velocities (3, 4, 5m/s). Lower limb trajectories and ground reaction forces were captured, and global optimization was used to derive the variables. The relationships between load magnitude and joint power and angle vectors, at each running velocity, were analyzed using Statistical Parametric Mapping Canonical Correlation Analysis. Incremental load magnitude was positively correlated to joint power in the second half of stance. Increasing load magnitude was also positively correlated with alterations in three dimensional ankle angles during mid-stance (4.0 and 5.0m/s), knee angles at mid-stance (at 5.0m/s), and hip angles during toe-off (at all velocities). Post hoc analyses indicated that at faster running velocities (4.0 and 5.0m/s), increasing load magnitude appeared to alter power contribution in a distal-to-proximal (ankle→hip) joint sequence from mid-stance to toe-off. In addition, kinematic changes due to increasing load influenced both sagittal and non-sagittal plane lower limb joint angles. This study provides a list of plausible factors that may influence running energy cost and injury risk during load carriage running. Copyright © 2016 Elsevier B.V. All rights reserved.

Computer-aided diagnosis with radiogenomics: analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images.

PubMed

Kai, Chiharu; Uchiyama, Yoshikazu; Shiraishi, Junji; Fujita, Hiroshi; Doi, Kunio

2018-05-10

In the post-genome era, a novel research field, 'radiomics' has been developed to offer a new viewpoint for the use of genotypes in radiology and medicine research which have traditionally focused on the analysis of imaging phenotypes. The present study analyzed brain morphological changes related to the individual's genotype. Our data consisted of magnetic resonance (MR) images of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), as well as their apolipoprotein E (APOE) genotypes. First, statistical parametric mapping (SPM) 12 was used for three-dimensional anatomical standardization of the brain MR images. A total of 30 normal images were used to create a standard normal brain image. Z-score maps were generated to identify the differences between an abnormal image and the standard normal brain. Our experimental results revealed that cerebral atrophies, depending on genotypes, can occur in different locations and that morphological changes may differ between MCI and AD. Using a classifier to characterize cerebral atrophies related to an individual's genotype, we developed a computer-aided diagnosis (CAD) scheme to identify the disease. For the early detection of cerebral diseases, a screening system using MR images, called Brain Check-up, is widely performed in Japan. Therefore, our proposed CAD scheme would be used in Brain Check-up.

Schooling mediates brain reserve in Alzheimer's disease: findings of fluoro-deoxy-glucose-positron emission tomography.

PubMed

Perneczky, R; Drzezga, A; Diehl-Schmid, J; Schmid, G; Wohlschläger, A; Kars, S; Grimmer, T; Wagenpfeil, S; Monsch, A; Kurz, A

2006-09-01

Functional imaging studies report that higher education is associated with more severe pathology in patients with Alzheimer's disease, controlling for disease severity. Therefore, schooling seems to provide brain reserve against neurodegeneration. To provide further evidence for brain reserve in a large sample, using a sensitive technique for the indirect assessment of brain abnormality (18F-fluoro-deoxy-glucose-positron emission tomography (FDG-PET)), a comprehensive measure of global cognitive impairment to control for disease severity (total score of the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Battery) and an approach unbiased by predefined regions of interest for the statistical analysis (statistical parametric mapping (SPM)). 93 patients with mild Alzheimer's disease and 16 healthy controls underwent 18F-FDG-PET imaging of the brain. A linear regression analysis with education as independent and glucose utilisation as dependent variables, adjusted for global cognitive status and demographic variables, was conducted in SPM2. The regression analysis showed a marked inverse association between years of schooling and glucose metabolism in the posterior temporo-occipital association cortex and the precuneus in the left hemisphere. In line with previous reports, the findings suggest that education is associated with brain reserve and that people with higher education can cope with brain damage for a longer time.

Variance based joint sparsity reconstruction of synthetic aperture radar data for speckle reduction

NASA Astrophysics Data System (ADS)

Scarnati, Theresa; Gelb, Anne

2018-04-01

In observing multiple synthetic aperture radar (SAR) images of the same scene, it is apparent that the brightness distributions of the images are not smooth, but rather composed of complicated granular patterns of bright and dark spots. Further, these brightness distributions vary from image to image. This salt and pepper like feature of SAR images, called speckle, reduces the contrast in the images and negatively affects texture based image analysis. This investigation uses the variance based joint sparsity reconstruction method for forming SAR images from the multiple SAR images. In addition to reducing speckle, the method has the advantage of being non-parametric, and can therefore be used in a variety of autonomous applications. Numerical examples include reconstructions of both simulated phase history data that result in speckled images as well as the images from the MSTAR T-72 database.

Parametric optimisation and microstructural analysis on high power Yb-fibre laser welding of Ti-6Al-4V

NASA Astrophysics Data System (ADS)

Ahn, J.; Chen, L.; Davies, C. M.; Dear, J. P.

2016-11-01

In this work thin sheets of Ti-6Al-4V were full penetration welded using a 5 kW fibre laser in order to evaluate the effectiveness of high power fibre laser as a welding processing tool for welding Ti-6Al-4V with the requirements of the aircraft industry and to determine the effect of welding parameters including laser power, welding speed and beam focal position on the weld microstructure, bead profile and weld quality. It involved establishing an understanding of the influence of welding parameters on microstructural change, welding defects, and the characteristics of heat affected zone (HAZ) and weld metal (WM) of fibre laser welded joints. The optimum range of welding parameters which produced welds without cracking and porosity were identified. The influence of the welding parameters on the weld joint heterogeneity was characterised by conducting detailed microstructural analysis.

Hybrid microfiber-lithium-niobate nanowaveguide structures as high-purity heralded single-photon sources

NASA Astrophysics Data System (ADS)

Main, Philip; Mosley, Peter J.; Ding, Wei; Zhang, Lijian; Gorbach, Andrey V.

2016-12-01

We propose a compact, fiber-integrated architecture for photon-pair generation by parametric downconversion with unprecedented flexibility in the properties of the photons produced. Our approach is based on a thin-film lithium niobate nanowaveguide, evanescently coupled to a tapered silica microfiber. We demonstrate how controllable mode hybridization between the fiber and waveguide yields control over the joint spectrum of the photon pairs. We also investigate how independent engineering of the linear and nonlinear properties of the structure can be achieved through the addition of a tapered, proton-exchanged layer to the waveguide. This allows further refinement of the joint spectrum through custom profiling of the effective nonlinearity, drastically improving the purity of the heralded photons. We give details of a source design capable of generating heralded single photons in the telecom wavelength range with purity of at least 0.95, and we provide a feasible fabrication methodology.

On how high performers keep cool brains in situations of cognitive overload.

PubMed

Jaeggi, Susanne M; Buschkuehl, Martin; Etienne, Alex; Ozdoba, Christoph; Perrig, Walter J; Nirkko, Arto C

2007-06-01

What happens in the brain when we reach or exceed our capacity limits? Are there individual differences for performance at capacity limits? We used functional magnetic resonance imaging (fMRI) to investigate the impact of increases in processing demand on selected cortical areas when participants performed a parametrically varied and challenging dual task. Low-performing participants respond with large and load-dependent activation increases in many cortical areas when exposed to excessive task requirements, accompanied by decreasing performance. It seems that these participants recruit additional attentional and strategy-related resources with increasing difficulty, which are either not relevant or even detrimental to performance. In contrast, the brains of the high-performing participants "keep cool" in terms of activation changes, despite continuous correct performance, reflecting different and more efficient processing. These findings shed light on the differential implications of performance on activation patterns and underline the importance of the interindividual-differences approach in neuroimaging research.

Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.

PubMed

Pascual-Marqui, R D; Esslen, M; Kochi, K; Lehmann, D

2002-01-01

This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

Inference in the age of big data: Future perspectives on neuroscience.

PubMed

Bzdok, Danilo; Yeo, B T Thomas

2017-07-15

Neuroscience is undergoing faster changes than ever before. Over 100 years our field qualitatively described and invasively manipulated single or few organisms to gain anatomical, physiological, and pharmacological insights. In the last 10 years neuroscience spawned quantitative datasets of unprecedented breadth (e.g., microanatomy, synaptic connections, and optogenetic brain-behavior assays) and size (e.g., cognition, brain imaging, and genetics). While growing data availability and information granularity have been amply discussed, we direct attention to a less explored question: How will the unprecedented data richness shape data analysis practices? Statistical reasoning is becoming more important to distill neurobiological knowledge from healthy and pathological brain measurements. We argue that large-scale data analysis will use more statistical models that are non-parametric, generative, and mixing frequentist and Bayesian aspects, while supplementing classical hypothesis testing with out-of-sample predictions. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A probabilistic framework to infer brain functional connectivity from anatomical connections.

PubMed

Deligianni, Fani; Varoquaux, Gael; Thirion, Bertrand; Robinson, Emma; Sharp, David J; Edwards, A David; Rueckert, Daniel

2011-01-01

We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.

Dynamic changes in brain activity during prism adaptation.

PubMed

Luauté, Jacques; Schwartz, Sophie; Rossetti, Yves; Spiridon, Mona; Rode, Gilles; Boisson, Dominique; Vuilleumier, Patrik

2009-01-07

Prism adaptation does not only induce short-term sensorimotor plasticity, but also longer-term reorganization in the neural representation of space. We used event-related fMRI to study dynamic changes in brain activity during both early and prolonged exposure to visual prisms. Participants performed a pointing task before, during, and after prism exposure. Measures of trial-by-trial pointing errors and corrections allowed parametric analyses of brain activity as a function of performance. We show that during the earliest phase of prism exposure, anterior intraparietal sulcus was primarily implicated in error detection, whereas parieto-occipital sulcus was implicated in error correction. Cerebellum activity showed progressive increases during prism exposure, in accordance with a key role for spatial realignment. This time course further suggests that the cerebellum might promote neural changes in superior temporal cortex, which was selectively activated during the later phase of prism exposure and could mediate the effects of prism adaptation on cognitive spatial representations.

Measuring Asymmetric Interactions in Resting State Brain Networks*

PubMed Central

Joshi, Anand A.; Salloum, Ronald; Bhushan, Chitresh; Leahy, Richard M.

2015-01-01

Directed graph representations of brain networks are increasingly being used in brain image analysis to indicate the direction and level of influence among brain regions. Most of the existing techniques for directed graph representations are based on time series analysis and the concept of causality, and use time lag information in the brain signals. These time lag-based techniques can be inadequate for functional magnetic resonance imaging (fMRI) signal analysis due to the limited time resolution of fMRI as well as the low frequency hemodynamic response. The aim of this paper is to present a novel measure of necessity that uses asymmetry in the joint distribution of brain activations to infer the direction and level of interaction among brain regions. We present a mathematical formula for computing necessity and extend this measure to partial necessity, which can potentially distinguish between direct and indirect interactions. These measures do not depend on time lag for directed modeling of brain interactions and therefore are more suitable for fMRI signal analysis. The necessity measures were used to analyze resting state fMRI data to determine the presence of hierarchy and asymmetry of brain interactions during resting state. We performed ROI-wise analysis using the proposed necessity measures to study the default mode network. The empirical joint distribution of the fMRI signals was determined using kernel density estimation, and was used for computation of the necessity and partial necessity measures. The significance of these measures was determined using a one-sided Wilcoxon rank-sum test. Our results are consistent with the hypothesis that the posterior cingulate cortex plays a central role in the default mode network. PMID:26221690

Headache in acute ischaemic stroke: a lesion mapping study.

PubMed

Seifert, Christian L; Schönbach, Etienne M; Magon, Stefano; Gross, Elena; Zimmer, Claus; Förschler, Anette; Tölle, Thomas R; Mühlau, Mark; Sprenger, Till; Poppert, Holger

2016-01-01

Headache is a common symptom in acute ischaemic stroke, but the underlying mechanisms are incompletely understood. The aim of this lesion mapping study was to identify brain regions, which are related to the development of headache in acute ischaemic stroke. Patients with acute ischaemic stroke (n = 100) were assessed by brain MRI at 3 T including diffusion weighted imaging. We included 50 patients with stroke and headache as well as 50 patients with stroke but no headache symptoms. Infarcts were manually outlined and images were transformed into standard stereotaxic space using non-linear warping. Voxel-wise overlap and subtraction analyses of lesions as well as non-parametric statistics were conducted. The same analyses were carried out by flipping of left-sided lesions, so that all strokes were transformed to the same hemisphere. Between the headache group as well as the non-headache there was no difference in infarct volumes, in the distribution of affected vascular beds or in the clinical severity of strokes. The headache phenotype was tension-type like in most cases. Subtraction analysis revealed that in headache sufferers infarctions were more often distributed in two well-known areas of the central pain matrix: the insula and the somatosensory cortex. This result was confirmed in the flipped analysis and by non-parametric statistical testing (whole brain corrected P-value < 0.01). To the best of our knowledge, this is the first lesion mapping study investigating potential lesional patterns associated with headache in acute ischaemic stroke. Insular strokes turned out to be strongly associated with headache. As the insular cortex is a well-established region in pain processing, our results suggest that, at least in a subgroup of patients, acute stroke-related headache might be centrally driven. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Nonparametric predictive inference for combining diagnostic tests with parametric copula

NASA Astrophysics Data System (ADS)

Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.

2017-09-01

Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.

Building and using a statistical 3D motion atlas for analyzing myocardial contraction in MRI

NASA Astrophysics Data System (ADS)

Rougon, Nicolas F.; Petitjean, Caroline; Preteux, Francoise J.

2004-05-01

We address the issue of modeling and quantifying myocardial contraction from 4D MR sequences, and present an unsupervised approach for building and using a statistical 3D motion atlas for the normal heart. This approach relies on a state-of-the-art variational non rigid registration (NRR) technique using generalized information measures, which allows for robust intra-subject motion estimation and inter-subject anatomical alignment. The atlas is built from a collection of jointly acquired tagged and cine MR exams in short- and long-axis views. Subject-specific non parametric motion estimates are first obtained by incremental NRR of tagged images onto the end-diastolic (ED) frame. Individual motion data are then transformed into the coordinate system of a reference subject using subject-to-reference mappings derived by NRR of cine ED images. Finally, principal component analysis of aligned motion data is performed for each cardiac phase, yielding a mean model and a set of eigenfields encoding kinematic ariability. The latter define an organ-dedicated hierarchical motion basis which enables parametric motion measurement from arbitrary tagged MR exams. To this end, the atlas is transformed into subject coordinates by reference-to-subject NRR of ED cine frames. Atlas-based motion estimation is then achieved by parametric NRR of tagged images onto the ED frame, yielding a compact description of myocardial contraction during diastole.

New insights into the impact of neuro-inflammation in rheumatoid arthritis

PubMed Central

Fuggle, Nicholas R.; Howe, Franklyn A.; Allen, Rachel L.; Sofat, Nidhi

2014-01-01

Rheumatoid arthritis (RA) is considered to be, in many respects, an archetypal autoimmune disease that causes activation of pro-inflammatory pathways resulting in joint and systemic inflammation. RA remains a major clinical problem with the development of several new therapies targeted at cytokine inhibition in recent years. In RA, biologic therapies targeted at inhibition of tumor necrosis factor alpha (TNFα) have been shown to reduce joint inflammation, limit erosive change, reduce disability and improve quality of life. The cytokine TNFα has a central role in systemic RA inflammation and has also been shown to have pro-inflammatory effects in the brain. Emerging data suggests there is an important bidirectional communication between the brain and immune system in inflammatory conditions like RA. Recent work has shown how TNF inhibitor therapy in people with RA is protective for Alzheimer's disease. Functional MRI studies to measure brain activation in people with RA to stimulus by finger joint compression, have also shown that those who responded to TNF inhibition showed a significantly greater activation volume in thalamic, limbic, and associative areas of the brain than non-responders. Infections are the main risk of therapies with biologic drugs and infections have been shown to be related to disease flares in RA. Recent basic science data has also emerged suggesting that bacterial components including lipopolysaccharide induce pain by directly activating sensory neurons that modulate inflammation, a previously unsuspected role for the nervous system in host-pathogen interactions. In this review, we discuss the current evidence for neuro-inflammation as an important factor that impacts on disease persistence and pain in RA. PMID:25414636

Numerical investigation and Uncertainty Quantification of the Impact of the geological and geomechanical properties on the seismo-acoustic responses of underground chemical explosions

NASA Astrophysics Data System (ADS)

Ezzedine, S. M.; Pitarka, A.; Vorobiev, O.; Glenn, L.; Antoun, T.

2017-12-01

We have performed three-dimensional high resolution simulations of underground chemical explosions conducted recently in jointed rock outcrop as part of the Source Physics Experiments (SPE) being conducted at the Nevada National Security Site (NNSS). The main goal of the current study is to investigate the effects of the structural and geomechanical properties on the spall phenomena due to underground chemical explosions and its subsequent effect on the seismo-acoustic signature at far distances. Two parametric studies have been undertaken to assess the impact of different 1) conceptual geological models including a single layer and two layers model, with and without joints and with and without varying geomechanical properties, and 2) depth of bursts of the chemical explosions and explosion yields. Through these investigations we have explored not only the near-field response of the chemical explosions but also the far-field responses of the seismic and the acoustic signatures. The near-field simulations were conducted using the Eulerian and Lagrangian codes, GEODYN and GEODYN -L, respectively, while the far-field seismic simulations were conducted using the elastic wave propagation code, WPP, and the acoustic response using the Kirchhoff-Helmholtz-Rayleigh time-dependent approximation code, KHR. Though a series of simulations we have recorded the velocity field histories a) at the ground surface on an acoustic-source-patch for the acoustic simulations, and 2) on a seismic-source-box for the seismic simulations. We first analyzed the SPE3 experimental data and simulated results, then simulated SPE4-prime, SPE5, and SPE6 to anticipate their seismo-acoustic responses given conditions of uncertainties. SPE experiments were conducted in a granitic formation; we have extended the parametric study to include other geological settings such dolomite and alluvial formations. These parametric studies enabled us 1) investigating the geotechnical and geophysical key parameters that impact the seismo-acoustic responses of underground chemical explosions and 2) deciphering and ranking through a global sensitivity analysis the most important key parameters to be characterized on site to minimize uncertainties in prediction and discrimination.

Sex differences in amphetamine-induced displacement of [(18)F]fallypride in striatal and extrastriatal regions: a PET study.

PubMed

Riccardi, Patrizia; Zald, David; Li, Rui; Park, Sohee; Ansari, M Sib; Dawant, Benoit; Anderson, Sharlet; Woodward, Neil; Schmidt, Dennis; Baldwin, Ronald; Kessler, Robert

2006-09-01

The authors examined gender differences in d-amphetamine-induced displacements of [(18)F]fallypride in the striatal and extrastriatal brain regions and the correlations of these displacements with cognition and sensation seeking. Six women and seven men underwent positron emission tomography (PET) with [(18)F]fallypride before and after an oral dose of d-amphetamine. Percent displacements were calculated using regions of interest and parametric images of dopamine 2 (D(2)) receptor binding potential. Parametric images of dopamine release suggest that the female subjects had greater dopamine release than the male subjects in the right globus pallidus and right inferior frontal gyrus. Gender differences were observed in correlations of changes in cognition and sensation seeking with regional dopamine release. Findings revealed a greater dopamine release in women as well as gender differences in the relationship between regional dopamine release and sensation seeking and cognition.

Perceptual reversals during binocular rivalry: ERP components and their concomitant source differences.

PubMed

Britz, Juliane; Pitts, Michael A

2011-11-01

We used an intermittent stimulus presentation to investigate event-related potential (ERP) components associated with perceptual reversals during binocular rivalry. The combination of spatiotemporal ERP analysis with source imaging and statistical parametric mapping of the concomitant source differences yielded differences in three time windows: reversals showed increased activity in early visual (∼120 ms) and in inferior frontal and anterior temporal areas (∼400-600 ms) and decreased activity in the ventral stream (∼250-350 ms). The combination of source imaging and statistical parametric mapping suggests that these differences were due to differences in generator strength and not generator configuration, unlike the initiation of reversals in right inferior parietal areas. These results are discussed within the context of the extensive network of brain areas that has been implicated in the initiation, implementation, and appraisal of bistable perceptual reversals. Copyright © 2011 Society for Psychophysiological Research.

NIRS-SPM: statistical parametric mapping for near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tak, Sungho; Jang, Kwang Eun; Jung, Jinwook; Jang, Jaeduck; Jeong, Yong; Ye, Jong Chul

2008-02-01

Even though there exists a powerful statistical parametric mapping (SPM) tool for fMRI, similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Specifically, NIRS-SPM statistically analyzes the NIRS data using GLM and makes inference as the excursion probability which comes from the random field that are interpolated from the sparse measurement. In order to obtain correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS signal with fMRI, the spatial mapping between fMRI image and real coordinate in 3-D digitizer is estimated using Horn's algorithm. These powerful tools allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.

Thermal Analysis of a Carbon Fiber Rope Barrier for Use in the Reusable Solid Rocket Motor Nozzle Joint-2

NASA Technical Reports Server (NTRS)

Clayton, J. Louie

2002-01-01

This study provides development and verification of analysis methods used to assess performance of a carbon fiber rope (CFR) thermal barrier system that is currently being qualified for use in Reusable Solid Rocket Motor (RSRM) nozzle joint-2. Modeled geometry for flow calculations considers the joint to be vented with the porous CFR barriers placed in the 'open' assembly gap. Model development is based on a 1-D volume filling approach where flow resistances (assembly gap and CFRs) are defined by serially connected internal flow and the porous media 'Darcy' relationships. Combustion gas flow rates are computed using the volume filling code by assuming a lumped distribution total joint fill volume on a per linear circumferential inch basis. Gas compressibility, friction and heat transfer are included in the modeling. Gas-to-wall heat transfer is simulated by concurrent solution of the compressible flow equations and a large thermal 2-D finite element (FE) conduction grid. The derived numerical technique loosely couples the FE conduction matrix with the compressible gas flow equations. Free constants that appear in the governing equations are calibrated by parametric model comparison to hot fire subscale test results. The calibrated model is then used to make full-scale motor predictions using RSRM aft dome environments. Model results indicate that CFR thermal barrier systems will provide a thermally benign and controlled pressurization environment for the RSRM nozzle joint-2 primary seal activation.

Thermal Analysis of a Carbon Fiber Rope Barrier for Use in the Reusable Solid Rocket Motor Nozzle Joint-2

NASA Technical Reports Server (NTRS)

Clayton, J. Louie; Phelps, Lisa (Technical Monitor)

2001-01-01

This study provides for development and verification of analysis methods used to assess performance of a carbon fiber rope (CFR) thermal barrier system that is currently being qualified for use in Reusable Solid Rocket Motor (RSRM) nozzle joint-2. Modeled geometry for flow calculations considers the joint to be vented with the porous CFR barriers placed in the "open' assembly gap. Model development is based on a 1-D volume filling approach where flow resistances (assembly gap and CFRs) are defined by serially connected internal flow and the porous media "Darcy" relationships. Combustion gas flow rates are computed using the volume filling code by assuming a lumped distribution total joint fill volume on a per linear circumferential inch basis. Gas compressibility, friction and heat transfer are included in the modeling. Gas-to-wall heat transfer is simulated by concurrent solution of the compressible flow equations and a large thermal 2-D finite element (FE) conduction grid. The derived numerical technique loosely couples the FE conduction matrix with the compressible gas flow equations, Free constants that appear in the governing equations are calibrated by parametric model comparison to hot fire subscale test results. The calibrated model is then used to make full-scale motor predictions using RSRM aft dome environments. Model results indicate that CFR thermal barrier systems will provide a thermally benign and controlled pressurization environment for the RSRM nozzle joint-2 primary seal activation.

Nonlinear changes in brain activity during continuous word repetition: an event-related multiparametric functional MR imaging study.

PubMed

Hagenbeek, R E; Rombouts, S A R B; Veltman, D J; Van Strien, J W; Witter, M P; Scheltens, P; Barkhof, F

2007-10-01

Changes in brain activation as a function of continuous multiparametric word recognition have not been studied before by using functional MR imaging (fMRI), to our knowledge. Our aim was to identify linear changes in brain activation and, what is more interesting, nonlinear changes in brain activation as a function of extended word repetition. Fifteen healthy young right-handed individuals participated in this study. An event-related extended continuous word-recognition task with 30 target words was used to study the parametric effect of word recognition on brain activation. Word-recognition-related brain activation was studied as a function of 9 word repetitions. fMRI data were analyzed with a general linear model with regressors for linearly changing signal intensity and nonlinearly changing signal intensity, according to group average reaction time (RT) and individual RTs. A network generally associated with episodic memory recognition showed either constant or linearly decreasing brain activation as a function of word repetition. Furthermore, both anterior and posterior cingulate cortices and the left middle frontal gyrus followed the nonlinear curve of the group RT, whereas the anterior cingulate cortex was also associated with individual RT. Linear alteration in brain activation as a function of word repetition explained most changes in blood oxygen level-dependent signal intensity. Using a hierarchically orthogonalized model, we found evidence for nonlinear activation associated with both group and individual RTs.

Spatial working memory in heavy cannabis users: a functional magnetic resonance imaging study.

PubMed

Kanayama, Gen; Rogowska, Jadwiga; Pope, Harrison G; Gruber, Staci A; Yurgelun-Todd, Deborah A

2004-11-01

Many neuropsychological studies have documented deficits in working memory among recent heavy cannabis users. However, little is known about the effects of cannabis on brain activity. We assessed brain function among recent heavy cannabis users while they performed a working memory task. Functional magnetic resonance imaging was used to examine brain activity in 12 long-term heavy cannabis users, 6-36 h after last use, and in 10 control subjects while they performed a spatial working memory task. Regional brain activation was analyzed and compared using statistical parametric mapping techniques. Compared with controls, cannabis users exhibited increased activation of brain regions typically used for spatial working memory tasks (such as prefrontal cortex and anterior cingulate). Users also recruited additional regions not typically used for spatial working memory (such as regions in the basal ganglia). These findings remained essentially unchanged when re-analyzed using subjects' ages as a covariate. Brain activation showed little or no significant correlation with subjects' years of education, verbal IQ, lifetime episodes of cannabis use, or urinary cannabinoid levels at the time of scanning. Recent cannabis users displayed greater and more widespread brain activation than normal subjects when attempting to perform a spatial working memory task. This observation suggests that recent cannabis users may experience subtle neurophysiological deficits, and that they compensate for these deficits by "working harder"-calling upon additional brain regions to meet the demands of the task.

Absence of gender effect on children with attention-deficit/hyperactivity disorder as assessed by optimized voxel-based morphometry.

PubMed

Yang, Pinchen; Wang, Pei-Ning; Chuang, Kai-Hsiang; Jong, Yuh-Jyh; Chao, Tzu-Cheng; Wu, Ming-Ting

2008-12-30

Brain abnormalities, as determined by structural magnetic resonance imaging (MRI), have been reported in patients with attention-deficit hyperactivity disorder (ADHD); however, female subjects have been underrepresented in previous reports. In this study, we used optimized voxel-based morphometry to compare the total and regional gray matter volumes between groups of 7- to 17-year-old ADHD and healthy children (total 114 subjects). Fifty-seven children with ADHD (n=57, 35 males and 22 females) and healthy children (n=57) received MRI scans. Segmented brain MRI images were normalized into standardized stereotactic space, modulated to allow volumetric analysis, smoothed and compared at the voxel level with statistical parametric mapping. Global volumetric comparisons between groups revealed that the total brain volumes of ADHD children were smaller than those of the control children. As for the regional brain analysis, the brain volumes of ADHD children were found to be bilaterally smaller in the following regions as compared with normal control values: the caudate nucleus and the cerebellum. There were two clusters of regional decrease in the female brain, left posterior cingulum and right precuneus, as compared with the male brain. Brain regions showing the interaction effect of diagnosis and gender were negligible. These results were consistent with the hypothesized dysfunctional systems in ADHD, and they also suggested that neuroanatomical abnormalities in ADHD were not influenced by gender.

Sinus MRI scan

MedlinePlus

... your body: Brain aneurysm clips Certain types of artificial heart valves Heart defibrillator or pacemaker Inner ear (cochlear) implants Recently placed artificial joints Certain types of vascular stents Pain pumps ...

Spatial Attention, Motor Intention, and Bayesian Cue Predictability in the Human Brain.

PubMed

Kuhns, Anna B; Dombert, Pascasie L; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2017-05-24

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain. Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.

A case study of the Weather Research and Forecasting model applied to the Joint Urban 2003 tracer field experiment. Part 2: Gas tracer dispersion

DOE PAGES

Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.; ...

2016-07-28

Here, the Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The firstmore » method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model’s Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.« less

A case study of the Weather Research and Forecasting model applied to the Joint Urban 2003 tracer field experiment. Part 2: Gas tracer dispersion

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

Nelson, Matthew A.; Brown, Michael J.; Halverson, Scot A.

Here, the Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The firstmore » method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model’s Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.« less

The adaptive nature of eye movements in linguistic tasks: how payoff and architecture shape speed-accuracy trade-offs.

PubMed

Lewis, Richard L; Shvartsman, Michael; Singh, Satinder

2013-07-01

We explore the idea that eye-movement strategies in reading are precisely adapted to the joint constraints of task structure, task payoff, and processing architecture. We present a model of saccadic control that separates a parametric control policy space from a parametric machine architecture, the latter based on a small set of assumptions derived from research on eye movements in reading (Engbert, Nuthmann, Richter, & Kliegl, 2005; Reichle, Warren, & McConnell, 2009). The eye-control model is embedded in a decision architecture (a machine and policy space) that is capable of performing a simple linguistic task integrating information across saccades. Model predictions are derived by jointly optimizing the control of eye movements and task decisions under payoffs that quantitatively express different desired speed-accuracy trade-offs. The model yields distinct eye-movement predictions for the same task under different payoffs, including single-fixation durations, frequency effects, accuracy effects, and list position effects, and their modulation by task payoff. The predictions are compared to-and found to accord with-eye-movement data obtained from human participants performing the same task under the same payoffs, but they are found not to accord as well when the assumptions concerning payoff optimization and processing architecture are varied. These results extend work on rational analysis of oculomotor control and adaptation of reading strategy (Bicknell & Levy, ; McConkie, Rayner, & Wilson, 1973; Norris, 2009; Wotschack, 2009) by providing evidence for adaptation at low levels of saccadic control that is shaped by quantitatively varying task demands and the dynamics of processing architecture. Copyright © 2013 Cognitive Science Society, Inc.

The unrest of S. Miguel volcano (El Salvador, CA): installation of the monitoring network and observed volcano-tectonic ground deformation

NASA Astrophysics Data System (ADS)

Bonforte, A.; Hernandez, D.; Gutiérrez, E.; Handal, L.; Polío, C.; Rapisarda, S.; Scarlato, P.

2015-10-01

On 29 December 2013, the Chaparrastique volcano in El Salvador, close to the town of S. Miguel, erupted suddenly with explosive force, forming a more than 9 km high column and projecting ballistic projectiles as far as 3 km away. Pyroclastic Density Currents flowed to the north-northwest side of the volcano, while tephras were dispersed northwest and north-northeast. This sudden eruption prompted the local Ministry of Environment to request cooperation with Italian scientists in order to improve the monitoring of the volcano during this unrest. A joint force made up of an Italian team from the Istituto Nazionale di Geofisica e Vulcanologia and a local team from the Ministerio de Medio Ambiente y Recursos Naturales was organized to enhance the volcanological, geophysical and geochemical monitoring system to study the evolution of the phenomenon during the crisis. The joint team quickly installed a multi-parametric mobile network comprising seismic, geodetic and geochemical sensors, designed to cover all the volcano flanks from the lowest to the highest possible altitudes, and a thermal camera. To simplify the logistics for a rapid installation and for security reasons, some sensors were co-located into multi-parametric stations. Here, we describe the prompt design and installation of the geodetic monitoring network, the processing and results. The installation of a new ground deformation network can be considered an important result by itself, while the detection of some crucial deforming areas is very significant information, useful for dealing with future threats and for further studies on this poorly monitored volcano.

Negative Influence of Motor Impairments on Upper Limb Movement Patterns in Children with Unilateral Cerebral Palsy. A Statistical Parametric Mapping Study

PubMed Central

Simon-Martinez, Cristina; Jaspers, Ellen; Mailleux, Lisa; Desloovere, Kaat; Vanrenterghem, Jos; Ortibus, Els; Molenaers, Guy; Feys, Hilde; Klingels, Katrijn

2017-01-01

Upper limb three-dimensional movement analysis (UL-3DMA) offers a reliable and valid tool to evaluate movement patterns in children with unilateral cerebral palsy (uCP). However, it remains unknown to what extent the underlying motor impairments explain deviant movement patterns. Such understanding is key to develop efficient rehabilitation programs. Although UL-3DMA has been shown to be a useful tool to assess movement patterns, it results in a multitude of data, challenging the clinical interpretation and consequently its implementation. UL-3DMA reports are often reduced to summary metrics, such as average or peak values per joint. However, these metrics do not take into account the continuous nature of the data or the interdependency between UL joints, and do not provide phase-specific information of the movement pattern. Moreover, summary metrics may not be sensitive enough to estimate the impact of motor impairments. Recently, Statistical Parametric Mapping (SPM) was proposed to overcome these problems. We collected UL-3DMA of 60 children with uCP and 60 typically developing children during eight functional tasks and evaluated the impact of spasticity and muscle weakness on UL movement patterns. SPM vector field analysis was used to analyze movement patterns at the level of five joints (wrist, elbow, shoulder, scapula, and trunk). Children with uCP showed deviant movement patterns in all joints during a large percentage of the movement cycle. Spasticity and muscle weakness negatively impacted on UL movement patterns during all tasks, which resulted in increased wrist flexion, elbow pronation and flexion, increased shoulder external rotation, decreased shoulder elevation with a preference for movement in the frontal plane and increased trunk internal rotation. Scapular position was altered during movement initiation, although scapular movements were not affected by muscle weakness or spasticity. In conclusion, we identified pathological movement patterns in children with uCP and additionally mapped the negative impact of spasticity and muscle weakness on these movement patterns, providing useful insights that will contribute to treatment planning. Last, we also identified a subset of the most relevant tasks for studying UL movements in children with uCP, which will facilitate the interpretation of UL-3DMA data and undoubtedly contribute to its clinical implementation. PMID:29051729

Beyond Hemispheric Dominance: Brain Regions Underlying the Joint Lateralization of Language and Arithmetic to the Left Hemisphere

ERIC Educational Resources Information Center

Pinel, Philippe; Dehaene, Stanislas

2010-01-01

Language and arithmetic are both lateralized to the left hemisphere in the majority of right-handed adults. Yet, does this similar lateralization reflect a single overall constraint of brain organization, such an overall "dominance" of the left hemisphere for all linguistic and symbolic operations? Is it related to the lateralization of specific…

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

PubMed Central

Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

2016-01-01

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping

PubMed Central

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-01-01

Background Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. Methods The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). Results A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. Conclusion The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques. PMID:18312639

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping.

PubMed

McGoron, Anthony J; Capille, Michael; Georgiou, Michael F; Sanchez, Pablo; Solano, Juan; Gonzalez-Brito, Manuel; Kuluz, John W

2008-02-29

Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets. The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM). A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM. The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques.

Influence of chronic bromocriptine and levodopa administration on cerebral type 1 cannabinoid receptor binding.

PubMed

Casteels, Cindy; Vanbilloen, Bert; Vercammen, Dorien; Bosier, Barbara; Lambert, Didier M; Bormans, Guy; Van Laere, Koen

2010-08-01

The endocannabinoid system is an important modulatory system in the brain. Complex interactions with brain dopaminergic circuits have been demonstrated. The aim of this study was to investigate the in vivo effect of the commonly used antiparkinsonian drugs, levodopa (L-DOPA) and bromocriptine, on type 1 cannabinoid (CB1) receptors, using the PET radioligand [(18)F]MK-9470. Seventeen female Wistar rats were studied at baseline and after chronic exposure to either L-DOPA (6 mg/kg/day with 1.5 mg/kg/day carbidopa; n = 6), bromocriptine (4 mg/kg/day; n = 5), or saline (n = 6). [(18)F]MK-9470 binding was assessed in vivo using small animal PET imaging. [(18)F]MK-9470 parametric images were generated, anatomically standardized to Paxinos space and analyzed by voxel-based statistical parametric mapping (SPM2) and a predefined volume-of-interest (VOI) approach. In a 2 x 2 analysis design (condition vs. treatment), no significant changes in absolute or relative [(18)F]MK-9470 binding were present upon chronic exposure to L-DOPA or bromocriptine as compared to saline treatment. The post hoc comparison of chronic scans to baseline within each treatment modality showed regional increases in relative [(18)F]MK-9470 binding in the thalamus (peak average value +6.3%) and in the sensorimotor cortex and hippocampus (peak average value +10.2%) after bromocriptine exposure, while no changes were found for L-DOPA. Chronic administration of L-DOPA and bromocriptine at the applied doses does not produce major cerebral changes in in vivo cannabinoid CB1 receptor binding of [(18)F]MK-9470 in the rat brain. These results also suggest that similar chronic L-DOPA and bromocriptine usage is unlikely to interfere with human PET imaging in healthy conditions using this radioligand.

Multivariate decoding of brain images using ordinal regression.

PubMed

Doyle, O M; Ashburner, J; Zelaya, F O; Williams, S C R; Mehta, M A; Marquand, A F

2013-11-01

Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states. In these examples, the variable (target) we want to predict is ordinal in nature. Conventional classification schemes assume that the targets are nominal and hence ignore their ranked nature, whereas parametric and/or non-parametric regression models enforce a metric notion of distance between classes. Here, we propose a novel, alternative multivariate approach that overcomes these limitations - whole brain probabilistic ordinal regression using a Gaussian process framework. We applied this technique to two data sets of pharmacological neuroimaging data from healthy volunteers. The first study was designed to investigate the effect of ketamine on brain activity and its subsequent modulation with two compounds - lamotrigine and risperidone. The second study investigates the effect of scopolamine on cerebral blood flow and its modulation using donepezil. We compared ordinal regression to multi-class classification schemes and metric regression. Considering the modulation of ketamine with lamotrigine, we found that ordinal regression significantly outperformed multi-class classification and metric regression in terms of accuracy and mean absolute error. However, for risperidone ordinal regression significantly outperformed metric regression but performed similarly to multi-class classification both in terms of accuracy and mean absolute error. For the scopolamine data set, ordinal regression was found to outperform both multi-class and metric regression techniques considering the regional cerebral blood flow in the anterior cingulate cortex. Ordinal regression was thus the only method that performed well in all cases. Our results indicate the potential of an ordinal regression approach for neuroimaging data while providing a fully probabilistic framework with elegant approaches for model selection. Copyright © 2013. Published by Elsevier Inc.

Pharmacologic Modulation of Hand Pain in Osteoarthritis: A Double-Blind Placebo-Controlled Functional Magnetic Resonance Imaging Study Using Naproxen

PubMed Central

Sanders, Duncan; Krause, Kristina; O'Muircheartaigh, Jonathan; Thacker, Michael A; Huggins, John P; Vennart, William; Massat, Nathalie J; Choy, Ernest; Williams, Steven C R; Howard, Matthew A

2015-01-01

Objective In an attempt to shed light on management of chronic pain conditions, there has long been a desire to complement behavioral measures of pain perception with measures of underlying brain mechanisms. Using functional magnetic resonance imaging (fMRI), we undertook this study to investigate changes in brain activity following the administration of naproxen or placebo in patients with pain related to osteoarthritis (OA) of the carpometacarpal (CMC) joint. Methods A placebo-controlled, double-blind, 2-period crossover study was performed in 19 individuals with painful OA of the CMC joint of the right hand. Following placebo or naproxen treatment periods, a functionally relevant task was performed, and behavioral measures of the pain experience were collected in identical fMRI examinations. Voxelwise and a priori region of interest analyses were performed to detect between-period differences in brain activity. Results Significant reductions in brain activity following treatment with naproxen, compared to placebo, were observed in brain regions commonly associated with pain perception, including the bilateral primary somatosensory cortex, thalamus, and amygdala. Significant relationships between changes in perceived pain intensity and changes in brain activity were also observed in brain regions previously associated with pain intensity. Conclusion This study demonstrates the sensitivity of fMRI to detect the mechanisms underlying treatments of known efficacy. The data illustrate the enticing potential of fMRI as an adjunct to self-report for detecting early signals of efficacy of novel therapies, both pharmacologic and nonpharmacologic, in small numbers of individuals with persistent pain. PMID:25533872

Computational Pipeline for NIRS-EEG Joint Imaging of tDCS-Evoked Cerebral Responses-An Application in Ischemic Stroke.

PubMed

Guhathakurta, Debarpan; Dutta, Anirban

2016-01-01

Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about -15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization.

Computational Pipeline for NIRS-EEG Joint Imaging of tDCS-Evoked Cerebral Responses—An Application in Ischemic Stroke

PubMed Central

Guhathakurta, Debarpan; Dutta, Anirban

2016-01-01

Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about −15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization. PMID:27378836

The Brain Circuitry Underlying the Temporal Evolution of Nausea in Humans

PubMed Central

Sheehan, James D.; Kim, Jieun; LaCount, Lauren T.; Park, Kyungmo; Kaptchuk, Ted J.; Rosen, Bruce R.; Kuo, Braden

2013-01-01

Nausea is a universal human experience. It evolves slowly over time, and brain mechanisms underlying this evolution are not well understood. Our functional magnetic resonance imaging (fMRI) approach evaluated brain activity contributing to and arising from increasing motion sickness. Subjects rated transitions to increasing nausea, produced by visually induced vection within the fMRI environment. We evaluated parametrically increasing brain activity 1) precipitating increasing nausea and 2) following transition to stronger nausea. All subjects demonstrated visual stimulus–associated activation (P < 0.01) in primary and extrastriate visual cortices. In subjects experiencing motion sickness, increasing phasic activity preceding nausea was found in amygdala, putamen, and dorsal pons/locus ceruleus. Increasing sustained response following increased nausea was found in a broader network including insular, anterior cingulate, orbitofrontal, somatosensory and prefrontal cortices. Moreover, sustained anterior insula activation to strong nausea was correlated with midcingulate activation (r = 0.87), suggesting a closer linkage between these specific regions within the brain circuitry subserving nausea perception. Thus, while phasic activation in fear conditioning and noradrenergic brainstem regions precipitates transition to strong nausea, sustained activation following this transition occurs in a broader interoceptive, limbic, somatosensory, and cognitive network, reflecting the multiple dimensions of this aversive commonly occurring symptom. PMID:22473843

The brain circuitry underlying the temporal evolution of nausea in humans.

PubMed

Napadow, Vitaly; Sheehan, James D; Kim, Jieun; Lacount, Lauren T; Park, Kyungmo; Kaptchuk, Ted J; Rosen, Bruce R; Kuo, Braden

2013-04-01

Nausea is a universal human experience. It evolves slowly over time, and brain mechanisms underlying this evolution are not well understood. Our functional magnetic resonance imaging (fMRI) approach evaluated brain activity contributing to and arising from increasing motion sickness. Subjects rated transitions to increasing nausea, produced by visually induced vection within the fMRI environment. We evaluated parametrically increasing brain activity 1) precipitating increasing nausea and 2) following transition to stronger nausea. All subjects demonstrated visual stimulus-associated activation (P < 0.01) in primary and extrastriate visual cortices. In subjects experiencing motion sickness, increasing phasic activity preceding nausea was found in amygdala, putamen, and dorsal pons/locus ceruleus. Increasing sustained response following increased nausea was found in a broader network including insular, anterior cingulate, orbitofrontal, somatosensory and prefrontal cortices. Moreover, sustained anterior insula activation to strong nausea was correlated with midcingulate activation (r = 0.87), suggesting a closer linkage between these specific regions within the brain circuitry subserving nausea perception. Thus, while phasic activation in fear conditioning and noradrenergic brainstem regions precipitates transition to strong nausea, sustained activation following this transition occurs in a broader interoceptive, limbic, somatosensory, and cognitive network, reflecting the multiple dimensions of this aversive commonly occurring symptom.

Changes of Brain Glucose Metabolism in the Pretreatment Patients with Non-Small Cell Lung Cancer: A Retrospective PET/CT Study.

PubMed

Zhang, Weishan; Ning, Ning; Li, Xianjun; Niu, Gang; Bai, Lijun; Guo, Youmin; Yang, Jian

2016-01-01

The tumor-to-brain communication has been emphasized by recent converging evidences. This study aimed to compare the difference of brain glucose metabolism between patients with non-small cell lung cancer (NSCLC) and control subjects. NSCLC patients prior to oncotherapy and control subjects without malignancy confirmed by 6 months follow-up were collected and underwent the resting state 18F-fluoro-D-glucose (FDG) PET/CT. Normalized FDG metabolism was calculated by a signal intensity ratio of each brain region to whole brain. Brain glucose metabolism was compared between NSCLC patients and control group using two samples t-test and multivariate test by statistical parametric maps (SPM) software. Compared with the control subjects (n = 76), both brain glucose hyper- and hypometabolism regions with significant statistical differences (P<0.01) were found in the NSCLC patients (n = 83). The hypermetabolism regions (bilateral insula, putamen, pallidum, thalamus, hippocampus and amygdala, the right side of cerebellum, orbital part of right inferior frontal gyrus and vermis) were component parts of visceral to brain signal transduction pathways, and the hypometabolism regions (the left superior parietal lobule, bilateral inferior parietal lobule and left fusiform gyrus) lied in dorsal attention network and visuospatial function areas. The changes of brain glucose metabolism exist in NSCLC patients prior to oncotherapy, which might be attributed to lung-cancer related visceral sympathetic activation and decrease of dorsal attention network function.

Taking two to tango: fMRI analysis of improvised joint action with physical contact

PubMed Central

Belyk, Michel; Brown, Steven

2018-01-01

Many forms of joint action involve physical coupling between the participants, such as when moving a sofa together or dancing a tango. We report the results of a novel two-person functional MRI study in which trained couple dancers engaged in bimanual contact with an experimenter standing next to the bore of the magnet, and in which the two alternated between being the leader and the follower of joint improvised movements. Leading showed a general pattern of self-orientation, being associated with brain areas involved in motor planning, navigation, sequencing, action monitoring, and error correction. In contrast, following showed a far more sensory, externally-oriented pattern, revealing areas involved in somatosensation, proprioception, motion tracking, social cognition, and outcome monitoring. We also had participants perform a “mutual” condition in which the movement patterns were pre-learned and the roles were symmetric, thereby minimizing any tendency toward either leading or following. The mutual condition showed greater activity in brain areas involved in mentalizing and social reward than did leading or following. Finally, the analysis of improvisation revealed the dual importance of motor-planning and working-memory areas. We discuss these results in terms of theories of both joint action and improvisation. PMID:29324862

Rubber Hand Illusion Affects Joint Angle Perception

PubMed Central

Butz, Martin V.; Kutter, Esther F.; Lorenz, Corinna

2014-01-01

The Rubber Hand Illusion (RHI) is a well-established experimental paradigm. It has been shown that the RHI can affect hand location estimates, arm and hand motion towards goals, the subjective visual appearance of the own hand, and the feeling of body ownership. Several studies also indicate that the peri-hand space is partially remapped around the rubber hand. Nonetheless, the question remains if and to what extent the RHI can affect the perception of other body parts. In this study we ask if the RHI can alter the perception of the elbow joint. Participants had to adjust an angular representation on a screen according to their proprioceptive perception of their own elbow joint angle. The results show that the RHI does indeed alter the elbow joint estimation, increasing the agreement with the position and orientation of the artificial hand. Thus, the results show that the brain does not only adjust the perception of the hand in body-relative space, but it also modifies the perception of other body parts. In conclusion, we propose that the brain continuously strives to maintain a consistent internal body image and that this image can be influenced by the available sensory information sources, which are mediated and mapped onto each other by means of a postural, kinematic body model. PMID:24671172

The power of emotional valence-from cognitive to affective processes in reading.

PubMed

Altmann, Ulrike; Bohrn, Isabel C; Lubrich, Oliver; Menninghaus, Winfried; Jacobs, Arthur M

2012-01-01

The comprehension of stories requires the reader to imagine the cognitive and affective states of the characters. The content of many stories is unpleasant, as they often deal with conflict, disturbance or crisis. Nevertheless, unpleasant stories can be liked and enjoyed. In this fMRI study, we used a parametric approach to examine (1) the capacity of increasing negative valence of story contents to activate the mentalizing network (cognitive and affective theory of mind, ToM), and (2) the neural substrate of liking negatively valenced narratives. A set of 80 short narratives was compiled, ranging from neutral to negative emotional valence. For each story mean rating values on valence and liking were obtained from a group of 32 participants in a prestudy, and later included as parametric regressors in the fMRI analysis. Another group of 24 participants passively read the narratives in a three Tesla MRI scanner. Results revealed a stronger engagement of affective ToM-related brain areas with increasingly negative story valence. Stories that were unpleasant, but simultaneously liked, engaged the medial prefrontal cortex (mPFC), which might reflect the moral exploration of the story content. Further analysis showed that the more the mPFC becomes engaged during the reading of negatively valenced stories, the more coactivation can be observed in other brain areas related to the neural processing of affective ToM and empathy.

The power of emotional valence—from cognitive to affective processes in reading

PubMed Central

Altmann, Ulrike; Bohrn, Isabel C.; Lubrich, Oliver; Menninghaus, Winfried; Jacobs, Arthur M.

2012-01-01

The comprehension of stories requires the reader to imagine the cognitive and affective states of the characters. The content of many stories is unpleasant, as they often deal with conflict, disturbance or crisis. Nevertheless, unpleasant stories can be liked and enjoyed. In this fMRI study, we used a parametric approach to examine (1) the capacity of increasing negative valence of story contents to activate the mentalizing network (cognitive and affective theory of mind, ToM), and (2) the neural substrate of liking negatively valenced narratives. A set of 80 short narratives was compiled, ranging from neutral to negative emotional valence. For each story mean rating values on valence and liking were obtained from a group of 32 participants in a prestudy, and later included as parametric regressors in the fMRI analysis. Another group of 24 participants passively read the narratives in a three Tesla MRI scanner. Results revealed a stronger engagement of affective ToM-related brain areas with increasingly negative story valence. Stories that were unpleasant, but simultaneously liked, engaged the medial prefrontal cortex (mPFC), which might reflect the moral exploration of the story content. Further analysis showed that the more the mPFC becomes engaged during the reading of negatively valenced stories, the more coactivation can be observed in other brain areas related to the neural processing of affective ToM and empathy. PMID:22754519

Neural mechanisms of planning: A computational analysis using event-related fMRI

PubMed Central

Fincham, Jon M.; Carter, Cameron S.; van Veen, Vincent; Stenger, V. Andrew; Anderson, John R.

2002-01-01

To investigate the neural mechanisms of planning, we used a novel adaptation of the Tower of Hanoi (TOH) task and event-related functional MRI. Participants were trained in applying a specific strategy to an isomorph of the five-disk TOH task. After training, participants solved novel problems during event-related functional MRI. A computational cognitive model of the task was used to generate a reference time series representing the expected blood oxygen level-dependent response in brain areas involved in the manipulation and planning of goals. This time series was used as one term within a general linear modeling framework to identify brain areas in which the time course of activity varied as a function of goal-processing events. Two distinct time courses of activation were identified, one in which activation varied parametrically with goal-processing operations, and the other in which activation became pronounced only during goal-processing intensive trials. Regions showing the parametric relationship comprised a frontoparietal system and include right dorsolateral prefrontal cortex [Brodmann's area (BA 9)], bilateral parietal (BA 40/7), and bilateral premotor (BA 6) areas. Regions preferentially engaged only during goal-intensive processing include left inferior frontal gyrus (BA 44). The implications of these results for the current model, as well as for our understanding of the neural mechanisms of planning and functional specialization of the prefrontal cortex, are discussed. PMID:11880658

History of Suicide Attempt Is Associated with Reduced Medial Prefrontal Cortex Activity during Emotional Decision-Making among Men with Schizophrenia: An Exploratory fMRI Study.

PubMed

Potvin, Stéphane; Tikàsz, Andràs; Richard-Devantoy, Stéphane; Lungu, Ovidiu; Dumais, Alexandre

2018-01-01

Despite the high prevalence of suicidal ideas/attempts in schizophrenia, only a handful of neuroimaging studies have examined the neurobiological differences associated with suicide risk in this population. The main objective of the current exploratory study is to examine the neurofunctional correlates associated with a history of suicide attempt in schizophrenia, using a risky decision-making task, in order to show alterations in brain reward regions in this population. Thirty-two male outpatients with schizophrenia were recruited: 13 patients with (SCZ + S) and 19 without a history of suicidal attempt (SCZ - S). Twenty-one healthy men with no history of mental disorders or suicidal attempt/idea were also recruited. Participants were scanned using fMRI while performing the Balloon Analogue Risk Task . A rapid event-related fMRI paradigm was used, separating decision and outcome events, and the explosion probabilities were included as parametric modulators. The most important finding of this study is that SCZ + S patients had reduced activations of the medial prefrontal cortex during the success outcome event (with parametric modulation), relative to both SCZ - S patients and controls, as illustrated by a spatial conjunction analysis. These exploratory results suggest that a history of suicidal attempt in schizophrenia is associated with blunted brain reward activity during emotional decision-making.

History of Suicide Attempt Is Associated with Reduced Medial Prefrontal Cortex Activity during Emotional Decision-Making among Men with Schizophrenia: An Exploratory fMRI Study

PubMed Central

Richard-Devantoy, Stéphane; Dumais, Alexandre

2018-01-01

Despite the high prevalence of suicidal ideas/attempts in schizophrenia, only a handful of neuroimaging studies have examined the neurobiological differences associated with suicide risk in this population. The main objective of the current exploratory study is to examine the neurofunctional correlates associated with a history of suicide attempt in schizophrenia, using a risky decision-making task, in order to show alterations in brain reward regions in this population. Thirty-two male outpatients with schizophrenia were recruited: 13 patients with (SCZ + S) and 19 without a history of suicidal attempt (SCZ − S). Twenty-one healthy men with no history of mental disorders or suicidal attempt/idea were also recruited. Participants were scanned using fMRI while performing the Balloon Analogue Risk Task. A rapid event-related fMRI paradigm was used, separating decision and outcome events, and the explosion probabilities were included as parametric modulators. The most important finding of this study is that SCZ + S patients had reduced activations of the medial prefrontal cortex during the success outcome event (with parametric modulation), relative to both SCZ − S patients and controls, as illustrated by a spatial conjunction analysis. These exploratory results suggest that a history of suicidal attempt in schizophrenia is associated with blunted brain reward activity during emotional decision-making. PMID:29686902

Parametric modulation of neural activity by emotion in youth with bipolar disorder, severe mood dysregulation, and healthy subjects

PubMed Central

Thomas, Laura A.; Brotman, Melissa A.; Muhrer, Eli M.; Rosen, Brooke H.; Bones, Brian L.; Reynolds, Richard C.; Deveney, Christen; Pine, Daniel S.; Leibenluft, Ellen

2012-01-01

Context Youth with bipolar disorder (BD) and those with severe, non-episodic irritability (severe mood dysregulation, SMD) show amygdala dysfunction during face emotion processing. However, studies have not compared such patients to each other and to comparison subjects in neural responsiveness to subtle changes in face emotion; the ability to process such changes is important for social cognition. We employed a novel parametrically designed faces paradigm. Objective Using a parametrically morphed emotional faces task, we compared activation in the amygdala and across the brain in BD, SMD, and healthy volunteers (HV). Design Case-control study. Setting Government research institute. Participants 57 youths (19 BD, 15 SMD, 23 HV). Main Outcome Measure Blood oxygenated level dependent (BOLD) data. Neutral faces were morphed with angry and happy faces in 25% intervals; static face stimuli appeared for 3000ms. Subjects performed hostility or non-emotional facial feature (i.e., nose width) ratings. Slope of BOLD activity was calculated across neutral-to-angry (N→A) and neutral-to-happy (N→H) face stimuli. Results In HV, but not BD or SMD, there was a positive association between left amygdala activity and anger on the face. In the N→H whole brain analysis, BD and SMD modulated parietal, temporal, and medial-frontal areas differently from each other and from HV; with increasing facial-happiness, SMD increased, while BD decreased, activity in parietal, temporal, and frontal regions. Conclusions Youth with BD or SMD differ from HV in modulation of amygdala activity in response to small changes in facial anger displays. In contrast, BD and SMD show distinct perturbations in regions mediating attention and face processing in association with changes in the emotional intensity of facial happiness displays. These findings demonstrate similarities and differences in the neural correlates of face emotion processing in BD and SMD, suggesting these distinct clinical presentations may reflect differing pathologies along a mood disorders spectrum. PMID:23026912

Dielectric properties of dog brain tissue measured in vitro across the 0.3-3 GHz band.

PubMed

Mohammed, Beadaa; Bialkowski, Konstanty; Abbosh, Amin; Mills, Paul C; Bradley, Andrew P

2016-09-22

Dielectric properties of dead Greyhound female dogs' brain tissues at different ages were measured at room temperature across the frequency range of 0.3-3 GHz. Measurements were made on excised tissues, in vitro in the laboratory, to carry out dielectric tests on sample tissues. Each dataset for a brain tissue was parametrized using the Cole-Cole expression, and the relevant Cole-Cole parameters for four tissue types are provided. A comparison was made with the database available in literature for other animals and human brain tissue. Results of two types of tissues (white matter and skull) showed systematic variation in dielectric properties as a function of animal age, whereas no significant change related to age was noticed for other tissues. Results provide critical information regarding dielectric properties of animal tissues for a realistic animal head model that can be used to verify the validity and reliability of a microwave head scanner for animals prior to testing on live animals. Bioelectromagnetics. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

PET imaging and quantitation of Internet-addicted patients and normal controls

NASA Astrophysics Data System (ADS)

Jeong, Ha-Kyu; Kim, Hee-Joung; Jung, Haijo; Son, Hye-Kyung; Kim, Dong-Hyeon; Yun, Mijin; Shin, Yee-Jin; Lee, Jong-Doo

2002-04-01

Internet addicted patients (IAPs) have widely been increased, as Internet games are becoming very popular in daily life. The purpose of this study was to investigate regional brain activation patterns associated with excessive use of Internet games in adolescents. Six normal controls (NCs) and eight IAPs who were classified as addiction group by adapted version of DSM-IV for pathologic gambling were participated. 18F-FDG PET studies were performed for all adolescents at their rest and activated condition after 20 minutes of each subject's favorite Internet game. To investigate quantitative metabolic differences in both groups, all possible combinations of group comparison were carried out using Statistical Parametric Mapping (SPM 99). Regional brain activation foci were identified on Talairach coordinate. SPM results showed increased metabolic activation in occipital lobes for both groups. Higher metabolisms were seen at resting condition in IAPs than that of in NCs. In comparison to both groups, IAPs showed different patterns of regional brain metabolic activation compared with that of NCs. It suggests that addictive use of Internet games may result in functional alteration of developing brain in adolescents.

Common and distinct networks underlying reward valence and processing stages: A meta-analysis of functional neuroimaging studies

PubMed Central

Liu, Xun; Hairston, Jacqueline; Schrier, Madeleine; Fan, Jin

2011-01-01

To better understand the reward circuitry in human brain, we conducted activation likelihood estimation (ALE) and parametric voxel-based meta-analyses (PVM) on 142 neuroimaging studies that examined brain activation in reward-related tasks in healthy adults. We observed several core brain areas that participated in reward-related decision making, including the nucleus accumbens (NAcc), caudate, putamen, thalamus, orbitofrontal cortex (OFC), bilateral anterior insula, anterior (ACC) and posterior (PCC) cingulate cortex, as well as cognitive control regions in the inferior parietal lobule and prefrontal cortex (PFC). The NAcc was commonly activated by both positive and negative rewards across various stages of reward processing (e.g., anticipation, outcome, and evaluation). In addition, the medial OFC and PCC preferentially responded to positive rewards, whereas the ACC, bilateral anterior insula, and lateral PFC selectively responded to negative rewards. Reward anticipation activated the ACC, bilateral anterior insula, and brain stem, whereas reward outcome more significantly activated the NAcc, medial OFC, and amygdala. Neurobiological theories of reward-related decision making should therefore distributed and interrelated representations of reward valuation and valence assessment into account. PMID:21185861

Application of multivariate Gaussian detection theory to known non-Gaussian probability density functions

NASA Astrophysics Data System (ADS)

Schwartz, Craig R.; Thelen, Brian J.; Kenton, Arthur C.

1995-06-01

A statistical parametric multispectral sensor performance model was developed by ERIM to support mine field detection studies, multispectral sensor design/performance trade-off studies, and target detection algorithm development. The model assumes target detection algorithms and their performance models which are based on data assumed to obey multivariate Gaussian probability distribution functions (PDFs). The applicability of these algorithms and performance models can be generalized to data having non-Gaussian PDFs through the use of transforms which convert non-Gaussian data to Gaussian (or near-Gaussian) data. An example of one such transform is the Box-Cox power law transform. In practice, such a transform can be applied to non-Gaussian data prior to the introduction of a detection algorithm that is formally based on the assumption of multivariate Gaussian data. This paper presents an extension of these techniques to the case where the joint multivariate probability density function of the non-Gaussian input data is known, and where the joint estimate of the multivariate Gaussian statistics, under the Box-Cox transform, is desired. The jointly estimated multivariate Gaussian statistics can then be used to predict the performance of a target detection algorithm which has an associated Gaussian performance model.

Cross-Shear Implementation in Sliding-Distance-Coupled Finite Element Analysis of Wear in Metal-on-Polyethylene Total Joint Arthroplasty: Intervertebral Total Disc Replacement as an Illustrative Application

PubMed Central

Goreham-Voss, Curtis M.; Hyde, Philip J.; Hall, Richard M.; Fisher, John; Brown, Thomas D.

2010-01-01

Computational simulations of wear of orthopaedic total joint replacement implants have proven to valuably complement laboratory physical simulators, for pre-clinical estimation of abrasive/adhesive wear propensity. This class of numerical formulations has primarily involved implementation of the Archard/Lancaster relationship, with local wear computed as the product of (finite element) contact stress, sliding speed, and a bearing-couple-dependent wear factor. The present study introduces an augmentation, whereby the influence of interface cross-shearing motion transverse to the prevailing molecular orientation of the polyethylene articular surface is taken into account in assigning the instantaneous local wear factor. The formulation augment is implemented within a widely-utilized commercial finite element software environment (ABAQUS). Using a contemporary metal-on-polyethylene total disc replacement (ProDisc-L) as an illustrative implant, physically validated computational results are presented to document the role of cross-shearing effects in alternative laboratory consensus testing protocols. Going forward, this formulation permits systematically accounting for cross-shear effects in parametric computational wear studies of metal-on-polyethylene joint replacements, heretofore a substantial limitation of such analyses. PMID:20399432

Symbolic joint entropy reveals the coupling of various brain regions

NASA Astrophysics Data System (ADS)

Ma, Xiaofei; Huang, Xiaolin; Du, Sidan; Liu, Hongxing; Ning, Xinbao

2018-01-01

The convergence and divergence of oscillatory behavior of different brain regions are very important for the procedure of information processing. Measurements of coupling or correlation are very useful to study the difference of brain activities. In this study, EEG signals were collected from ten subjects under two conditions, i.e. eyes closed state and idle with eyes open. We propose a nonlinear algorithm, symbolic joint entropy, to compare the coupling strength among the frontal, temporal, parietal and occipital lobes and between two different states. Instead of decomposing the EEG into different frequency bands (theta, alpha, beta, gamma etc.), the novel algorithm is to investigate the coupling from the entire spectrum of brain wave activities above 4Hz. The coupling coefficients in two states with different time delay steps are compared and the group statistics are presented as well. We find that the coupling coefficient of eyes open state with delay consistently lower than that of eyes close state across the group except for one subject, whereas the results without delay are not consistent. The differences between two brain states with non-zero delay can reveal the intrinsic inter-region coupling better. We also use the well-known Hénon map data to validate the algorithm proposed in this paper. The result shows that the method is robust and has a great potential for other physiologic time series.

Multiscale Reconstruction for Magnetic Resonance Fingerprinting

PubMed Central

Pierre, Eric Y.; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A.

2015-01-01

Purpose To reduce acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in-vivo data using the highly-undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD) and B0 field variations in the brain was achieved in vivo for a 256×256 matrix for a total acquisition time of 10.2s, representing a 3-fold reduction in acquisition time. Conclusions The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. PMID:26132462

An instrumented spatial linkage for measuring knee joint kinematics.

PubMed

Rosvold, Joshua M; Atarod, Mohammad; Frank, Cyril B; Shrive, Nigel G

2016-01-01

In this study, the design and development of a highly accurate instrumented spatial linkage (ISL) for kinematic analysis of the ovine stifle joint is described. The ovine knee is a promising biomechanical model of the human knee joint. The ISL consists of six digital rotational encoders providing six degrees of freedom (6-DOF) to its motion. The ISL makes use of the complete and parametrically continuous (CPC) kinematic modeling method to describe the kinematic relationship between encoder readings and the relative positions and orientation of its two ends. The CPC method is useful when calibrating the ISL, because a small change in parameters corresponds to a small change in calculated positions and orientations and thus a smaller optimization error, compared to other kinematic models. The ISL is attached rigidly to the femur and the tibia for motion capture, and the CPC kinematic model is then employed to transform the angle sensor readings to relative motion of the two ends of the linkage, and thereby, the stifle joint motion. The positional accuracy for ISL after calibration and optimization was 0.3±0.2mm (mean +/- standard deviation). The ISL was also evaluated dynamically to ensure that accurate results were maintained, and achieved an accuracy of 0.1mm. Compared to the traditional motion capture methods, this system provides increased accuracy, reduced processing time, and ease of use. Future work will be on the application of the ISL to the ovine gait and determination of in vivo joint motions and tissue loads. Accurate measurement of knee joint kinematics is essential in understanding injury mechanisms and development of potential preventive or treatment strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

Computing Science and Statistics: Proceedings of the Symposium on the Interface: Computationally Intensive Methods in Statistics (20th) Held in Fairfax, Virginia on April 20-23, 1988

DTIC Science & Technology

1989-03-15

essence of the idea ycessible mtho forunrtandig eth- Tis tand thP ra) rm guh ide propet oaes nd d of e aessie meh bsd fooesadng asymptoti- isthe for s...network? This of Such empirical parametric model fitting is of course depends heavily on the class of net- course the essence of much of applied...smaller problems is the essence of graphical modeling. A model hy- attributes. Let e be the discrete joint outcome space for those N pergraph, g

Effects of time ordering in quantum nonlinear optics

NASA Astrophysics Data System (ADS)

Quesada, Nicolás; Sipe, J. E.

2014-12-01

We study time-ordering corrections to the description of spontaneous parametric down-conversion (SPDC), four-wave mixing (SFWM), and frequency conversion using the Magnus expansion. Analytic approximations to the evolution operator that are unitary are obtained. They are Gaussian preserving, and allow us to understand order-by-order the effects of time ordering. We show that the corrections due to time ordering vanish exactly if the phase-matching function is sufficiently broad. The calculation of the effects of time ordering on the joint spectral amplitude of the photons generated in SPDC and SFWM are reduced to quadrature.

Full statistical mode reconstruction of a light field via a photon-number-resolved measurement

NASA Astrophysics Data System (ADS)

Burenkov, I. A.; Sharma, A. K.; Gerrits, T.; Harder, G.; Bartley, T. J.; Silberhorn, C.; Goldschmidt, E. A.; Polyakov, S. V.

2017-05-01

We present a method to reconstruct the complete statistical mode structure and optical losses of multimode conjugated optical fields using an experimentally measured joint photon-number probability distribution. We demonstrate that this method evaluates classical and nonclassical properties using a single measurement technique and is well suited for quantum mesoscopic state characterization. We obtain a nearly perfect reconstruction of a field comprised of up to ten modes based on a minimal set of assumptions. To show the utility of this method, we use it to reconstruct the mode structure of an unknown bright parametric down-conversion source.

Multimodal Fusion with Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

PubMed Central

Qi, Shile; Calhoun, Vince D.; van Erp, Theo G. M.; Bustillo, Juan; Damaraju, Eswar; Turner, Jessica A.; Du, Yuhui; Chen, Jiayu; Yu, Qingbao; Mathalon, Daniel H.; Ford, Judith M.; Voyvodic, James; Mueller, Bryon A.; Belger, Aysenil; Ewen, Sarah Mc; Potkin, Steven G.; Preda, Adrian; Jiang, Tianzi

2017-01-01

Multimodal fusion is an effective approach to take advantage of cross-information among multiple imaging data to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. To date, there is increasing interest to uncover the neurocognitive mapping of specific behavioral measurement on enriched brain imaging data; hence, a supervised, goal-directed model that enables a priori information as a reference to guide multimodal data fusion is in need and a natural option. Here we proposed a fusion with reference model, called “multi-site canonical correlation analysis with reference plus joint independent component analysis” (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to reference information, such as cognitive scores. In a 3-way fusion simulation, the proposed method was compared with its alternatives on estimation accuracy of both target component decomposition and modality linkage detection. MCCAR+jICA outperforms others with higher precision. In human imaging data, working memory performance was utilized as a reference to investigate the covarying functional and structural brain patterns among 3 modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Interestingly, similar brain maps were identified between the two cohorts, with substantial overlap in the executive control networks in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports, while MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the potential of such results to identify potential neuromarkers for mental disorders. PMID:28708547

Comparison of simultaneously recorded [H2(15)O]-PET and LORETA during cognitive and pharmacological activation.

PubMed

Gamma, Alex; Lehmann, Dietrich; Frei, Edi; Iwata, Kazuki; Pascual-Marqui, Roberto D; Vollenweider, Franz X

2004-06-01

The complementary strengths and weaknesses of established functional brain imaging methods (high spatial, low temporal resolution) and EEG-based techniques (low spatial, high temporal resolution) make their combined use a promising avenue for studying brain processes at a more fine-grained level. However, this strategy requires a better understanding of the relationship between hemodynamic/metabolic and neuroelectric measures of brain activity. We investigated possible correspondences between cerebral blood flow (CBF) as measured by [H2O]-PET and intracerebral electric activity computed by Low Resolution Brain Electromagnetic Tomography (LORETA) from scalp-recorded multichannel EEG in healthy human subjects during cognitive and pharmacological stimulation. The two imaging modalities were compared by descriptive, correlational, and variance analyses, the latter carried out using statistical parametric mapping (SPM99). Descriptive visual comparison showed a partial overlap between the sets of active brain regions detected by the two modalities. A number of exclusively positive correlations of neuroelectric activity with regional CBF were found across the whole EEG frequency range, including slow wave activity, the latter finding being in contrast to most previous studies conducted in patients. Analysis of variance revealed an extensive lack of statistically significant correspondences between brain activity changes as measured by PET vs. EEG-LORETA. In general, correspondences, to the extent they were found, were dependent on experimental condition, brain region, and EEG frequency. Copyright 2004 Wiley-Liss, Inc.

Brain organization and the origin of insects: an assessment

PubMed Central

Strausfeld, Nicholas James

2009-01-01

Within the Arthropoda, morphologies of neurons, the organization of neurons within neuropils and the occurrence of neuropils can be highly conserved and provide robust characters for phylogenetic analyses. The present paper reviews some features of insect and crustacean brains that speak against an entomostracan origin of the insects, contrary to received opinion. Neural organization in brain centres, comprising olfactory pathways, optic lobes and a central neuropil that is thought to play a cardinal role in multi-joint movement, support affinities between insects and malacostracan crustaceans. PMID:19324805

Decoding Lifespan Changes of the Human Brain Using Resting-State Functional Connectivity MRI

PubMed Central

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8–79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' “brain ages” from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI. PMID:22952990

Decoding lifespan changes of the human brain using resting-state functional connectivity MRI.

PubMed

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8-79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' "brain ages" from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI.

VA/DoD Joint Executive Council FY 2009: Joint Strategic Plan FY 2010-2012

DTIC Science & Technology

2009-01-01

through the Military Health System (MHS) Population Health Portal . HEC Traumatic Brain Injury and Psychological Health In FY 2009, VA and DoD made...available using the Deployment Occupational and Environmental Health Surveillance Portal . TBI and MH assessment tools were evaluated and monitored through...with increased access, VA maintained the frequency of encounters for treatment of PTSD and other MH conditions in Veterans of prior eras. To forecast

Brain extraction from normal and pathological images: A joint PCA/Image-Reconstruction approach.

PubMed

Han, Xu; Kwitt, Roland; Aylward, Stephen; Bakas, Spyridon; Menze, Bjoern; Asturias, Alexander; Vespa, Paul; Van Horn, John; Niethammer, Marc

2018-08-01

Brain extraction from 3D medical images is a common pre-processing step. A variety of approaches exist, but they are frequently only designed to perform brain extraction from images without strong pathologies. Extracting the brain from images exhibiting strong pathologies, for example, the presence of a brain tumor or of a traumatic brain injury (TBI), is challenging. In such cases, tissue appearance may substantially deviate from normal tissue appearance and hence violates algorithmic assumptions for standard approaches to brain extraction; consequently, the brain may not be correctly extracted. This paper proposes a brain extraction approach which can explicitly account for pathologies by jointly modeling normal tissue appearance and pathologies. Specifically, our model uses a three-part image decomposition: (1) normal tissue appearance is captured by principal component analysis (PCA), (2) pathologies are captured via a total variation term, and (3) the skull and surrounding tissue is captured by a sparsity term. Due to its convexity, the resulting decomposition model allows for efficient optimization. Decomposition and image registration steps are alternated to allow statistical modeling of normal tissue appearance in a fixed atlas coordinate system. As a beneficial side effect, the decomposition model allows for the identification of potentially pathological areas and the reconstruction of a quasi-normal image in atlas space. We demonstrate the effectiveness of our approach on four datasets: the publicly available IBSR and LPBA40 datasets which show normal image appearance, the BRATS dataset containing images with brain tumors, and a dataset containing clinical TBI images. We compare the performance with other popular brain extraction models: ROBEX, BEaST, MASS, BET, BSE and a recently proposed deep learning approach. Our model performs better than these competing approaches on all four datasets. Specifically, our model achieves the best median (97.11) and mean (96.88) Dice scores over all datasets. The two best performing competitors, ROBEX and MASS, achieve scores of 96.23/95.62 and 96.67/94.25 respectively. Hence, our approach is an effective method for high quality brain extraction for a wide variety of images. Copyright © 2018 Elsevier Inc. All rights reserved.

A question of separation: disentangling tracer bias and gravitational non-linearity with counts-in-cells statistics

NASA Astrophysics Data System (ADS)

Uhlemann, C.; Feix, M.; Codis, S.; Pichon, C.; Bernardeau, F.; L'Huillier, B.; Kim, J.; Hong, S. E.; Laigle, C.; Park, C.; Shin, J.; Pogosyan, D.

2018-02-01

Starting from a very accurate model for density-in-cells statistics of dark matter based on large deviation theory, a bias model for the tracer density in spheres is formulated. It adopts a mean bias relation based on a quadratic bias model to relate the log-densities of dark matter to those of mass-weighted dark haloes in real and redshift space. The validity of the parametrized bias model is established using a parametrization-independent extraction of the bias function. This average bias model is then combined with the dark matter PDF, neglecting any scatter around it: it nevertheless yields an excellent model for densities-in-cells statistics of mass tracers that is parametrized in terms of the underlying dark matter variance and three bias parameters. The procedure is validated on measurements of both the one- and two-point statistics of subhalo densities in the state-of-the-art Horizon Run 4 simulation showing excellent agreement for measured dark matter variance and bias parameters. Finally, it is demonstrated that this formalism allows for a joint estimation of the non-linear dark matter variance and the bias parameters using solely the statistics of subhaloes. Having verified that galaxy counts in hydrodynamical simulations sampled on a scale of 10 Mpc h-1 closely resemble those of subhaloes, this work provides important steps towards making theoretical predictions for density-in-cells statistics applicable to upcoming galaxy surveys like Euclid or WFIRST.

Towards the development of a spring-based continuum robot for neurosurgery

NASA Astrophysics Data System (ADS)

Kim, Yeongjin; Cheng, Shing Shin; Desai, Jaydev P.

2015-03-01

Brain tumor is usually life threatening due to the uncontrolled growth of abnormal cells native to the brain or the spread of tumor cells from outside the central nervous system to the brain. The risks involved in carrying out surgery within such a complex organ can cause severe anxiety in cancer patients. However, neurosurgery, which remains one of the more effective ways of treating brain tumors focused in a confined volume, can have a tremendously increased success rate if the appropriate imaging modality is used for complete tumor removal. Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast and is the imaging modality of choice for brain tumor imaging. MRI combined with continuum soft robotics has immense potential to be the revolutionary treatment technique in the field of brain cancer. It eliminates the concern of hand tremor and guarantees a more precise procedure. One of the prototypes of Minimally Invasive Neurosurgical Intracranial Robot (MINIR-II), which can be classified as a continuum soft robot, consists of a snake-like body made of three segments of rapid prototyped plastic springs. It provides improved dexterity with higher degrees of freedom and independent joint control. It is MRI-compatible, allowing surgeons to track and determine the real-time location of the robot relative to the brain tumor target. The robot was manufactured in a single piece using rapid prototyping technology at a low cost, allowing it to disposable after each use. MINIR-II has two DOFs at each segment with both joints controlled by two pairs of MRI-compatible SMA spring actuators. Preliminary motion tests have been carried out using vision-tracking method and the robot was able to move to different positions based on user commands.

In vivo multiphoton microscopy beyond 1 mm in the brain

NASA Astrophysics Data System (ADS)

Miller, David R.; Medina, Flor A.; Hassan, Ahmed; Perillo, Evan P.; Hagan, Kristen; Kazmi, S. M. Shams; Zemelman, Boris V.; Dunn, Andrew K.

2017-02-01

We perform high-resolution, non-invasive, in vivo deep-tissue imaging of the mouse neocortex using multiphoton microscopy with a high repetition rate optical parametric amplifier laser source tunable between λ=1,100 and 1,400 nm. We demonstrate an imaging depth of 1,200 μm in vasculature and 1,160 μm in neurons. We also demonstrate deep-tissue imaging using Indocyanine Green (ICG), which is FDA approved and a promising route to translate multiphoton microscopy to human applications.

Group B Strep Infection

MedlinePlus

... tract, lungs, bones and joints, heart valve (called endocarditis), or the fluid around the brain and spinal ... Family Health, Infants and Toddlers, WomenTags: arthritis, caregiving, endocarditis, group B, infection, maternal-fetal, maternity, postpartum, sepsis, ...

MRI

MedlinePlus

... the test, tell your provider if you have: Artificial heart valves Brain aneurysm clips Heart defibrillator or pacemaker Inner ear (cochlear) implants Kidney disease or dialysis (you may not ... artificial joints Vascular stents Worked with sheet metal in ...

Magnetic resonance angiography

MedlinePlus

... your provider if you have: Brain aneurysm clips Artificial heart valve Heart defibrillator or pacemaker Inner ear (cochlear) implants Insulin or chemotherapy port Intrauterine device (IUD) Kidney ... artificial joints Vascular stent Worked with sheet metal in ...

Joint Mission Command Implementation

DTIC Science & Technology

2016-01-22

choose. The paper finds that trust is strongly influenced by the subconscious brain and treating it like a tool ignores biology and results in... bias for action and empowerment.14 Since then, the services have evaluated their own concepts of command assessing them against Dempsey’s vision. Lt...understanding, intent, and trust, only trust is strongly influenced by the subconscious brain. Treating trust like it can be taught, or a behavior that

Joint Blind Source Separation by Multi-set Canonical Correlation Analysis

PubMed Central

Li, Yi-Ou; Adalı, Tülay; Wang, Wei; Calhoun, Vince D

2009-01-01

In this work, we introduce a simple and effective scheme to achieve joint blind source separation (BSS) of multiple datasets using multi-set canonical correlation analysis (M-CCA) [1]. We first propose a generative model of joint BSS based on the correlation of latent sources within and between datasets. We specify source separability conditions, and show that, when the conditions are satisfied, the group of corresponding sources from each dataset can be jointly extracted by M-CCA through maximization of correlation among the extracted sources. We compare source separation performance of the M-CCA scheme with other joint BSS methods and demonstrate the superior performance of the M-CCA scheme in achieving joint BSS for a large number of datasets, group of corresponding sources with heterogeneous correlation values, and complex-valued sources with circular and non-circular distributions. We apply M-CCA to analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects and show its utility in estimating meaningful brain activations from a visuomotor task. PMID:20221319

Dissociable prefrontal brain systems for attention and emotion

NASA Astrophysics Data System (ADS)

Yamasaki, Hiroshi; Labar, Kevin S.; McCarthy, Gregory

2002-08-01

The prefrontal cortex has been implicated in a variety of attentional, executive, and mnemonic mental operations, yet its functional organization is still highly debated. The present study used functional MRI to determine whether attentional and emotional functions are segregated into dissociable prefrontal networks in the human brain. Subjects discriminated infrequent and irregularly presented attentional targets (circles) from frequent standards (squares) while novel distracting scenes, parametrically varied for emotional arousal, were intermittently presented. Targets differentially activated middle frontal gyrus, posterior parietal cortex, and posterior cingulate gyrus. Novel distracters activated inferior frontal gyrus, amygdala, and fusiform gyrus, with significantly stronger activation evoked by the emotional scenes. The anterior cingulate gyrus was the only brain region with equivalent responses to attentional and emotional stimuli. These results show that attentional and emotional functions are segregated into parallel dorsal and ventral streams that extend into prefrontal cortex and are integrated in the anterior cingulate. These findings may have implications for understanding the neural dynamics underlying emotional distractibility on attentional tasks in affective disorders. novelty | prefrontal cortex | amygdala | cingulate gyrus

Novel approaches to address spectral distortions in photon counting x-ray CT using artificial neural networks

NASA Astrophysics Data System (ADS)

Touch, M.; Clark, D. P.; Barber, W.; Badea, C. T.

2016-04-01

Spectral CT using a photon-counting x-ray detector (PCXD) can potentially increase accuracy of measuring tissue composition. However, PCXD spectral measurements suffer from distortion due to charge sharing, pulse pileup, and Kescape energy loss. This study proposes two novel artificial neural network (ANN)-based algorithms: one to model and compensate for the distortion, and another one to directly correct for the distortion. The ANN-based distortion model was obtained by training to learn the distortion from a set of projections with a calibration scan. The ANN distortion was then applied in the forward statistical model to compensate for distortion in the projection decomposition. ANN was also used to learn to correct distortions directly in projections. The resulting corrected projections were used for reconstructing the image, denoising via joint bilateral filtration, and decomposition into three-material basis functions: Compton scattering, the photoelectric effect, and iodine. The ANN-based distortion model proved to be more robust to noise and worked better compared to using an imperfect parametric distortion model. In the presence of noise, the mean relative errors in iodine concentration estimation were 11.82% (ANN distortion model) and 16.72% (parametric model). With distortion correction, the mean relative error in iodine concentration estimation was improved by 50% over direct decomposition from distorted data. With our joint bilateral filtration, the resulting material image quality and iodine detectability as defined by the contrast-to-noise ratio were greatly enhanced allowing iodine concentrations as low as 2 mg/ml to be detected. Future work will be dedicated to experimental evaluation of our ANN-based methods using 3D-printed phantoms.

Biomechanical analysis of gait waveform data: exploring differences between shod and barefoot running in habitually shod runners.

PubMed

Tam, Nicholas; Prins, Danielle; Divekar, Nikhil V; Lamberts, Robert P

2017-10-01

The aim of this study was to utilise one-dimensional statistical parametric mapping to compare differences between biomechanical and electromyographical waveforms in runners when running in barefoot or shod conditions. Fifty habitually shod runners were assessed during overground running at their current 10-km race running speed. Electromyography, kinematics and ground reaction forces were collected during these running trials. Joint kinetics were calculated using inverse dynamics. One-dimensional statistical parametric mapping one sample t-test was conducted to assess differences over an entire gait cycle on the variables of interest when barefoot or shod (p<0.05). Only sagittal plane differences were found between barefoot and shod conditions at the knee during late stance (18-23% of the gait cycle) and swing phase (74-90%); at the ankle early stance (0-6%), mid-stance (28-38%) and swing phase (81-100%). Differences in sagittal plane moments were also found at the ankle during early stance (2, 4-5%) and knee during early stance (5-11%). Condition differences were also found in vertical ground reaction force during early stance between (3-10%). An acute bout of barefoot running in habitual shod runners invokes temporal differences throughout the gait cycle. Specifically, a co-ordinative responses between the knee and ankle joint in the sagittal plane with a delay in the impact transient peak; onset of the knee extension and ankle plantarflexion moment in the shod compared to barefoot condition was found. This appears to affect the delay in knee extension and ankle plantarflexion during late stance. This study provides a glimpse into the co-ordination of the lower limb when running in differing footwear. Copyright © 2017 Elsevier B.V. All rights reserved.

A framework for multivariate data-based at-site flood frequency analysis: Essentiality of the conjugal application of parametric and nonparametric approaches

NASA Astrophysics Data System (ADS)

Vittal, H.; Singh, Jitendra; Kumar, Pankaj; Karmakar, Subhankar

2015-06-01

In watershed management, flood frequency analysis (FFA) is performed to quantify the risk of flooding at different spatial locations and also to provide guidelines for determining the design periods of flood control structures. The traditional FFA was extensively performed by considering univariate scenario for both at-site and regional estimation of return periods. However, due to inherent mutual dependence of the flood variables or characteristics [i.e., peak flow (P), flood volume (V) and flood duration (D), which are random in nature], analysis has been further extended to multivariate scenario, with some restrictive assumptions. To overcome the assumption of same family of marginal density function for all flood variables, the concept of copula has been introduced. Although, the advancement from univariate to multivariate analyses drew formidable attention to the FFA research community, the basic limitation was that the analyses were performed with the implementation of only parametric family of distributions. The aim of the current study is to emphasize the importance of nonparametric approaches in the field of multivariate FFA; however, the nonparametric distribution may not always be a good-fit and capable of replacing well-implemented multivariate parametric and multivariate copula-based applications. Nevertheless, the potential of obtaining best-fit using nonparametric distributions might be improved because such distributions reproduce the sample's characteristics, resulting in more accurate estimations of the multivariate return period. Hence, the current study shows the importance of conjugating multivariate nonparametric approach with multivariate parametric and copula-based approaches, thereby results in a comprehensive framework for complete at-site FFA. Although the proposed framework is designed for at-site FFA, this approach can also be applied to regional FFA because regional estimations ideally include at-site estimations. The framework is based on the following steps: (i) comprehensive trend analysis to assess nonstationarity in the observed data; (ii) selection of the best-fit univariate marginal distribution with a comprehensive set of parametric and nonparametric distributions for the flood variables; (iii) multivariate frequency analyses with parametric, copula-based and nonparametric approaches; and (iv) estimation of joint and various conditional return periods. The proposed framework for frequency analysis is demonstrated using 110 years of observed data from Allegheny River at Salamanca, New York, USA. The results show that for both univariate and multivariate cases, the nonparametric Gaussian kernel provides the best estimate. Further, we perform FFA for twenty major rivers over continental USA, which shows for seven rivers, all the flood variables followed nonparametric Gaussian kernel; whereas for other rivers, parametric distributions provide the best-fit either for one or two flood variables. Thus the summary of results shows that the nonparametric method cannot substitute the parametric and copula-based approaches, but should be considered during any at-site FFA to provide the broadest choices for best estimation of the flood return periods.

A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data.

PubMed

Calhoun, V; Adali, T; Liu, J

2006-01-01

The acquisition of multiple brain imaging types for a given study is a very common practice. However these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform joint independent component analysis across image modalities, including structural MRI data, functional MRI activation data and EEG data, and to visualize the results via a joint histogram visualization technique. Evaluation of which combination of fused data is most useful is determined by using the Kullback-Leibler divergence. We demonstrate our method on a data set composed of functional MRI data from two tasks, structural MRI data, and EEG data collected on patients with schizophrenia and healthy controls. We show that combining data types can improve our ability to distinguish differences between groups.

Motor impairment factors related to brain injury timing in early hemiparesis Part I: expression of upper extremity weakness

PubMed Central

Sukal-Moulton, Theresa; Krosschell, Kristin J.; Gaebler-Spira, Deborah J.; Dewald, Julius P.A.

2014-01-01

Background Extensive neuromotor development occurs early in human life, but the time that a brain injury occurs during development has not been rigorously studied when quantifying motor impairments. Objective This study investigated the impact of timing of brain injury on magnitude and distribution of weakness in the paretic arm of individuals with childhood-onset hemiparesis. Methods Twenty-four individuals with hemiparesis were divided into time periods of injury before birth (PRE-natal, n=8), around the time of birth (PERI-natal, n=8) or after 6 months of age (POST-natal, n=8). They, along with 8 typically developing peers, participated in maximal isometric shoulder, elbow, wrist, and finger torque generation tasks using a multiple degree-of-freedom load cell to quantify torques in 10 directions. A mixed model ANOVA was used to determine the effect of group and task on a calculated relative weakness ratio between arms. Results There was a significant effect of both time of injury group (p<0.001) and joint torque direction (p<0.001) on the relative weakness of the paretic arm. Distal joints were more affected compared to proximal joints, especially in the POST-natal group. Conclusions The distribution of weakness provides evidence for the relative preservation of ipsilateral corticospinal motor pathways to the paretic limb in those individuals injured earlier, while those who sustained later injury may rely more on indirect ipsilateral cortico-bulbospinal projections during the generation of torques with the paretic arm. PMID:24009182

Motor impairment factors related to brain injury timing in early hemiparesis. Part I: expression of upper-extremity weakness.

PubMed

Sukal-Moulton, Theresa; Krosschell, Kristin J; Gaebler-Spira, Deborah J; Dewald, Julius P A

2014-01-01

Extensive neuromotor development occurs early in human life, but the time that a brain injury occurs during development has not been rigorously studied when quantifying motor impairments. This study investigated the impact of timing of brain injury on the magnitude and distribution of weakness in the paretic arm of individuals with childhood-onset hemiparesis. A total of 24 individuals with hemiparesis were divided into time periods of injury before birth (PRE-natal, n = 8), around the time of birth (PERI-natal, n = 8), or after 6 months of age (POST-natal, n = 8). They, along with 8 typically developing peers, participated in maximal isometric shoulder, elbow, wrist, and finger torque generation tasks using a multiple-degree-of-freedom load cell to quantify torques in 10 directions. A mixed-model ANOVA was used to determine the effect of group and task on a calculated relative weakness ratio between arms. There was a significant effect of both time of injury group (P < .001) and joint torque direction (P < .001) on the relative weakness of the paretic arm. Distal joints were more affected compared with proximal joints, especially in the POST-natal group. The distribution of weakness provides evidence for the relative preservation of ipsilateral corticospinal motor pathways to the paretic limb in those individuals injured earlier, whereas those who sustained later injury may rely more on indirect ipsilateral corticobulbospinal projections during the generation of torques with the paretic arm.

Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

2018-05-01

Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

Influence of the bond-slip relationship on the flexural capacity of R.C. joints damaged by corrosion

NASA Astrophysics Data System (ADS)

Imperatore, Stefania

2016-06-01

In moderate and aggressive environmental condition, old reinforced concrete structures are often subjected to corrosive phenomena. Corrosion causes cracking, loss of diameter in reinforcement and variation of the bond behavior between steel and concrete. Then, in presence of cyclic actions like the seismic ones, old R.C. elements vary their ultimate drift, ductility, plastic rotation capacity and energy dissipation with the corrosion level. The problem is of current interest: the issue has been introduced in some paragraph of the Model Code 2010 and a committee is now drafting a new document on assessment strategies on existing concrete structures also damaged by corrosion. In this work, a first step on the analysis of the impact of the corrosion on the seismic behavior of R.C. elements is assessed: by mean FEM analyses, of a poor detailed column/foundation joint is analyzed in a parametric way in order to evaluate the influence of the bond-slip degradation by corrosion on the element flexural capacity.

Approximate Uncertainty Modeling in Risk Analysis with Vine Copulas

PubMed Central

Bedford, Tim; Daneshkhah, Alireza

2015-01-01

Many applications of risk analysis require us to jointly model multiple uncertain quantities. Bayesian networks and copulas are two common approaches to modeling joint uncertainties with probability distributions. This article focuses on new methodologies for copulas by developing work of Cooke, Bedford, Kurowica, and others on vines as a way of constructing higher dimensional distributions that do not suffer from some of the restrictions of alternatives such as the multivariate Gaussian copula. The article provides a fundamental approximation result, demonstrating that we can approximate any density as closely as we like using vines. It further operationalizes this result by showing how minimum information copulas can be used to provide parametric classes of copulas that have such good levels of approximation. We extend previous approaches using vines by considering nonconstant conditional dependencies, which are particularly relevant in financial risk modeling. We discuss how such models may be quantified, in terms of expert judgment or by fitting data, and illustrate the approach by modeling two financial data sets. PMID:26332240

Study of weld offset in longitudinally welded SSME HPFTP inlet

NASA Technical Reports Server (NTRS)

Min, J. B.; Spanyer, K. S.; Brunair, R. M.

1992-01-01

Welded joints are an essential part of rocket engine structures such as the Space Shuttle Main Engine (SSME) turbopumps. Defects produced in the welding process can be detrimental to weld performance. Recently, review of the SSME high pressure fuel turbopump (HPFTP) titanium inlet X-rays revealed several weld discrepancies such as penetrameter density issues, film processing discrepancies, weld width discrepancies, porosity, lack of fusion, and weld offsets. Currently, the sensitivity of welded structures to defects is of concern. From a fatigue standpoint, weld offset may have a serious effect since local yielding, in general, aggravates cyclic stress effects. Therefore, the weld offset issue is considered in this report. Using the FEM and beamlike plate approximations, parametric studies were conducted to determine the influence of weld offsets and a variation of weld widths in longitudinally welded cylindrical structures with equal wall thicknesses on both sides of the joint. Following the study, some conclusions are derived for the weld offsets.

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 flow is introduced and used to model the propagation of information between GM areas through WM fiber bundles. The link capacity, i.e., ability to transfer information, is characterized by the relative strength of fiber bundles, e.g., fiber count gathered from the tractography of dMRI data. The node information demand is considered to be proportional to the correlation between neural activity at various cortical areas involved in a particular functional mode (e.g. visual, motor, etc.). These two properties lead to the link capacity and node demand constraints in the proposed model. Moreover, the information flow of a link cannot exceed the demand from either end node. This is captured by the feasibility constraints. Two different cost functions are considered in the optimization formulation in this paper. The first cost function, the reciprocal of fiber strength represents the unit cost for information passing through the link. In the second cost function, a min-max (minimizing the maximal link load) approach is used to balance the usage of each link. Optimizing the first cost function selects the pathway with strongest fiber strength for information propagation. In the second case, the optimization procedure finds all the possible propagation pathways and allocates the flow proportionally to their strength. Additionally, a penalty term is incorporated with both the cost functions to capture the possible missing and weak anatomical connections. With this set of constraints and the proposed cost functions, solving the network optimization problem recovers missing and weak anatomical connections supported by the functional information and provides the functional-associated anatomical subnetworks. Feasibility is demonstrated using realistic diffusion and functional MRI phantom data. It is shown that the proposed model recovers the maximum number of true connections, with fewest number of false connections when compared with the connectivity derived from a joint probabilistic model using the expectation-maximization (EM) algorithm presented in a prior work. We also apply the proposed method to data provided by the Human Connectome Project (HCP).

The Interface of Mechanics and Nociception in Joint Pathophysiology: Insights From the Facet and Temporomandibular Joints

PubMed Central

Sperry, Megan M.; Ita, Meagan E.; Kartha, Sonia; Zhang, Sijia; Yu, Ya-Hsin; Winkelstein, Beth

2017-01-01

Chronic joint pain is a widespread problem that frequently occurs with aging and trauma. Pain occurs most often in synovial joints, the body's load bearing joints. The mechanical and molecular mechanisms contributing to synovial joint pain are reviewed using two examples, the cervical spinal facet joints and the temporomandibular joint (TMJ). Although much work has focused on the macroscale mechanics of joints in health and disease, the combined influence of tissue mechanics, molecular processes, and nociception in joint pain has only recently become a focus. Trauma and repeated loading can induce structural and biochemical changes in joints, altering their microenvironment and modifying the biomechanics of their constitutive tissues, which themselves are innervated. Peripheral pain sensors can become activated in response to changes in the joint microenvironment and relay pain signals to the spinal cord and brain where pain is processed and perceived. In some cases, pain circuitry is permanently changed, which may be a potential mechanism for sustained joint pain. However, it is most likely that alterations in both the joint microenvironment and the central nervous system (CNS) contribute to chronic pain. As such, the challenge of treating joint pain and degeneration is temporally and spatially complicated. This review summarizes anatomy, physiology, and pathophysiology of these joints and the sensory pain relays. Pain pathways are postulated to be sensitized by many factors, including degeneration and biochemical priming, with effects on thresholds for mechanical injury and/or dysfunction. Initiators of joint pain are discussed in the context of clinical challenges including the diagnosis and treatment of pain. PMID:28056123

A discriminative model-constrained EM approach to 3D MRI brain tissue classification and intensity non-uniformity correction

NASA Astrophysics Data System (ADS)

Wels, Michael; Zheng, Yefeng; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2011-06-01

We describe a fully automated method for tissue classification, which is the segmentation into cerebral gray matter (GM), cerebral white matter (WM), and cerebral spinal fluid (CSF), and intensity non-uniformity (INU) correction in brain magnetic resonance imaging (MRI) volumes. It combines supervised MRI modality-specific discriminative modeling and unsupervised statistical expectation maximization (EM) segmentation into an integrated Bayesian framework. While both the parametric observation models and the non-parametrically modeled INUs are estimated via EM during segmentation itself, a Markov random field (MRF) prior model regularizes segmentation and parameter estimation. Firstly, the regularization takes into account knowledge about spatial and appearance-related homogeneity of segments in terms of pairwise clique potentials of adjacent voxels. Secondly and more importantly, patient-specific knowledge about the global spatial distribution of brain tissue is incorporated into the segmentation process via unary clique potentials. They are based on a strong discriminative model provided by a probabilistic boosting tree (PBT) for classifying image voxels. It relies on the surrounding context and alignment-based features derived from a probabilistic anatomical atlas. The context considered is encoded by 3D Haar-like features of reduced INU sensitivity. Alignment is carried out fully automatically by means of an affine registration algorithm minimizing cross-correlation. Both types of features do not immediately use the observed intensities provided by the MRI modality but instead rely on specifically transformed features, which are less sensitive to MRI artifacts. Detailed quantitative evaluations on standard phantom scans and standard real-world data show the accuracy and robustness of the proposed method. They also demonstrate relative superiority in comparison to other state-of-the-art approaches to this kind of computational task: our method achieves average Dice coefficients of 0.93 ± 0.03 (WM) and 0.90 ± 0.05 (GM) on simulated mono-spectral and 0.94 ± 0.02 (WM) and 0.92 ± 0.04 (GM) on simulated multi-spectral data from the BrainWeb repository. The scores are 0.81 ± 0.09 (WM) and 0.82 ± 0.06 (GM) and 0.87 ± 0.05 (WM) and 0.83 ± 0.12 (GM) for the two collections of real-world data sets—consisting of 20 and 18 volumes, respectively—provided by the Internet Brain Segmentation Repository.

Construction and evaluation of quantitative small-animal PET probabilistic atlases for [¹⁸F]FDG and [¹⁸F]FECT functional mapping of the mouse brain.

PubMed

Casteels, Cindy; Vunckx, Kathleen; Aelvoet, Sarah-Ann; Baekelandt, Veerle; Bormans, Guy; Van Laere, Koen; Koole, Michel

2013-01-01

Automated voxel-based or pre-defined volume-of-interest (VOI) analysis of small-animal PET data in mice is necessary for optimal information usage as the number of available resolution elements is limited. We have mapped metabolic ([(18)F]FDG) and dopamine transporter ([(18)F]FECT) small-animal PET data onto a 3D Magnetic Resonance Microscopy (MRM) mouse brain template and aligned them in space to the Paxinos co-ordinate system. In this way, ligand-specific templates for sensitive analysis and accurate anatomical localization were created. Next, using a pre-defined VOI approach, test-retest and intersubject variability of various quantification methods were evaluated. Also, the feasibility of mouse brain statistical parametric mapping (SPM) was explored for [(18)F]FDG and [(18)F]FECT imaging of 6-hydroxydopamine-lesioned (6-OHDA) mice. Twenty-three adult C57BL6 mice were scanned with [(18)F]FDG and [(18)F]FECT. Registrations and affine spatial normalizations were performed using SPM8. [(18)F]FDG data were quantified using (1) an image-derived-input function obtained from the liver (cMRglc), using (2) standardized uptake values (SUVglc) corrected for blood glucose levels and by (3) normalizing counts to the whole-brain uptake. Parametric [(18)F]FECT binding images were constructed by reference to the cerebellum. Registration accuracy was determined using random simulated misalignments and vectorial mismatch determination. Registration accuracy was between 0.21-1.11 mm. Regional intersubject variabilities of cMRglc ranged from 15.4% to 19.2%, while test-retest values were between 5.0% and 13.0%. For [(18)F]FECT uptake in the caudate-putamen, these values were 13.0% and 10.3%, respectively. Regional values of cMRglc positively correlated to SUVglc measured within the 45-60 min time frame (spearman r = 0.71). Next, SPM analysis of 6-OHDA-lesioned mice showed hypometabolism in the bilateral caudate-putamen and cerebellum, and an unilateral striatal decrease in DAT availability. MRM-based small-animal PET templates facilitate accurate assessment and spatial localization of mouse brain function using VOI or voxel-based analysis. Regional intersubject- and test-retest variations indicate that for these targets accuracy comparable to humans can be achieved.

A discriminative model-constrained EM approach to 3D MRI brain tissue classification and intensity non-uniformity correction.

PubMed

Wels, Michael; Zheng, Yefeng; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2011-06-07

We describe a fully automated method for tissue classification, which is the segmentation into cerebral gray matter (GM), cerebral white matter (WM), and cerebral spinal fluid (CSF), and intensity non-uniformity (INU) correction in brain magnetic resonance imaging (MRI) volumes. It combines supervised MRI modality-specific discriminative modeling and unsupervised statistical expectation maximization (EM) segmentation into an integrated Bayesian framework. While both the parametric observation models and the non-parametrically modeled INUs are estimated via EM during segmentation itself, a Markov random field (MRF) prior model regularizes segmentation and parameter estimation. Firstly, the regularization takes into account knowledge about spatial and appearance-related homogeneity of segments in terms of pairwise clique potentials of adjacent voxels. Secondly and more importantly, patient-specific knowledge about the global spatial distribution of brain tissue is incorporated into the segmentation process via unary clique potentials. They are based on a strong discriminative model provided by a probabilistic boosting tree (PBT) for classifying image voxels. It relies on the surrounding context and alignment-based features derived from a probabilistic anatomical atlas. The context considered is encoded by 3D Haar-like features of reduced INU sensitivity. Alignment is carried out fully automatically by means of an affine registration algorithm minimizing cross-correlation. Both types of features do not immediately use the observed intensities provided by the MRI modality but instead rely on specifically transformed features, which are less sensitive to MRI artifacts. Detailed quantitative evaluations on standard phantom scans and standard real-world data show the accuracy and robustness of the proposed method. They also demonstrate relative superiority in comparison to other state-of-the-art approaches to this kind of computational task: our method achieves average Dice coefficients of 0.93 ± 0.03 (WM) and 0.90 ± 0.05 (GM) on simulated mono-spectral and 0.94 ± 0.02 (WM) and 0.92 ± 0.04 (GM) on simulated multi-spectral data from the BrainWeb repository. The scores are 0.81 ± 0.09 (WM) and 0.82 ± 0.06 (GM) and 0.87 ± 0.05 (WM) and 0.83 ± 0.12 (GM) for the two collections of real-world data sets-consisting of 20 and 18 volumes, respectively-provided by the Internet Brain Segmentation Repository.

The "pseudo-CT myelogram sign": an aid to the diagnosis of underlying brain stem and spinal cord trauma in the presence of major craniocervical region injury on post-mortem CT.

PubMed

Bolster, F; Ali, Z; Daly, B

2017-12-01

To document the detection of underlying low-attenuation spinal cord or brain stem injuries in the presence of the "pseudo-CT myelogram sign" (PCMS) on post-mortem computed tomography (PMCT). The PCMS was identified on PMCT in 20 decedents (11 male, nine female; age 3-83 years, mean age 35.3 years) following fatal blunt trauma at a single forensic centre. Osseous and ligamentous craniocervical region injuries and brain stem or spinal cord trauma detectable on PMCT were recorded. PMCT findings were compared to conventional autopsy in all cases. PMCT-detected transection of the brain stem or high cervical cord in nine of 10 cases compared to autopsy (90% sensitivity). PMCT was 92.86% sensitive in detection of atlanto-occipital joint injuries (n=14), and 100% sensitive for atlanto-axial joint (n=8) injuries. PMCT detected more cervical spine and skull base fractures (n=22, and n=10, respectively) compared to autopsy (n=13, and n=5, respectively). The PCMS is a novel description of a diagnostic finding, which if present in fatal craniocervical region trauma, is very sensitive for underlying spinal cord and brain stem injuries not ordinarily visible on PMCT. Its presence may also predict major osseous and/or ligamentous injuries in this region when anatomical displacement is not evident on PMCT. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Multiparametric, Longitudinal Optical Coherence Tomography Imaging Reveals Acute Injury and Chronic Recovery in Experimental Ischemic Stroke

PubMed Central

Srinivasan, Vivek J.; Mandeville, Emiri T.; Can, Anil; Blasi, Francesco; Climov, Mihail; Daneshmand, Ali; Lee, Jeong Hyun; Yu, Esther; Radhakrishnan, Harsha; Lo, Eng H.; Sakadžić, Sava; Eikermann-Haerter, Katharina; Ayata, Cenk

2013-01-01

Progress in experimental stroke and translational medicine could be accelerated by high-resolution in vivo imaging of disease progression in the mouse cortex. Here, we introduce optical microscopic methods that monitor brain injury progression using intrinsic optical scattering properties of cortical tissue. A multi-parametric Optical Coherence Tomography (OCT) platform for longitudinal imaging of ischemic stroke in mice, through thinned-skull, reinforced cranial window surgical preparations, is described. In the acute stages, the spatiotemporal interplay between hemodynamics and cell viability, a key determinant of pathogenesis, was imaged. In acute stroke, microscopic biomarkers for eventual infarction, including capillary non-perfusion, cerebral blood flow deficiency, altered cellular scattering, and impaired autoregulation of cerebral blood flow, were quantified and correlated with histology. Additionally, longitudinal microscopy revealed remodeling and flow recovery after one week of chronic stroke. Intrinsic scattering properties serve as reporters of acute cellular and vascular injury and recovery in experimental stroke. Multi-parametric OCT represents a robust in vivo imaging platform to comprehensively investigate these properties. PMID:23940761

Spectral decompositions of multiple time series: a Bayesian non-parametric approach.

PubMed

Macaro, Christian; Prado, Raquel

2014-01-01

We consider spectral decompositions of multiple time series that arise in studies where the interest lies in assessing the influence of two or more factors. We write the spectral density of each time series as a sum of the spectral densities associated to the different levels of the factors. We then use Whittle's approximation to the likelihood function and follow a Bayesian non-parametric approach to obtain posterior inference on the spectral densities based on Bernstein-Dirichlet prior distributions. The prior is strategically important as it carries identifiability conditions for the models and allows us to quantify our degree of confidence in such conditions. A Markov chain Monte Carlo (MCMC) algorithm for posterior inference within this class of frequency-domain models is presented.We illustrate the approach by analyzing simulated and real data via spectral one-way and two-way models. In particular, we present an analysis of functional magnetic resonance imaging (fMRI) brain responses measured in individuals who participated in a designed experiment to study pain perception in humans.

Effects of lithium on brain glucose metabolism in healthy men.

PubMed

Kohno, Tomoya; Shiga, Tohru; Toyomaki, Atsuhito; Kusumi, Ichiro; Matsuyama, Tetsuaki; Inoue, Tetsuya; Katoh, Chietsugu; Koyama, Tsukasa; Tamaki, Nagara

2007-12-01

Lithium is clinically available for the treatment of mood disorders. However, it has remained unclear how lithium acts on the brain to produce its effects. The aim of this study was to evaluate the effects of chronic lithium on human brain activity using positron emission tomography and clarify the correlation between brain activity changes and cognitive functional changes as induced by chronic lithium administration. A total of 20 healthy male subjects (mean age, 32 +/- 6 years) underwent positron emission tomographic scans with F-fluorodeoxyglucose and a battery of neuropsychological tests at baseline condition and after 4 weeks of lithium administration. Brain metabolic data were analyzed using statistical parametric mapping. Lithium increased relative regional cerebral glucose metabolism (rCMRglc) in the bilateral dorsomedial frontal cortices including the anterior cingulate gyrus and decreased rCMRglc in the right cerebellum and left lingual gyrus/cuneus. There was no difference in any of the variables of cognitive functions between the baseline condition and after chronic lithium administration. There was no correlation between rCMRglc changes in any of the brain regions and individual variable changes in any of the neuropsychological tests. The results suggest that the effects of chronic lithium are associated with increased activity in the bilateral dorsomedial frontal cortices including the anterior cingulate gyrus and decreased activity in the right cerebellum and left lingual gyrus/cuneus.

Brain structural plasticity with spaceflight.

PubMed

Koppelmans, Vincent; Bloomberg, Jacob J; Mulavara, Ajitkumar P; Seidler, Rachael D

2016-01-01

Humans undergo extensive sensorimotor adaptation during spaceflight due to altered vestibular inputs and body unloading. No studies have yet evaluated the effects of spaceflight on human brain structure despite the fact that recently reported optic nerve structural changes are hypothesized to occur due to increased intracranial pressure occurring with microgravity. This is the first report on human brain structural changes with spaceflight. We evaluated retrospective longitudinal T2-weighted MRI scans and balance data from 27 astronauts (thirteen ~2-week shuttle crew members and fourteen ~6-month International Space Station crew members) to determine spaceflight effects on brain structure, and whether any pre to postflight brain changes are associated with balance changes. Data were obtained from the NASA Lifetime Surveillance of Astronaut Health. Brain scans were segmented into gray matter maps and normalized into MNI space using a stepwise approach through subject specific templates. Non-parametric permutation testing was used to analyze pre to postflight volumetric gray matter changes. We found extensive volumetric gray matter decreases, including large areas covering the temporal and frontal poles and around the orbits. This effect was larger in International Space Station versus shuttle crew members in some regions. There were bilateral focal gray matter increases within the medial primary somatosensory and motor cortex; i.e., the cerebral areas where the lower limbs are represented. These intriguing findings are observed in a retrospective data set; future prospective studies should probe the underlying mechanisms and behavioral consequences.

[Three-dimensional reconstruction of functional brain images].

PubMed

Inoue, M; Shoji, K; Kojima, H; Hirano, S; Naito, Y; Honjo, I

1999-08-01

We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: 1) routine images by SPM, 2) three-dimensional static images, and 3) three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface model is the most common method of three-dimensional display. However, the volume rendering method may be more effective for imaging regions such as the brain.

Task by stimulus interactions in brain responses during Chinese character processing.

PubMed

Yang, Jianfeng; Wang, Xiaojuan; Shu, Hua; Zevin, Jason D

2012-04-02

In the visual word recognition literature, it is well understood that various stimulus effects interact with behavioral task. For example, effects of word frequency are exaggerated and effects of spelling-to-sound regularity are reduced in the lexical decision task, relative to reading aloud. Neuroimaging studies of reading often examine effects of task and stimulus properties on brain activity independently, but potential interactions between task demands and stimulus effects have not been extensively explored. To address this issue, we conducted lexical decision and symbol detection tasks using stimuli that varied parametrically in their word-likeness, and tested for task by stimulus class interactions. Interactions were found throughout the reading system, such that stimulus selectivity was observed during the lexical decision task, but not during the symbol detection task. Further, the pattern of stimulus selectivity was directly related to task difficulty, so that the strongest brain activity was observed to the most word-like stimuli that required "no" responses, whereas brain activity to words, which elicit rapid and accurate "yes" responses were relatively weak. This is in line with models that argue for task-dependent specialization of brain regions, and contrasts with the notion of task-independent stimulus selectivity in the reading system. Copyright © 2012 Elsevier Inc. All rights reserved.

Syrinx of the Spinal Cord and Brain Stem

MedlinePlus

... View The Professional Version For doctors and medical students Consumer Version Merck Manual Consumer Version × MERCK MANUAL - ... View The Professional Version For doctors and medical students Home Medical Topics Blood Disorders Bone, Joint, and ...

[Developmental amnesia and early brain damage: neuropsychology and neuroimaging].

PubMed

Crespo-Eguilaz, N; Dominguez, P D; Vaquero, M; Narbona, J

2018-03-01

To contribute to neuropsychological profiling of developmental amnesia subsequent to bilateral damage to both hippocampi in early age. The total sample of 24 schoolchildren from both sexes is distributed in three groups: perinatal hypoxic-ischaemic encephalopathy and everyday complaints of memory in school age (n = 8); perinatal hypoxic-ischaemic encephalopathy without memory complaints (n = 7); and a group of typically developing (n = 9). All participants in every groups did have normal general intelligence and attention. Both clinical groups had, as another clinical consequence, spastic cerebral palsy (diplegia). Neuropsychological exam consisted on tests of general intelligence, attentional abilities, declarative memory and semantic knowledge. All participants had a brain magnetic resonance image and spectroscopy of hippocampi. Scheltens criteria were used for visual estimation of hippocampal atrophy. Parametric and non-parametric statistical contrasts were made. Despite preservation of semantic and procedural learning, declarative-episodic memory is impaired in the first group versus the other two groups. A significant proportion of bilateral hippocampal atrophy is only present in the first group versus the other two non-amnesic groups using Scheltens estimation on MRI. Two cases without evident atrophy did have diminished NAA/(Cho + Cr) index in both hippocampi. Taken together, these results contribute to delineate developmental amnesia as an specific impairment due to early partial bihippocampal damage, in agreement with previous studies. After diagnosis of developmental amnesia, a specific psychoeducational intervention must be made; also this impairment could be candidate for pharmacological trials in the future.

Localized N20 Component of Somatosensory Evoked Magnetic Fields in Frontoparietal Brain Tumor Patients Using Noise-Normalized Approaches.

PubMed

Elaina, Nor Safira; Malik, Aamir Saeed; Shams, Wafaa Khazaal; Badruddin, Nasreen; Abdullah, Jafri Malin; Reza, Mohammad Faruque

2018-06-01

To localize sensorimotor cortical activation in 10 patients with frontoparietal tumors using quantitative magnetoencephalography (MEG) with noise-normalized approaches. Somatosensory evoked magnetic fields (SEFs) were elicited in 10 patients with somatosensory tumors and in 10 control participants using electrical stimulation of the median nerve via the right and left wrists. We localized the N20m component of the SEFs using dynamic statistical parametric mapping (dSPM) and standardized low-resolution brain electromagnetic tomography (sLORETA) combined with 3D magnetic resonance imaging (MRI). The obtained coordinates were compared between groups. Finally, we statistically evaluated the N20m parameters across hemispheres using non-parametric statistical tests. The N20m sources were accurately localized to Brodmann area 3b in all members of the control group and in seven of the patients; however, the sources were shifted in three patients relative to locations outside the primary somatosensory cortex (SI). Compared with the affected (tumor) hemispheres in the patient group, N20m amplitudes and the strengths of the current sources were significantly lower in the unaffected hemispheres and in both hemispheres of the control group. These results were consistent for both dSPM and sLORETA approaches. Tumors in the sensorimotor cortex lead to cortical functional reorganization and an increase in N20m amplitude and current-source strengths. Noise-normalized approaches for MEG analysis that are integrated with MRI show accurate and reliable localization of sensorimotor function.

fMRat: an extension of SPM for a fully automatic analysis of rodent brain functional magnetic resonance series.

PubMed

Chavarrías, Cristina; García-Vázquez, Verónica; Alemán-Gómez, Yasser; Montesinos, Paula; Pascau, Javier; Desco, Manuel

2016-05-01

The purpose of this study was to develop a multi-platform automatic software tool for full processing of fMRI rodent studies. Existing tools require the usage of several different plug-ins, a significant user interaction and/or programming skills. Based on a user-friendly interface, the tool provides statistical parametric brain maps (t and Z) and percentage of signal change for user-provided regions of interest. The tool is coded in MATLAB (MathWorks(®)) and implemented as a plug-in for SPM (Statistical Parametric Mapping, the Wellcome Trust Centre for Neuroimaging). The automatic pipeline loads default parameters that are appropriate for preclinical studies and processes multiple subjects in batch mode (from images in either Nifti or raw Bruker format). In advanced mode, all processing steps can be selected or deselected and executed independently. Processing parameters and workflow were optimized for rat studies and assessed using 460 male-rat fMRI series on which we tested five smoothing kernel sizes and three different hemodynamic models. A smoothing kernel of FWHM = 1.2 mm (four times the voxel size) yielded the highest t values at the somatosensorial primary cortex, and a boxcar response function provided the lowest residual variance after fitting. fMRat offers the features of a thorough SPM-based analysis combined with the functionality of several SPM extensions in a single automatic pipeline with a user-friendly interface. The code and sample images can be downloaded from https://github.com/HGGM-LIM/fmrat .

Design and optimization of an ultra wideband and compact microwave antenna for radiometric monitoring of brain temperature.

PubMed

Rodrigues, Dario B; Maccarini, Paolo F; Salahi, Sara; Oliveira, Tiago R; Pereira, Pedro J S; Limao-Vieira, Paulo; Snow, Brent W; Reudink, Doug; Stauffer, Paul R

2014-07-01

We present the modeling efforts on antenna design and frequency selection to monitor brain temperature during prolonged surgery using noninvasive microwave radiometry. A tapered log-spiral antenna design is chosen for its wideband characteristics that allow higher power collection from deep brain. Parametric analysis with the software HFSS is used to optimize antenna performance for deep brain temperature sensing. Radiometric antenna efficiency (η) is evaluated in terms of the ratio of power collected from brain to total power received by the antenna. Anatomical information extracted from several adult computed tomography scans is used to establish design parameters for constructing an accurate layered 3-D tissue phantom. This head phantom includes separate brain and scalp regions, with tissue equivalent liquids circulating at independent temperatures on either side of an intact skull. The optimized frequency band is 1.1-1.6 GHz producing an average antenna efficiency of 50.3% from a two turn log-spiral antenna. The entire sensor package is contained in a lightweight and low-profile 2.8 cm diameter by 1.5 cm high assembly that can be held in place over the skin with an electromagnetic interference shielding adhesive patch. The calculated radiometric equivalent brain temperature tracks within 0.4 °C of the measured brain phantom temperature when the brain phantom is lowered 10 °C and then returned to the original temperature (37 °C) over a 4.6-h experiment. The numerical and experimental results demonstrate that the optimized 2.5-cm log-spiral antenna is well suited for the noninvasive radiometric sensing of deep brain temperature.

Detection of rheumatoid arthritis using infrared imaging

NASA Astrophysics Data System (ADS)

Frize, Monique; Adéa, Cynthia; Payeur, Pierre; Di Primio, Gina; Karsh, Jacob; Ogungbemile, Abiola

2011-03-01

Rheumatoid arthritis (RA) is an inflammatory disease causing pain, swelling, stiffness, and loss of function in joints; it is difficult to diagnose in early stages. An early diagnosis and treatment can delay the onset of severe disability. Infrared (IR) imaging offers a potential approach to detect changes in degree of inflammation. In 18 normal subjects and 13 patients diagnosed with Rheumatoid Arthritis (RA), thermal images were collected from joints of hands, wrists, palms, and knees. Regions of interest (ROIs) were manually selected from all subjects and all parts imaged. For each subject, values were calculated from the temperature measurements: Mode/Max, Median/Max, Min/Max, Variance, Max-Min, (Mode-Mean), and Mean/Min. The data sets did not have a normal distribution, therefore non parametric tests (Kruskal-Wallis and Ranksum) were applied to assess if the data from the control group and the patient group were significantly different. Results indicate that: (i) thermal images can be detected on patients with the disease; (ii) the best joints to image are the metacarpophalangeal joints of the 2nd and 3rd fingers and the knees; the difference between the two groups was significant at the 0.05 level; (iii) the best calculations to differentiate between normal subjects and patients with RA are the Mode/Max, Variance, and Max-Min. We concluded that it is possible to reliably detect RA in patients using IR imaging. Future work will include a prospective study of normal subjects and patients that will compare IR results with Magnetic Resonance (MR) analysis.

Methode d'identification parametrique pour la surveillance in situ des joints a recouvrement par propagation d'ondes vibratoires

NASA Astrophysics Data System (ADS)

Francoeur, Dany

Cette these de doctorat s'inscrit dans le cadre de projets CRIAQ (Consortium de recherche et d'innovation en aerospatiale du Quebec) orientes vers le developpement d'approches embarquees pour la detection de defauts dans des structures aeronautiques. L'originalite de cette these repose sur le developpement et la validation d'une nouvelle methode de detection, quantification et localisation d'une entaille dans une structure de joint a recouvrement par la propagation d'ondes vibratoires. La premiere partie expose l'etat des connaissances sur l'identification d'un defaut dans le contexte du Structural Health Monitoring (SHM), ainsi que la modelisation de joint a recouvrements. Le chapitre 3 developpe le modele de propagation d'onde d'un joint a recouvrement endommage par une entaille pour une onde de flexion dans la plage des moyennes frequences (10-50 kHz). A cette fin, un modele de transmission de ligne (TLM) est realise pour representer un joint unidimensionnel (1D). Ce modele 1D est ensuite adapte a un joint bi-dimensionnel (2D) en faisant l'hypothese d'un front d'onde plan incident et perpendiculaire au joint. Une methode d'identification parametrique est ensuite developpee pour permettre a la fois la calibration du modele du joint a recouvrement sain, la detection puis la caracterisation de l'entaille situee sur le joint. Cette methode est couplee a un algorithme qui permet une recherche exhaustive de tout l'espace parametrique. Cette technique permet d'extraire une zone d'incertitude reliee aux parametres du modele optimal. Une etude de sensibilite est egalement realisee sur l'identification. Plusieurs resultats de mesure sur des joints a recouvrements 1D et 2D sont realisees permettant ainsi l'etude de la repetabilite des resultats et la variabilite de differents cas d'endommagement. Les resultats de cette etude demontrent d'abord que la methode de detection proposee est tres efficace et permet de suivre la progression d'endommagement. De tres bons resultats de quantification et de localisation d'entailles ont ete obtenus dans les divers joints testes (1D et 2D). Il est prevu que l'utilisation d'ondes de Lamb permettraient d'etendre la plage de validite de la methode pour de plus petits dommages. Ces travaux visent d'abord la surveillance in-situ des structures de joint a recouvrements, mais d'autres types de defauts. (comme les disbond) et. de structures complexes sont egalement envisageables. Mots cles : joint a recouvrement, surveillance in situ, localisation et caracterisation de dommages

Further Results of Soft-Inplane Tiltrotor Aeromechanics Investigation Using Two Multibody Analyses

NASA Technical Reports Server (NTRS)

Masarati, Pierangelo; Quaranta, Giuseppe; Piatak, David J.; Singleton, Jeffrey D.

2004-01-01

This investigation focuses on the development of multibody analytical models to predict the dynamic response, aeroelastic stability, and blade loading of a soft-inplane tiltrotor wind-tunnel model. Comprehensive rotorcraft-based multibody analyses enable modeling of the rotor system to a high level of detail such that complex mechanics and nonlinear effects associated with control system geometry and joint deadband may be considered. The influence of these and other nonlinear effects on the aeromechanical behavior of the tiltrotor model are examined. A parametric study of the design parameters which may have influence on the aeromechanics of the soft-inplane rotor system are also included in this investigation.

Differential diagnosis of normal pressure hydrocephalus by MRI mean diffusivity histogram analysis.

PubMed

Ivkovic, M; Liu, B; Ahmed, F; Moore, D; Huang, C; Raj, A; Kovanlikaya, I; Heier, L; Relkin, N

2013-01-01

Accurate diagnosis of normal pressure hydrocephalus is challenging because the clinical symptoms and radiographic appearance of NPH often overlap those of other conditions, including age-related neurodegenerative disorders such as Alzheimer and Parkinson diseases. We hypothesized that radiologic differences between NPH and AD/PD can be characterized by a robust and objective MR imaging DTI technique that does not require intersubject image registration or operator-defined regions of interest, thus avoiding many pitfalls common in DTI methods. We collected 3T DTI data from 15 patients with probable NPH and 25 controls with AD, PD, or dementia with Lewy bodies. We developed a parametric model for the shape of intracranial mean diffusivity histograms that separates brain and ventricular components from a third component composed mostly of partial volume voxels. To accurately fit the shape of the third component, we constructed a parametric function named the generalized Voss-Dyke function. We then examined the use of the fitting parameters for the differential diagnosis of NPH from AD, PD, and DLB. Using parameters for the MD histogram shape, we distinguished clinically probable NPH from the 3 other disorders with 86% sensitivity and 96% specificity. The technique yielded 86% sensitivity and 88% specificity when differentiating NPH from AD only. An adequate parametric model for the shape of intracranial MD histograms can distinguish NPH from AD, PD, or DLB with high sensitivity and specificity.

Multiscale reconstruction for MR fingerprinting.

PubMed

Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A

2016-06-01

To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Stochastic climate dynamics: Stochastic parametrizations and their global effects

NASA Astrophysics Data System (ADS)

Ghil, Michael

2010-05-01

A well-known difficulty in modeling the atmosphere and oceans' general circulation is the limited, albeit increasing resolution possible in the numerical solution of the governing partial differential equations. While the mass, energy and momentum of an individual cloud, in the atmosphere, or convection chimney, in the oceans, is negligible, their combined effects over long times are not. Until recently, small, subgrid-scale processes were represented in general circulation models (GCMs) by deterministic "parametrizations." While A. Arakawa and associates had realized over three decades ago the conceptual need for ensembles of clouds in such parametrizations, it is only very recently that truly stochastic parametrizations have been introduced into GCMs and weather prediction models. These parametrizations essentially transform a deterministic autonomous system into a non-autonomous one, subject to random forcing. To study systematically the long-term effects of such a forcing has to rely on theory of random dynamical systems (RDS). This theory allows one to consider the detailed geometric structure of the random attractors associated with nonlinear, stochastically perturbed systems. These attractors extend the concept of strange attractors from autonomous dynamical systems to non-autonomous systems with random forcing. To illustrate the essence of the theory, its concepts and methods, we carry out a high-resolution numerical study of two "toy" models in their respective phase spaces. This study allows one to obtain a good approximation of their global random attractors, as well as of the time-dependent invariant measures supported by these attractors. The first of the two models studied herein is the Arnol'd family of circle maps in the presence of noise. The maps' fine-grained, resonant landscape --- associated with Arnol'd tongues --- is smoothed by the noise, thus permitting a comparison with the observable aspects of the "Devil's staircase" that arises in modeling the El Nino-Southern Oscillation (ENSO). These results are confirmed by studying a "French garden" that is obtained by smoothing a "Devil's quarry." Such a quarry results from coupling two circle maps, and random forcing leads to a smoothed version thereof. We thus suspect that stochastic parametrizations will stabilize the sensitive dependence on parameters that has been noticed in the development of GCMs. This talk represents joint work with Mickael D. Chekroun, D. Kondrashov, Eric Simonnet and I. Zaliapin. Several other talks and posters complement the results presented here and provide further insights into RDS theory and its application to the geosciences.

Effects of overnight fasting on working memory-related brain network: an fMRI study.

PubMed

Chechko, Natalia; Vocke, Sebastian; Habel, Ute; Toygar, Timur; Kuckartz, Lisa; Berthold-Losleben, Mark; Laoutidis, Zacharias G; Orfanos, Stelios; Wassenberg, Annette; Karges, Wölfram; Schneider, Frank; Kohn, Nils

2015-03-01

Glucose metabolism serves as the central source of energy for the human brain. Little is known about the effects of blood glucose level (BGL) on higher-order cognitive functions within a physiological range (e.g., after overnight fasting). In this randomized, placebo-controlled, double blind study, we assessed the impact of overnight fasting (14 h) on brain activation during a working memory task. We sought to mimic BGLs that occur naturally in healthy humans after overnight fasting. After standardized periods of food restriction, 40 (20 male) healthy participants were randomly assigned to receive either glucagon to balance the BGL or placebo (NaCl). A parametric fMRI paradigm, including 2-back and 0-back tasks, was used. Subclinically low BGL following overnight fasting was found to be linked to reduced involvement of the bilateral dorsal midline thalamus and the bilateral basal ganglia, suggesting high sensitivity of those regions to minimal changes in BGLs. Our results indicate that overnight fasting leads to physiologically low levels of glucose, impacting brain activation during working memory tasks even when there are no differences in cognitive performance. © 2014 Wiley Periodicals, Inc.

Statistics of Weighted Brain Networks Reveal Hierarchical Organization and Gaussian Degree Distribution

PubMed Central

Ivković, Miloš; Kuceyeski, Amy; Raj, Ashish

2012-01-01

Whole brain weighted connectivity networks were extracted from high resolution diffusion MRI data of 14 healthy volunteers. A statistically robust technique was proposed for the removal of questionable connections. Unlike most previous studies our methods are completely adapted for networks with arbitrary weights. Conventional statistics of these weighted networks were computed and found to be comparable to existing reports. After a robust fitting procedure using multiple parametric distributions it was found that the weighted node degree of our networks is best described by the normal distribution, in contrast to previous reports which have proposed heavy tailed distributions. We show that post-processing of the connectivity weights, such as thresholding, can influence the weighted degree asymptotics. The clustering coefficients were found to be distributed either as gamma or power-law distribution, depending on the formula used. We proposed a new hierarchical graph clustering approach, which revealed that the brain network is divided into a regular base-2 hierarchical tree. Connections within and across this hierarchy were found to be uncommonly ordered. The combined weight of our results supports a hierarchically ordered view of the brain, whose connections have heavy tails, but whose weighted node degrees are comparable. PMID:22761649

Statistics of weighted brain networks reveal hierarchical organization and Gaussian degree distribution.

PubMed

Ivković, Miloš; Kuceyeski, Amy; Raj, Ashish

2012-01-01

Whole brain weighted connectivity networks were extracted from high resolution diffusion MRI data of 14 healthy volunteers. A statistically robust technique was proposed for the removal of questionable connections. Unlike most previous studies our methods are completely adapted for networks with arbitrary weights. Conventional statistics of these weighted networks were computed and found to be comparable to existing reports. After a robust fitting procedure using multiple parametric distributions it was found that the weighted node degree of our networks is best described by the normal distribution, in contrast to previous reports which have proposed heavy tailed distributions. We show that post-processing of the connectivity weights, such as thresholding, can influence the weighted degree asymptotics. The clustering coefficients were found to be distributed either as gamma or power-law distribution, depending on the formula used. We proposed a new hierarchical graph clustering approach, which revealed that the brain network is divided into a regular base-2 hierarchical tree. Connections within and across this hierarchy were found to be uncommonly ordered. The combined weight of our results supports a hierarchically ordered view of the brain, whose connections have heavy tails, but whose weighted node degrees are comparable.

Musculoskeletal loading during the round-off in female gymnastics: the effect of hand position.

PubMed

Farana, Roman; Jandacka, Daniel; Uchytil, Jaroslav; Zahradnik, David; Irwin, Gareth

2014-06-01

Chronic elbow injuries from tumbling in female gymnastics present a serious problem for performers. This research examined how the biomechanical characteristics of impact loading and elbow kinematics and kinetics change as a function of technique selection. Seven international-level female gymnasts performed 10 trials of the round-off from a hurdle step to flic-flac with 'parallel' and 'T-shape' hand positions. Synchronized kinematic (3D-automated motion analysis system; 247 Hz) and kinetic (two force plates; 1,235 Hz) data were collected for each trial. Wilcoxon non-parametric test and effect-size statistics determined differences between the hand positions examined in this study. Significant differences (p < 0.05) and large effect sizes (ES > 0.8) were observed for peak vertical ground reaction force (GRF), anterior-posterior GRF, resultant GRF, loading rates of these forces and elbow joint angles, and internal moments of force in sagittal, transverse, and frontal planes. In conclusion, the T-shape hand position reduces vertical, anterior-posterior, and resultant contact forces and has a decreased loading rate indicating a safer technique for the round-off. Significant differences observed in joint elbow moments highlighted that the T-shape position may prevent overloading of the joint complex and consequently reduce the potential for elbow injury.

Reconstructing for joint angles on the shoulder and elbow from non-invasive electroencephalographic signals through electromyography

PubMed Central

Choi, Kyuwan

2013-01-01

In this study, first the cortical activities over 2240 vertexes on the brain were estimated from 64 channels electroencephalography (EEG) signals using the Hierarchical Bayesian estimation while 5 subjects did continuous arm reaching movements. From the estimated cortical activities, a sparse linear regression method selected only useful features in reconstructing the electromyography (EMG) signals and estimated the EMG signals of 9 arm muscles. Then, a modular artificial neural network was used to estimate four joint angles from the estimated EMG signals of 9 muscles: one for movement control and the other for posture control. The estimated joint angles using this method have the correlation coefficient (CC) of 0.807 (±0.10) and the normalized root-mean-square error (nRMSE) of 0.176 (±0.29) with the actual joint angles. PMID:24167469

Cervical MRI scan

MedlinePlus

... you have: Brain aneurysm clips Certain types of artificial heart valves Heart defibrillator or pacemaker Inner ear (cochlear) implants Kidney disease or dialysis (you may not be able to receive contrast) Recently placed artificial joints Certain types of vascular stents Worked with ...

Lumbar MRI scan

MedlinePlus

... you have: Brain aneurysm clips Certain types of artificial heart valves Heart defibrillator or pacemaker Inner ear (cochlear) implants Kidney disease or dialysis (you may not be able to receive contrast) Recently placed artificial joints Certain types of vascular stents Worked with ...

Shoulder MRI scan

MedlinePlus

... you have: Brain aneurysm clips Certain types of artificial heart valves Heart defibrillator or pacemaker Inner ear (cochlear) implants Kidney disease or dialysis (you may not be able to receive contrast) Recently placed artificial joints Certain types of vascular stents Worked with ...

Aids to radiological differential diagnosis

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

Chapman, S.; Nakielny, R.

This book is composed of lists of differential diagnoses divided into categories: bone, spine, joints, respiratory, cardio-vascular, abdomen, gastrointestinal, urinary tract, soft tissues, face and neck, and skull and brain. It does not contain any reproductions of radiographs.

Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model

PubMed Central

Gooya, Ali; Pohl, Kilian M.; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR ) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth. PMID:21995070

Joint segmentation and deformable registration of brain scans guided by a tumor growth model.

PubMed

Gooya, Ali; Pohl, Kilian M; Bilello, Michel; Biros, George; Davatzikos, Christos

2011-01-01

This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorithm that incorporates a glioma growth model for atlas seeding, a process which modifies the normal atlas into one with a tumor and edema. The modified atlas is registered into the patient space and utilized for the posterior probability estimation of various tissue labels. EM iteratively refines the estimates of the registration parameters, the posterior probabilities of tissue labels and the tumor growth model parameters. We have applied this approach to 10 glioma scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE, T2 and FLAIR) and validated the result by comparing them to manual segmentations by clinical experts. The resulting segmentations look promising and quantitatively match well with the expert provided ground truth.

Hemin offers neuroprotection through inducing exogenous neuroglobin in focal cerebral hypoxic-ischemia in rats

PubMed Central

Song, Xue; Xu, Rui; Xie, Fei; Zhu, Haiyuan; Zhu, Ji; Wang, Xin

2014-01-01

Objective: To investigate the inducible effect of hemin on exogenous neuroglobin (Ngb) in focal cerebral hypoxic-ischemia in rats. Methods: 125 healthy SD rats were randomly divided into five groups: sham-operation control group, operation group, hemin treatment group, exogenous Ngb treatment group, and hemin and exogenous Ngb joint treatment group. Twenty-four hours after focal cerebral hypoxic-ischemia, Ngb expression was evaluated by immunocytochemistry, RT-PCR, and western blot analyses, while the brain water content and infarct volume were examined. Results: Immunocytochemistry, RT-PCR, and western blot analyses showed more pronounced Ngb expression in the hemin and exogenous Ngb joint operation group than in the hemin or exogenous Ngb individual treatment groups, thus producing significant differences in brain water content and infarct volume (p < 0.05). Conclusions: Hemin may be beneficial in protecting against focal cerebral hypoxic-ischemia through inducing the expression of exogenous Ngb. PMID:24966924

A Within-subjects Experimental Protocol to Assess the Effects of Social Input on Infant EEG.

PubMed

St John, Ashley M; Kao, Katie; Chita-Tegmark, Meia; Liederman, Jacqueline; Grieve, Philip G; Tarullo, Amanda R

2017-05-03

Despite the importance of social interactions for infant brain development, little research has assessed functional neural activation while infants socially interact. Electroencephalography (EEG) power is an advantageous technique to assess infant functional neural activation. However, many studies record infant EEG only during one baseline condition. This protocol describes a paradigm that is designed to comprehensively assess infant EEG activity in both social and nonsocial contexts as well as tease apart how different types of social inputs differentially relate to infant EEG. The within-subjects paradigm includes four controlled conditions. In the nonsocial condition, infants view objects on computer screens. The joint attention condition involves an experimenter directing the infant's attention to pictures. The joint attention condition includes three types of social input: language, face-to-face interaction, and the presence of joint attention. Differences in infant EEG between the nonsocial and joint attention conditions could be due to any of these three types of input. Therefore, two additional conditions (one with language input while the experimenter is hidden behind a screen and one with face-to-face interaction) were included to assess the driving contextual factors in patterns of infant neural activation. Representative results demonstrate that infant EEG power varied by condition, both overall and differentially by brain region, supporting the functional nature of infant EEG power. This technique is advantageous in that it includes conditions that are clearly social or nonsocial and allows for examination of how specific types of social input relate to EEG power. This paradigm can be used to assess how individual differences in age, affect, socioeconomic status, and parent-infant interaction quality relate to the development of the social brain. Based on the demonstrated functional nature of infant EEG power, future studies should consider the role of EEG recording context and design conditions that are clearly social or nonsocial.

Histopathologic lesions in conventional pigs experimentally infected with Haemophilus parasuis serovar 5.

PubMed

Palzer, A; Austin-Busse, R-L; Ladinig, A; Balka, G; Zoels, S; Ritzmann, M

2015-01-01

In the present study various tissues of pigs were investigated for the presence of histopathologic lesions after an experimental infection with Haemophilus (H.) parasuis serovar 5. Conventional pigs (n = 36) were divided into a control group B (n = 9) and a challenge group A (n = 27), which was infected intratracheally. Pigs that did not die prior to study termination were euthanized on day 14 post inoculation. Postmortem samples of the lung, heart, liver, kidney, spleen, left tarsal joint capsule and brain were collected. All but one pig with detectable histopathologic lesions (n = 11) showed typical macroscopic changes. Histopathologic examination of all tissue samples identified pyelitis (n = 10), synovitis (n = 7) and meningitis (n = 7) and all those animals were euthanized prior to study termination. No histopathologic lesions were found in pigs of the control group. The correlations between pyelitis and meningitis, pyelitis and synovitis and synovitis and meningitis were significant (p < 0.001). No significant correlation could be observed between the histopathologic and the clinical examination of the joints. The investigation of samples from the joints by PCR was not significantly correlated with the observed synovitis. The clinical observation of neurologic signs was significantly correlated with meningitis (p = 0.03). A significant correlation (p < 0.001) could be detected between meningitis and the detection of H. parasuis by PCR in brain samples. H. parasuis constantly causes clinical signs and pathologic lesions as soon as it infects the brain while it can infect the joints without causing histopathologic lesions. Pigs with histopathologic lesions do not always show typical clinical signs. Only few studies described the finding of kidney lesions in pigs with Glässer's disease and this is the first study to describe a pyelitis in pigs experimentally infected with H. parasuis. The observed pyelitis mainly occurred in acute cases.

Kinetic modeling of PET-FDG in the brain without blood sampling.

PubMed

Bentourkia, M'hamed

2006-12-01

The aim in this work is to report a new method to calculate parametric images from a single scan acquisition with positron emission tomography (PET) and fluorodeoxyglucose (FDG) in the human brain without blood sampling. It is usually practical for research or clinical purposes to inject the patient in an isolated room and to start the PET acquisition only for some 10-20 min, about 30 min after FDG injection. In order to calculate the cerebral metabolic rates for glucose (CMRG), usually several blood samples are required. The proposed method considers the relation between the uptake of the tracer in the cerebellum as a reference tissue and the population based input curve. Similar results were obtained for CMRG values with the present method in comparison to the usual autoradiographic and the non-linear least squares fitting of regions of interest.

Fractional motion model for characterization of anomalous diffusion from NMR signals.

PubMed

Fan, Yang; Gao, Jia-Hong

2015-07-01

Measuring molecular diffusion has been used to characterize the properties of living organisms and porous materials. NMR is able to detect the diffusion process in vivo and noninvasively. The fractional motion (FM) model is appropriate to describe anomalous diffusion phenomenon in crowded environments, such as living cells. However, no FM-based NMR theory has yet been established. Here, we present a general formulation of the FM-based NMR signal under the influence of arbitrary magnetic field gradient waveforms. An explicit analytic solution of the stretched exponential decay format for NMR signals with finite-width Stejskal-Tanner bipolar pulse magnetic field gradients is presented. Signals from a numerical simulation matched well with the theoretical prediction. In vivo diffusion-weighted brain images were acquired and analyzed using the proposed theory, and the resulting parametric maps exhibit remarkable contrasts between different brain tissues.

Fractional motion model for characterization of anomalous diffusion from NMR signals

NASA Astrophysics Data System (ADS)

Fan, Yang; Gao, Jia-Hong

2015-07-01

Measuring molecular diffusion has been used to characterize the properties of living organisms and porous materials. NMR is able to detect the diffusion process in vivo and noninvasively. The fractional motion (FM) model is appropriate to describe anomalous diffusion phenomenon in crowded environments, such as living cells. However, no FM-based NMR theory has yet been established. Here, we present a general formulation of the FM-based NMR signal under the influence of arbitrary magnetic field gradient waveforms. An explicit analytic solution of the stretched exponential decay format for NMR signals with finite-width Stejskal-Tanner bipolar pulse magnetic field gradients is presented. Signals from a numerical simulation matched well with the theoretical prediction. In vivo diffusion-weighted brain images were acquired and analyzed using the proposed theory, and the resulting parametric maps exhibit remarkable contrasts between different brain tissues.

Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

NASA Astrophysics Data System (ADS)

Rahimi, A.; Zhang, L.

2012-12-01

Rainfall-Runoff analysis is the key component for many hydrological and hydraulic designs in which the dependence of rainfall and runoff needs to be studied. It is known that the convenient bivariate distribution are often unable to model the rainfall-runoff variables due to that they either have constraints on the range of the dependence or fixed form for the marginal distributions. Thus, this paper presents an approach to derive the entropy-based joint rainfall-runoff distribution using Shannon entropy theory. The distribution derived can model the full range of dependence and allow different specified marginals. The modeling and estimation can be proceeded as: (i) univariate analysis of marginal distributions which includes two steps, (a) using the nonparametric statistics approach to detect modes and underlying probability density, and (b) fitting the appropriate parametric probability density functions; (ii) define the constraints based on the univariate analysis and the dependence structure; (iii) derive and validate the entropy-based joint distribution. As to validate the method, the rainfall-runoff data are collected from the small agricultural experimental watersheds located in semi-arid region near Riesel (Waco), Texas, maintained by the USDA. The results of unviariate analysis show that the rainfall variables follow the gamma distribution, whereas the runoff variables have mixed structure and follow the mixed-gamma distribution. With this information, the entropy-based joint distribution is derived using the first moments, the first moments of logarithm transformed rainfall and runoff, and the covariance between rainfall and runoff. The results of entropy-based joint distribution indicate: (1) the joint distribution derived successfully preserves the dependence between rainfall and runoff, and (2) the K-S goodness of fit statistical tests confirm the marginal distributions re-derived reveal the underlying univariate probability densities which further assure that the entropy-based joint rainfall-runoff distribution are satisfactorily derived. Overall, the study shows the Shannon entropy theory can be satisfactorily applied to model the dependence between rainfall and runoff. The study also shows that the entropy-based joint distribution is an appropriate approach to capture the dependence structure that cannot be captured by the convenient bivariate joint distributions. Joint Rainfall-Runoff Entropy Based PDF, and Corresponding Marginal PDF and Histogram for W12 Watershed The K-S Test Result and RMSE on Univariate Distributions Derived from the Maximum Entropy Based Joint Probability Distribution;

A practical solution to reduce soft tissue artifact error at the knee using adaptive kinematic constraints.

PubMed

Potvin, Brigitte M; Shourijeh, Mohammad S; Smale, Kenneth B; Benoit, Daniel L

2017-09-06

Musculoskeletal modeling and simulations have vast potential in clinical and research fields, but face various challenges in representing the complexities of the human body. Soft tissue artifact from skin-mounted markers may lead to non-physiological representation of joint motions being used as inputs to models in simulations. To address this, we have developed adaptive joint constraints on five of the six degree of freedom of the knee joint based on in vivo tibiofemoral joint motions recorded during walking, hopping and cutting motions from subjects instrumented with intra-cortical pins inserted into their tibia and femur. The constraint boundaries vary as a function of knee flexion angle and were tested on four whole-body models including four to six knee degrees of freedom. A musculoskeletal model developed in OpenSim simulation software was constrained to these in vivo boundaries during level gait and inverse kinematics and dynamics were then resolved. Statistical parametric mapping indicated significant differences (p<0.05) in kinematics between bone pin constrained and unconstrained model conditions, notably in knee translations, while hip and ankle flexion/extension angles were also affected, indicating the error at the knee propagates to surrounding joints. These changes to hip, knee, and ankle kinematics led to measurable changes in hip and knee transverse plane moments, and knee frontal plane moments and forces. Since knee flexion angle can be validly represented using skin mounted markers, our tool uses this reliable measure to guide the five other degrees of freedom at the knee and provide a more valid representation of the kinematics for these degrees of freedom. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improvement of Blood-Brain Barrier Integrity in Traumatic Brain Injury and Hemorrhagic Shock Following Treatment With Valproic Acid and Fresh Frozen Plasma.

PubMed

Nikolian, Vahagn C; Dekker, Simone E; Bambakidis, Ted; Higgins, Gerald A; Dennahy, Isabel S; Georgoff, Patrick E; Williams, Aaron M; Andjelkovic, Anuska V; Alam, Hasan B

2018-01-01

Combined traumatic brain injury and hemorrhagic shock are highly lethal. Following injuries, the integrity of the blood-brain barrier can be impaired, contributing to secondary brain insults. The status of the blood-brain barrier represents a potential factor impacting long-term neurologic outcomes in combined injuries. Treatment strategies involving plasma-based resuscitation and valproic acid therapy have shown efficacy in this setting. We hypothesize that a component of this beneficial effect is related to blood-brain barrier preservation. Following controlled traumatic brain injury, hemorrhagic shock, various resuscitation and treatment strategies were evaluated for their association with blood-brain barrier integrity. Analysis of gene expression profiles was performed using Porcine Gene ST 1.1 microarray. Pathway analysis was completed using network analysis tools (Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene Set Enrichment Analysis). Female Yorkshire swine were subjected to controlled traumatic brain injury and 2 hours of hemorrhagic shock (40% blood volume, mean arterial pressure 30-35 mmHg). Subjects were resuscitated with 1) normal saline, 2) fresh frozen plasma, 3) hetastarch, 4) fresh frozen plasma + valproic acid, or 5) hetastarch + valproic acid (n = 5 per group). After 6 hours of observation, brains were harvested for evaluation. Immunofluoroscopic evaluation of the traumatic brain injury site revealed significantly increased expression of tight-junction associated proteins (zona occludin-1, claudin-5) following combination therapy (fresh frozen plasma + valproic acid and hetastarch + valproic acid). The extracellular matrix protein laminin was found to have significantly improved expression with combination therapies. Pathway analysis indicated that valproic acid significantly modulated pathways involved in endothelial barrier function and cell signaling. Resuscitation with fresh frozen plasma results in improved expression of proteins essential for blood-brain barrier integrity. The addition of valproic acid provides significant improvement to these protein expression profiles. This is likely secondary to activation of key pathways related to endothelial functions.

To Design, or not to Design: An Introduction to a Six Article Series

DTIC Science & Technology

2011-03-04

theory centralizes on a hierarchal „ brain ‟ function that reinforces the aforementioned 14 Shimon Naveh...Joint Doctrine „Operational Art‟ and „effects-based-operations‟ principles that link a central „ brain ‟ with the actions of the system rival. “Capturing...in its passage through World War II that it liked; and it has not been able to free itself from the sweet memories of the Army that liberated France

A Wind-Tunnel Parametric Investigation of Tiltrotor Whirl-Flutter Stability Boundaries

NASA Technical Reports Server (NTRS)

Piatak, David J.; Kvaternik, Raymond G.; Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Bennett, Richard L.; Brown, Ross K.

2001-01-01

A wind-tunnel investigation of tiltrotor whirl-flutter stability boundaries has been conducted on a 1/5-size semispan tiltrotor model known as the Wing and Rotor Aeroelastic Test System (WRATS) in the NASA-Langley Transonic Dynamics Tunnel as part of a joint NASA/Army/Bell Helicopter Textron, Inc. (BHTI) research program. The model was first developed by BHTI as part of the JVX (V-22) research and development program in the 1980's and was recently modified to incorporate a hydraulically-actuated swashplate control system for use in active controls research. The modifications have changed the model's pylon mass properties sufficiently to warrant testing to re-establish its baseline stability boundaries. A parametric investigation of the effect of rotor design variables on stability was also conducted. The model was tested in both the on-downstop and off-downstop configurations, at cruise flight and hover rotor rotational speeds, and in both air and heavy gas (R-134a) test mediums. Heavy gas testing was conducted to quantify Mach number compressibility effects on tiltrotor stability. Experimental baseline stability boundaries in air are presented with comparisons to results from parametric variations of rotor pitch-flap coupling and control system stiffness. Increasing the rotor pitch-flap coupling (delta(sub 3) more negative) was found to have a destabilizing effect on stability, while a reduction in control system stiffness was found to have little effect on whirl-flutter stability. Results indicate that testing in R-134a, and thus matching full-scale tip Mach number, has a destabilizing effect, which demonstrates that whirl-flutter stability boundaries in air are unconservative.

Local changes in neocortical circuit dynamics coincide with the spread of seizures to thalamus in a model of epilepsy.

PubMed

Neubauer, Florian B; Sederberg, Audrey; MacLean, Jason N

2014-01-01

During the generalization of epileptic seizures, pathological activity in one brain area recruits distant brain structures into joint synchronous discharges. However, it remains unknown whether specific changes in local circuit activity are related to the aberrant recruitment of anatomically distant structures into epileptiform discharges. Further, it is not known whether aberrant areas recruit or entrain healthy ones into pathological activity. Here we study the dynamics of local circuit activity during the spread of epileptiform discharges in the zero-magnesium in vitro model of epilepsy. We employ high-speed multi-photon imaging in combination with dual whole-cell recordings in acute thalamocortical (TC) slices of the juvenile mouse to characterize the generalization of epileptic activity between neocortex and thalamus. We find that, although both structures are exposed to zero-magnesium, the initial onset of focal epileptiform discharge occurs in cortex. This suggests that local recurrent connectivity that is particularly prevalent in cortex is important for the initiation of seizure activity. Subsequent recruitment of thalamus into joint, generalized discharges is coincident with an increase in the coherence of local cortical circuit activity that itself does not depend on thalamus. Finally, the intensity of population discharges is positively correlated between both brain areas. This suggests that during and after seizure generalization not only the timing but also the amplitude of epileptiform discharges in thalamus is entrained by cortex. Together these results suggest a central role of neocortical activity for the onset and the structure of pathological recruitment of thalamus into joint synchronous epileptiform discharges.

Local changes in neocortical circuit dynamics coincide with the spread of seizures to thalamus in a model of epilepsy

PubMed Central

Neubauer, Florian B.; Sederberg, Audrey; MacLean, Jason N.

2014-01-01

During the generalization of epileptic seizures, pathological activity in one brain area recruits distant brain structures into joint synchronous discharges. However, it remains unknown whether specific changes in local circuit activity are related to the aberrant recruitment of anatomically distant structures into epileptiform discharges. Further, it is not known whether aberrant areas recruit or entrain healthy ones into pathological activity. Here we study the dynamics of local circuit activity during the spread of epileptiform discharges in the zero-magnesium in vitro model of epilepsy. We employ high-speed multi-photon imaging in combination with dual whole-cell recordings in acute thalamocortical (TC) slices of the juvenile mouse to characterize the generalization of epileptic activity between neocortex and thalamus. We find that, although both structures are exposed to zero-magnesium, the initial onset of focal epileptiform discharge occurs in cortex. This suggests that local recurrent connectivity that is particularly prevalent in cortex is important for the initiation of seizure activity. Subsequent recruitment of thalamus into joint, generalized discharges is coincident with an increase in the coherence of local cortical circuit activity that itself does not depend on thalamus. Finally, the intensity of population discharges is positively correlated between both brain areas. This suggests that during and after seizure generalization not only the timing but also the amplitude of epileptiform discharges in thalamus is entrained by cortex. Together these results suggest a central role of neocortical activity for the onset and the structure of pathological recruitment of thalamus into joint synchronous epileptiform discharges. PMID:25232306

A novel Brain Computer Interface for classification of social joint attention in autism and comparison of 3 experimental setups: A feasibility study.

PubMed

Amaral, Carlos P; Simões, Marco A; Mouga, Susana; Andrade, João; Castelo-Branco, Miguel

2017-10-01

We present a novel virtual-reality P300-based Brain Computer Interface (BCI) paradigm using social cues to direct the focus of attention. We combined interactive immersive virtual-reality (VR) technology with the properties of P300 signals in a training tool which can be used in social attention disorders such as autism spectrum disorder (ASD). We tested the novel social attention training paradigm (P300-based BCI paradigm for rehabilitation of joint-attention skills) in 13 healthy participants, in 3 EEG systems. The more suitable setup was tested online with 4 ASD subjects. Statistical accuracy was assessed based on the detection of P300, using spatial filtering and a Naïve-Bayes classifier. We compared: 1 - g.Mobilab+ (active dry-electrodes, wireless transmission); 2 - g.Nautilus (active electrodes, wireless transmission); 3 - V-Amp with actiCAP Xpress dry-electrodes. Significant statistical classification was achieved in all systems. g.Nautilus proved to be the best performing system in terms of accuracy in the detection of P300, preparation time, speed and reported comfort. Proof of concept tests in ASD participants proved that this setup is feasible for training joint attention skills in ASD. This work provides a unique combination of 'easy-to-use' BCI systems with new technologies such as VR to train joint-attention skills in autism. Our P300 BCI paradigm is feasible for future Phase I/II clinical trials to train joint-attention skills, with successful classification within few trials, online in ASD participants. The g.Nautilus system is the best performing one to use with the developed BCI setup. Copyright © 2017 Elsevier B.V. All rights reserved.

Neurovisceral phenotypes in the expression of psychiatric symptoms

PubMed Central

Eccles, Jessica A.; Owens, Andrew P.; Mathias, Christopher J.; Umeda, Satoshi; Critchley, Hugo D.

2015-01-01

This review explores the proposal that vulnerability to psychological symptoms, particularly anxiety, originates in constitutional differences in the control of bodily state, exemplified by a set of conditions that include Joint Hypermobility, Postural Tachycardia Syndrome and Vasovagal Syncope. Research is revealing how brain-body mechanisms underlie individual differences in psychophysiological reactivity that can be important for predicting, stratifying and treating individuals with anxiety disorders and related conditions. One common constitutional difference is Joint Hypermobility, in which there is an increased range of joint movement as a result of a variant of collagen. Joint hypermobility is over-represented in people with anxiety, mood and neurodevelopmental disorders. It is also linked to stress-sensitive medical conditions such as irritable bowel syndrome, chronic fatigue syndrome and fibromyalgia. Structural differences in “emotional” brain regions are reported in hypermobile individuals, and many people with joint hypermobility manifest autonomic abnormalities, typically Postural Tachycardia Syndrome. Enhanced heart rate reactivity during postural change and as recently recognized factors causing vasodilatation (as noted post-prandially, post-exertion and with heat) is characteristic of Postural Tachycardia Syndrome, and there is a phenomenological overlap with anxiety disorders, which may be partially accounted for by exaggerated neural reactivity within ventromedial prefrontal cortex. People who experience Vasovagal Syncope, a heritable tendency to fainting induced by emotional challenges (and needle/blood phobia), are also more vulnerable to anxiety disorders. Neuroimaging implicates brainstem differences in vulnerability to faints, yet the structural integrity of the caudate nucleus appears important for the control of fainting frequency in relation to parasympathetic tone and anxiety. Together there is clinical and neuroanatomical evidence to show that common constitutional differences affecting autonomic responsivity are linked to psychiatric symptoms, notably anxiety. PMID:25713509

[Trigeminal motor paralysis and dislocation of the temporo-mandibular joints].

PubMed

Ohkawa, S; Yoshida, T; Ohsumi, Y; Tabuchi, M

1996-07-01

A 64-year-old woman with diabetes mellitus was admitted to our hospital with left hemiparesis of sudden onset. A brain MRI demonstrated a cerebral infarction in the ventral part of the right lower pons. When left hemiparesis worsened, she had dislocation of the temporo-mandibular joints repeatedly. Then, her lower jaw deviated to the right when she opened her mouth. Also, there was decreased contraction of the right masseter when she clenched her teeth. These findings suggest that there was trigeminal motor paralysis on the right side resulting from involvement of the intrapontine trigeminal motor nerve. She has no history of dislocation of the temporo-mandibular joints. An X-ray film showed that the temporo-mandibular joints were intact. Thus, it is possible that deviation of the lower jaw was the cause of this dislocation. We suspect that dislocation of the temporo-mandibular joints may occur as a complication of unilateral trigeminal motor paralysis. This has not been reported to our knowledge.

Discriminating Schizophrenia and Bipolar Disorder by Fusing FMRI and DTI in A Multimodal CCA+ Joint ICA Model

PubMed Central

Sui, Jing; Pearlson, Godfrey; Adali, Tülay; Kiehl, Kent A.; Caprihan, Arvind; Liu, Jingyu; Yamamoto, Jeremy; Calhoun, Vince D.

2011-01-01

Diverse structural and functional brain alterations have been identified in both schizophrenia and bipolar disorder, but with variable replicability, significant overlap and often in limited number of subjects. In this paper, we aimed to clarify differences between bipolar disorder and schizophrenia by combining fMRI (collected during an auditory oddball task) and diffusion tensor imaging (DTI) data. We proposed a fusion method, “multimodal CCA+ joint ICA’, which increases flexibility in statistical assumptions beyond existing approaches and can achieve higher estimation accuracy. The data collected from 164 participants (62 healthy controls, 54 schizophrenia and 48 bipolar) were extracted into “features” (contrast maps for fMRI and fractional anisotropy (FA) for DTI) and analyzed in multiple facets to investigate the group differences for each pair-wised groups and each modality. Specifically, both patient groups shared significant dysfunction in dorsolateral prefrontal cortex and thalamus, as well as reduced white matter (WM) integrity in anterior thalamic radiation and uncinate fasciculus. Schizophrenia and bipolar subjects were separated by functional differences in medial frontal and visual cortex, as well as WM tracts associated with occipital and frontal lobes. Both patients and controls showed similar spatial distributions in motor and parietal regions, but exhibited significant variations in temporal lobe. Furthermore, there were different group trends for age effects on loading parameters in motor cortex and multiple WM regions, suggesting brain dysfunction and WM disruptions occurred in identified regions for both disorders. Most importantly, we can visualize an underlying function-structure network by evaluating the joint components with strong links between DTI and fMRI. Our findings suggest that although the two patient groups showed several distinct brain patterns from each other and healthy controls, they also shared common abnormalities in prefrontal thalamic WM integrity and in frontal brain mechanisms. PMID:21640835

Parametric Optimization Of Gas Metal Arc Welding Process By Using Grey Based Taguchi Method On Aisi 409 Ferritic Stainless Steel

NASA Astrophysics Data System (ADS)

Ghosh, Nabendu; Kumar, Pradip; Nandi, Goutam

2016-10-01

Welding input process parameters play a very significant role in determining the quality of the welded joint. Only by properly controlling every element of the process can product quality be controlled. For better quality of MIG welding of Ferritic stainless steel AISI 409, precise control of process parameters, parametric optimization of the process parameters, prediction and control of the desired responses (quality indices) etc., continued and elaborate experiments, analysis and modeling are needed. A data of knowledge - base may thus be generated which may be utilized by the practicing engineers and technicians to produce good quality weld more precisely, reliably and predictively. In the present work, X-ray radiographic test has been conducted in order to detect surface and sub-surface defects of weld specimens made of Ferritic stainless steel. The quality of the weld has been evaluated in terms of yield strength, ultimate tensile strength and percentage of elongation of the welded specimens. The observed data have been interpreted, discussed and analyzed by considering ultimate tensile strength ,yield strength and percentage elongation combined with use of Grey-Taguchi methodology.

Deep brain stimulation enhances movement complexity during gait in individuals with Parkinson's disease.

PubMed

Powell, Douglas W; Blackmore, Sarah E; Puppa, Melissa; Lester, Deranda; Murray, Nicholas G; Reed-Jones, Rebecca J; Xia, Rui-Ping

2018-05-08

Deep brain stimulation (DBS) is associated with substantial improvements in motor symptoms of PD. Emerging evidence has suggested that nonlinear measures of complexity may provide greater insight into the efficacy of anti-PD treatments. This study investigated sample entropy and complexity index values in individuals with PD when DBS was OFF compared to ON. Five individuals with PD using DBS performed a four-minute treadmill walking task while 3D kinematics were collected over two periods of 30 s. Participants were tested in the DBS-ON and DBS-OFF conditions. Sample entropy (SE) and complexity index (CI) values were calculated for ankle, knee and hip joint angles. Paired samples t-tests were used to compare mean SE and CI values between the DBS-OFF and DBS-ON conditions, respectively. No differences in SE or CI were observed between the DBS-ON and DBS-OFF conditions at the ankle. At the knee, the DBS-ON was associated with greater SE and CI values than the DBS-OFF condition. At the hip, DBS-ON was associated with greater SE and CI values than the DBS-OFF condition. DBS enhances complexity of movement at the hip and knee joints while complexity at the ankle joint is not significantly altered. Greater complexity of knee and hip joint motion may represent increased adaptability and a greater number of available strategies to complete the gait task. Copyright © 2018 Elsevier B.V. All rights reserved.

Stimulated Parametric Decay of Large Amplitude Alfvén waves in the Large Plasma Device (LaPD)

NASA Astrophysics Data System (ADS)

Dorfman, S. E.; Carter, T.; Pribyl, P.; Tripathi, S.; Van Compernolle, B.; Vincena, S. T.

2012-12-01

Alfvén waves, a fundamental mode of magnetized plasmas, are ubiquitous in lab and space. While the linear behaviour of these waves has been extensively studied [1], non-linear effects are important in many real systems, including the solar wind and solar corona. In particular, a parametric decay process in which a large amplitude Alfvén wave decays into an ion acoustic wave and backward propagating Alfvén wave may be key to the spectrum of solar wind turbulence. Ion acoustic waves have been observed in the heliosphere, but their origin and role have not yet been determined [2]. Such waves produced by parametric decay in the corona could contribute to coronal heating [3]. Parametric decay has also been suggested as an intermediate instability mediating the observed turbulent cascade of Alfvén waves to small spatial scales [4]. The present laboratory experiments aim to stimulate the parametric decay process by launching counter-propagating Alfvén waves from antennas placed at either end of the Large Plasma Device (LaPD). The resulting beat response has a dispersion relation consistent with an ion acoustic wave. Also consistent with a stimulated decay process: 1) The beat amplitude peaks when the frequency difference between the two Alfvén waves is near the value predicted by Alfvén-ion acoustic wave coupling. 2) This peak beat frequency scales with antenna and plasma parameters as predicted by three wave matching. 3) The beat amplitude peaks at the same location as the magnetic field from the Alfvén waves. 4) The beat wave is carried by the ions and propagates in the direction of the higher-frequency Alfvén wave. Strong damping observed after the pump Alfvén waves are turned off and observed heating of the plasma by the Alfvén waves are under investigation. [1] W. Gekelman, J. Geophys. Res., 104:14417-14436, July 1999. [2] A. Mangeney,et. al., Annales Geophysicae, Volume 17, Number 3 (1999). [3] F. Pruneti, F and M. Velli, ESA Spec. Pub. 404, 623 (1997). [4] P. Yoon and T. Fang, Plasma Phys. Control. Fusion 50 (2008). This work was performed at UCLA's Basic Plasma Science Facility, which is jointly supported by the U.S. DoE and NSF.

Neural networks improve brain cancer detection with Raman spectroscopy in the presence of light artifacts

NASA Astrophysics Data System (ADS)

Jermyn, Michael; Desroches, Joannie; Mercier, Jeanne; St-Arnaud, Karl; Guiot, Marie-Christine; Petrecca, Kevin; Leblond, Frederic

2016-03-01

It is often difficult to identify cancer tissue during brain cancer (glioma) surgery. Gliomas invade into areas of normal brain, and this cancer invasion is frequently not detected using standard preoperative magnetic resonance imaging (MRI). This results in enduring invasive cancer following surgery and leads to recurrence. A hand-held Raman spectroscopy is able to rapidly detect cancer invasion in patients with grade 2-4 gliomas. However, ambient light sources can produce spectral artifacts which inhibit the ability to distinguish between cancer and normal tissue using the spectral information available. To address this issue, we have demonstrated that artificial neural networks (ANN) can accurately classify invasive cancer versus normal brain tissue, even when including measurements with significant spectral artifacts from external light sources. The non-parametric and adaptive model used by ANN makes it suitable for detecting complex non-linear spectral characteristics associated with different tissues and the confounding presence of light artifacts. The use of ANN for brain cancer detection with Raman spectroscopy, in the presence of light artifacts, improves the robustness and clinical translation potential for intraoperative use. Integration with the neurosurgical workflow is facilitated by accounting for the effect of light artifacts which may occur, due to operating room lights, neuronavigation systems, windows, or other light sources. The ability to rapidly detect invasive brain cancer under these conditions may reduce residual cancer remaining after surgery, and thereby improve patient survival.

Dysbindin modulates brain function during visual processing in children.

PubMed

Mechelli, A; Viding, E; Kumar, A; Pettersson-Yeo, W; Fusar-Poli, P; Tognin, S; O'Donovan, M C; McGuire, P

2010-01-01

Schizophrenia is a neurodevelopmental disorder, and risk genes are thought to act through disruption of brain development. Several genetic studies have identified dystrobrevin binding protein 1 (DTNBP1, also known as dysbindin) as a potential susceptibility gene for schizophrenia, but its impact on brain function is poorly understood. It has been proposed that DTNBP1 may be associated with differences in visual processing. To test this, we examined the impact on visual processing in 61 healthy children aged 10-12 years of a genetic variant in DTNBP1 (rs2619538) that was common to all schizophrenia associated haplotypes in an earlier UK-Irish study. We tested the hypothesis that carriers of the risk allele would show altered occipital cortical function relative to noncarriers. Functional Magnetic Resonance Imaging (fMRI) was used to measure brain responses during a visual matching task. The data were analysed using statistical parametric mapping and statistical inferences were made at p<0.05 (corrected for multiple comparisons). Relative to noncarriers, carriers of the risk allele had greater activation in the lingual, fusiform gyrus and inferior occipital gyri. In these regions DTNBP1 genotype accounted for 19%, 20% and 14% of the inter-individual variance, respectively. Our results suggest that that genetic variation in DTNBP1 is associated with differences in the function of brain areas that mediate visual processing, and that these effects are evident in young children. These findings are consistent with the notion that the DTNBP1 gene influences brain development and can thereby modulate vulnerability to schizophrenia.

Dynamic optical imaging of vascular and metabolic reactivity in rheumatoid joints.

PubMed

Lasker, Joseph M; Fong, Christopher J; Ginat, Daniel T; Dwyer, Edward; Hielscher, Andreas H

2007-01-01

Dynamic optical imaging is increasingly applied to clinically relevant areas such as brain and cancer imaging. In this approach, some external stimulus is applied and changes in relevant physiological parameters (e.g., oxy- or deoxyhemoglobin concentrations) are determined. The advantage of this approach is that the prestimulus state can be used as a reference or baseline against which the changes can be calibrated. Here we present the first application of this method to the problem of characterizing joint diseases, especially effects of rheumatoid arthritis (RA) in the proximal interphalangeal finger joints. Using a dual-wavelength tomographic imaging system together with previously implemented model-based iterative image reconstruction schemes, we have performed initial dynamic imaging case studies on a limited number of healthy volunteers and patients diagnosed with RA. Focusing on three cases studies, we illustrated our major finds. These studies support our hypothesis that differences in the vascular reactivity exist between affected and unaffected joints.

Multi-subject Manifold Alignment of Functional Network Structures via Joint Diagonalization.

PubMed

Nenning, Karl-Heinz; Kollndorfer, Kathrin; Schöpf, Veronika; Prayer, Daniela; Langs, Georg

2015-01-01

Functional magnetic resonance imaging group studies rely on the ability to establish correspondence across individuals. This enables location specific comparison of functional brain characteristics. Registration is often based on morphology and does not take variability of functional localization into account. This can lead to a loss of specificity, or confounds when studying diseases. In this paper we propose multi-subject functional registration by manifold alignment via coupled joint diagonalization. The functional network structure of each subject is encoded in a diffusion map, where functional relationships are decoupled from spatial position. Two-step manifold alignment estimates initial correspondences between functionally equivalent regions. Then, coupled joint diagonalization establishes common eigenbases across all individuals, and refines the functional correspondences. We evaluate our approach on fMRI data acquired during a language paradigm. Experiments demonstrate the benefits in matching accuracy achieved by coupled joint diagonalization compared to previously proposed functional alignment approaches, or alignment based on structural correspondences.

Lower extremity kinematics during walking and elliptical training in individuals with and without traumatic brain injury.

PubMed

Buster, Thad; Burnfield, Judith; Taylor, Adam P; Stergiou, Nicholas

2013-12-01

Elliptical training may be an option for practicing walking-like activity for individuals with traumatic brain injuries (TBI). Understanding similarities and differences between participants with TBI and neurologically healthy individuals during elliptical trainer use and walking may help guide clinical applications incorporating elliptical trainers. Ten participants with TBI and a comparison group of 10 neurologically healthy participants underwent 2 familiarization sessions and 1 data collection session. Kinematic data were collected as participants walked on a treadmill or on an elliptical trainer. Gait-related measures, including coefficient of multiple correlations (a measure of similarity between ensemble joint movement profiles; coefficient of multiple correlations [CMCs]), critical event joint angles, variability of peak critical event joint angles (standard deviations [SDs]) of peak critical event joint angles, and maximum Lyapunov exponents (a measure of the organization of the variability [LyEs]) were compared between groups and conditions. Coefficient of multiple correlations values comparing the similarity in ensemble motion profiles between the TBI and comparison participants exceeded 0.85 for the hip, knee, and ankle joints. The only critical event joint angle that differed significantly between participants with TBI and comparison participants was the ankle during terminal stance. Variability was higher for the TBI group (6 of 11 comparisons significant) compared with comparison participants. Hip and knee joint movement patterns of both participants with TBI and comparison participants on the elliptical trainer were similar to walking (CMCs ≥ 0.87). Variability was higher during elliptical trainer usage compared with walking (5 of 11 comparisons significant). Hip LyEs were higher during treadmill walking. Ankle LyEs were greater during elliptical trainer usage. Movement patterns of participants with TBI were similar to, but more variable than, those of comparison participants while using both the treadmill and the elliptical trainer. If incorporation of complex movements similar to walking is a goal of rehabilitation, elliptical training is a reasonable alternative to treadmill-based training.Video Abstract available (see Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A65) for more insights from the authors.

Enactive cinema paves way for understanding complex real-time social interaction in neuroimaging experiments

PubMed Central

Tikka, Pia; Väljamäe, Aleksander; de Borst, Aline W.; Pugliese, Roberto; Ravaja, Niklas; Kaipainen, Mauri; Takala, Tapio

2012-01-01

We outline general theoretical and practical implications of what we promote as enactive cinema for the neuroscientific study of online socio-emotional interaction. In a real-time functional magnetic resonance imaging (rt-fMRI) setting, participants are immersed in cinematic experiences that simulate social situations. While viewing, their physiological reactions—including brain responses—are tracked, representing implicit and unconscious experiences of the on-going social situations. These reactions, in turn, are analyzed in real-time and fed back to modify the cinematic sequences they are viewing while being scanned. Due to the engaging cinematic content, the proposed setting focuses on living-by in terms of shared psycho-physiological epiphenomena of experience rather than active coping in terms of goal-oriented motor actions. It constitutes a means to parametrically modify stimuli that depict social situations and their broader environmental contexts. As an alternative to studying the variation of brain responses as a function of a priori fixed stimuli, this method can be applied to survey the range of stimuli that evoke similar responses across participants at particular brain regions of interest. PMID:23125829

Monetary reward magnitude effects on behavior and brain function during goal-directed behavior.

PubMed

Rosell-Negre, P; Bustamante, J C; Fuentes-Claramonte, P; Costumero, V; Benabarre, S; Barrós-Loscertales, A

2017-08-01

Reward may modulate the cognitive processes required for goal achievement, while individual differences in personality may affect reward modulation. Our aim was to test how different monetary reward magnitudes modulate brain activation and performance during goal-directed behavior, and whether individual differences in reward sensitivity affect this modulation. For this purpose, we scanned 37 subjects with a parametric design in which we varied the magnitude of monetary rewards (€0, €0.01, €0.5, €1 or €1.5) in a blocked fashion while participants performed an interference counting-Stroop condition. The results showed that the brain activity of left dorsolateral prefrontal cortex (DLPFC) and the striatum were modulated by increasing and decreasing reward magnitudes, respectively. Behavioral performance improved as the magnitude of monetary reward increased while comparing the non reward (€0) condition to any other reward condition, or the lower €0.01 to any other reward condition, and this improvement was related with individual differences in reward sensitivity. In conclusion, the locus of influence of monetary incentives overlaps the activity of the regions commonly involved in cognitive control.

Regional CBF in chronic stable TBI treated with hyperbaric oxygen.

PubMed

Barrett, K F; Masel, B; Patterson, J; Scheibel, R S; Corson, K P; Mader, J T

2004-01-01

To investigate whether Hyperbaric Oxygen Therapy (HBO2) could improve neurologic deficits and regional cerebral blood flow (rCBF) in chronic traumatic brain injuries (TBI), the authors employed a nonrandomized control pilot trial. Five subjects, at least three years post head injury, received HBO2. Five head injured controls (HIC) were matched for age, sex, and type of injury. Five healthy subjects served as normal controls. Sixty-eight normal volunteers comprised a reference data bank against which to compare SPECT brain scans. HBO2 subjects received 120 HBO2 in blocks of 80 and 40 treatments with an interval five-month break. Normal controls underwent a single SPECT brain scan, HBO2, and repeat SPECT battery. TBI subjects were evaluated by neurologic, neuropsychometric, exercise testing, and pre and post study MRIs, or CT scans if MRI was contraindicated. Statistical Parametric Mapping was applied to SPECT scans for rCBF analysis. There were no significant objective changes in neurologic, neuropsychometric, exercise testing, MRIs, or rCBF. In this small pilot study, HBO2 did not effect clinical or regional cerebral blood flow improvement in TBI subjects.

Pain when love is near

NASA Astrophysics Data System (ADS)

Tamam, S.; Ahmad, A. H.; Aziz, M. E.; Kamil, W. A.

2017-05-01

The aim of the study is to investigate brain responses to acute laser pain when a loved one is nearby. Laser pain stimuli at individual pain threshold were delivered using Th:YAG laser to 17 female participants. The participants were categorised into two groups, Love Hurts or Love Heals, according to their responses to pain stimulation during the presence of their loved ones. fMRI brain activation was obtained using 3 T Philips Achieva MRI scanner utilising blocked design paradigm comprising 15 blocks of stimulation phase and 15 blocks of no stimulation. fMRI images were analysed using statistical parametric mapping (SPM) focusing on random effects (RFX) analysis. We found that both groups activated pain-related areas such as the thalamus, secondary somatosensory cortex, insula and cingulate cortex. However, Love Hurts showed more activity in thalamus, parahippocampal gyrus and hippocampus; while Love Heals showed more activity in the entire part of cingulate cortex during the presence of their loved ones. In conclusion, there may be specific brain regions responsible for modulation of pain due to the presence of a loved one thus manifesting as Love Hurts or Love Heals.

Three validation metrics for automated probabilistic image segmentation of brain tumours

PubMed Central

Zou, Kelly H.; Wells, William M.; Kikinis, Ron; Warfield, Simon K.

2005-01-01

SUMMARY The validity of brain tumour segmentation is an important issue in image processing because it has a direct impact on surgical planning. We examined the segmentation accuracy based on three two-sample validation metrics against the estimated composite latent gold standard, which was derived from several experts’ manual segmentations by an EM algorithm. The distribution functions of the tumour and control pixel data were parametrically assumed to be a mixture of two beta distributions with different shape parameters. We estimated the corresponding receiver operating characteristic curve, Dice similarity coefficient, and mutual information, over all possible decision thresholds. Based on each validation metric, an optimal threshold was then computed via maximization. We illustrated these methods on MR imaging data from nine brain tumour cases of three different tumour types, each consisting of a large number of pixels. The automated segmentation yielded satisfactory accuracy with varied optimal thresholds. The performances of these validation metrics were also investigated via Monte Carlo simulation. Extensions of incorporating spatial correlation structures using a Markov random field model were considered. PMID:15083482

Regional Brain Activity in Abstinent Methamphetamine Dependent Males Following Cue Exposure.

PubMed

Malcolm, Robert; Myrick, Hugh; Li, Xingbao; Henderson, Scott; Brady, Kathleen T; George, Mark S; See, Ronald E

Neuroimaging of drug-associated cue presentations has aided in understanding the neurobiological substrates of craving and relapse for cocaine, alcohol, and nicotine. However, imaging of cue-reactivity in methamphetamine addiction has been much less studied. Nine caucasian male methamphetamine-dependent subjects and nine healthy controls were scanned in a Phillips 3.0T MRI scan when they viewed a randomized presentation of visual cues of methamphetamine, neutral objects, and rest conditions. Functional Imaging data were analyzed with Statistical Parametric Mapping software 5 (SPM 5). Methamphetamine subjects had significant brain activation in the ventral striatum and medial frontal cortex in comparison to meth pictures and neutral pictures in healthy controls (p<0.005, threshold 15 voxels). Interestingly the ventral striatum activation significantly correlated with the days since the last use of meth (r=-0.76, p=0.017). No significant activity was found in healthy control group. The preliminary data suggest that methamphetamine dependent subjects, when exposed to methamphetamine-associated visual cues, have increased brain activity in ventral striatum, caudate nucleus and medial frontal cortex which subserve craving, drug-seeking, and drug use.

Enactive cinema paves way for understanding complex real-time social interaction in neuroimaging experiments.

PubMed

Tikka, Pia; Väljamäe, Aleksander; de Borst, Aline W; Pugliese, Roberto; Ravaja, Niklas; Kaipainen, Mauri; Takala, Tapio

2012-01-01

We outline general theoretical and practical implications of what we promote as enactive cinema for the neuroscientific study of online socio-emotional interaction. In a real-time functional magnetic resonance imaging (rt-fMRI) setting, participants are immersed in cinematic experiences that simulate social situations. While viewing, their physiological reactions-including brain responses-are tracked, representing implicit and unconscious experiences of the on-going social situations. These reactions, in turn, are analyzed in real-time and fed back to modify the cinematic sequences they are viewing while being scanned. Due to the engaging cinematic content, the proposed setting focuses on living-by in terms of shared psycho-physiological epiphenomena of experience rather than active coping in terms of goal-oriented motor actions. It constitutes a means to parametrically modify stimuli that depict social situations and their broader environmental contexts. As an alternative to studying the variation of brain responses as a function of a priori fixed stimuli, this method can be applied to survey the range of stimuli that evoke similar responses across participants at particular brain regions of interest.

To cut or not to cut? Assessing the modular structure of brain networks.

PubMed

Chang, Yu-Teng; Pantazis, Dimitrios; Leahy, Richard M

2014-05-01

A wealth of methods has been developed to identify natural divisions of brain networks into groups or modules, with one of the most prominent being modularity. Compared with the popularity of methods to detect community structure, only a few methods exist to statistically control for spurious modules, relying almost exclusively on resampling techniques. It is well known that even random networks can exhibit high modularity because of incidental concentration of edges, even though they have no underlying organizational structure. Consequently, interpretation of community structure is confounded by the lack of principled and computationally tractable approaches to statistically control for spurious modules. In this paper we show that the modularity of random networks follows a transformed version of the Tracy-Widom distribution, providing for the first time a link between module detection and random matrix theory. We compute parametric formulas for the distribution of modularity for random networks as a function of network size and edge variance, and show that we can efficiently control for false positives in brain and other real-world networks. Copyright © 2014 Elsevier Inc. All rights reserved.

Psychological Evaluation and Prescription Development Handbook.

ERIC Educational Resources Information Center

Vigo County School Corp., Terre Haute, IN.

Developed to aid children with learning difficulties, from mental retardation or brain injury to maladjustment or physical or environmental handicaps, the joint school services program provides psychological evaluation and prescription development. The handbook reviews theories of child development and surveys behavior modification and…

Quantification of Load Dependent Brain Activity in Parametric N-Back Working Memory Tasks using Pseudo-continuous Arterial Spin Labeling (pCASL) Perfusion Imaging.

PubMed

Zou, Qihong; Gu, Hong; Wang, Danny J J; Gao, Jia-Hong; Yang, Yihong

2011-04-01

Brain activation and deactivation induced by N-back working memory tasks and their load effects have been extensively investigated using positron emission tomography (PET) and blood-oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI). However, the underlying mechanisms of BOLD fMRI are still not completely understood and PET imaging requires injection of radioactive tracers. In this study, a pseudo-continuous arterial spin labeling (pCASL) perfusion imaging technique was used to quantify cerebral blood flow (CBF), a well understood physiological index reflective of cerebral metabolism, in N-back working memory tasks. Using pCASL, we systematically investigated brain activation and deactivation induced by the N-back working memory tasks and further studied the load effects on brain activity based on quantitative CBF. Our data show increased CBF in the fronto-parietal cortices, thalamus, caudate, and cerebellar regions, and decreased CBF in the posterior cingulate cortex and medial prefrontal cortex, during the working memory tasks. Most of the activated/deactivated brain regions show an approximately linear relationship between CBF and task loads (0, 1, 2 and 3 back), although several regions show non-linear relationships (quadratic and cubic). The CBF-based spatial patterns of brain activation/deactivation and load effects from this study agree well with those obtained from BOLD fMRI and PET techniques. These results demonstrate the feasibility of ASL techniques to quantify human brain activity during high cognitive tasks, suggesting its potential application to assessing the mechanisms of cognitive deficits in neuropsychiatric and neurological disorders.

BRAPH: A graph theory software for the analysis of brain connectivity

PubMed Central

Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B.; Westman, Eric; Volpe, Giovanni

2017-01-01

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. PMID:28763447

BRAPH: A graph theory software for the analysis of brain connectivity.

PubMed

Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B; Westman, Eric; Volpe, Giovanni

2017-01-01

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.

Towards mapping the brain connectome in depression: functional connectivity by perfusion SPECT.

PubMed

Gardner, Ann; Åstrand, Disa; Öberg, Johanna; Jacobsson, Hans; Jonsson, Cathrine; Larsson, Stig; Pagani, Marco

2014-08-30

Several studies have demonstrated altered brain functional connectivity in the resting state in depression. However, no study has investigated interregional networking in patients with persistent depressive disorder (PDD). The aim of this study was to assess differences in brain perfusion distribution and connectivity between large groups of patients and healthy controls. Participants comprised 91 patients with PDD and 65 age- and sex-matched healthy controls. Resting state perfusion was investigated by single photon emission computed tomography, and group differences were assessed by Statistical Parametric Mapping. Brain connectivity was explored through a voxel-wise interregional correlation analysis using as covariate of interest the normalized values of clusters of voxels in which perfusion differences were found in group analysis. Significantly increased regional brain perfusion distribution covering a large part of the cerebellum was observed in patients as compared with controls. Patients showed a significant negative functional connectivity between the cerebellar cluster and caudate, bilaterally. This study demonstrated inverse relative perfusion between the cerebellum and the caudate in PDD. Functional uncoupling may be associated with a dysregulation between the role of the cerebellum in action control and of the caudate in action selection, initiation and decision making in the patients. The potential impact of the resting state condition and the possibility of mitochondrial impairment are discussed. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Imaging deductive reasoning and the new paradigm

PubMed Central

Oaksford, Mike

2015-01-01

There has been a great expansion of research into human reasoning at all of Marr’s explanatory levels. There is a tendency for this work to progress within a level largely ignoring the others which can lead to slippage between levels (Chater et al., 2003). It is argued that recent brain imaging research on deductive reasoning—implementational level—has largely ignored the new paradigm in reasoning—computational level (Over, 2009). Consequently, recent imaging results are reviewed with the focus on how they relate to the new paradigm. The imaging results are drawn primarily from a recent meta-analysis by Prado et al. (2011) but further imaging results are also reviewed where relevant. Three main observations are made. First, the main function of the core brain region identified is most likely elaborative, defeasible reasoning not deductive reasoning. Second, the subtraction methodology and the meta-analytic approach may remove all traces of content specific System 1 processes thought to underpin much human reasoning. Third, interpreting the function of the brain regions activated by a task depends on theories of the function that a task engages. When there are multiple interpretations of that function, interpreting what an active brain region is doing is not clear cut. It is concluded that there is a need to more tightly connect brain activation to function, which could be achieved using formalized computational level models and a parametric variation approach. PMID:25774130

Angular default mode network connectivity across working memory load.

PubMed

Vatansever, D; Manktelow, A E; Sahakian, B J; Menon, D K; Stamatakis, E A

2017-01-01

Initially identified during no-task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large-scale brain networks. Nevertheless, its contribution to whole-brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI-based n-back paradigm with parametric increases in difficulty. Using a voxel-wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n-back task load. Subsequent seed-based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large-scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n-back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41-52, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Abnormal resting-state connectivity of motor and cognitive networks in early manifest Huntington's disease.

PubMed

Wolf, R C; Sambataro, F; Vasic, N; Depping, M S; Thomann, P A; Landwehrmeyer, G B; Süssmuth, S D; Orth, M

2014-11-01

Functional magnetic resonance imaging (fMRI) of multiple neural networks during the brain's 'resting state' could facilitate biomarker development in patients with Huntington's disease (HD) and may provide new insights into the relationship between neural dysfunction and clinical symptoms. To date, however, very few studies have examined the functional integrity of multiple resting state networks (RSNs) in manifest HD, and even less is known about whether concomitant brain atrophy affects neural activity in patients. Using MRI, we investigated brain structure and RSN function in patients with early HD (n = 20) and healthy controls (n = 20). For resting-state fMRI data a group-independent component analysis identified spatiotemporally distinct patterns of motor and prefrontal RSNs of interest. We used voxel-based morphometry to assess regional brain atrophy, and 'biological parametric mapping' analyses to investigate the impact of atrophy on neural activity. Compared with controls, patients showed connectivity changes within distinct neural systems including lateral prefrontal, supplementary motor, thalamic, cingulate, temporal and parietal regions. In patients, supplementary motor area and cingulate cortex connectivity indices were associated with measures of motor function, whereas lateral prefrontal connectivity was associated with cognition. This study provides evidence for aberrant connectivity of RSNs associated with motor function and cognition in early manifest HD when controlling for brain atrophy. This suggests clinically relevant changes of RSN activity in the presence of HD-associated cortical and subcortical structural abnormalities.

Simultaneously multiparametric spectroscopic monitoring of tissue viability in the brain and small intestine

NASA Astrophysics Data System (ADS)

Tolmasov, Michael; Barbiro-Michaely, Efrat; Mayevsky, Avraham

2007-02-01

Under body O II imbalance, the Autonomic Nervous System is responsible for redistribution of blood flow with preference to the most vital organs (brain, heart), while the less vital organs (intestine, GI tract) are hypoperfused. The aim of this study was to develop and use an animal model for real time monitoring of tissue viability in the brain, and the small intestine, under various levels of oxygen and blood supply. Male Wistar rats were anesthetized, the brain cortex and intestinal serosa were exposed and connected by optical fibers to the Multi-Site Multi-Parametric (MSMP) monitoring system. Tissue blood flow (TBF) and mitochondrial NADH redox state were monitored simultaneously in the two organs. The rats were subjected to short anoxia, 20 minutes hypoxia or epinephrine (2& 8μg/kg I.V.). Under oxygen deficiency, cerebral blood flow (CBF) was elevated, whereas intestinal TBF was reduced. Mitochondrial NADH was significantly elevated in both organs. Systemic injection of Adrenaline showed a dose-depended increase in systemic blood pressure and CBF response whereas, intestinal TBF similarly decreased in both doses. In addition, NADH was elevated (reduced form) in the intestine whereas oxidation was observed in the brain. In conclusion, our preliminary results may imply the ability of using of the MSMP for monitoring non-vital organs in order to detect early changes in the balance between oxygen supply and demand in the body.

An intermittent control model of flexible human gait using a stable manifold of saddle-type unstable limit cycle dynamics

PubMed Central

Fu, Chunjiang; Suzuki, Yasuyuki; Kiyono, Ken; Morasso, Pietro; Nomura, Taishin

2014-01-01

Stability of human gait is the ability to maintain upright posture during walking against external perturbations. It is a complex process determined by a number of cross-related factors, including gait trajectory, joint impedance and neural control strategies. Here, we consider a control strategy that can achieve stable steady-state periodic gait while maintaining joint flexibility with the lowest possible joint impedance. To this end, we carried out a simulation study of a heel-toe footed biped model with hip, knee and ankle joints and a heavy head-arms-trunk element, working in the sagittal plane. For simplicity, the model assumes a periodic desired joint angle trajectory and joint torques generated by a set of feed-forward and proportional-derivative feedback controllers, whereby the joint impedance is parametrized by the feedback gains. We could show that a desired steady-state gait accompanied by the desired joint angle trajectory can be established as a stable limit cycle (LC) for the feedback controller with an appropriate set of large feedback gains. Moreover, as the feedback gains are decreased for lowering the joint stiffness, stability of the LC is lost only in a few dimensions, while leaving the remaining large number of dimensions quite stable: this means that the LC becomes saddle-type, with a low-dimensional unstable manifold and a high-dimensional stable manifold. Remarkably, the unstable manifold remains of low dimensionality even when the feedback gains are decreased far below the instability point. We then developed an intermittent neural feedback controller that is activated only for short periods of time at an optimal phase of each gait stride. We characterized the robustness of this design by showing that it can better stabilize the unstable LC with small feedback gains, leading to a flexible gait, and in particular we demonstrated that such an intermittent controller performs better if it drives the state point to the stable manifold, rather than directly to the LC. The proposed intermittent control strategy might have a high affinity for the inverted pendulum analogy of biped gait, providing a dynamic view of how the step-to-step transition from one pendular stance to the next can be achieved stably in a robust manner by a well-timed neural intervention that exploits the stable modes embedded in the unstable dynamics. PMID:25339687

An intermittent control model of flexible human gait using a stable manifold of saddle-type unstable limit cycle dynamics.

PubMed

Fu, Chunjiang; Suzuki, Yasuyuki; Kiyono, Ken; Morasso, Pietro; Nomura, Taishin

2014-12-06

Stability of human gait is the ability to maintain upright posture during walking against external perturbations. It is a complex process determined by a number of cross-related factors, including gait trajectory, joint impedance and neural control strategies. Here, we consider a control strategy that can achieve stable steady-state periodic gait while maintaining joint flexibility with the lowest possible joint impedance. To this end, we carried out a simulation study of a heel-toe footed biped model with hip, knee and ankle joints and a heavy head-arms-trunk element, working in the sagittal plane. For simplicity, the model assumes a periodic desired joint angle trajectory and joint torques generated by a set of feed-forward and proportional-derivative feedback controllers, whereby the joint impedance is parametrized by the feedback gains. We could show that a desired steady-state gait accompanied by the desired joint angle trajectory can be established as a stable limit cycle (LC) for the feedback controller with an appropriate set of large feedback gains. Moreover, as the feedback gains are decreased for lowering the joint stiffness, stability of the LC is lost only in a few dimensions, while leaving the remaining large number of dimensions quite stable: this means that the LC becomes saddle-type, with a low-dimensional unstable manifold and a high-dimensional stable manifold. Remarkably, the unstable manifold remains of low dimensionality even when the feedback gains are decreased far below the instability point. We then developed an intermittent neural feedback controller that is activated only for short periods of time at an optimal phase of each gait stride. We characterized the robustness of this design by showing that it can better stabilize the unstable LC with small feedback gains, leading to a flexible gait, and in particular we demonstrated that such an intermittent controller performs better if it drives the state point to the stable manifold, rather than directly to the LC. The proposed intermittent control strategy might have a high affinity for the inverted pendulum analogy of biped gait, providing a dynamic view of how the step-to-step transition from one pendular stance to the next can be achieved stably in a robust manner by a well-timed neural intervention that exploits the stable modes embedded in the unstable dynamics.

Neuroelectrical Decomposition of Spontaneous Brain Activity Measured with Functional Magnetic Resonance Imaging

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; Chang, Catie; Duan, Qi; van Gelderen, Peter; Duyn, Jeff H.

2014-01-01

Spontaneous activity in the human brain occurs in complex spatiotemporal patterns that may reflect functionally specialized neural networks. Here, we propose a subspace analysis method to elucidate large-scale networks by the joint analysis of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data. The new approach is based on the notion that the neuroelectrical activity underlying the fMRI signal may have EEG spectral features that report on regional neuronal dynamics and interregional interactions. Applying this approach to resting healthy adults, we indeed found characteristic spectral signatures in the EEG correlates of spontaneous fMRI signals at individual brain regions as well as the temporal synchronization among widely distributed regions. These spectral signatures not only allowed us to parcel the brain into clusters that resembled the brain's established functional subdivision, but also offered important clues for disentangling the involvement of individual regions in fMRI network activity. PMID:23796947

Information flow between interacting human brains: Identification, validation, and relationship to social expertise.

PubMed

Bilek, Edda; Ruf, Matthias; Schäfer, Axel; Akdeniz, Ceren; Calhoun, Vince D; Schmahl, Christian; Demanuele, Charmaine; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2015-04-21

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender's and receiver's temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.

Development of quantitative analysis method for stereotactic brain image: assessment of reduced accumulation in extent and severity using anatomical segmentation.

PubMed

Mizumura, Sunao; Kumita, Shin-ichiro; Cho, Keiichi; Ishihara, Makiko; Nakajo, Hidenobu; Toba, Masahiro; Kumazaki, Tatsuo

2003-06-01

Through visual assessment by three-dimensional (3D) brain image analysis methods using stereotactic brain coordinates system, such as three-dimensional stereotactic surface projections and statistical parametric mapping, it is difficult to quantitatively assess anatomical information and the range of extent of an abnormal region. In this study, we devised a method to quantitatively assess local abnormal findings by segmenting a brain map according to anatomical structure. Through quantitative local abnormality assessment using this method, we studied the characteristics of distribution of reduced blood flow in cases with dementia of the Alzheimer type (DAT). Using twenty-five cases with DAT (mean age, 68.9 years old), all of whom were diagnosed as probable Alzheimer's disease based on NINCDS-ADRDA, we collected I-123 iodoamphetamine SPECT data. A 3D brain map using the 3D-SSP program was compared with the data of 20 cases in the control group, who age-matched the subject cases. To study local abnormalities on the 3D images, we divided the whole brain into 24 segments based on anatomical classification. We assessed the extent of an abnormal region in each segment (rate of the coordinates with a Z-value that exceeds the threshold value, in all coordinates within a segment), and severity (average Z-value of the coordinates with a Z-value that exceeds the threshold value). This method clarified orientation and expansion of reduced accumulation, through classifying stereotactic brain coordinates according to the anatomical structure. This method was considered useful for quantitatively grasping distribution abnormalities in the brain and changes in abnormality distribution.

Brain Activation during Addition and Subtraction Tasks In-Noise and In-Quiet

PubMed Central

Abd Hamid, Aini Ismafairus; Yusoff, Ahmad Nazlim; Mukari, Siti Zamratol-Mai Sarah; Mohamad, Mazlyfarina

2011-01-01

Background: In spite of extensive research conducted to study how human brain works, little is known about a special function of the brain that stores and manipulates information—the working memory—and how noise influences this special ability. In this study, Functional magnetic resonance imaging (fMRI) was used to investigate brain responses to arithmetic problems solved in noisy and quiet backgrounds. Methods: Eighteen healthy young males performed simple arithmetic operations of addition and subtraction with in-quiet and in-noise backgrounds. The MATLAB-based Statistical Parametric Mapping (SPM8) was implemented on the fMRI datasets to generate and analyse the activated brain regions. Results: Group results showed that addition and subtraction operations evoked extended activation in the left inferior parietal lobe, left precentral gyrus, left superior parietal lobe, left supramarginal gyrus, and left middle temporal gyrus. This supported the hypothesis that the human brain relatively activates its left hemisphere more compared with the right hemisphere when solving arithmetic problems. The insula, middle cingulate cortex, and middle frontal gyrus, however, showed more extended right hemispheric activation, potentially due to the involvement of attention, executive processes, and working memory. For addition operations, there was extensive left hemispheric activation in the superior temporal gyrus, inferior frontal gyrus, and thalamus. In contrast, subtraction tasks evoked a greater activation of similar brain structures in the right hemisphere. For both addition and subtraction operations, the total number of activated voxels was higher for in-noise than in-quiet conditions. Conclusion: These findings suggest that when arithmetic operations were delivered auditorily, the auditory, attention, and working memory functions were required to accomplish the executive processing of the mathematical calculation. The respective brain activation patterns appear to be modulated by the noisy background condition. PMID:22135581

A stereotaxic, population-averaged T1w ovine brain atlas including cerebral morphology and tissue volumes

PubMed Central

Nitzsche, Björn; Frey, Stephen; Collins, Louis D.; Seeger, Johannes; Lobsien, Donald; Dreyer, Antje; Kirsten, Holger; Stoffel, Michael H.; Fonov, Vladimir S.; Boltze, Johannes

2015-01-01

Standard stereotaxic reference systems play a key role in human brain studies. Stereotaxic coordinate systems have also been developed for experimental animals including non-human primates, dogs, and rodents. However, they are lacking for other species being relevant in experimental neuroscience including sheep. Here, we present a spatial, unbiased ovine brain template with tissue probability maps (TPM) that offer a detailed stereotaxic reference frame for anatomical features and localization of brain areas, thereby enabling inter-individual and cross-study comparability. Three-dimensional data sets from healthy adult Merino sheep (Ovis orientalis aries, 12 ewes and 26 neutered rams) were acquired on a 1.5 T Philips MRI using a T1w sequence. Data were averaged by linear and non-linear registration algorithms. Moreover, animals were subjected to detailed brain volume analysis including examinations with respect to body weight (BW), age, and sex. The created T1w brain template provides an appropriate population-averaged ovine brain anatomy in a spatial standard coordinate system. Additionally, TPM for gray (GM) and white (WM) matter as well as cerebrospinal fluid (CSF) classification enabled automatic prior-based tissue segmentation using statistical parametric mapping (SPM). Overall, a positive correlation of GM volume and BW explained about 15% of the variance of GM while a positive correlation between WM and age was found. Absolute tissue volume differences were not detected, indeed ewes showed significantly more GM per bodyweight as compared to neutered rams. The created framework including spatial brain template and TPM represent a useful tool for unbiased automatic image preprocessing and morphological characterization in sheep. Therefore, the reported results may serve as a starting point for further experimental and/or translational research aiming at in vivo analysis in this species. PMID:26089780

Functional MRI and intraoperative brain mapping to evaluate brain plasticity in patients with brain tumours and hemiparesis

PubMed Central

Roux, F; Boulanouar, K; Ibarrola, D; Tremoulet, M; Chollet, F; Berry, I

2000-01-01

OBJECTIVE—To support the hypothesis about the potential compensatory role of ipsilateral corticofugal pathways when the contralateral pathways are impaired by brain tumours.
METHODS—Retrospective analysis was carried out on the results of functional MRI (fMRI) of a selected group of five paretic patients with Rolandic brain tumours who exhibited an abnormally high ipsilateral/contralateral ratio of activation—that is, movements of the paretic hand activated predominately the ipsilateral cortex. Brain activation was achieved with a flexion extension of the fingers. Statistical parametric activation was obtained using a t test and a threshold of p<0.001. These patients, candidates for tumour resection, also underwent cortical intraoperative stimulation that was correlated to the fMRI spatial data using three dimensional reconstructions of the brain. Three patients also had postoperative control fMRI.
RESULTS—The absence of fMRI activation of the primary sensorimotor cortex normally innervating the paretic hand for the threshold chosen, was correlated with completely negative cortical responses of the cortical hand area during the operation. The preoperative fMRI activation of these patients predominantly found in the ipsilateral frontal and primary sensorimotor cortices could be related to the residual ipsilateral hand function. Postoperatively, the fMRI activation returned to more classic patterns of activation, reflecting the consequences of therapy.
CONCLUSION—In paretic patients with brain tumours, ipsilateral control could be implicated in the residual hand function, when the normal primary pathways are impaired. The possibility that functional tissue still remains in the peritumorous sensorimotor cortex even when the preoperative fMRI and the cortical intraoperative stimulations are negative, should be taken into account when planning the tumour resection and during the operation.

 PMID:10990503

Volumetric electromagnetic phase-shift spectroscopy of brain edema and hematoma.

PubMed

Gonzalez, Cesar A; Valencia, Jose A; Mora, Alfredo; Gonzalez, Fernando; Velasco, Beatriz; Porras, Martin A; Salgado, Javier; Polo, Salvador M; Hevia-Montiel, Nidiyare; Cordero, Sergio; Rubinsky, Boris

2013-01-01

Motivated by the need of poor and rural Mexico, where the population has limited access to advanced medical technology and services, we have developed a new paradigm for medical diagnostic based on the technology of "Volumetric Electromagnetic Phase Shift Spectroscopy" (VEPS), as an inexpensive partial substitute to medical imaging. VEPS, can detect changes in tissue properties inside the body through non-contact, multi-frequency electromagnetic measurements from the exterior of the body, and thereby provide rapid and inexpensive diagnostics in a way that is amenable for use in economically disadvantaged parts of the world. We describe the technology and report results from a limited pilot study with 46 healthy volunteers and eight patients with CT radiology confirmed brain edema and brain hematoma. Data analysis with a non-parametric statistical Mann-Whitney U test, shows that in the frequency range of from 26 MHz to 39 MHz, VEPS can distinguish non-invasively and without contact, with a statistical significance of p<0.05, between healthy subjects and those with a medical conditions in the brain. In the frequency range of between 153 MHz to 166 MHz it can distinguish with a statistical significance of p<0.05 between subjects with brain edema and those with a hematoma in the brain. A classifier build from measurements in these two frequency ranges can provide instantaneous diagnostic of the medical condition of the brain of a patient, from a single set of measurements. While this is a small-scale pilot study, it illustrates the potential of VEPS to change the paradigm of medical diagnostic of brain injury through a VEPS classifier-based technology. Obviously substantially larger-scale studies are needed to verify and expand on the findings in this small pilot study.

Volumetric Electromagnetic Phase-Shift Spectroscopy of Brain Edema and Hematoma

PubMed Central

Gonzalez, Cesar A.; Valencia, Jose A.; Mora, Alfredo; Gonzalez, Fernando; Velasco, Beatriz; Porras, Martin A.; Salgado, Javier; Polo, Salvador M.; Hevia-Montiel, Nidiyare; Cordero, Sergio; Rubinsky, Boris

2013-01-01

Motivated by the need of poor and rural Mexico, where the population has limited access to advanced medical technology and services, we have developed a new paradigm for medical diagnostic based on the technology of “Volumetric Electromagnetic Phase Shift Spectroscopy” (VEPS), as an inexpensive partial substitute to medical imaging. VEPS, can detect changes in tissue properties inside the body through non-contact, multi-frequency electromagnetic measurements from the exterior of the body, and thereby provide rapid and inexpensive diagnostics in a way that is amenable for use in economically disadvantaged parts of the world. We describe the technology and report results from a limited pilot study with 46 healthy volunteers and eight patients with CT radiology confirmed brain edema and brain hematoma. Data analysis with a non-parametric statistical Mann-Whitney U test, shows that in the frequency range of from 26 MHz to 39 MHz, VEPS can distinguish non-invasively and without contact, with a statistical significance of p<0.05, between healthy subjects and those with a medical conditions in the brain. In the frequency range of between 153 MHz to 166 MHz it can distinguish with a statistical significance of p<0.05 between subjects with brain edema and those with a hematoma in the brain. A classifier build from measurements in these two frequency ranges can provide instantaneous diagnostic of the medical condition of the brain of a patient, from a single set of measurements. While this is a small-scale pilot study, it illustrates the potential of VEPS to change the paradigm of medical diagnostic of brain injury through a VEPS classifier-based technology. Obviously substantially larger-scale studies are needed to verify and expand on the findings in this small pilot study. PMID:23691001

Relationship between white matter lesions and regional cerebral blood flow changes during longitudinal follow up in Alzheimer's disease.

PubMed

Hanaoka, Takuya; Kimura, Noriyuki; Aso, Yasuhiro; Takemaru, Makoto; Kimura, Yuki; Ishibashi, Masato; Matsubara, Etsuro

2016-07-01

The aim of the present study was to evaluate the relationship between baseline white matter lesions (WML) and changes in regional cerebral blood flow during longitudinal follow up of patients with Alzheimer's disease (AD). A total of 38 patients with AD were included in the study (16 men, 22 women; mean age 77.8 years). All patients were evaluated using the Mini-Mental State Examination and brain perfusion single-photon emission computed tomography at baseline with an approximately 2-year follow up. The patients were divided into two subgroups according to the presence of WML on magnetic resonance imaging. Single-photon emission computed tomography data were analyzed using a voxel-by-voxel group analysis with Statistical Parametric Mapping 8 and region of interest analysis using FineSRT. Changes in Mini-Mental State Examination scores and regional cerebral blood flow were analyzed using the Wilcoxon signed-rank test. Mean Mini-Mental State Examination scores in AD patients with WML significantly decreased from 19.4 ± 4.8 to 15.5 ± 6.5 (P = 0.003). Statistical Parametric Mapping 8 and FineSRT analysis showed more severe and widespread regional cerebral blood flow reduction, mainly in the frontal and mesial temporal regions in AD patients with WML compared with those without WML. Baseline WML could predict a rapid progression of cognitive and brain functional impairment during longitudinal follow up in AD. Geriatr Gerontol Int 2016; 16: 836-842. © 2015 Japan Geriatrics Society.

Knowledge acquisition is governed by striatal prediction errors.

PubMed

Pine, Alex; Sadeh, Noa; Ben-Yakov, Aya; Dudai, Yadin; Mendelsohn, Avi

2018-04-26

Discrepancies between expectations and outcomes, or prediction errors, are central to trial-and-error learning based on reward and punishment, and their neurobiological basis is well characterized. It is not known, however, whether the same principles apply to declarative memory systems, such as those supporting semantic learning. Here, we demonstrate with fMRI that the brain parametrically encodes the degree to which new factual information violates expectations based on prior knowledge and beliefs-most prominently in the ventral striatum, and cortical regions supporting declarative memory encoding. These semantic prediction errors determine the extent to which information is incorporated into long-term memory, such that learning is superior when incoming information counters strong incorrect recollections, thereby eliciting large prediction errors. Paradoxically, by the same account, strong accurate recollections are more amenable to being supplanted by misinformation, engendering false memories. These findings highlight a commonality in brain mechanisms and computational rules that govern declarative and nondeclarative learning, traditionally deemed dissociable.

Hybrid BCI approach to control an artificial tibio-femoral joint.

PubMed

Mercado, Luis; Rodriguez-Linan, Angel; Torres-Trevino, Luis M; Quiroz, G

2016-08-01

Brain-Computer Interfaces (BCIs) for disabled people should allow them to use their remaining functionalities as control possibilities. BCIs connect the brain with external devices to perform the volition or intent of movement, regardless if that individual is unable to perform the task due to body impairments. In this work we fuse electromyographic (EMG) with electroencephalographic (EEG) activity in a framework called "Hybrid-BCI" (hBCI) approach to control the movement of a simulated tibio-femoral joint. Two mathematical models of a tibio-femoral joint are used to emulate the kinematic and dynamic behavior of the knee. The interest is to reproduce different velocities of the human gait cycle. The EEG signals are used to classify the user intent, which are the velocity changes, meanwhile the superficial EMG signals are used to estimate the amplitude of such intent. A multi-level controller is used to solve the trajectory tracking problem involved. The lower level consists of an individual controller for each model, it solves the tracking of the desired trajectory even considering different velocities of the human gait cycle. The mid-level uses a combination of a logical operator and a finite state machine for the switching between models. Finally, the highest level consists in a support vector machine to classify the desired activity.

Unusual infections due to Listeria monocytogenes in the Southern California Desert.

PubMed

Cone, Lawrence A; Somero, Michael S; Qureshi, Farsana J; Kerkar, Shuba; Byrd, Richard G; Hirschberg, Joel M; Gauto, Anibal R

2008-11-01

During the past 22 years, 14 patients have been hospitalized with infection due to Listeria monocytogenes at the Eisenhower Medical Center, a regional 300-bed hospital in the desert southwest of Southern California. A large number of patients are retired, elderly, and have underlying and often systemic disease. Blood agar and routine media were inoculated with liquid from a sterile site such as blood, cerebrospinal fluid, or joint fluid and observed daily for growth. Appropriate biochemical studies were used to speciate the organism. While bacteremia and meningitis constitute 75% of infections in most studies, they made up only 36% of patients in the current study. Listeriosis occurred mostly in patients with infected aortic aneurysms and brain abscesses, and in prosthetic joint infections. While mortality is generally stated to be around 45% in patients with listeriosis, it was 35% in this study. However, there were no deaths in five patients with bacteremia or meningitis inferring that organ involvement poses a greater hazard for survival. Listeriosis usually presents as a bacteremia or meningitis due to a food-borne invasive infection. In the desert of Southern California most cases are seen in older patients with underlying disease and present with infected aortic aneurysms, prosthetic joints, and brain abscesses. They represent a greater threat to survival due to organ involvement.

Accessing northern California earthquake data via Internet

NASA Astrophysics Data System (ADS)

Romanowicz, Barbara; Neuhauser, Douglas; Bogaert, Barbara; Oppenheimer, David

The Northern California Earthquake Data Center (NCEDC) provides easy access to central and northern California digital earthquake data. It is located at the University of California, Berkeley, and is operated jointly with the U.S. Geological Survey (USGS) in Menlo Park, Calif., and funded by the University of California and the National Earthquake Hazard Reduction Program. It has been accessible to users in the scientific community through Internet since mid-1992.The data center provides an on-line archive for parametric and waveform data from two regional networks: the Northern California Seismic Network (NCSN) operated by the USGS and the Berkeley Digital Seismic Network (BDSN) operated by the Seismographic Station at the University of California, Berkeley.

CASPASE-12 and rheumatoid arthritis in African-Americans

PubMed Central

Marshall, Laura; Obaidullah, Mohammad; Fuchs, Trista; Fineberg, Naomi S.; Brinkley, Garland; Mikuls, Ted R.; Bridges, S. Louis; Hermel, Evan

2014-01-01

CASPASE-12 (CASP12) has a down-regulatory function during infection, and thus may protect against inflammatory disease. We investigated the distribution of CASP12 alleles (#rs497116) in African-Americans (AA) with rheumatoid arthritis (RA). CASP12 alleles were genotyped in 953 RA patients and 342 controls. Statistical analyses comparing genotype groups were performed using Kruskal-Wallis non-parametric ANOVA with Mann-Whitney U tests and chi-square tests. There was no significant difference in the overall distribution of CASP12 genotypes within AA with RA, but CASP12 homozygous patients had lower baseline joint narrowing scores. CASP12 homozygosity appears to be a subtle protective factor for some aspects of RA in AA patients. PMID:24515649

Widely tunable single photon source with high purity at telecom wavelength.

PubMed

Jin, Rui-Bo; Shimizu, Ryosuke; Wakui, Kentaro; Benichi, Hugo; Sasaki, Masahide

2013-05-06

We theoretically and experimentally investigate the spectral tunability and purity of photon pairs generated from spontaneous parametric down conversion in periodically poled KTiOPO(4) crystal with group-velocity matching condition. The numerical simulation predicts that the spectral purity can be kept higher than 0.81 when the wavelength is tuned from 1460 nm to 1675 nm, which covers the S-, C-, L-, and U-band in telecommunication wavelengths. We also experimentally measured the joint spectral intensity at 1565 nm, 1584 nm and 1565 nm, yielding Schmidt numbers of 1.01, 1.02 and 1.04, respectively. Such a photon source is useful for quantum information and communication systems.

Long-term neural and physiological phenotyping of a single human

PubMed Central

Poldrack, Russell A.; Laumann, Timothy O.; Koyejo, Oluwasanmi; Gregory, Brenda; Hover, Ashleigh; Chen, Mei-Yen; Gorgolewski, Krzysztof J.; Luci, Jeffrey; Joo, Sung Jun; Boyd, Ryan L.; Hunicke-Smith, Scott; Simpson, Zack Booth; Caven, Thomas; Sochat, Vanessa; Shine, James M.; Gordon, Evan; Snyder, Abraham Z.; Adeyemo, Babatunde; Petersen, Steven E.; Glahn, David C.; Reese Mckay, D.; Curran, Joanne E.; Göring, Harald H. H.; Carless, Melanie A.; Blangero, John; Dougherty, Robert; Leemans, Alexander; Handwerker, Daniel A.; Frick, Laurie; Marcotte, Edward M.; Mumford, Jeanette A.

2015-01-01

Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders. PMID:26648521

Preliminary design, analysis, and costing of a dynamic scale model of the NASA space station

NASA Technical Reports Server (NTRS)

Gronet, M. J.; Pinson, E. D.; Voqui, H. L.; Crawley, E. F.; Everman, M. R.

1987-01-01

The difficulty of testing the next generation of large flexible space structures on the ground places an emphasis on other means for validating predicted on-orbit dynamic behavior. Scale model technology represents one way of verifying analytical predictions with ground test data. This study investigates the preliminary design, scaling and cost trades for a Space Station dynamic scale model. The scaling of nonlinear joint behavior is studied from theoretical and practical points of view. Suspension system interaction trades are conducted for the ISS Dual Keel Configuration and Build-Up Stages suspended in the proposed NASA/LaRC Large Spacecraft Laboratory. Key issues addressed are scaling laws, replication vs. simulation of components, manufacturing, suspension interactions, joint behavior, damping, articulation capability, and cost. These issues are the subject of parametric trades versus the scale model factor. The results of these detailed analyses are used to recommend scale factors for four different scale model options, each with varying degrees of replication. Potential problems in constructing and testing the scale model are identified, and recommendations for further study are outlined.

Evaluation of dispersion strengthened nickel-base alloy heat shields for space shuttle application

NASA Technical Reports Server (NTRS)

Johnson, R., Jr.; Killpatrick, D. H.

1973-01-01

The work reported constitutes the first phase of a two-phase program. Vehicle environments having critical effects on the thermal protection system are defined; TD Ni-20Cr material characteristics are reviewed and compared with TD Ni-20Cr produced in previous development efforts; cyclic load, temperature, and pressure effects on TD Ni-20Cr sheet material are investigated; the effects of braze reinforcement in improving the efficiency of spotwelded, diffusion-bonded, or seam-welded joints are evaluated through tests of simple lap-shear joint samples; parametric studies of metallic radiative thermal protection systems are reported; and the design, instrumentation, and testing of full-scale subsize heat shield panels are described. Tests of full-scale subsize panels included simulated meteoroid impact tests; simulated entry flight aerodynamic heating in an arc-heated plasma stream; programmed differential pressure loads and temperatures simulating mission conditions; and acoustic tests simulating sound levels experienced by heat shields during about boost flight. Test results are described, and the performances of two heat shield designs are compared and evaluated.

Sensitivity of biomechanical outcomes to independent variations of hindfoot and forefoot stiffness in foot prostheses.

PubMed

Adamczyk, Peter Gabriel; Roland, Michelle; Hahn, Michael E

2017-08-01

Many studies have reported the effects of different foot prostheses on gait, but most results cannot be generalized because the prostheses' properties are seldom reported. We varied hindfoot and forefoot stiffness in an experimental foot prosthesis, in increments of 15N/mm, and tested the parametric effects of these variations on treadmill walking in unilateral transtibial amputees, at speeds from 0.7 to 1.5m/s. We computed outcomes such as prosthesis energy return, center of mass (COM) mechanics, ground reaction forces, and joint mechanics, and computed their sensitivity to component stiffness. A stiffer hindfoot led to reduced prosthesis energy return, increased ground reaction force (GRF) loading rate, and greater stance-phase knee flexion and knee extensor moment. A stiffer forefoot resulted in reduced prosthetic-side ankle push-off and COM push-off work, and increased knee extension and knee flexor moment in late stance. The sensitivity parameters obtained from these tests may be useful in clinical prescription and further research into compensatory mechanisms of joint function. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetics Home Reference: granulomatosis with polyangiitis

MedlinePlus

... other regions of the body, including the eyes, middle and inner ear structures, skin, joints, nerves, heart, and brain. Depending ... involved, additional symptoms can include skin rashes, inner ear pain, swollen and ... is most common in middle-aged adults, although it can occur at any ...

Dorsomedial SCN neuronal subpopulations subserve different functions in human dementia.

PubMed

Harper, David G; Stopa, Edward G; Kuo-Leblanc, Victoria; McKee, Ann C; Asayama, Kentaro; Volicer, Ladislav; Kowall, Neil; Satlin, Andrew

2008-06-01

The suprachiasmatic nuclei (SCN) are necessary and sufficient for the maintenance of circadian rhythms in primate and other mammalian species. The human dorsomedial SCN contains populations of non-species-specific vasopressin and species-specific neurotensin neurons. We made time-series recordings of core body temperature and locomotor activity in 19 elderly, male, end-stage dementia patients and 8 normal elderly controls. Following the death of the dementia patients, neuropathological diagnostic information and tissue samples from the hypothalamus were obtained. Hypothalamic tissue was also obtained from eight normal control cases that had not had activity or core temperature recordings previously. Core temperature was analysed for parametric, circadian features, and activity was analysed for non-parametric and parametric circadian features. These indices were then correlated with the degree of degeneration seen in the SCN (glia/neuron ratio) and neuronal counts from the dorsomedial SCN (vasopressin, neurotensin). Specific loss of SCN neurotensin neurons was associated with loss of activity and temperature amplitude without increase in activity fragmentation. Loss of SCN vasopressin neurons was associated with increased activity fragmentation but not loss of amplitude. Evidence for a circadian rhythm of vasopressinergic activity was seen in the dementia cases but no evidence was seen for a circadian rhythm in neurotensinergic activity. These results provide evidence that the SCN is necessary for the maintenance of the circadian rhythm in humans, information on the role of neuronal subpopulations in subserving this function and the utility of dementia in elaborating brain-behaviour relationships in the human.

Dynamic-contrast-enhanced-MRI with extravasating contrast reagent: Rat cerebral glioma blood volume determination

NASA Astrophysics Data System (ADS)

Li, Xin; Rooney, William D.; Várallyay, Csanád G.; Gahramanov, Seymur; Muldoon, Leslie L.; Goodman, James A.; Tagge, Ian J.; Selzer, Audrey H.; Pike, Martin M.; Neuwelt, Edward A.; Springer, Charles S.

2010-10-01

The accurate mapping of the tumor blood volume (TBV) fraction ( vb) is a highly desired imaging biometric goal. It is commonly thought that achieving this is difficult, if not impossible, when small molecule contrast reagents (CRs) are used for the T1-weighted (Dynamic-Contrast-Enhanced) DCE-MRI technique. This is because angiogenic malignant tumor vessels allow facile CR extravasation. Here, a three-site equilibrium water exchange model is applied to DCE-MRI data from the cerebrally-implanted rat brain U87 glioma, a tumor exhibiting rapid CR extravasation. Analyses of segments of the (and the entire) DCE data time-course with this "shutter-speed" pharmacokinetic model, which admits finite water exchange kinetics, allow TBV estimation from the first-pass segment. Pairwise parameter determinances were tested with grid searches of 2D parametric error surfaces. Tumor blood volume ( vb), as well as ve (the extracellular, extravascular space volume fraction), and Ktrans (a CR extravasation rate measure) parametric maps are presented. The role of the Patlak Plot in DCE-MRI is also considered.

MR Analysis of Regional Brain Volume in Adolescent Idiopathic Scoliosis: Neurological Manifestation of a Systemic Disease

PubMed Central

Liu, Tianming; Chu, Winnie C.W.; Young, Geoffrey; Li, Kaiming; Yeung, Benson H.Y.; Guo, Lei; Man, Gene C.W.; Lam, Wynnie W.M.; Wong, Stephen T.C.; Cheng, Jack C.Y.

2008-01-01

Purpose To investigate whether regional brain volumes in adolescent idiopathic scoliosis (AIS) patients differ from matched control subjects as AIS subjects are reported to have poor performance on combined visual and proprioceptive testing and impaired postural balance in previous studies. Materials and Methods Twenty AIS female patients with typical right-convex thoracic curve (age range,11−18 years; mean, 14.1 years) and 26 female controls (mean age, 14.8 years) underwent three-dimensional magnetization prepared rapid acquisition gradient echo (3D-MPRAGE) MR imaging. Volumes of 99 preselected neuroanatomical regions were compared by statistical parametric mapping and atlas-based hybrid warping. Results Analysis of variance statistics revealed significant mean volumetric differences in 22 brain regions between AIS and controls. Ten regions were larger in AIS including the left frontal gyri and white matter in left frontal, parietal, and temporal regions, corpus callosum and brainstem. Twelve regions were smaller in AIS, including right-sided descending white matter tracts (anterior and posterior limbs of the right internal capsule and the cerebral peduncle) and deep nucleus (caudate), bilateral perirhinal cortices, left hippocampus and amygdala, bilateral precuneus gyri, and left middle and inferior occipital gyri. Conclusion Regional brain volume difference in AIS subjects may help to explain neurological abnormalities in this group. PMID:18302230

MR Vascular Fingerprinting in Stroke and Brain Tumors Models

NASA Astrophysics Data System (ADS)

Lemasson, B.; Pannetier, N.; Coquery, N.; Boisserand, Ligia S. B.; Collomb, Nora; Schuff, N.; Moseley, M.; Zaharchuk, G.; Barbier, E. L.; Christen, T.

2016-11-01

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases.

MR Vascular Fingerprinting in Stroke and Brain Tumors Models

PubMed Central

Lemasson, B.; Pannetier, N.; Coquery, N.; Boisserand, Ligia S. B.; Collomb, Nora; Schuff, N.; Moseley, M.; Zaharchuk, G.; Barbier, E. L.; Christen, T.

2016-01-01

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases. PMID:27883015

Comparative functional MRI study to assess brain activation upon active and passive finger movements in patients with cerebral infarction.

PubMed

Fu, Yue; Zhang, Quan; Zhang, Jing; Zhang, Yun Ting

2015-01-01

To compare the effects of active and passive movements on brain activation in patients with cerebral infarction using fMRI. Twenty-four hemiplegic patients with cerebral infarction were evaluated using fMRI. All patients performed active and passive finger opposition movements. Patients were instructed to perform the finger opposition movement for the active movement task. For the passive movement task, the subject's fingers were moved by the examiner to perform the finger opposition movement. Statistical parametric mapping software was used for statistical analyses and to process all data. In the affected hemisphere, sensorimotor cortex (SMC) activation intensity and range were significantly stronger during the passive movement of the affected fingers compared to the active movement of the affected fingers (p < 0.05). However, there were no significant differences between active and passive movements of unaffected fingers in SMC activation intensity and range in the unaffected hemisphere (p > 0.05). In addition, the passive movement activated many other regions of the brain. The brain regions activated by passive movements of the affected fingers tended to center toward the contralateral SMC. Our findings suggest that passive movements induce cortical reorganization in patients with cerebral infarction. Therefore, passive movement is likely beneficial for motor function recovery in patients with cerebral infarction.

The 2014 Nobel Prize in Physiology or Medicine: a spatial model for cognitive neuroscience.

PubMed

Burgess, Neil

2014-12-17

Understanding how the cognitive functions of the brain arise from its basic physiological components has been an enticing final frontier in science for thousands of years. The Nobel Prize in Physiology or Medicine 2014 was awarded one half to John O'Keefe, the other half jointly to May-Britt Moser and Edvard I. Moser "for their discoveries of cells that constitute a positioning system in the brain." This prize recognizes both a paradigm shift in the study of cognitive neuroscience, and some of the amazing insights that have followed from it concerning how the world is represented within the brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Mirror neuron system as the joint from action to language.

PubMed

Chen, Wei; Yuan, Ti-Fei

2008-08-01

Mirror neuron system (MNS) represents one of the most important discoveries of cognitive neuroscience in the past decade, and it has been found to involve in multiple aspects of brain functions including action understanding, imitation, language understanding, empathy, action prediction and speech evolution. This manuscript reviewed the function of MNS in action understanding as well as language evolution, and specifically assessed its roles as the bridge from body language to fluent speeches. Then we discussed the speech defects of autism patients due to the disruption of MNS. Finally, given that MNS is plastic in adult brain, we proposed MNS targeted therapy provides an efficient rehabilitation approach for brain damages conditions as well as autism patients.

The articulo-cardiac sympathetic reflex in spinalized, anesthetized rats.

PubMed

Nakayama, Tomohiro; Suzuki, Atsuko; Ito, Ryuzo

2006-04-01

Somatic afferent regulation of heart rate by noxious knee joint stimulation has been proven in anesthetized cats to be a reflex response whose reflex center is in the brain and whose efferent arc is a cardiac sympathetic nerve. In the present study we examined whether articular stimulation could influence heart rate by this efferent sympathetic pathway in spinalized rats. In central nervous system (CNS)-intact rats, noxious articular movement of either the knee or elbow joint resulted in an increase in cardiac sympathetic nerve activity and heart rate. However, although in acutely spinalized rats a noxious movement of the elbow joint resulted in a significant increase in cardiac sympathetic nerve activity and heart rate, a noxious movement of the knee joint had no such effect and resulted in only a marginal increase in heart rate. Because this marginal increase was abolished by adrenalectomy suggests that it was due to the release of adrenal catecholamines. In conclusion, the spinal cord appears to be capable of mediating, by way of cardiac sympathetic nerves, the propriospinally induced reflex increase in heart rate that follows noxious stimulation of the elbow joint, but not the knee joint.

Parametric Investigation on Microstructure and Mechanical Properties of Ultrasonic spot welded Aluminium to Copper sheets

NASA Astrophysics Data System (ADS)

Prasad Satpathy, Mantra; Das Mohapatra, Kasinath; Sahoo, Ananda Kumar; Sahoo, Susanta Kumar

2018-03-01

Ultrasonic welding is one of the promising solid state welding methods which have been widely used to join highly conductive materials like aluminum and copper. Despite these applications in the automotive field, other industries also have a strong interest to adopt this process for joining of various advanced alloys. In some of its applications, poor weld strength and sticking of the workpiece to the tool are issues. Thus, an attempt has been taken in the present study to overcome these issues by performing experiments with a suitable range of weld parameters. The major objectives of this study are to obtain a good joint strength with a reduced sticking phenomenon and microstructure of Al-Cu weld coupons. The results uncovered the mechanical strength of the joint increased up to 0.34 sec of weld time and afterward, it gradually decreased. Meantime, the plastic deformation in the weld zone enhanced the formation of an intermetallic layer of 1.5 μm thick, and it is composed of mainly Al2Cu compound. The temperature evolved during the welding process is also measured by thermocouples to show its relationship with the plastic deformation. The present work exemplifies a finer understanding of the failure behavior of joints and provides an insight of ultrasonic welding towards the improvement in the quality of weld.

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

Effects of cell phone radiofrequency signal exposure on brain glucose metabolism.

PubMed

Volkow, Nora D; Tomasi, Dardo; Wang, Gene-Jack; Vaska, Paul; Fowler, Joanna S; Telang, Frank; Alexoff, Dave; Logan, Jean; Wong, Christopher

2011-02-23

The dramatic increase in use of cellular telephones has generated concern about possible negative effects of radiofrequency signals delivered to the brain. However, whether acute cell phone exposure affects the human brain is unclear. To evaluate if acute cell phone exposure affects brain glucose metabolism, a marker of brain activity. Randomized crossover study conducted between January 1 and December 31, 2009, at a single US laboratory among 47 healthy participants recruited from the community. Cell phones were placed on the left and right ears and positron emission tomography with ((18)F)fluorodeoxyglucose injection was used to measure brain glucose metabolism twice, once with the right cell phone activated (sound muted) for 50 minutes ("on" condition) and once with both cell phones deactivated ("off" condition). Statistical parametric mapping was used to compare metabolism between on and off conditions using paired t tests, and Pearson linear correlations were used to verify the association of metabolism and estimated amplitude of radiofrequency-modulated electromagnetic waves emitted by the cell phone. Clusters with at least 1000 voxels (volume >8 cm(3)) and P < .05 (corrected for multiple comparisons) were considered significant. Brain glucose metabolism computed as absolute metabolism (μmol/100 g per minute) and as normalized metabolism (region/whole brain). Whole-brain metabolism did not differ between on and off conditions. In contrast, metabolism in the region closest to the antenna (orbitofrontal cortex and temporal pole) was significantly higher for on than off conditions (35.7 vs 33.3 μmol/100 g per minute; mean difference, 2.4 [95% confidence interval, 0.67-4.2]; P = .004). The increases were significantly correlated with the estimated electromagnetic field amplitudes both for absolute metabolism (R = 0.95, P < .001) and normalized metabolism (R = 0.89; P < .001). In healthy participants and compared with no exposure, 50-minute cell phone exposure was associated with increased brain glucose metabolism in the region closest to the antenna. This finding is of unknown clinical significance.

Joint Spatial-Spectral Feature Space Clustering for Speech Activity Detection from ECoG Signals

PubMed Central

Kanas, Vasileios G.; Mporas, Iosif; Benz, Heather L.; Sgarbas, Kyriakos N.; Bezerianos, Anastasios; Crone, Nathan E.

2014-01-01

Brain machine interfaces for speech restoration have been extensively studied for more than two decades. The success of such a system will depend in part on selecting the best brain recording sites and signal features corresponding to speech production. The purpose of this study was to detect speech activity automatically from electrocorticographic signals based on joint spatial-frequency clustering of the ECoG feature space. For this study, the ECoG signals were recorded while a subject performed two different syllable repetition tasks. We found that the optimal frequency resolution to detect speech activity from ECoG signals was 8 Hz, achieving 98.8% accuracy by employing support vector machines (SVM) as a classifier. We also defined the cortical areas that held the most information about the discrimination of speech and non-speech time intervals. Additionally, the results shed light on the distinct cortical areas associated with the two syllable repetition tasks and may contribute to the development of portable ECoG-based communication. PMID:24658248

Automated Voxel-Based Analysis of Volumetric Dynamic Contrast-Enhanced CT Data Improves Measurement of Serial Changes in Tumor Vascular Biomarkers

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

Coolens, Catherine, E-mail: catherine.coolens@rmp.uhn.on.ca; Department of Radiation Oncology, University of Toronto, Toronto, Ontario; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario

2015-01-01

Objectives: Development of perfusion imaging as a biomarker requires more robust methodologies for quantification of tumor physiology that allow assessment of volumetric tumor heterogeneity over time. This study proposes a parametric method for automatically analyzing perfused tissue from volumetric dynamic contrast-enhanced (DCE) computed tomography (CT) scans and assesses whether this 4-dimensional (4D) DCE approach is more robust and accurate than conventional, region-of-interest (ROI)-based CT methods in quantifying tumor perfusion with preliminary evaluation in metastatic brain cancer. Methods and Materials: Functional parameter reproducibility and analysis of sensitivity to imaging resolution and arterial input function were evaluated in image sets acquired from amore » 320-slice CT with a controlled flow phantom and patients with brain metastases, whose treatments were planned for stereotactic radiation surgery and who consented to a research ethics board-approved prospective imaging biomarker study. A voxel-based temporal dynamic analysis (TDA) methodology was used at baseline, at day 7, and at day 20 after treatment. The ability to detect changes in kinetic parameter maps in clinical data sets was investigated for both 4D TDA and conventional 2D ROI-based analysis methods. Results: A total of 7 brain metastases in 3 patients were evaluated over the 3 time points. The 4D TDA method showed improved spatial efficacy and accuracy of perfusion parameters compared to ROI-based DCE analysis (P<.005), with a reproducibility error of less than 2% when tested with DCE phantom data. Clinically, changes in transfer constant from the blood plasma into the extracellular extravascular space (K{sub trans}) were seen when using TDA, with substantially smaller errors than the 2D method on both day 7 post radiation surgery (±13%; P<.05) and by day 20 (±12%; P<.04). Standard methods showed a decrease in K{sub trans} but with large uncertainty (111.6 ± 150.5) %. Conclusions: Parametric voxel-based analysis of 4D DCE CT data resulted in greater accuracy and reliability in measuring changes in perfusion CT-based kinetic metrics, which have the potential to be used as biomarkers in patients with metastatic brain cancer.« less

Social cues at encoding affect memory in 4-month-old infants.

PubMed

Kopp, Franziska; Lindenberger, Ulman

2012-01-01

Available evidence suggests that infants use adults' social cues for learning by the second half of the first year of life. However, little is known about the short-term or long-term effects of joint attention interactions on learning and memory in younger infants. In the present study, 4-month-old infants were familiarized with visually presented objects in either of two conditions that differed in the degree of joint attention (high vs. low). Brain activity in response to familiar and novel objects was assessed immediately after the familiarization phase (immediate recognition), and following a 1-week delay (delayed recognition). The latency of the Nc component differentiated between recognition of old versus new objects. Pb amplitude and latency were affected by joint attention in delayed recognition. Moreover, the frequency of infant gaze to the experimenter during familiarization differed between the two experimental groups and modulated the Pb response. Results show that joint attention affects the mechanisms of long-term retention in 4-month-old infants. We conclude that joint attention helps children at this young age to recognize the relevance of learned items.

The effect of selective tibial neurotomy and rehabilitation in a quadriplegic patient with ankle spasticity following traumatic brain injury.

PubMed

Jang, Sung Ho; Park, Sung-Min; Kim, Seong Ho; Ahn, Sang Ho; Cho, Yun Woo; Ahn, Mi Ok

2004-08-31

Ankle spasticity following brain injury leads to abnormal posture and joint contracture; making standing or walking impossible. This study investigates the efficacy of selective tibial neurotomy (STN) and intensive rehabilitation in a patient who suffered ankle spasticity after brain injury. This case describes a 37-year-old man whose traumatic brain injury (TBI) resulted in severe right ankle spasticity and contracture. He was unable to stand due to severe right ankle spasticity and contracture. Intensive rehabilitation and STN allowed him to walk without brace at 6 months and run at 12 months after STN. STN is an effective procedure to resolve localized spasticity of the ankle and it may be considered as a management strategy after local injection to alleviate ankle spasticity and/or contracture prior to orthopaedic surgery.

Joint independent component analysis for simultaneous EEG-fMRI: principle and simulation.

PubMed

Moosmann, Matthias; Eichele, Tom; Nordby, Helge; Hugdahl, Kenneth; Calhoun, Vince D

2008-03-01

An optimized scheme for the fusion of electroencephalography and event related potentials with functional magnetic resonance imaging (BOLD-fMRI) data should simultaneously assess all available electrophysiologic and hemodynamic information in a common data space. In doing so, it should be possible to identify features of latent neural sources whose trial-to-trial dynamics are jointly reflected in both modalities. We present a joint independent component analysis (jICA) model for analysis of simultaneous single trial EEG-fMRI measurements from multiple subjects. We outline the general idea underlying the jICA approach and present results from simulated data under realistic noise conditions. Our results indicate that this approach is a feasible and physiologically plausible data-driven way to achieve spatiotemporal mapping of event related responses in the human brain.

Computing local edge probability in natural scenes from a population of oriented simple cells

PubMed Central

Ramachandra, Chaithanya A.; Mel, Bartlett W.

2013-01-01

A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell—an oriented linear filter followed by a divisive normalization—fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels. PMID:24381295

Cognitive control of drug craving inhibits brain reward regions in cocaine abusers

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

Volkow, N.D.; Fowler, J.; Wang, G.J.

Loss of control over drug taking is considered a hallmark of addiction and is critical in relapse. Dysfunction of frontal brain regions involved with inhibitory control may underlie this behavior. We evaluated whether addicted subjects when instructed to purposefully control their craving responses to drug-conditioned stimuli can inhibit limbic brain regions implicated in drug craving. We used PET and 2-deoxy-2[18F]fluoro-D-glucose to measure brain glucose metabolism (marker of brain function) in 24 cocaine abusers who watched a cocaine-cue video and compared brain activation with and without instructions to cognitively inhibit craving. A third scan was obtained at baseline (without video). Statisticalmore » parametric mapping was used for analysis and corroborated with regions of interest. The cocaine-cue video increased craving during the no-inhibition condition (pre 3 {+-} 3, post 6 {+-} 3; p < 0.001) but not when subjects were instructed to inhibit craving (pre 3 {+-} 2, post 3 {+-} 3). Comparisons with baseline showed visual activation for both cocaine-cue conditions and limbic inhibition (accumbens, orbitofrontal, insula, cingulate) when subjects purposefully inhibited craving (p < 0.001). Comparison between cocaine-cue conditions showed lower metabolism with cognitive inhibition in right orbitofrontal cortex and right accumbens (p < 0.005), which was associated with right inferior frontal activation (r = -0.62, p < 0.005). Decreases in metabolism in brain regions that process the predictive (nucleus accumbens) and motivational value (orbitofrontal cortex) of drug-conditioned stimuli were elicited by instruction to inhibit cue-induced craving. This suggests that cocaine abusers may retain some ability to inhibit craving and that strengthening fronto-accumbal regulation may be therapeutically beneficial in addiction.« less

Cardiorespiratory fitness, cognition and brain structure after TIA or minor ischemic stroke.

PubMed

Boss, H Myrthe; Van Schaik, Sander M; Witkamp, Theo D; Geerlings, Mirjam I; Weinstein, Henry C; Van den Berg-Vos, Renske M

2017-10-01

Background It is not known whether cardiorespiratory fitness is associated with better cognitive performance and brain structure in patients with a TIA or minor ischemic stroke. Aims To examine the association between cardiorespiratory fitness, cognition and brain structure in patients with a TIA and minor stroke. Methods The study population consisted of patients with a TIA or minor stroke with a baseline measurement of the peak oxygen consumption, a MRI scan of brain and neuropsychological assessment. Composite z-scores were calculated for the cognitive domains attention, memory and executive functioning. White matter hyperintensities, microbleeds and lacunes were rated visually. The mean apparent diffusion coefficient was measured in regions of interest in frontal and occipital white matter and in the centrum semiovale as a marker of white matter structure. Normalized brain volumes were estimated by use of Statistical Parametric Mapping. Results In 84 included patients, linear regression analysis adjusted for age, sex and education showed that a higher peak oxygen consumption was associated with higher cognitive z-scores, a larger grey matter volume (B = 0.15 (95% CI 0.05; 0.26)) and a lower mean apparent diffusion coefficient (B = -.004 (95% CI -.007; -.001)). We found no association between the peak oxygen consumption and severe white matter hyperintensities, microbleeds, lacunes and total brain volume. Conclusions These data suggest that cardiorespiratory fitness is associated with better cognitive performance, greater grey matter volume and greater integrity of the white matter in patients with a TIA or minor ischemic stroke. Further prospective trials are necessary to define the effect of cardiorespiratory fitness on cognition and brain structure in patients with TIA or minor stroke.

Hybrid MR-PET of brain tumours using amino acid PET and chemical exchange saturation transfer MRI.

PubMed

da Silva, N A; Lohmann, P; Fairney, J; Magill, A W; Oros Peusquens, A-M; Choi, C-H; Stirnberg, R; Stoffels, G; Galldiks, N; Golay, X; Langen, K-J; Jon Shah, N

2018-06-01

PET using radiolabelled amino acids has become a promising tool in the diagnostics of gliomas and brain metastasis. Current research is focused on the evaluation of amide proton transfer (APT) chemical exchange saturation transfer (CEST) MR imaging for brain tumour imaging. In this hybrid MR-PET study, brain tumours were compared using 3D data derived from APT-CEST MRI and amino acid PET using O-(2- 18 F-fluoroethyl)-L-tyrosine ( 18 F-FET). Eight patients with gliomas were investigated simultaneously with 18 F-FET PET and APT-CEST MRI using a 3-T MR-BrainPET scanner. CEST imaging was based on a steady-state approach using a B 1 average power of 1μT. B 0 field inhomogeneities were corrected a Prametric images of magnetisation transfer ratio asymmetry (MTR asym ) and differences to the extrapolated semi-solid magnetisation transfer reference method, APT# and nuclear Overhauser effect (NOE#), were calculated. Statistical analysis of the tumour-to-brain ratio of the CEST data was performed against PET data using the non-parametric Wilcoxon test. A tumour-to-brain ratio derived from APT# and 18 F-FET presented no significant differences, and no correlation was found between APT# and 18 F-FET PET data. The distance between local hot spot APT# and 18 F-FET were different (average 20 ± 13 mm, range 4-45 mm). For the first time, CEST images were compared with 18 F-FET in a simultaneous MR-PET measurement. Imaging findings derived from 18 F-FET PET and APT CEST MRI seem to provide different biological information. The validation of these imaging findings by histological confirmation is necessary, ideally using stereotactic biopsy.

Stereotaxic 18F-FDG PET and MRI templates with three-dimensional digital atlas for statistical parametric mapping analysis of tree shrew brain.

PubMed

Huang, Qi; Nie, Binbin; Ma, Chen; Wang, Jing; Zhang, Tianhao; Duan, Shaofeng; Wu, Shang; Liang, Shengxiang; Li, Panlong; Liu, Hua; Sun, Hua; Zhou, Jiangning; Xu, Lin; Shan, Baoci

2018-01-01

Tree shrews are proposed as an alternative animal model to nonhuman primates due to their close affinity to primates. Neuroimaging techniques are widely used to study brain functions and structures of humans and animals. However, tree shrews are rarely applied in neuroimaging field partly due to the lack of available species specific analysis methods. In this study, 10 PET/CT and 10 MRI images of tree shrew brain were used to construct PET and MRI templates; based on histological atlas we reconstructed a three-dimensional digital atlas with 628 structures delineated; then the digital atlas and templates were aligned into a stereotaxic space. Finally, we integrated the digital atlas and templates into a toolbox for tree shrew brain spatial normalization, statistical analysis and results localization. We validated the feasibility of the toolbox by simulated data with lesions in laterodorsal thalamic nucleus (LD). The lesion volumes of simulated PET and MRI images were (12.97±3.91)mm 3 and (7.04±0.84)mm 3 . Statistical results at p<0.005 showed the lesion volumes of PET and MRI were 13.18mm 3 and 8.06mm 3 in LD. To our knowledge, we report the first PET template and digital atlas of tree shrew brain. Compared to the existing MRI templates, our MRI template was aligned into stereotaxic space. And the toolbox is the first software dedicated for tree shrew brain analysis. The templates and digital atlas of tree shrew brain, as well as the toolbox, facilitate the use of tree shrews in neuroimaging field. Copyright © 2017 Elsevier B.V. All rights reserved.

Potential predictors for the amount of intra-operative brain shift during deep brain stimulation surgery

NASA Astrophysics Data System (ADS)

Datteri, Ryan; Pallavaram, Srivatsan; Konrad, Peter E.; Neimat, Joseph S.; D'Haese, Pierre-François; Dawant, Benoit M.

2011-03-01

A number of groups have reported on the occurrence of intra-operative brain shift during deep brain stimulation (DBS) surgery. This has a number of implications for the procedure including an increased chance of intra-cranial bleeding and complications due to the need for more exploratory electrodes to account for the brain shift. It has been reported that the amount of pneumocephalus or air invasion into the cranial cavity due to the opening of the dura correlates with intraoperative brain shift. Therefore, pre-operatively predicting the amount of pneumocephalus expected during surgery is of interest toward accounting for brain shift. In this study, we used 64 DBS patients who received bilateral electrode implantations and had a post-operative CT scan acquired immediately after surgery (CT-PI). For each patient, the volumes of the pneumocephalus, left ventricle, right ventricle, third ventricle, white matter, grey matter, and cerebral spinal fluid were calculated. The pneumocephalus was calculated from the CT-PI utilizing a region growing technique that was initialized with an atlas-based image registration method. A multi-atlas-based image segmentation method was used to segment out the ventricles of each patient. The Statistical Parametric Mapping (SPM) software package was utilized to calculate the volumes of the cerebral spinal fluid (CSF), white matter and grey matter. The volume of individual structures had a moderate correlation with pneumocephalus. Utilizing a multi-linear regression between the volume of the pneumocephalus and the statistically relevant individual structures a Pearson's coefficient of r = 0.4123 (p = 0.0103) was found. This study shows preliminary results that could be used to develop a method to predict the amount of pneumocephalus ahead of the surgery.

Costs explained by function rather than diagnosis--results from the SNAC Nordanstig elderly cohort in Sweden.

PubMed

Lindholm, C; Gustavsson, A; Jönsson, L; Wimo, A

2013-05-01

Because the prevalence of many brain disorders rises with age, and brain disorders are costly, the economic burden of brain disorders will increase markedly during the next decades. The purpose of this study is to analyze how the costs to society vary with different levels of functioning and with the presence of a brain disorder. Resource utilization and costs from a societal viewpoint were analyzed versus cognition, activities of daily living (ADL), instrumental activities of daily living (IADL), brain disorder diagnosis and age in a population-based cohort of people aged 65 years and older in Nordanstig in Northern Sweden. Descriptive statistics, non-parametric bootstrapping and a generalized linear model (GLM) were used for the statistical analyses. Most people were zero users of care. Societal costs of dementia were by far the highest, ranging from SEK 262,000 (mild) to SEK 519,000 per year (severe dementia). In univariate analysis, all measures of functioning were significantly related to costs. When controlling for ADL and IADL in the multivariate GLM, cognition did not have a statistically significant effect on total cost. The presence of a brain disorder did not impact total cost when controlling for function. The greatest shift in costs was seen when comparing no dependency in ADL and dependency in one basic ADL function. It is the level of functioning, rather than the presence of a brain disorder diagnosis, which predicts costs. ADLs are better explanatory variables of costs than Mini mental state examination. Most people in a population-based cohort are zero users of care. Copyright © 2012 John Wiley & Sons, Ltd.

Higher cortical and lower subcortical metabolism in detoxified methamphetamine abusers.

PubMed

Volkow, N D; Chang, L; Wang, G J; Fowler, J S; Franceschi, D; Sedler, M J; Gatley, S J; Hitzemann, R; Ding, Y S; Wong, C; Logan, J

2001-03-01

Methamphetamine has raised concerns because it may be neurotoxic to the human brain. Although prior work has focused primarily on the effects of methamphetamine on dopamine cells, there is evidence that other neuronal types are affected. The authors measured regional brain glucose metabolism, which serves as a marker of brain function, to assess if there is evidence of functional changes in methamphetamine abusers in regions other than those innervated by dopamine cells. Fifteen detoxified methamphetamine abusers and 21 comparison subjects underwent positron emission tomography following administration of [(18)F]fluorodeoxyglucose. Whole brain metabolism in the methamphetamine abusers was 14% higher than that of comparison subjects; the differences were most accentuated in the parietal cortex (20%). After normalization for whole brain metabolism, methamphetamine abusers exhibited significantly lower metabolism in the thalamus (17% difference) and striatum (where the differences were larger for the caudate [12%] than for the putamen [6%]). Statistical parametric mapping analyses corroborated these findings, revealing higher metabolism in the parietal cortex and lower metabolism in the thalamus and striatum of methamphetamine abusers. The fact that the parietal cortex is a region devoid of any significant dopaminergic innervation suggests that the higher metabolism seen in this region in the methamphetamine abusers is the result of methamphetamine effects in circuits other than those modulated by dopamine. In addition, the lower metabolism in the striatum and thalamus (major outputs of dopamine signals into the cortex) is likely to reflect the functional consequence of methamphetamine in dopaminergic circuits. These results provide evidence that, in humans, methamphetamine abuse results in changes in function of dopamine- and nondopamine-innervated brain regions.

Inverse association between BMI and prefrontal metabolic activity in healthy adults.

PubMed

Volkow, Nora D; Wang, Gene-Jack; Telang, Frank; Fowler, Joanna S; Goldstein, Rita Z; Alia-Klein, Nelly; Logan, Jean; Wong, Christopher; Thanos, Panayotis K; Ma, Yemine; Pradhan, Kith

2009-01-01

Obesity has been associated with a higher risk for impaired cognitive function, which most likely reflects associated medical complications (i.e., cerebrovascular pathology). However, there is also evidence that in healthy individuals excess weight may adversely affect cognition (executive function, attention, and memory). Here, we measured regional brain glucose metabolism (using positron emission tomography (PET) and 2-deoxy-2[(18)F]fluoro-D-glucose (FDG)) to assess the relationship between BMI and brain metabolism (marker of brain function) in 21 healthy controls (BMI range 19-37 kg/m(2)) studied during baseline (no stimulation) and during cognitive stimulation (numerical calculations). Statistical parametric mapping (SPM) revealed a significant negative correlation between BMI and metabolic activity in prefrontal cortex (Brodmann areas 8, 9, 10, 11, 44) and cingulate gyrus (Brodmann area 32) but not in other regions. Moreover, baseline metabolism in these prefrontal regions was positively associated with performance on tests of memory (California Verbal Learning Test) and executive function (Stroop Interference and Symbol Digit Modality tests). In contrast, the regional brain changes during cognitive stimulation were not associated with BMI nor with neuropsychological performance. The observed association between higher BMI and lower baseline prefrontal metabolism may underlie the impaired performance reported in healthy obese individuals on some cognitive tests of executive function. On the other hand, the lack of an association between BMI and brain metabolic activation during cognitive stimulation indicates that BMI does not influence brain glucose utilization during cognitive performance. These results further highlight the urgency to institute public health interventions to prevent obesity.

Association between increased EEG signal complexity and cannabis dependence.

PubMed

Laprevote, Vincent; Bon, Laura; Krieg, Julien; Schwitzer, Thomas; Bourion-Bedes, Stéphanie; Maillard, Louis; Schwan, Raymund

2017-12-01

Both acute and regular cannabis use affects the functioning of the brain. While several studies have demonstrated that regular cannabis use can impair the capacity to synchronize neural assemblies during specific tasks, less is known about spontaneous brain activity. This can be explored by measuring EEG complexity, which reflects the spontaneous variability of human brain activity. A recent study has shown that acute cannabis use can affect that complexity. Since the characteristics of cannabis use can affect the impact on brain functioning, this study sets out to measure EEG complexity in regular cannabis users with or without dependence, in comparison with healthy controls. We recruited 26 healthy controls, 25 cannabis users without cannabis dependence and 14 cannabis users with cannabis dependence, based on DSM IV TR criteria. The EEG signal was extracted from at least 250 epochs of the 500ms pre-stimulation phase during a visual evoked potential paradigm. Brain complexity was estimated using Lempel-Ziv Complexity (LZC), which was compared across groups by non-parametric Kruskall-Wallis ANOVA. The analysis revealed a significant difference between the groups, with higher LZC in participants with cannabis dependence than in non-dependent cannabis users. There was no specific localization of this effect across electrodes. We showed that cannabis dependence is associated to an increased spontaneous brain complexity in regular users. This result is in line with previous results in acute cannabis users. It may reflect increased randomness of neural activity in cannabis dependence. Future studies should explore whether this effect is permanent or diminishes with cannabis cessation. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Brain activity correlates with emotional perception induced by dynamic avatars.

PubMed

Goldberg, Hagar; Christensen, Andrea; Flash, Tamar; Giese, Martin A; Malach, Rafael

2015-11-15

An accurate judgment of the emotional state of others is a prerequisite for successful social interaction and hence survival. Thus, it is not surprising that we are highly skilled at recognizing the emotions of others. Here we aimed to examine the neuronal correlates of emotion recognition from gait. To this end we created highly controlled dynamic body-movement stimuli based on real human motion-capture data (Roether et al., 2009). These animated avatars displayed gait in four emotional (happy, angry, fearful, and sad) and speed-matched neutral styles. For each emotional gait and its equivalent neutral gait, avatars were displayed at five morphing levels between the two. Subjects underwent fMRI scanning while classifying the emotions and the emotional intensity levels expressed by the avatars. Our results revealed robust brain selectivity to emotional compared to neutral gait stimuli in brain regions which are involved in emotion and biological motion processing, such as the extrastriate body area (EBA), fusiform body area (FBA), superior temporal sulcus (STS), and the amygdala (AMG). Brain activity in the amygdala reflected emotional awareness: for visually identical stimuli it showed amplified stronger response when the stimulus was perceived as emotional. Notably, in avatars gradually morphed along an emotional expression axis there was a parametric correlation between amygdala activity and emotional intensity. This study extends the mapping of emotional decoding in the human brain to the domain of highly controlled dynamic biological motion. Our results highlight an extensive level of brain processing of emotional information related to body language, which relies mostly on body kinematics. Copyright © 2015. Published by Elsevier Inc.

Abnormal resting-state brain activities in patients with first-episode obsessive-compulsive disorder

PubMed Central

Niu, Qihui; Yang, Lei; Song, Xueqin; Chu, Congying; Liu, Hao; Zhang, Lifang; Li, Yan; Zhang, Xiang; Cheng, Jingliang; Li, Youhui

2017-01-01

Objective This paper attempts to explore the brain activity of patients with obsessive-compulsive disorder (OCD) and its correlation with the disease at resting duration in patients with first-episode OCD, providing a forceful imaging basis for clinic diagnosis and pathogenesis of OCD. Methods Twenty-six patients with first-episode OCD and 25 healthy controls (HC group; matched for age, sex, and education level) underwent functional magnetic resonance imaging (fMRI) scanning at resting state. Statistical parametric mapping 8, data processing assistant for resting-state fMRI analysis toolkit, and resting state fMRI data analysis toolkit packages were used to process the fMRI data on Matlab 2012a platform, and the difference of regional homogeneity (ReHo) values between the OCD group and HC group was detected with independent two-sample t-test. With age as a concomitant variable, the Pearson correlation analysis was adopted to study the correlation between the disease duration and ReHo value of whole brain. Results Compared with HC group, the ReHo values in OCD group were decreased in brain regions, including left thalamus, right thalamus, right paracentral lobule, right postcentral gyrus, and the ReHo value was increased in the left angular gyrus region. There was a negative correlation between disease duration and ReHo value in the bilateral orbitofrontal cortex (OFC). Conclusion OCD is a multifactorial disease generally caused by abnormal activities of many brain regions at resting state. Worse brain activity of the OFC is related to the OCD duration, which provides a new insight to the pathogenesis of OCD. PMID:28243104

Static Strength of Adhesively-bonded Woven Fabric Kenaf Composite Plates

NASA Astrophysics Data System (ADS)

Hilton, Ahmad; Lee, Sim Yee; Supar, Khairi

2017-06-01

Natural fibers are potentially used as reinforcing materials and combined with epoxy resin as matrix system to form a superior specific strength (or stiffness) materials known as composite materials. The advantages of implementing natural fibers such as kenaf fibers are renewable, less hazardous during fabrication and handling process; and relatively cheap compared to synthetic fibers. The aim of current work is to conduct a parametric study on static strength of adhesively bonded woven fabric kenaf composite plates. Fabrication of composite panels were conducted using hand lay-up techniques, with variation of stacking sequence, over-lap length, joint types and lay-up types as identified in testing series. Quasi-static testing was carried out using mechanical testing following code of practice. Load-displacement profiles were analyzed to study its structural response prior to ultimate failures. It was found that cross-ply lay-up demonstrates better static strength compared to quasi-isotropic lay-up counterparts due to larger volume of 0° plies exhibited in cross-ply lay-up. Consequently, larger overlap length gives better joining strength, as expected, however this promotes to weight penalty in the joining structure. Most samples showed failures within adhesive region known as cohesive failure modes, however, few sample demonstrated interface failure. Good correlations of parametric study were found and discussed in the respective section.

Research on the Integration of Bionic Geometry Modeling and Simulation of Robot Foot Based on Characteristic Curve

NASA Astrophysics Data System (ADS)

He, G.; Zhu, H.; Xu, J.; Gao, K.; Zhu, D.

2017-09-01

The bionic research of shape is an important aspect of the research on bionic robot, and its implementation cannot be separated from the shape modeling and numerical simulation of the bionic object, which is tedious and time-consuming. In order to improve the efficiency of shape bionic design, the feet of animals living in soft soil and swamp environment are taken as bionic objects, and characteristic skeleton curve, section curve, joint rotation variable, position and other parameters are used to describe the shape and position information of bionic object’s sole, toes and flipper. The geometry modeling of the bionic object is established by using the parameterization of characteristic curves and variables. Based on this, the integration framework of parametric modeling and finite element modeling, dynamic analysis and post-processing of sinking process in soil is proposed in this paper. The examples of bionic ostrich foot and bionic duck foot are also given. The parametric modeling and integration technique can achieve rapid improved design based on bionic object, and it can also greatly improve the efficiency and quality of robot foot bionic design, and has important practical significance to improve the level of bionic design of robot foot’s shape and structure.

Brain activation in response to randomized visual stimulation as obtained from conjunction and differential analysis: an fMRI study

NASA Astrophysics Data System (ADS)

Nasaruddin, N. H.; Yusoff, A. N.; Kaur, S.

2014-11-01

The objective of this multiple-subjects functional magnetic resonance imaging (fMRI) study was to identify the common brain areas that are activated when viewing black-and-white checkerboard pattern stimuli of various shapes, pattern and size and to investigate specific brain areas that are involved in processing static and moving visual stimuli. Sixteen participants viewed the moving (expanding ring, rotating wedge, flipping hour glass and bowtie and arc quadrant) and static (full checkerboard) stimuli during an fMRI scan. All stimuli have black-and-white checkerboard pattern. Statistical parametric mapping (SPM) was used in generating brain activation. Differential analyses were implemented to separately search for areas involved in processing static and moving stimuli. In general, the stimuli of various shapes, pattern and size activated multiple brain areas mostly in the left hemisphere. The activation in the right middle temporal gyrus (MTG) was found to be significantly higher in processing moving visual stimuli as compared to static stimulus. In contrast, the activation in the left calcarine sulcus and left lingual gyrus were significantly higher for static stimulus as compared to moving stimuli. Visual stimulation of various shapes, pattern and size used in this study indicated left lateralization of activation. The involvement of the right MTG in processing moving visual information was evident from differential analysis, while the left calcarine sulcus and left lingual gyrus are the areas that are involved in the processing of static visual stimulus.

Typical cerebral metabolic patterns in neurodegenerative brain diseases.

PubMed

Teune, Laura K; Bartels, Anna L; de Jong, Bauke M; Willemsen, Antoon T M; Eshuis, Silvia A; de Vries, Jeroen J; van Oostrom, Joost C H; Leenders, Klaus L

2010-10-30

The differential diagnosis of neurodegenerative brain diseases on clinical grounds is difficult, especially at an early disease stage. Several studies have found specific regional differences of brain metabolism applying [(18)F]-fluoro-deoxyglucose positron emission tomography (FDG-PET), suggesting that this method can assist in early differential diagnosis of neurodegenerative brain diseases.We have studied patients who had an FDG-PET scan on clinical grounds at an early disease stage and included those with a retrospectively confirmed diagnosis according to strictly defined clinical research criteria. Ninety-six patients could be included of which 20 patients with Parkinson's disease (PD), 21 multiple system atrophy (MSA), 17 progressive supranuclear palsy (PSP), 10 corticobasal degeneration (CBD), 6 dementia with Lewy bodies (DLB), 15 Alzheimer's disease (AD), and 7 frontotemporal dementia (FTD). FDG PET images of each patient group were analyzed and compared to18 healthy controls using Statistical Parametric Mapping (SPM5).Disease-specific patterns of relatively decreased metabolic activity were found in PD (contralateral parietooccipital and frontal regions), MSA (bilateral putamen and cerebellar hemispheres), PSP (prefrontal cortex and caudate nucleus, thalamus, and mesencephalon), CBD (contralateral cortical regions), DLB (occipital and parietotemporal regions), AD (parietotemporal regions), and FTD (frontotemporal regions).The integrated method addressing a spectrum of various neurodegenerative brain diseases provided means to discriminate patient groups also at early disease stages. Clinical follow-up enabled appropriate patient inclusion. This implies that an early diagnosis in individual patients can be made by comparing each subject's metabolic findings with a complete database of specific disease related patterns.

Longitudinal Brain Magnetic Resonance Imaging CO2 Stress Testing in Individual Adolescent Sports-Related Concussion Patients: A Pilot Study.

PubMed

Mutch, W Alan C; Ellis, Michael J; Ryner, Lawrence N; Morissette, Marc P; Pries, Philip J; Dufault, Brenden; Essig, Marco; Mikulis, David J; Duffin, James; Fisher, Joseph A

2016-01-01

Advanced neuroimaging studies in concussion have been limited to detecting group differences between concussion patients and healthy controls. In this small pilot study, we used brain magnetic resonance imaging (MRI) CO2 stress testing to longitudinally assess cerebrovascular responsiveness (CVR) in individual sports-related concussion (SRC) patients. Six SRC patients (three males and three females; mean age = 15.7, range = 15-17 years) underwent longitudinal brain MRI CO2 stress testing using blood oxygen level-dependent (BOLD) MRI and model-based prospective end-tidal CO2 targeting under isoxic conditions. First-level and second-level comparisons were undertaken using statistical parametric mapping (SPM) to score the scans and compare them to an atlas of 24 healthy control subjects. All tests were well tolerated and without any serious adverse events. Anatomical MRI was normal in all study participants. The CO2 stimulus was consistent between the SRC patients and control subjects and within SRC patients across the longitudinal study. Individual SRC patients demonstrated both quantitative and qualitative patient-specific alterations in CVR (p < 0.005) that correlated strongly with clinical findings, and that persisted beyond clinical recovery. Standardized brain MRI CO2 stress testing is capable of providing a longitudinal assessment of CVR in individual SRC patients. Consequently, larger prospective studies are needed to examine the utility of brain MRI CO2 stress testing as a clinical tool to help guide the evaluation, classification, and longitudinal management of SRC patients.

Corticonic models of brain mechanisms underlying cognition and intelligence

NASA Astrophysics Data System (ADS)

Farhat, Nabil H.

The concern of this review is brain theory or more specifically, in its first part, a model of the cerebral cortex and the way it: (a) interacts with subcortical regions like the thalamus and the hippocampus to provide higher-level-brain functions that underlie cognition and intelligence, (b) handles and represents dynamical sensory patterns imposed by a constantly changing environment, (c) copes with the enormous number of such patterns encountered in a lifetime by means of dynamic memory that offers an immense number of stimulus-specific attractors for input patterns (stimuli) to select from, (d) selects an attractor through a process of “conjugation” of the input pattern with the dynamics of the thalamo-cortical loop, (e) distinguishes between redundant (structured) and non-redundant (random) inputs that are void of information, (f) can do categorical perception when there is access to vast associative memory laid out in the association cortex with the help of the hippocampus, and (g) makes use of “computation” at the edge of chaos and information driven annealing to achieve all this. Other features and implications of the concepts presented for the design of computational algorithms and machines with brain-like intelligence are also discussed. The material and results presented suggest, that a Parametrically Coupled Logistic Map network (PCLMN) is a minimal model of the thalamo-cortical complex and that marrying such a network to a suitable associative memory with re-entry or feedback forms a useful, albeit, abstract model of a cortical module of the brain that could facilitate building a simple artificial brain. In the second part of the review, the results of numerical simulations and drawn conclusions in the first part are linked to the most directly relevant works and views of other workers. What emerges is a picture of brain dynamics on the mesoscopic and macroscopic scales that gives a glimpse of the nature of the long sought after brain code underlying intelligence and other higher level brain functions.

Designing a hands-on brain computer interface laboratory course.

PubMed

Khalighinejad, Bahar; Long, Laura Kathleen; Mesgarani, Nima

2016-08-01

Devices and systems that interact with the brain have become a growing field of research and development in recent years. Engineering students are well positioned to contribute to both hardware development and signal analysis techniques in this field. However, this area has been left out of most engineering curricula. We developed an electroencephalography (EEG) based brain computer interface (BCI) laboratory course to educate students through hands-on experiments. The course is offered jointly by the Biomedical Engineering, Electrical Engineering, and Computer Science Departments of Columbia University in the City of New York and is open to senior undergraduate and graduate students. The course provides an effective introduction to the experimental design, neuroscience concepts, data analysis techniques, and technical skills required in the field of BCI.

Mössbauer and X-ray study of biodegradation of 57Fe3 O 4 magnetic nanoparticles in rat brain

NASA Astrophysics Data System (ADS)

Gabbasov, R. R.; Cherepanov, V. M.; Chuev, M. A.; Lomov, A. A.; Mischenko, I. N.; Nikitin, M. P.; Polikarpov, M. A.; Panchenko, V. Y.

2016-12-01

Biodegradation of a 57Fe3 O 4 - based dextran - stabilized ferrofluid in the ventricular cavities of the rat brain was studied by X-ray diffraction and Mössbauer spectroscopy. A two-step process of biodegradation, consisting of fast disintegration of the initial composite magnetic beads into separate superparamagnetic nanoparticles and subsequent slow dissolution of the nanoparticles has been found. Joint fitting of the couples of Mössbauer spectra measured at different temperatures in the formalism of multi-level relaxation model with one set of fitting parameters, allowed us to measure concentration of exogenous iron in the rat brain as a function of time after the injection of nanoparticles.

Effect of 12-Day Spaceflight on Brain of Thick-Toed Geckos

NASA Astrophysics Data System (ADS)

Proshchina, A. E.; Karlamova, A. S.; Barabanovet, V. M.; Godovalova, O. S.; Guilimova, V. I.; Krivova, Y. S.; Makarov, A. N.; Nikitin, V. B.; Savelieva, E. S.; Saveliev, S. V.

2008-06-01

In the frames of Russian-American joint space experiment onboard Foton-M3 satellite there was undertaken a study of spaceflight influence on brain of the thick-toed gecko (Pachydactylus turneri Gray, 1864). Serial brain sections were stained according to Nissl and also the immunohistochemical method with antibodies to NGF-receptor (p75NGFR), CD95 (also known as Fas and APO-1), glial fibrillary acidic protein (GFAP) and transferrin-receptor (CD71). Detailed examination of the sections of rhombencephalon revealed cytological changes in the neuron bodies of vestibular nuclei inside the flight group. Immunohistochemicaly we found the increase density of CD95 and p75NGFR and decrease of GFAP expression in medial cortex and epithalamus in flight group compared both control.

Terrorist-Insurgent Thinking and Joint Special Operational Planning Doctrine and Procedures

DTIC Science & Technology

2010-09-01

b. Often organized planners, with some military training/experience c. Usually the brains behind operations or targeting and having the most detailed... Storytelling and Terrorism: Towards a Compre- hensive ‘Counter-Narrative Strategy,’ ” Strategic Insights IV:3 (March 2005), 1-16. Center for Army Lessons

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

PubMed Central

Bilek, Edda; Ruf, Matthias; Schäfer, Axel; Akdeniz, Ceren; Calhoun, Vince D.; Schmahl, Christian; Demanuele, Charmaine; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2015-01-01

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender’s and receiver’s temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions. PMID:25848050

Changes in gait patterns induced by rhythmic auditory stimulation for adolescents with acquired brain injury.

PubMed

Kim, Soo Ji; Shin, Yoon-Kyum; Yoo, Ga Eul; Chong, Hyun Ju; Cho, Sung-Rae

2016-12-01

The effects of rhythmic auditory stimulation (RAS) on gait in adolescents with acquired brain injury (ABI) were investigated. A total of 14 adolescents with ABI were initially recruited, and 12 were included in the final analysis (n = 6 each). They were randomly assigned to the experimental (RAS) or the control (conventional gait training) groups. The experimental group received gait training with RAS three times a week for 4 weeks. For both groups, spatiotemporal parameters and kinematic data, such as dynamic motions of joints on three-dimensional planes during a gait cycle and the range of motion in each joint, were collected. Significant group differences in pre-post changes were observed in cadence, walking velocity, and step time, indicating that there were greater improvements in those parameters in the RAS group compared with the control group. Significant increases in hip and knee motions in the sagittal plane were also observed in the RAS group. The changes in kinematic data significantly differed between groups, particularly from terminal stance to mid-swing phase. An increase of both spatiotemporal parameters and corresponding kinematic changes of hip and knee joints after RAS protocol indicates that the use of rhythmic cueing may change gait patterns in adolescents with ABI. © 2016 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

The potential role of brain asymmetry in the development of adolescent idiopathic scoliosis: a hypothesis.

PubMed

Niesluchowski, W; Dabrowska, A; Kedzior, K; Zagrajek, T

1999-10-01

The size asymmetry of cerebral hemispheres may predispose to head tilt and asymmetric blocking of the zygapophysial joints, potentially leading to the development of compensatory curvatures in the lower segments of the spine. To analyze the effects of spinal manipulation, maintained by an exercise program, on the progression of idiopathic adolescent scoliosis in 2 children aged 6 and 10. The scoliosis found was 16 and 60 degrees. For diagnosis and monitoring of therapy, we recorded qualitative parameters of shoulder asymmetry, axillary line asymmetry, and scapular angle position. Manual treatment consisted of the examinations of all sliding motion in zygapophysial joints and both sacroiliac joints and removing the limitations of the sliding motions according to the method of Karel Lewit. The treatment procedure consisted of 3 or 4 manipulations within 17 months and an exercise program. The manipulation effects were maintained by the exercise program. The exercises were done in 2 or 3 sessions weekly for a year. In both patients we observed that scoliosis decompensation was successfully stopped and the effects of the correction persisted for 10 years. Brain and head asymmetry may be only a transient state, predisposing to asymmetric blocking at the atlanto-occipital level. Removal of blocking may prevent curve progression in children who had adolescent idiopathic scoliosis. The manipulative therapy may also have a promising effect on retarding curve progression when used in skeletally immature patient.

The influence of head diameter and wall thickness on deformations of metallic acetabular press-fit cups and UHMWPE liners: a finite element analysis.

PubMed

Goebel, Paul; Kluess, Daniel; Wieding, Jan; Souffrant, Robert; Heyer, Horst; Sander, Manuela; Bader, Rainer

2013-03-01

To increase the range of motion of total hip endoprostheses, prosthetic heads need to be enlarged, which implies that the cup and/or liner thickness must decrease. This may have negative effects on the wear rate, because the acetabular cups and liners could deform during press-fit implantation and hip joint loading. We compared the metal cup and polyethylene liner deformations that occurred when different wall thicknesses were used in order to evaluate the resulting changes in the clearance of the articulating region. A parametric finite element model utilized three cup and liner wall thicknesses to analyze cup and liner deformations after press-fit implantation into the pelvic bone. The resultant hip joint force during heel strike was applied while the femur was fixed, accounting for physiological muscle forces. The deformation behavior of the liner under joint loading was therefore assessed as a function of the head diameter and the resulting clearance. Press-fit implantation showed diametral cup deformations of 0.096, 0.034, and 0.014 mm for cup wall thicknesses of 3, 5, and 7 mm, respectively. The largest deformations (average 0.084 ± 0.003 mm) of liners with thicknesses of 4, 6, and 8 mm occurred with the smallest cup wall thickness (3 mm). The smallest liner deformation (0.011 mm) was obtained with largest cup and liner wall thicknesses. Under joint loading, liner deformations in thin-walled acetabular cups (3 mm) reduced the initial clearance by about 50 %. Acetabular press-fit cups with wall thicknesses of ≤5 mm should only be used in combination with polyethylene liners >6 mm thick in order to minimize the reduction in clearance.

Prescribing joint co-ordinates during model preparation to improve inverse kinematic estimates of elbow joint angles.

PubMed

Wells, D J M; Alderson, J A; Dunne, J; Elliott, B C; Donnelly, C J

2017-01-25

To appropriately use inverse kinematic (IK) modelling for the assessment of human motion, a musculoskeletal model must be prepared 1) to match participant segment lengths (scaling) and 2) to align the model׳s virtual markers positions with known, experimentally derived kinematic marker positions (marker registration). The purpose of this study was to investigate whether prescribing joint co-ordinates during the marker registration process (within the modelling framework OpenSim) will improve IK derived elbow kinematics during an overhead sporting task. To test this, the upper limb kinematics of eight cricket bowlers were recorded during two testing sessions, with a different tester each session. The bowling trials were IK modelled twice: once with an upper limb musculoskeletal model prepared with prescribed participant specific co-ordinates during marker registration - MR PC - and once with the same model prepared without prescribed co-ordinates - MR; and by an established direct kinematic (DK) upper limb model. Whilst both skeletal model preparations had strong inter-tester repeatability (MR: Statistical Parametric Mapping (SPM1D)=0% different; MR PC : SPM1D=0% different), when compared with DK model elbow FE waveform estimates, IK estimates using the MR PC model (RMSD=5.2±2.0°, SPM1D=68% different) were in closer agreement than the estimates from the MR model (RMSD=44.5±18.5°, SPM1D=100% different). Results show that prescribing participant specific joint co-ordinates during the marker registration phase of model preparation increases the accuracy and repeatability of IK solutions when modelling overhead sporting tasks in OpenSim. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of lateralized design on muscle and joint reaction forces for reverse shoulder arthroplasty.

PubMed

Liou, William; Yang, Yang; Petersen-Fitts, Graysen R; Lombardo, Daniel J; Stine, Sasha; Sabesan, Vani J

2017-04-01

Manufacturers of reverse shoulder arthroplasty (RSA) implants have recently designed innovative implants to optimize performance in rotator cuff-deficient shoulders. These advancements are not without tradeoffs and can have negative biomechanical effects. The objective of this study was to develop an integrated finite element analysis-kinematic model to compare the muscle forces and joint reaction forces (JRFs) of 3 different RSA designs. A kinematic model of a normal shoulder joint was adapted from the Delft model and integrated with the well-validated OpenSim shoulder model. Static optimizations then allowed for calculation of the individual muscle forces, moment arms, and JRFs relative to net joint moments. Three-dimensional computer models of 3 RSA designs-humeral lateralized design (HLD), glenoid lateralized design, and Grammont design-were integrated, and parametric studies were performed. Overall, there were decreases in deltoid and rotator cuff muscle forces for all 3 RSA designs. These decreases were greatest in the middle deltoid of the HLD model for abduction and flexion and in the rotator cuff muscles under both internal rotation and external rotation. The JRFs in abduction and flexion decreased similarly for all RSA designs compared with the normal shoulder model, with the greatest decrease seen in the HLD model. These findings demonstrate that the design characteristics implicit in these modified RSA prostheses result in mechanical differences most prominently seen in the deltoid muscle and overall JRFs. Further research using this novel integrated model can help guide continued optimization of RSA design and clinical outcomes. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions

PubMed Central

Golkar, Mahsa A.; Sobhani Tehrani, Ehsan; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness is a dynamic, nonlinear relationship between the position of a joint and the torque acting about it, which can be used to describe the biomechanics of the joint and associated limb(s). This paper models and quantifies changes in ankle dynamic stiffness and its individual elements, intrinsic and reflex stiffness, in healthy human subjects during isometric, time-varying (TV) contractions of the ankle plantarflexor muscles. A subspace, linear parameter varying, parallel-cascade (LPV-PC) algorithm was used to identify the model from measured input position perturbations and output torque data using voluntary torque as the LPV scheduling variable (SV). Monte-Carlo simulations demonstrated that the algorithm is accurate, precise, and robust to colored measurement noise. The algorithm was then used to examine stiffness changes associated with TV isometric contractions. The SV was estimated from the Soleus EMG using a Hammerstein model of EMG-torque dynamics identified from unperturbed trials. The LPV-PC algorithm identified (i) a non-parametric LPV impulse response function (LPV IRF) for intrinsic stiffness and (ii) a LPV-Hammerstein model for reflex stiffness consisting of a LPV static nonlinearity followed by a time-invariant state-space model of reflex dynamics. The results demonstrated that: (a) intrinsic stiffness, in particular ankle elasticity, increased significantly and monotonically with activation level; (b) the gain of the reflex pathway increased from rest to around 10–20% of subject's MVC and then declined; and (c) the reflex dynamics were second order. These findings suggest that in healthy human ankle, reflex stiffness contributes most at low muscle contraction levels, whereas, intrinsic contributions monotonically increase with activation level. PMID:28579954

Clinical application of 3D arterial spin-labeled brain perfusion imaging for Alzheimer disease: comparison with brain perfusion SPECT.

PubMed

Takahashi, H; Ishii, K; Hosokawa, C; Hyodo, T; Kashiwagi, N; Matsuki, M; Ashikaga, R; Murakami, T

2014-05-01

Alzheimer disease is the most common neurodegenerative disorder with dementia, and a practical and economic biomarker for diagnosis of Alzheimer disease is needed. Three-dimensional arterial spin-labeling, with its high signal-to-noise ratio, enables measurement of cerebral blood flow precisely without any extrinsic tracers. We evaluated the performance of 3D arterial spin-labeling compared with SPECT, and demonstrated the 3D arterial spin-labeled imaging characteristics in the diagnosis of Alzheimer disease. This study included 68 patients with clinically suspected Alzheimer disease who underwent both 3D arterial spin-labeling and SPECT imaging. Two readers independently assessed both images. Kendall W coefficients of concordance (K) were computed, and receiver operating characteristic analyses were performed for each reader. The differences between the images in regional perfusion distribution were evaluated by means of statistical parametric mapping, and the incidence of hypoperfusion of the cerebral watershed area, referred to as "borderzone sign" in the 3D arterial spin-labeled images, was determined. Readers showed K = 0.82/0.73 for SPECT/3D arterial spin-labeled imaging, and the respective areas under the receiver operating characteristic curve were 0.82/0.69 for reader 1 and 0.80/0.69 for reader 2. Statistical parametric mapping showed that the perisylvian and medial parieto-occipital perfusion in the arterial spin-labeled images was significantly higher than that in the SPECT images. Borderzone sign was observed on 3D arterial spin-labeling in 70% of patients misdiagnosed with Alzheimer disease. The diagnostic performance of 3D arterial spin-labeling and SPECT for Alzheimer disease was almost equivalent. Three-dimensional arterial spin-labeled imaging was more influenced by hemodynamic factors than was SPECT imaging. © 2014 by American Journal of Neuroradiology.

Sci-Thur PM - Colourful Interactions: Highlights 04: A Fast Quantitative MRI Acquisition and Processing Pipeline for Radiation Treatment Planning and Simulation

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

Jutras, Jean-David

MRI-only Radiation Treatment Planning (RTP) is becoming increasingly popular because of a simplified work-flow, and less inconvenience to the patient who avoids multiple scans. The advantages of MRI-based RTP over traditional CT-based RTP lie in its superior soft-tissue contrast, and absence of ionizing radiation dose. The lack of electron-density information in MRI can be addressed by automatic tissue classification. To distinguish bone from air, which both appear dark in MRI, an ultra-short echo time (UTE) pulse sequence may be used. Quantitative MRI parametric maps can provide improved tissue segmentation/classification and better sensitivity in monitoring disease progression and treatment outcome thanmore » standard weighted images. Superior tumor contrast can be achieved on pure T{sub 1} images compared to conventional T{sub 1}-weighted images acquired in the same scan duration and voxel resolution. In this study, we have developed a robust and fast quantitative MRI acquisition and post-processing work-flow that integrates these latest advances into the MRI-based RTP of brain lesions. Using 3D multi-echo FLASH images at two different optimized flip angles (both acquired in under 9 min, and 1mm isotropic resolution), parametric maps of T{sub 1}, proton-density (M{sub 0}), and T{sub 2}{sup *} are obtained with high contrast-to-noise ratio, and negligible geometrical distortions, water-fat shifts and susceptibility effects. An additional 3D UTE MRI dataset is acquired (in under 4 min) and post-processed to classify tissues for dose simulation. The pipeline was tested on four healthy volunteers and a clinical trial on brain cancer patients is underway.« less

Rhinencephalon changes in tuberous sclerosis complex.

PubMed

Manara, Renzo; Brotto, Davide; Bugin, Samuela; Pelizza, Maria Federica; Sartori, Stefano; Nosadini, Margherita; Azzolini, Sara; Iaconetta, Giorgio; Parazzini, Cecilia; Murgia, Alessandra; Peron, Angela; Canevini, Paola; Labriola, Francesca; Vignoli, Aglaia; Toldo, Irene

2018-06-17

Despite complex olfactory bulb embryogenesis, its development abnormalities in tuberous sclerosis complex (TSC) have been poorly investigated. Brain MRIs of 110 TSC patients (mean age 11.5 years; age range 0.5-38 years; 52 female; 26 TSC1, 68 TSC2, 8 without mutation identified in TSC1 or TSC2, 8 not tested) were retrospectively evaluated. Signal and morphological abnormalities consistent with olfactory bulb hypo/aplasia or with olfactory bulb hamartomas were recorded. Cortical tuber number was visually assessed and a neurological severity score was obtained. Patients with and without rhinencephalon abnormalities were compared using appropriate parametric and non-parametric tests. Eight of110 (7.2%) TSC patients presented rhinencephalon MRI changes encompassing olfactory bulb bilateral aplasia (2/110), bilateral hypoplasia (2/110), unilateral hypoplasia (1/110), unilateral hamartoma (2/110), and bilateral hamartomas (1/110); olfactory bulb hypo/aplasia always displayed ipsilateral olfactory sulcus hypoplasia, while no TSC patient harboring rhinencephalon hamartomas had concomitant forebrain sulcation abnormalities. None of the patients showed overt olfactory deficits or hypogonadism, though young age and poor compliance hampered a proper evaluation in most cases. TSC patients with rhinencephalon changes had more cortical tubers (47 ± 29.1 vs 26.2 ± 19.6; p = 0.006) but did not differ for clinical severity (p = 0.45) compared to the other patients of the sample. Olfactory bulb and/or forebrain changes are not rare among TSC subjects. Future studies investigating clinical consequences in older subjects (anosmia, gonadic development etc.) will define whether rhinencephalon changes are simply an imaging feature among the constellation of TSC-related brain changes or a feature to be searched for possible implications in the management of TSC subjects.

A parametric model and estimation techniques for the inharmonicity and tuning of the piano.

PubMed

Rigaud, François; David, Bertrand; Daudet, Laurent

2013-05-01

Inharmonicity of piano tones is an essential property of their timbre that strongly influences the tuning, leading to the so-called octave stretching. It is proposed in this paper to jointly model the inharmonicity and tuning of pianos on the whole compass. While using a small number of parameters, these models are able to reflect both the specificities of instrument design and tuner's practice. An estimation algorithm is derived that can run either on a set of isolated note recordings, but also on chord recordings, assuming that the played notes are known. It is applied to extract parameters highlighting some tuner's choices on different piano types and to propose tuning curves for out-of-tune pianos or piano synthesizers.

Robust H∞ output-feedback control for path following of autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Hu, Chuan; Jing, Hui; Wang, Rongrong; Yan, Fengjun; Chadli, Mohammed

2016-03-01

This paper presents a robust H∞ output-feedback control strategy for the path following of autonomous ground vehicles (AGVs). Considering the vehicle lateral velocity is usually hard to measure with low cost sensor, a robust H∞ static output-feedback controller based on the mixed genetic algorithms (GA)/linear matrix inequality (LMI) approach is proposed to realize the path following without the information of the lateral velocity. The proposed controller is robust to the parametric uncertainties and external disturbances, with the parameters including the tire cornering stiffness, vehicle longitudinal velocity, yaw rate and road curvature. Simulation results based on CarSim-Simulink joint platform using a high-fidelity and full-car model have verified the effectiveness of the proposed control approach.

Testing averaged cosmology with type Ia supernovae and BAO data

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

Santos, B.; Alcaniz, J.S.; Coley, A.A.

An important problem in precision cosmology is the determination of the effects of averaging and backreaction on observational predictions, particularly in view of the wealth of new observational data and improved statistical techniques. In this paper, we discuss the observational viability of a class of averaged cosmologies which consist of a simple parametrized phenomenological two-scale backreaction model with decoupled spatial curvature parameters. We perform a Bayesian model selection analysis and find that this class of averaged phenomenological cosmological models is favored with respect to the standard ΛCDM cosmological scenario when a joint analysis of current SNe Ia and BAO datamore » is performed. In particular, the analysis provides observational evidence for non-trivial spatial curvature.« less

Parameter dimension of turbulence-induced phase errors and its effects on estimation in phase diversity

NASA Technical Reports Server (NTRS)

Thelen, Brian J.; Paxman, Richard G.

1994-01-01

The method of phase diversity has been used in the context of incoherent imaging to estimate jointly an object that is being imaged and phase aberrations induced by atmospheric turbulence. The method requires a parametric model for the phase-aberration function. Typically, the parameters are coefficients to a finite set of basis functions. Care must be taken in selecting a parameterization that properly balances accuracy in the representation of the phase-aberration function with stability in the estimates. It is well known that over parameterization can result in unstable estimates. Thus a certain amount of model mismatch is often desirable. We derive expressions that quantify the bias and variance in object and aberration estimates as a function of parameter dimension.

Antecedents and Outcomes of Joint Trajectories of Mother-Son Conflict and Warmth during Middle Childhood and Adolescence

PubMed Central

Trentacosta, Christopher J.; Criss, Michael M.; Shaw, Daniel S.; Lacourse, Eric; Hyde, Luke W.; Dishion, Thomas J.

2011-01-01

This study investigated the development of mother-son relationship quality from ages 5 to 15 in a sample of 265 low-income families. Non-parametric random effects modeling was utilized to uncover distinct and homogeneous developmental trajectories of conflict and warmth; antecedents and outcomes of the trajectory groups also were examined. Four conflict trajectory groups and three warmth trajectory groups were identified. Difficult temperament in early childhood discriminated both conflict and warmth trajectory group membership (TGM), and adult relationship quality in early childhood was related to warmth trajectories. In addition, conflict TGM differentiated youth antisocial behavior during adolescence, and warmth trajectories predicted adolescent peer relationship quality and youth moral disengagement. Implications for socialization processes are discussed. PMID:21883153

Experimental demonstration of entanglement-enhanced classical communication over a quantum channel with correlated noise.

PubMed

Banaszek, Konrad; Dragan, Andrzej; Wasilewski, Wojciech; Radzewicz, Czesław

2004-06-25

We present an experiment demonstrating the entanglement enhanced capacity of a quantum channel with correlated noise, modeled by a fiber optic link exhibiting fluctuating birefringence. In this setting, introducing entanglement between two photons is required to maximize the amount of information that can be encoded into their joint polarization degree of freedom. We demonstrated this effect using a fiber-coupled source of entangled photon pairs based on spontaneous parametric down-conversion, and a linear-optics Bell state measurement. The obtained experimental classical capacity with entangled states is equal to 0.82+/-0.04 per a photon pair, and it exceeds approximately 2.5 times the theoretical upper limit when no quantum correlations are allowed.

EVA/ORU model architecture using RAMCOST

NASA Technical Reports Server (NTRS)

Ntuen, Celestine A.; Park, Eui H.; Wang, Y. M.; Bretoi, R.

1990-01-01

A parametrically driven simulation model is presented in order to provide a detailed insight into the effects of various input parameters in the life testing of a modular space suit. The RAMCOST model employed is a user-oriented simulation model for studying the life-cycle costs of designs under conditions of uncertainty. The results obtained from the EVA simulated model are used to assess various mission life testing parameters such as the number of joint motions per EVA cycle time, part availability, and number of inspection requirements. RAMCOST first simulates EVA completion for NASA application using a probabilistic like PERT network. With the mission time heuristically determined, RAMCOST then models different orbital replacement unit policies with special application to the astronaut's space suit functional designs.

Emphasis of spatial cues in the temporal fine structure during the rising segments of amplitude-modulated sounds

PubMed Central

Dietz, Mathias; Marquardt, Torsten; Salminen, Nelli H.; McAlpine, David

2013-01-01

The ability to locate the direction of a target sound in a background of competing sources is critical to the survival of many species and important for human communication. Nevertheless, brain mechanisms that provide for such accurate localization abilities remain poorly understood. In particular, it remains unclear how the auditory brain is able to extract reliable spatial information directly from the source when competing sounds and reflections dominate all but the earliest moments of the sound wave reaching each ear. We developed a stimulus mimicking the mutual relationship of sound amplitude and binaural cues, characteristic to reverberant speech. This stimulus, named amplitude modulated binaural beat, allows for a parametric and isolated change of modulation frequency and phase relations. Employing magnetoencephalography and psychoacoustics it is demonstrated that the auditory brain uses binaural information in the stimulus fine structure only during the rising portion of each modulation cycle, rendering spatial information recoverable in an otherwise unlocalizable sound. The data suggest that amplitude modulation provides a means of “glimpsing” low-frequency spatial cues in a manner that benefits listening in noisy or reverberant environments. PMID:23980161

Machine learning patterns for neuroimaging-genetic studies in the cloud.

PubMed

Da Mota, Benoit; Tudoran, Radu; Costan, Alexandru; Varoquaux, Gaël; Brasche, Goetz; Conrod, Patricia; Lemaitre, Herve; Paus, Tomas; Rietschel, Marcella; Frouin, Vincent; Poline, Jean-Baptiste; Antoniu, Gabriel; Thirion, Bertrand

2014-01-01

Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines.

Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

Exploiting Complexity Information for Brain Activation Detection

PubMed Central

Zhang, Yan; Liang, Jiali; Lin, Qiang; Hu, Zhenghui

2016-01-01

We present a complexity-based approach for the analysis of fMRI time series, in which sample entropy (SampEn) is introduced as a quantification of the voxel complexity. Under this hypothesis the voxel complexity could be modulated in pertinent cognitive tasks, and it changes through experimental paradigms. We calculate the complexity of sequential fMRI data for each voxel in two distinct experimental paradigms and use a nonparametric statistical strategy, the Wilcoxon signed rank test, to evaluate the difference in complexity between them. The results are compared with the well known general linear model based Statistical Parametric Mapping package (SPM12), where a decided difference has been observed. This is because SampEn method detects brain complexity changes in two experiments of different conditions and the data-driven method SampEn evaluates just the complexity of specific sequential fMRI data. Also, the larger and smaller SampEn values correspond to different meanings, and the neutral-blank design produces higher predictability than threat-neutral. Complexity information can be considered as a complementary method to the existing fMRI analysis strategies, and it may help improving the understanding of human brain functions from a different perspective. PMID:27045838

VRT (verbal reasoning test): a new test for assessment of verbal reasoning. Test realization and Italian normative data from a multicentric study.

PubMed

Basagni, Benedetta; Luzzatti, Claudio; Navarrete, Eduardo; Caputo, Marina; Scrocco, Gessica; Damora, Alessio; Giunchi, Laura; Gemignani, Paola; Caiazzo, Annarita; Gambini, Maria Grazia; Avesani, Renato; Mancuso, Mauro; Trojano, Luigi; De Tanti, Antonio

2017-04-01

Verbal reasoning is a complex, multicomponent function, which involves activation of functional processes and neural circuits distributed in both brain hemispheres. Thus, this ability is often impaired after brain injury. The aim of the present study is to describe the construction of a new verbal reasoning test (VRT) for patients with brain injury and to provide normative values in a sample of healthy Italian participants. Three hundred and eighty healthy Italian subjects (193 women and 187 men) of different ages (range 16-75 years) and educational level (primary school to postgraduate degree) underwent the VRT. VRT is composed of seven subtests, investigating seven different domains. Multiple linear regression analysis revealed a significant effect of age and education on the participants' performance in terms of both VRT total score and all seven subtest scores. No gender effect was found. A correction grid for raw scores was built from the linear equation derived from the scores. Inferential cut-off scores were estimated using a non-parametric technique, and equivalent scores were computed. We also provided a grid for the correction of results by z scores.

A Scalable Framework For Segmenting Magnetic Resonance Images

PubMed Central

Hore, Prodip; Goldgof, Dmitry B.; Gu, Yuhua; Maudsley, Andrew A.; Darkazanli, Ammar

2009-01-01

A fast, accurate and fully automatic method of segmenting magnetic resonance images of the human brain is introduced. The approach scales well allowing fast segmentations of fine resolution images. The approach is based on modifications of the soft clustering algorithm, fuzzy c-means, that enable it to scale to large data sets. Two types of modifications to create incremental versions of fuzzy c-means are discussed. They are much faster when compared to fuzzy c-means for medium to extremely large data sets because they work on successive subsets of the data. They are comparable in quality to application of fuzzy c-means to all of the data. The clustering algorithms coupled with inhomogeneity correction and smoothing are used to create a framework for automatically segmenting magnetic resonance images of the human brain. The framework is applied to a set of normal human brain volumes acquired from different magnetic resonance scanners using different head coils, acquisition parameters and field strengths. Results are compared to those from two widely used magnetic resonance image segmentation programs, Statistical Parametric Mapping and the FMRIB Software Library (FSL). The results are comparable to FSL while providing significant speed-up and better scalability to larger volumes of data. PMID:20046893

Exploring DeepMedic for the purpose of segmenting white matter hyperintensity lesions

NASA Astrophysics Data System (ADS)

Lippert, Fiona; Cheng, Bastian; Golsari, Amir; Weiler, Florian; Gregori, Johannes; Thomalla, Götz; Klein, Jan

2018-02-01

DeepMedic, an open source software library based on a multi-channel multi-resolution 3D convolutional neural network, has recently been made publicly available for brain lesion segmentations. It has already been shown that segmentation tasks on MRI data of patients having traumatic brain injuries, brain tumors, and ischemic stroke lesions can be performed very well. In this paper we describe how it can efficiently be used for the purpose of detecting and segmenting white matter hyperintensity lesions. We examined if it can be applied to single-channel routine 2D FLAIR data. For evaluation, we annotated 197 datasets with different numbers and sizes of white matter hyperintensity lesions. Our experiments have shown that substantial results with respect to the segmentation quality can be achieved. Compared to the original parametrization of the DeepMedic neural network, the timings for training can be drastically reduced if adjusting corresponding training parameters, while at the same time the Dice coefficients remain nearly unchanged. This enables for performing a whole training process within a single day utilizing a NVIDIA GeForce GTX 580 graphics board which makes this library also very interesting for research purposes on low-end GPU hardware.

Anatomy-guided joint tissue segmentation and topological correction for 6-month infant brain MRI with risk of autism.

PubMed

Wang, Li; Li, Gang; Adeli, Ehsan; Liu, Mingxia; Wu, Zhengwang; Meng, Yu; Lin, Weili; Shen, Dinggang

2018-06-01

Tissue segmentation of infant brain MRIs with risk of autism is critically important for characterizing early brain development and identifying biomarkers. However, it is challenging due to low tissue contrast caused by inherent ongoing myelination and maturation. In particular, at around 6 months of age, the voxel intensities in both gray matter and white matter are within similar ranges, thus leading to the lowest image contrast in the first postnatal year. Previous studies typically employed intensity images and tentatively estimated tissue probabilities to train a sequence of classifiers for tissue segmentation. However, the important prior knowledge of brain anatomy is largely ignored during the segmentation. Consequently, the segmentation accuracy is still limited and topological errors frequently exist, which will significantly degrade the performance of subsequent analyses. Although topological errors could be partially handled by retrospective topological correction methods, their results may still be anatomically incorrect. To address these challenges, in this article, we propose an anatomy-guided joint tissue segmentation and topological correction framework for isointense infant MRI. Particularly, we adopt a signed distance map with respect to the outer cortical surface as anatomical prior knowledge, and incorporate such prior information into the proposed framework to guide segmentation in ambiguous regions. Experimental results on the subjects acquired from National Database for Autism Research demonstrate the effectiveness to topological errors and also some levels of robustness to motion. Comparisons with the state-of-the-art methods further demonstrate the advantages of the proposed method in terms of both segmentation accuracy and topological correctness. © 2018 Wiley Periodicals, Inc.

A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.

PubMed

Sui, Jing; Adali, Tülay; Pearlson, Godfrey; Yang, Honghui; Sponheim, Scott R; White, Tonya; Calhoun, Vince D

2010-05-15

Collection of multiple-task brain imaging data from the same subject has now become common practice in medical imaging studies. In this paper, we propose a simple yet effective model, "CCA+ICA", as a powerful tool for multi-task data fusion. This joint blind source separation (BSS) model takes advantage of two multivariate methods: canonical correlation analysis and independent component analysis, to achieve both high estimation accuracy and to provide the correct connection between two datasets in which sources can have either common or distinct between-dataset correlation. In both simulated and real fMRI applications, we compare the proposed scheme with other joint BSS models and examine the different modeling assumptions. The contrast images of two tasks: sensorimotor (SM) and Sternberg working memory (SB), derived from a general linear model (GLM), were chosen to contribute real multi-task fMRI data, both of which were collected from 50 schizophrenia patients and 50 healthy controls. When examining the relationship with duration of illness, CCA+ICA revealed a significant negative correlation with temporal lobe activation. Furthermore, CCA+ICA located sensorimotor cortex as the group-discriminative regions for both tasks and identified the superior temporal gyrus in SM and prefrontal cortex in SB as task-specific group-discriminative brain networks. In summary, we compared the new approach to some competitive methods with different assumptions, and found consistent results regarding each of their hypotheses on connecting the two tasks. Such an approach fills a gap in existing multivariate methods for identifying biomarkers from brain imaging data.

Development of structure and function in the infant brain: Implications for cognition, language and social behaviour

PubMed Central

Paterson, Sarah J.; Heim, Sabine; Friedman, Jennifer Thomas; Choudhury, Naseem; Benasich, April A.

2007-01-01

Recent advances in cognitive neuroscience have allowed us to begin investigating the development of both structure and function in the infant brain. However, despite the rapid evolution of technology, surprisingly few studies have examined the intersection between brain and behaviour over the first years of life. Even fewer have done so in the context of a particular research question. This paper aims to provide an overview of four domains that have been studied using techniques amenable to elucidating the brain/behaviour interface: language, face processing, object permanence, and joint attention, with particular emphasis on studies focusing on early development. The importance of the unique role of development and the interplay between structure and function is stressed throughout. It is hoped that this review will serve as a catalyst for further thinking about the substantial gaps in our understanding of the relationship between brain and behaviour across development. Further, our aim is to provide ideas about candidate brain areas that are likely to be implicated in particular behaviours or cognitive domains. PMID:16890291

Hyperpolarized 13C pyruvate mouse brain metabolism with absorptive-mode EPSI at 1 T

NASA Astrophysics Data System (ADS)

Miloushev, Vesselin Z.; Di Gialleonardo, Valentina; Salamanca-Cardona, Lucia; Correa, Fabian; Granlund, Kristin L.; Keshari, Kayvan R.

2017-02-01

The expected signal in echo-planar spectroscopic imaging experiments was explicitly modeled jointly in spatial and spectral dimensions. Using this as a basis, absorptive-mode type detection can be achieved by appropriate choice of spectral delays and post-processing techniques. We discuss the effects of gradient imperfections and demonstrate the implementation of this sequence at low field (1.05 T), with application to hyperpolarized [1-13C] pyruvate imaging of the mouse brain. The sequence achieves sufficient signal-to-noise to monitor the conversion of hyperpolarized [1-13C] pyruvate to lactate in the mouse brain. Hyperpolarized pyruvate imaging of mouse brain metabolism using an absorptive-mode EPSI sequence can be applied to more sophisticated murine disease and treatment models. The simple modifications presented in this work, which permit absorptive-mode detection, are directly translatable to human clinical imaging and generate improved absorptive-mode spectra without the need for refocusing pulses.

When instructions fail. The effects of stimulus control training on brain injury survivors' attending and reporting during hearing screenings.

PubMed

Schlund, M W

2000-10-01

Bedside hearing screenings are routinely conducted by speech and language pathologists for brain injury survivors during rehabilitation. Cognitive deficits resulting from brain injury, however, may interfere with obtaining estimates of auditory thresholds. Poor comprehension or attention deficits often compromise patient abilities to follow procedural instructions. This article describes the effects of jointly applying behavioral methods and psychophysical methods to improve two severely brain-injured survivors' attending and reporting on auditory test stimuli presentation. Treatment consisted of stimulus control training that involved differentially reinforcing responding in the presence and absence of an auditory test tone. Subsequent hearing screenings were conducted with novel auditory test tones and a common titration procedure. Results showed that prior stimulus control training improved attending and reporting such that hearing screenings were conducted and estimates of auditory thresholds were obtained.

The application of integrated knowledge-based systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

NASA Technical Reports Server (NTRS)

Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris

1992-01-01

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through BRAIN, an integrated network of both human and computer elements. BRAIN will function as an advisor to mission managers by assessing the risk of inflight biomedical problems and recommending appropriate countermeasures. Described here is a joint effort among various NASA elements to develop BRAIN and the Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of knowledge acquisition, integration of IDRA components, the use of expert systems to automate the biomedical prediction process, development of a user friendly interface, and integration of IDRA and ExerCISys systems. Because C language, CLIPS and the X-Window System are portable and easily integrated, they were chosen ss the tools for the initial IDRA prototype.

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM). Contrast-enhanced MRI (CE-MRI) targets enhancing core (ENH) but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT), despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML) algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM. We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei) for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set. We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients). The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients). Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

Atlantoaxial Joint Distraction with a New Expandable Device for the Treatment of Basilar Invagination with Preservation of the C2 Nerve Root: A Cadaveric Anatomical Study.

PubMed

Polli, Filippo Maria; Trungu, Sokol; Miscusi, Massimo; Forcato, Stefano; Visocchi, Massimiliano; Raco, Antonino

2017-01-01

Atlantoaxial joint distraction has been advocated for the decompression of the brain stem in patients affected by basilar invagination, avoiding direct transoral decompression. This technique requires C2 ganglion resection and it is often impossible to perform due to the peculiar bony anatomy. We describe a cadaveric anatomical study supporting the feasibility of C1-C2 distraction performed with an expandable device, allowing easier insertion of the tool and preservation of the C2 nerve root. In five adult cadaveric specimens, posterior atlantoaxial surgical exposure was performed and an expandable system was inserted within the C1-C2 joint. The expansion of the device, leading to active distraction of the joint space, together with all the surgical steps of the technique was recorded with anatomical pictures and the final results were checked with a computed tomography (CT) scan. Insertion of the device was easily performed in all cases without anatomical conflict with the C2 ganglion; CT scans confirmed the distraction of the C1-C2 joint. This cadaveric anatomical study confirms the feasibility of the introduction of an expandable and flexible device within the C1-C2 joint, allowing it's distraction and preservation of the C2 ganglion.

Joint association discovery and diagnosis of Alzheimer's disease by supervised heterogeneous multiview learning.

PubMed

Zhe, Shandian; Xu, Zenglin; Qi, Yuan; Yu, Peng

2014-01-01

A key step for Alzheimer's disease (AD) study is to identify associations between genetic variations and intermediate phenotypes (e.g., brain structures). At the same time, it is crucial to develop a noninvasive means for AD diagnosis. Although these two tasks-association discovery and disease diagnosis-have been treated separately by a variety of approaches, they are tightly coupled due to their common biological basis. We hypothesize that the two tasks can potentially benefit each other by a joint analysis, because (i) the association study discovers correlated biomarkers from different data sources, which may help improve diagnosis accuracy, and (ii) the disease status may help identify disease-sensitive associations between genetic variations and MRI features. Based on this hypothesis, we present a new sparse Bayesian approach for joint association study and disease diagnosis. In this approach, common latent features are extracted from different data sources based on sparse projection matrices and used to predict multiple disease severity levels based on Gaussian process ordinal regression; in return, the disease status is used to guide the discovery of relationships between the data sources. The sparse projection matrices not only reveal the associations but also select groups of biomarkers related to AD. To learn the model from data, we develop an efficient variational expectation maximization algorithm. Simulation results demonstrate that our approach achieves higher accuracy in both predicting ordinal labels and discovering associations between data sources than alternative methods. We apply our approach to an imaging genetics dataset of AD. Our joint analysis approach not only identifies meaningful and interesting associations between genetic variations, brain structures, and AD status, but also achieves significantly higher accuracy for predicting ordinal AD stages than the competing methods.

Bayesian deconvolution of [corrected] fMRI data using bilinear dynamical systems.

PubMed

Makni, Salima; Beckmann, Christian; Smith, Steve; Woolrich, Mark

2008-10-01

In Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993], a particular case of the Linear Dynamical Systems (LDSs) was used to model the dynamic behavior of the BOLD response in functional MRI. This state-space model, called bilinear dynamical system (BDS), is used to deconvolve the fMRI time series in order to estimate the neuronal response induced by the different stimuli of the experimental paradigm. The BDS model parameters are estimated using an expectation-maximization (EM) algorithm proposed by Ghahramani and Hinton [Ghahramani, Z., Hinton, G.E. 1996. Parameter Estimation for Linear Dynamical Systems. Technical Report, Department of Computer Science, University of Toronto]. In this paper we introduce modifications to the BDS model in order to explicitly model the spatial variations of the haemodynamic response function (HRF) in the brain using a non-parametric approach. While in Penny et al. [Penny, W., Ghahramani, Z., Friston, K.J. 2005. Bilinear dynamical systems. Philos. Trans. R. Soc. Lond. B Biol. Sci. 360(1457) 983-993] the relationship between neuronal activation and fMRI signals is formulated as a first-order convolution with a kernel expansion using basis functions (typically two or three), in this paper, we argue in favor of a spatially adaptive GLM in which a local non-parametric estimation of the HRF is performed. Furthermore, in order to overcome the overfitting problem typically associated with simple EM estimates, we propose a full Variational Bayes (VB) solution to infer the BDS model parameters. We demonstrate the usefulness of our model which is able to estimate both the neuronal activity and the haemodynamic response function in every voxel of the brain. We first examine the behavior of this approach when applied to simulated data with different temporal and noise features. As an example we will show how this method can be used to improve interpretability of estimates from an independent component analysis (ICA) analysis of fMRI data. We finally demonstrate its use on real fMRI data in one slice of the brain.

Attenuation of cue-induced smoking urges and brain reward activity in smokers treated successfully with bupropion.

PubMed

Weinstein, A; Greif, J; Yemini, Z; Lerman, H; Weizman, A; Even-Sapir, E

2010-06-01

Twenty-two regular smokers (15+ cigarettes per day) were treated with bupropion and group therapy for 2 months. Subjects underwent positron emission tomography (PET) studies using measures of brain global and regional glucose metabolism (regional cerebral metabolic rates of glucose [rCMRglc]) with [18F]-Fluorodeoxyglucose (FDG) twice, after watching a videotape showing smoking scenes and after watching a control movie in counter-balanced order. A questionnaire of smoking urges (QSU) was filled in before and after watching both the movies. Changes in brain metabolic rates of FDG were analysed using Statistical Parametric Maps (SPM 2) in 11 smokers who abstained from smoking in comparison with 11 smokers who continued to smoke during the second month of treatment. Still-smokers had higher craving scores after watching the videotape showing smoking scenes compared with non-smokers. Second, watching the videotape showing smoking scenes compared with the control videotape in still-smokers resulted in increased metabolic rates in the striatum, thalamus and midbrain. Third, the ratings of the urge to smoke cigarettes while watching the videotape showing smoking scenes in still-smokers were associated with brain metabolic activity in the ventral striatum, anterior cingulate, orbitofrontal cortex, middle temporal lobe, hippocampus, insula, midbrain and thalamus. In conclusion, successfully treated smokers showed attenuated craving and reduced activity in the mesolimbic reward circuit.

Parametric analysis of the biomechanical response of head subjected to the primary blast loading--a data mining approach.

PubMed

Zhu, Feng; Kalra, Anil; Saif, Tal; Yang, Zaihan; Yang, King H; King, Albert I

2016-01-01

Traumatic brain injury due to primary blast loading has become a signature injury in recent military conflicts and terrorist activities. Extensive experimental and computational investigations have been conducted to study the interrelationships between intracranial pressure response and intrinsic or 'input' parameters such as the head geometry and loading conditions. However, these relationships are very complicated and are usually implicit and 'hidden' in a large amount of simulation/test data. In this study, a data mining method is proposed to explore such underlying information from the numerical simulation results. The heads of different species are described as a highly simplified two-part (skull and brain) finite element model with varying geometric parameters. The parameters considered include peak incident pressure, skull thickness, brain radius and snout length. Their interrelationship and coupling effect are discovered by developing a decision tree based on the large simulation data-set. The results show that the proposed data-driven method is superior to the conventional linear regression method and is comparable to the nonlinear regression method. Considering its capability of exploring implicit information and the relatively simple relationships between response and input variables, the data mining method is considered to be a good tool for an in-depth understanding of the mechanisms of blast-induced brain injury. As a general method, this approach can also be applied to other nonlinear complex biomechanical systems.

Lesion registration for longitudinal disease tracking in an imaging informatics-based multiple sclerosis eFolder

NASA Astrophysics Data System (ADS)

Ma, Kevin; Liu, Joseph; Zhang, Xuejun; Lerner, Alex; Shiroishi, Mark; Amezcua, Lilyana; Liu, Brent

2016-03-01

We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results stored in DICOM-SR format. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system needs to quantify lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. In order to perform lesion registration, we have developed a brain warping and normalizing methodology using Statistical Parametric Mapping (SPM) MATLAB toolkit for brain MRI. Patients' brain MR images are processed via SPM's normalization processes, and the brain images are analyzed and warped according to the tissue probability map. Lesion identification and contouring are completed by neuroradiologists, and lesion volume quantification is completed by the eFolder's CAD program. Lesion comparison results in longitudinal studies show key growth and active regions. The results display successful lesion registration and tracking over a longitudinal study. Lesion change results are graphically represented in the web-based user interface, and users are able to correlate patient progress and changes in the MRI images. The completed lesion and disease tracking tool would enable the eFolder to provide complete patient profiles, improve the efficiency of patient care, and perform comprehensive data analysis through an integrated imaging informatics system.

Cerebellar contribution to motor and cognitive performance in multiple sclerosis: An MRI sub-regional volumetric analysis.

PubMed

D'Ambrosio, Alessandro; Pagani, Elisabetta; Riccitelli, Gianna C; Colombo, Bruno; Rodegher, Mariaemma; Falini, Andrea; Comi, Giancarlo; Filippi, Massimo; Rocca, Maria A

2017-08-01

To investigate the role of cerebellar sub-regions on motor and cognitive performance in multiple sclerosis (MS) patients. Whole and sub-regional cerebellar volumes, brain volumes, T2 hyperintense lesion volumes (LV), and motor performance scores were obtained from 95 relapse-onset MS patients and 32 healthy controls (HC). MS patients also underwent an evaluation of working memory and processing speed functions. Cerebellar anterior and posterior lobes were segmented using the Spatially Unbiased Infratentorial Toolbox (SUIT) from Statistical Parametric Mapping (SPM12). Multivariate linear regression models assessed the relationship between magnetic resonance imaging (MRI) measures and motor/cognitive scores. Compared to HC, only secondary progressive multiple sclerosis (SPMS) patients had lower cerebellar volumes (total and posterior cerebellum). In MS patients, lower anterior cerebellar volume and brain T2 LV predicted worse motor performance, whereas lower posterior cerebellar volume and brain T2 LV predicted poor cognitive performance. Global measures of brain volume and infratentorial T2 LV were not selected by the final multivariate models. Cerebellar volumetric abnormalities are likely to play an important contribution to explain motor and cognitive performance in MS patients. Consistently with functional mapping studies, cerebellar posterior-inferior volume accounted for variance in cognitive measures, whereas anterior cerebellar volume accounted for variance in motor performance, supporting the assessment of cerebellar damage at sub-regional level.

Brain activity related to phonation in young patients with adductor spasmodic dysphonia.

PubMed

Kiyuna, Asanori; Maeda, Hiroyuki; Higa, Asano; Shingaki, Kouta; Uehara, Takayuki; Suzuki, Mikio

2014-06-01

This study investigated the brain activities during phonation of young patients with adductor spasmodic dysphonia (ADSD) of relatively short disease duration (<10 years). Six subjects with ADSD of short duration (mean age: 24. 3 years; mean disease duration: 41 months) and six healthy controls (mean age: 30.8 years) underwent functional magnetic resonance imaging (fMRI) using a sparse sampling method to identify brain activity during vowel phonation (/i:/). Intragroup and intergroup analyses were performed using statistical parametric mapping software. Areas of activation in the ADSD and control groups were similar to those reported previously for vowel phonation. All of the activated areas were observed bilaterally and symmetrically. Intergroup analysis revealed higher brain activities in the SD group in the auditory-related areas (Brodmann's areas [BA] 40, 41), motor speech areas (BA44, 45), bilateral insula (BA13), bilateral cerebellum, and middle frontal gyrus (BA46). Areas with lower activation were in the left primary sensory area (BA1-3) and bilateral subcortical nucleus (putamen and globus pallidus). The auditory cortical responses observed may reflect that young ADSD patients control their voice by use of the motor speech area, insula, inferior parietal cortex, and cerebellum. Neural activity in the primary sensory area and basal ganglia may affect the voice symptoms of young ADSD patients with short disease duration. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.