Phases of five-dimensional theories, monopole walls, and melting crystals

NASA Astrophysics Data System (ADS)

Cherkis, Sergey A.

2014-06-01

Moduli spaces of doubly periodic monopoles, also called monopole walls or monowalls, are hyperkähler; thus, when four-dimensional, they are self-dual gravitational instantons. We find all monowalls with lowest number of moduli. Their moduli spaces can be identified, on the one hand, with Coulomb branches of five-dimensional supersymmetric quantum field theories on 3 × T 2 and, on the other hand, with moduli spaces of local Calabi-Yau metrics on the canonical bundle of a del Pezzo surface. We explore the asymptotic metric of these moduli spaces and compare our results with Seiberg's low energy description of the five-dimensional quantum theories. We also give a natural description of the phase structure of general monowall moduli spaces in terms of triangulations of Newton polygons, secondary polyhedra, and associahedral projections of secondary fans.

Experimental Evidence for Improved Neuroimaging Interpretation Using Three-Dimensional Graphic Models

ERIC Educational Resources Information Center

Ruisoto, Pablo; Juanes, Juan Antonio; Contador, Israel; Mayoral, Paula; Prats-Galino, Alberto

2012-01-01

Three-dimensional (3D) or volumetric visualization is a useful resource for learning about the anatomy of the human brain. However, the effectiveness of 3D spatial visualization has not yet been assessed systematically. This report analyzes whether 3D volumetric visualization helps learners to identify and locate subcortical structures more…

Detailed spatiotemporal brain mapping of chromatic vision combining high-resolution VEP with fMRI and retinotopy.

PubMed

Pitzalis, Sabrina; Strappini, Francesca; Bultrini, Alessandro; Di Russo, Francesco

2018-03-13

Neuroimaging studies have identified so far, several color-sensitive visual areas in the human brain, and the temporal dynamics of these activities have been separately investigated using the visual-evoked potentials (VEPs). In the present study, we combined electrophysiological and neuroimaging methods to determine a detailed spatiotemporal profile of chromatic VEP and to localize its neural generators. The accuracy of the present co-registration study was obtained by combining standard fMRI data with retinotopic and motion mapping data at the individual level. We found a sequence of occipito activities more complex than that typically reported for chromatic VEPs, including feed-forward and reentrant feedback. Results showed that chromatic human perception arises by the combined activity of at the least five parieto-occipital areas including V1, LOC, V8/VO, and the motion-sensitive dorsal region MT+. However, the contribution of V1 and V8/VO seems dominant because the re-entrant activity in these areas was present more than once (twice in V8/VO and thrice in V1). This feedforward and feedback chromatic processing appears delayed compared with the luminance processing. Associating VEPs and neuroimaging measures, we showed for the first time a complex spatiotemporal pattern of activity, confirming that chromatic stimuli produce intricate interactions of many different brain dorsal and ventral areas. © 2018 Wiley Periodicals, Inc.

Multimodal neuroimaging in presurgical evaluation of drug-resistant epilepsy☆

PubMed Central

Zhang, Jing; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Mei, Shanshan; Liu, Qingzhu; Li, Yunlin

2013-01-01

Intracranial EEG (icEEG) monitoring is critical in epilepsy surgical planning, but it has limitations. The advances of neuroimaging have made it possible to reveal epileptic abnormalities that could not be identified previously and improve the localization of the seizure focus and the vital cortex. A frequently asked question in the field is whether non-invasive neuroimaging could replace invasive icEEG or reduce the need for icEEG in presurgical evaluation. This review considers promising neuroimaging techniques in epilepsy presurgical assessment in order to address this question. In addition, due to large variations in the accuracies of neuroimaging across epilepsy centers, multicenter neuroimaging studies are reviewed, and there is much need for randomized controlled trials (RCTs) to better reveal the utility of presurgical neuroimaging. The results of multiple studies indicate that non-invasive neuroimaging could not replace invasive icEEG in surgical planning especially in non-lesional or extratemporal lobe epilepsies, but it could reduce the need for icEEG in certain cases. With technical advances, multimodal neuroimaging may play a greater role in presurgical evaluation to reduce the costs and risks of epilepsy surgery, and provide surgical options for more patients with drug-resistant epilepsy. PMID:24282678

Neuroinformatics challenges to the structural, connectomic, functional and electrophysiological multimodal imaging of human traumatic brain injury

PubMed Central

Goh, S. Y. Matthew; Irimia, Andrei; Torgerson, Carinna M.; Horn, John D. Van

2014-01-01

Throughout the past few decades, the ability to treat and rehabilitate traumatic brain injury (TBI) patients has become critically reliant upon the use of neuroimaging to acquire adequate knowledge of injury-related effects upon brain function and recovery. As a result, the need for TBI neuroimaging analysis methods has increased in recent years due to the recognition that spatiotemporal computational analyses of TBI evolution are useful for capturing the effects of TBI dynamics. At the same time, however, the advent of such methods has brought about the need to analyze, manage, and integrate TBI neuroimaging data using informatically inspired approaches which can take full advantage of their large dimensionality and informational complexity. Given this perspective, we here discuss the neuroinformatics challenges for TBI neuroimaging analysis in the context of structural, connectivity, and functional paradigms. Within each of these, the availability of a wide range of neuroimaging modalities can be leveraged to fully understand the heterogeneity of TBI pathology; consequently, large-scale computer hardware resources and next-generation processing software are often required for efficient data storage, management, and analysis of TBI neuroimaging data. However, each of these paradigms poses challenges in the context of informatics such that the ability to address them is critical for augmenting current capabilities to perform neuroimaging analysis of TBI and to improve therapeutic efficacy. PMID:24616696

The search for the number form area: A functional neuroimaging meta-analysis.

PubMed

Yeo, Darren J; Wilkey, Eric D; Price, Gavin R

2017-07-01

Recent studies report a putative "number form area" (NFA) in the inferior temporal gyrus (ITG) suggested to be specialized for Arabic numeral processing. However, a number of earlier studies report no such NFA. The reasons for such discrepancies across studies are unclear. To examine evidence for a convergent NFA across studies, we conducted two activation likelihood estimation meta-analyses on 31 and a subset of 20 neuroimaging studies that have contrasted digits with other meaningful symbols. Results suggest the potential existence of an NFA in the right ITG, in addition to a 'symbolic number processing network' comprising bilateral parietal regions, and right-lateralized superior and inferior frontal regions. Critically, convergent localization for the NFA was only evident when contrasts were appropriately controlled for task demands, and does not appear to depend on employing methods designed to overcome fMRI signal dropout in the ITG. Importantly, only five studies had foci within the identified ITG NFA cluster boundary, indicating that more empirical evidence is necessary to determine the true functional specialization and regional specificity of the putative NFA. Copyright © 2017 Elsevier Ltd. All rights reserved.

iELVis: An open source MATLAB toolbox for localizing and visualizing human intracranial electrode data.

PubMed

Groppe, David M; Bickel, Stephan; Dykstra, Andrew R; Wang, Xiuyuan; Mégevand, Pierre; Mercier, Manuel R; Lado, Fred A; Mehta, Ashesh D; Honey, Christopher J

2017-04-01

Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive. iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg. Copyright © 2017 Elsevier B.V. All rights reserved.

Mapping a multidimensional emotion in response to television commercials.

PubMed

Morris, Jon D; Klahr, Nelson J; Shen, Feng; Villegas, Jorge; Wright, Paul; He, Guojun; Liu, Yijun

2009-03-01

Unlike previous emotional studies using functional neuroimaging that have focused on either locating discrete emotions in the brain or linking emotional response to an external behavior, this study investigated brain regions in order to validate a three-dimensional construct--namely pleasure, arousal, and dominance (PAD) of emotion induced by marketing communication. Emotional responses to five television commercials were measured with Advertisement Self-Assessment Manikins (AdSAM) for PAD and with functional magnetic resonance imaging (fMRI) to identify corresponding patterns of brain activation. We found significant differences in the AdSAM scores on the pleasure and arousal rating scales among the stimuli. Using the AdSAM response as a model for the fMRI image analysis, we showed bilateral activations in the inferior frontal gyri and middle temporal gyri associated with the difference on the pleasure dimension, and activations in the right superior temporal gyrus and right middle frontal gyrus associated with the difference on the arousal dimension. These findings suggest a dimensional approach of constructing emotional changes in the brain and provide a better understanding of human behavior in response to advertising stimuli.

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis

PubMed Central

2011-01-01

Background A variety of neuroimaging software packages have been released from various laboratories worldwide, and many researchers use these packages in combination. Though most of these software packages are freely available, some people find them difficult to install and configure because they are mostly based on UNIX-like operating systems. We developed a live USB-bootable Linux package named "Lin4Neuro." This system includes popular neuroimaging analysis tools. The user interface is customized so that even Windows users can use it intuitively. Results The boot time of this system was only around 40 seconds. We performed a benchmark test of inhomogeneity correction on 10 subjects of three-dimensional T1-weighted MRI scans. The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive. We also installed Lin4Neuro on a virtualization software package that emulates the Linux environment on a Windows-based operation system. Although the processing speed was slower than that under other conditions, it remained comparable. Conclusions With Lin4Neuro in one's hand, one can access neuroimaging software packages easily, and immediately focus on analyzing data. Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis. It also provides a practical means of sharing analysis environments across sites. PMID:21266047

Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis.

PubMed

Nemoto, Kiyotaka; Dan, Ippeita; Rorden, Christopher; Ohnishi, Takashi; Tsuzuki, Daisuke; Okamoto, Masako; Yamashita, Fumio; Asada, Takashi

2011-01-25

A variety of neuroimaging software packages have been released from various laboratories worldwide, and many researchers use these packages in combination. Though most of these software packages are freely available, some people find them difficult to install and configure because they are mostly based on UNIX-like operating systems. We developed a live USB-bootable Linux package named "Lin4Neuro." This system includes popular neuroimaging analysis tools. The user interface is customized so that even Windows users can use it intuitively. The boot time of this system was only around 40 seconds. We performed a benchmark test of inhomogeneity correction on 10 subjects of three-dimensional T1-weighted MRI scans. The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive. We also installed Lin4Neuro on a virtualization software package that emulates the Linux environment on a Windows-based operation system. Although the processing speed was slower than that under other conditions, it remained comparable. With Lin4Neuro in one's hand, one can access neuroimaging software packages easily, and immediately focus on analyzing data. Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis. It also provides a practical means of sharing analysis environments across sites.

Local load-sharing fiber bundle model in higher dimensions.

PubMed

Sinha, Santanu; Kjellstadli, Jonas T; Hansen, Alex

2015-08-01

We consider the local load-sharing fiber bundle model in one to five dimensions. Depending on the breaking threshold distribution of the fibers, there is a transition where the fracture process becomes localized. In the localized phase, the model behaves as the invasion percolation model. The difference between the local load-sharing fiber bundle model and the equal load-sharing fiber bundle model vanishes with increasing dimensionality with the characteristics of a power law.

Pearls: stroke.

PubMed

Wozniak, Marcella A

2010-02-01

The diagnosis of ischemic stroke continues to be a clinical one, although advances in neuroimaging have expanded our understanding of the correlation between clinical symptoms and neuroanatomical localization. Careful neurologic examination allows localization in both neuroanatomical and vascular space. Findings on neuroimaging are then correlated to assess their clinical relevance. Transient ischemic attack is recognized as a warning sign for impending vascular disease, but even less specific transient neurologic symptoms are associated with increased risk. Stroke can occur at any age. For women, the postpartum period is a time of elevated risk for arterial ischemic stroke. (c) Thieme Medical Publishers.

Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?

PubMed

Portugal, Liana C L; Rosa, Maria João; Rao, Anil; Bebko, Genna; Bertocci, Michele A; Hinze, Amanda K; Bonar, Lisa; Almeida, Jorge R C; Perlman, Susan B; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A; Ciuffetelli, Gary; Rodriguez, Eric; Forbes, Erika E; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Arnold, Eugene L; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Pereira, Mirtes; Oliveira, Leticia; Phillips, Mary L; Mourao-Miranda, Janaina

2016-01-01

High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas. The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.

Estimating multivariate similarity between neuroimaging datasets with sparse canonical correlation analysis: an application to perfusion imaging.

PubMed

Rosa, Maria J; Mehta, Mitul A; Pich, Emilio M; Risterucci, Celine; Zelaya, Fernando; Reinders, Antje A T S; Williams, Steve C R; Dazzan, Paola; Doyle, Orla M; Marquand, Andre F

2015-01-01

An increasing number of neuroimaging studies are based on either combining more than one data modality (inter-modal) or combining more than one measurement from the same modality (intra-modal). To date, most intra-modal studies using multivariate statistics have focused on differences between datasets, for instance relying on classifiers to differentiate between effects in the data. However, to fully characterize these effects, multivariate methods able to measure similarities between datasets are needed. One classical technique for estimating the relationship between two datasets is canonical correlation analysis (CCA). However, in the context of high-dimensional data the application of CCA is extremely challenging. A recent extension of CCA, sparse CCA (SCCA), overcomes this limitation, by regularizing the model parameters while yielding a sparse solution. In this work, we modify SCCA with the aim of facilitating its application to high-dimensional neuroimaging data and finding meaningful multivariate image-to-image correspondences in intra-modal studies. In particular, we show how the optimal subset of variables can be estimated independently and we look at the information encoded in more than one set of SCCA transformations. We illustrate our framework using Arterial Spin Labeling data to investigate multivariate similarities between the effects of two antipsychotic drugs on cerebral blood flow.

Cerebral ganglioglioma with epilepsy: neuroimaging features and treatment.

PubMed

Nishio, S; Morioka, T; Mihara, F; Gondo, K; Fukui, M

2001-03-01

Gangliogliomas are an increasingly recognized cause of epilepsy in children. In this study the clinical, neuroimaging, and neurophysiological data of five patients with cerebral ganglioglioma and epilepsy are reviewed retrospectively. The average age of these patients was 4.4 years at onset and the average duration of seizures before diagnosis was 11 months. Tumors were located in the frontal (3), parietal (1), and occipital (1) lobes. While one cystic and four solid tumors showed various densities on CT and MRI, one frontal lesion was not demonstrated by CT scan but clearly shown by MRI. Scalp electroencephalography (EEG) showed neither localized nor epileptiform abnormalities in three patients, while the remaining two had these abnormalities. In one patient, invasive chronic electrocorticography (ECoG) recordings with subdural electrodes revealed an ictal onset zone located in the hand motor area. In all patients, intraoperative ECoG failed to reveal any epileptiform activities, and tumor removal alone was performed. For a mean of 3.4 years after surgery, all patients are alive and seizure-free, with stable imaging findings. Tumor resection may be the most important factor for optimal seizure control and prevention of tumor recurrence despite the fact that EEG and ECoG findings may conflict on tumor location.

Auditory neuroimaging with fMRI and PET.

PubMed

Talavage, Thomas M; Gonzalez-Castillo, Javier; Scott, Sophie K

2014-01-01

For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. This article is part of a Special Issue entitled Human Auditory Neuroimaging. Copyright © 2013 Elsevier B.V. All rights reserved.

Functional neuroimaging of emotional learning and autonomic reactions.

PubMed

Peper, Martin; Herpers, Martin; Spreer, Joachim; Hennig, Jürgen; Zentner, Josef

2006-06-01

This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.

Neuroimaging Field Methods Using Functional Near Infrared Spectroscopy (NIRS) Neuroimaging to Study Global Child Development: Rural Sub-Saharan Africa.

PubMed

Jasińska, Kaja K; Guei, Sosthène

2018-02-02

Portable neuroimaging approaches provide new advances to the study of brain function and brain development with previously inaccessible populations and in remote locations. This paper shows the development of field functional Near Infrared Spectroscopy (fNIRS) imaging to the study of child language, reading, and cognitive development in a rural village setting of Côte d'Ivoire. Innovation in methods and the development of culturally appropriate neuroimaging protocols allow a first-time look into the brain's development and children's learning outcomes in understudied environments. This paper demonstrates protocols for transporting and setting up a mobile laboratory, discusses considerations for field versus laboratory neuroimaging, and presents a guide for developing neuroimaging consent procedures and building meaningful long-term collaborations with local government and science partners. Portable neuroimaging methods can be used to study complex child development contexts, including the impact of significant poverty and adversity on brain development. The protocol presented here has been developed for use in Côte d'Ivoire, the world's primary source of cocoa, and where reports of child labor in the cocoa sector are common. Yet, little is known about the impact of child labor on brain development and learning. Field neuroimaging methods have the potential to yield new insights into such urgent issues, and the development of children globally.

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Auditory Neuroimaging with fMRI and PET

PubMed Central

Talavage, Thomas M.; Gonzalez-Castillo, Javier; Scott, Sophie K.

2013-01-01

For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. PMID:24076424

Neuroimaging studies of aggressive and violent behavior: current findings and implications for criminology and criminal justice.

PubMed

Bufkin, Jana L; Luttrell, Vickie R

2005-04-01

With the availability of new functional and structural neuroimaging techniques, researchers have begun to localize brain areas that may be dysfunctional in offenders who are aggressive and violent. Our review of 17 neuroimaging studies reveals that the areas associated with aggressive and/or violent behavioral histories, particularly impulsive acts, are located in the prefrontal cortex and the medial temporal regions. These findings are explained in the context of negative emotion regulation, and suggestions are provided concerning how such findings may affect future theoretical frameworks in criminology, crime prevention efforts, and the functioning of the criminal justice system.

Local stability of a five dimensional food chain model in the ocean

NASA Astrophysics Data System (ADS)

Kusumawinahyu, W. M.; Hidayatulloh, M. R.

2014-02-01

This paper discuss a food chain model on a microbiology ecosystem in the ocean, where predation process occurs. Four population growth rates are discussed, namely bacteria, phytoplankton, zooplankton, and protozoa growth rate. When the growth of nutrient density is also considered, the model is governed by a five dimensional dynamical system. The system considered in this paper is a modification of a model proposed by Hadley and Forbes [1], by taking Holling Type I as the functional response. For sake of simplicity, the model needs to be scaled. Dynamical behavior, such as existence condition of equilibrium points and their local stability are addressed. There are eight equilibrium points, where two of them exist under certain conditions. Three equilibrium points are unstable, while two points stable under certain conditions and the other three points are stable if the Ruth-Hurwitz criteria are satisfied. Numerical simulations are carried out to illustrate analytical findings.

How random is the random forest? Random forest algorithm on the service of structural imaging biomarkers for Alzheimer's disease: from Alzheimer's disease neuroimaging initiative (ADNI) database.

PubMed

Dimitriadis, Stavros I; Liparas, Dimitris

2018-06-01

Neuroinformatics is a fascinating research field that applies computational models and analytical tools to high dimensional experimental neuroscience data for a better understanding of how the brain functions or dysfunctions in brain diseases. Neuroinformaticians work in the intersection of neuroscience and informatics supporting the integration of various sub-disciplines (behavioural neuroscience, genetics, cognitive psychology, etc.) working on brain research. Neuroinformaticians are the pathway of information exchange between informaticians and clinicians for a better understanding of the outcome of computational models and the clinical interpretation of the analysis. Machine learning is one of the most significant computational developments in the last decade giving tools to neuroinformaticians and finally to radiologists and clinicians for an automatic and early diagnosis-prognosis of a brain disease. Random forest (RF) algorithm has been successfully applied to high-dimensional neuroimaging data for feature reduction and also has been applied to classify the clinical label of a subject using single or multi-modal neuroimaging datasets. Our aim was to review the studies where RF was applied to correctly predict the Alzheimer's disease (AD), the conversion from mild cognitive impairment (MCI) and its robustness to overfitting, outliers and handling of non-linear data. Finally, we described our RF-based model that gave us the 1 st position in an international challenge for automated prediction of MCI from MRI data.

The clinical value of large neuroimaging data sets in Alzheimer's disease.

PubMed

Toga, Arthur W

2012-02-01

Rapid advances in neuroimaging and cyberinfrastructure technologies have brought explosive growth in the Web-based warehousing, availability, and accessibility of imaging data on a variety of neurodegenerative and neuropsychiatric disorders and conditions. There has been a prolific development and emergence of complex computational infrastructures that serve as repositories of databases and provide critical functionalities such as sophisticated image analysis algorithm pipelines and powerful three-dimensional visualization and statistical tools. The statistical and operational advantages of collaborative, distributed team science in the form of multisite consortia push this approach in a diverse range of population-based investigations. Copyright © 2012 Elsevier Inc. All rights reserved.

Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

PubMed Central

Sweet, Jennifer A.; Pace, Jonathan; Girgis, Fady; Miller, Jonathan P.

2016-01-01

Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS. PMID:27445709

Effect of the degree of disorder on electronic and optical properties in random superlattices

NASA Technical Reports Server (NTRS)

Wang, E. G.; Su, W. P.; Ting, C. S.

1994-01-01

A three-dimensional tight-binding calculation is developed and used to study disorder effects in a realistic random superlattice. With increasing disorder, a tendency of possible indirect-direct band-gap transition is suggested. Direct evidence of mobility edges between localized and extended states in three-dimensional random systems is given. As system disorder increases, the optical absorption intensities increase dramatically from five to forty-five times stronger than the ordered (GaAs)(sub 1)/(AlAs)(sub 1) superlattice. It is believed that the degree of disorder significantly affects electronic and optical properties of GaAs/AlAs random superlattices.

ICA model order selection of task co-activation networks.

PubMed

Ray, Kimberly L; McKay, D Reese; Fox, Peter M; Riedel, Michael C; Uecker, Angela M; Beckmann, Christian F; Smith, Stephen M; Fox, Peter T; Laird, Angela R

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders.

ICA model order selection of task co-activation networks

PubMed Central

Ray, Kimberly L.; McKay, D. Reese; Fox, Peter M.; Riedel, Michael C.; Uecker, Angela M.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.; Laird, Angela R.

2013-01-01

Independent component analysis (ICA) has become a widely used method for extracting functional networks in the brain during rest and task. Historically, preferred ICA dimensionality has widely varied within the neuroimaging community, but typically varies between 20 and 100 components. This can be problematic when comparing results across multiple studies because of the impact ICA dimensionality has on the topology of its resultant components. Recent studies have demonstrated that ICA can be applied to peak activation coordinates archived in a large neuroimaging database (i.e., BrainMap Database) to yield whole-brain task-based co-activation networks. A strength of applying ICA to BrainMap data is that the vast amount of metadata in BrainMap can be used to quantitatively assess tasks and cognitive processes contributing to each component. In this study, we investigated the effect of model order on the distribution of functional properties across networks as a method for identifying the most informative decompositions of BrainMap-based ICA components. Our findings suggest dimensionality of 20 for low model order ICA to examine large-scale brain networks, and dimensionality of 70 to provide insight into how large-scale networks fractionate into sub-networks. We also provide a functional and organizational assessment of visual, motor, emotion, and interoceptive task co-activation networks as they fractionate from low to high model-orders. PMID:24339802

Low-Dimensional Models of "Neuro-Glio-Vascular Unit" for Describing Neural Dynamics under Normal and Energy-Starved Conditions.

PubMed

Chhabria, Karishma; Chakravarthy, V Srinivasa

2016-01-01

The motivation of developing simple minimal models for neuro-glio-vascular (NGV) system arises from a recent modeling study elucidating the bidirectional information flow within the NGV system having 89 dynamic equations (1). While this was one of the first attempts at formulating a comprehensive model for neuro-glio-vascular system, it poses severe restrictions in scaling up to network levels. On the contrary, low--dimensional models are convenient devices in simulating large networks that also provide an intuitive understanding of the complex interactions occurring within the NGV system. The key idea underlying the proposed models is to describe the glio-vascular system as a lumped system, which takes neural firing rate as input and returns an "energy" variable (analogous to ATP) as output. To this end, we present two models: biophysical neuro-energy (Model 1 with five variables), comprising KATP channel activity governed by neuronal ATP dynamics, and the dynamic threshold (Model 2 with three variables), depicting the dependence of neural firing threshold on the ATP dynamics. Both the models show different firing regimes, such as continuous spiking, phasic, and tonic bursting depending on the ATP production coefficient, ɛp, and external current. We then demonstrate that in a network comprising such energy-dependent neuron units, ɛp could modulate the local field potential (LFP) frequency and amplitude. Interestingly, low-frequency LFP dominates under low ɛp conditions, which is thought to be reminiscent of seizure-like activity observed in epilepsy. The proposed "neuron-energy" unit may be implemented in building models of NGV networks to simulate data obtained from multimodal neuroimaging systems, such as functional near infrared spectroscopy coupled to electroencephalogram and functional magnetic resonance imaging coupled to electroencephalogram. Such models could also provide a theoretical basis for devising optimal neurorehabilitation strategies, such as non-invasive brain stimulation for stroke patients.

Gravity and antigravity in a brane world with metastable gravitons

NASA Astrophysics Data System (ADS)

Gregory, R.; Rubakov, V. A.; Sibiryakov, S. M.

2000-09-01

In the framework of a five-dimensional three-brane model with quasi-localized gravitons we evaluate metric perturbations induced on the positive tension brane by matter residing thereon. We find that at intermediate distances, the effective four-dimensional theory coincides, up to small corrections, with General Relativity. This is in accord with Csaki, Erlich and Hollowood and in contrast to Dvali, Gabadadze and Porrati. We show, however, that at ultra-large distances this effective four-dimensional theory becomes dramatically different: conventional tensor gravity changes into scalar anti-gravity.

Neuroimaging findings in pediatric sports-related concussion.

PubMed

Ellis, Michael J; Leiter, Jeff; Hall, Thomas; McDonald, Patrick J; Sawyer, Scott; Silver, Norm; Bunge, Martin; Essig, Marco

2015-09-01

The goal in this review was to summarize the results of clinical neuroimaging studies performed in patients with sports-related concussion (SRC) who were referred to a multidisciplinar ypediatric concussion program. The authors conducted a retrospective review of medical records and neuroimaging findings for all patients referred to a multidisciplinary pediatric concussion program between September 2013 and July 2014. Inclusion criteria were as follows: 1) age ≤ 19 years; and 2) physician-diagnosed SRC. All patients underwent evaluation and follow-up by the same neurosurgeon. The 2 outcomes examined in this review were the frequency of neuroimaging studies performed in this population (including CT and MRI) and the findings of those studies. Clinical indications for neuroimaging and the impact of neuroimaging findings on clinical decision making were summarized where available. This investigation was approved by the local institutional ethics review board. A total of 151 patients (mean age 14 years, 59% female) were included this study. Overall, 36 patients (24%) underwent neuroimaging studies, the results of which were normal in 78% of cases. Sixteen percent of patients underwent CT imaging; results were normal in 79% of cases. Abnormal CT findings included the following: arachnoid cyst (1 patient), skull fracture (2 patients), suspected intracranial hemorrhage (1 patient), and suspected hemorrhage into an arachnoid cyst (1 patient). Eleven percent of patients underwent MRI; results were normal in 75% of cases. Abnormal MRI findings included the following: intraparenchymal hemorrhage and sylvian fissure arachnoid cyst (1 patient); nonhemorrhagic contusion (1 patient); demyelinating disease (1 patient); and posterior fossa arachnoid cyst, cerebellar volume loss, and nonspecific white matter changes (1 patient). Results of clinical neuroimaging studies are normal in the majority of pediatric patients with SRC. However, in selected cases neuroimaging can provide information that impacts decision making about return to play and retirement from the sport.

Prognostic Role of Functional Neuroimaging after Multilobar Resection in Patients with Localization-Related Epilepsy.

PubMed

Cho, Eun Bin; Joo, Eun Yeon; Seo, Dae-Won; Hong, Seung-Chyul; Hong, Seung Bong

2015-01-01

To investigate the usage of functional neuroimaging as a prognostic tool for seizure recurrence and long-term outcomes in patients with multilobar resection, we recruited 90 patients who received multilobar resections between 1995 and 2013 with at least 1-year follow-up (mean 8.0 years). All patients were monitored using intracranial electroencephalography (EEG) after pre-surgical evaluation. Clinical data (demographics, electrophysiology, and neuroimaging) were reviewed retrospectively. Surgical outcomes were evaluated at 1, 2, 5 years after surgery, and at the end of the study. After 1 year, 56 patients (62.2%) became Engel class I and at the last follow-up, 47 patients (52.2%) remained seizure-free. Furthermore, non-localized 18F-fluorodeoxyglucose positron emission tomography (PET), identifying hypometabolic areas not concordant with ictal onset zones, significantly correlated with seizure recurrence after 1 year. Non-lesional magnetic resonance imaging (MRI) and left-sided resection correlated with poor outcomes. In the last follow-up, non-localized PET and left-sided resection significantly correlated with seizure recurrence. Both localized PET and ictal-interictal SPECT subtraction co-registered to MR (SISCOM) predicted good surgical outcomes in the last follow-up (69.2%, Engel I). This study suggests that PET and SISCOM may predict postoperative outcomes for patients after multilobar epilepsy and shows comparable long-term surgical outcomes after multilobar resection.

Characterization of Atrophic Changes in the Cerebral Cortex Using Fractal Dimensional Analysis

PubMed Central

George, Anuh T.; Jeon, Tina; Hynan, Linda S.; Youn, Teddy S.; Kennedy, David N.; Dickerson, Bradford

2010-01-01

The purpose of this project is to apply a modified fractal analysis technique to high-resolution T1 weighted magnetic resonance images in order to quantify the alterations in the shape of the cerebral cortex that occur in patients with Alzheimer’s disease. Images were selected from the Alzheimer’s Disease Neuroimaging Initiative database (Control N=15, Mild-Moderate AD N=15). The images were segmented using a semi-automated analysis program. Four coronal and three axial profiles of the cerebral cortical ribbon were created. The fractal dimensions (Df) of the cortical ribbons were then computed using a box-counting algorithm. The mean Df of the cortical ribbons from AD patients were lower than age-matched controls on six of seven profiles. The fractal measure has regional variability which reflects local differences in brain structure. Fractal dimension is complementary to volumetric measures and may assist in identifying disease state or disease progression. PMID:20740072

Neuromarkers for Mental Disorders: Harnessing Population Neuroscience.

PubMed

Jollans, Lee; Whelan, Robert

2018-01-01

Despite abundant research into the neurobiology of mental disorders, to date neurobiological insights have had very little impact on psychiatric diagnosis or treatment. In this review, we contend that the search for neuroimaging biomarkers-neuromarkers-of mental disorders is a highly promising avenue toward improved psychiatric healthcare. However, many of the traditional tools used for psychiatric neuroimaging are inadequate for the identification of neuromarkers. Specifically, we highlight the need for larger samples and for multivariate analysis. Approaches such as machine learning are likely to be beneficial for interrogating high-dimensional neuroimaging data. We suggest that broad, population-based study designs will be important for developing neuromarkers of mental disorders, and will facilitate a move away from a phenomenological definition of mental disorder categories and toward psychiatric nosology based on biological evidence. We provide an outline of how the development of neuromarkers should occur, emphasizing the need for tests of external and construct validity, and for collaborative research efforts. Finally, we highlight some concerns regarding the development, and use of, neuromarkers in psychiatric healthcare.

A critical appraisal of neuroimaging studies of bipolar disorder: toward a new conceptualization of underlying neural circuitry and roadmap for future research

PubMed Central

Phillips, Mary L; Swartz, Holly A.

2014-01-01

Objective This critical review appraises neuroimaging findings in bipolar disorder in emotion processing, emotion regulation, and reward processing neural circuitry, to synthesize current knowledge of the neural underpinnings of bipolar disorder, and provide a neuroimaging research “roadmap” for future studies. Method We examined findings from all major studies in bipolar disorder that used fMRI, volumetric analyses, diffusion imaging, and resting state techniques, to inform current conceptual models of larger-scale neural circuitry abnormalities in bipolar disorder Results Bipolar disorder can be conceptualized in neural circuitry terms as parallel dysfunction in bilateral prefrontal cortical (especially ventrolateral prefrontal cortical)-hippocampal-amygdala emotion processing and emotion regulation neural circuitries, together with an “overactive” left-sided ventral striatal-ventrolateral and orbitofrontal cortical reward processing circuitry, that result in characteristic behavioral abnormalities associated with bipolar disorder: emotional lability, emotional dysregulation and heightened reward sensitivity. A potential structural basis for these functional abnormalities are gray matter decreases in prefrontal and temporal cortices, amygdala and hippocampus, and fractional anisotropy decreases in white matter tracts connecting prefrontal and subcortical regions. Conclusion Neuroimaging studies of bipolar disorder clearly demonstrate abnormalities in neural circuitries supporting emotion processing, emotion regulation and reward processing, although there are several limitations to these studies. Future neuroimaging research in bipolar disorder should include studies adopting dimensional approaches; larger studies examining neurodevelopmental trajectories in bipolar disorder and at-risk youth; multimodal neuroimaging studies using integrated systems approaches; and studies using pattern recognition approaches to provide clinically useful, individual-level data. Such studies will help identify clinically-relevant biomarkers to guide diagnosis and treatment decision-making for individuals with bipolar disorder. PMID:24626773

Northwestern University Schizophrenia Data and Software Tool (NUSDAST)

PubMed Central

Wang, Lei; Kogan, Alex; Cobia, Derin; Alpert, Kathryn; Kolasny, Anthony; Miller, Michael I.; Marcus, Daniel

2013-01-01

The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data), cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function), clinical (demographic, sibling relationship, SAPS and SANS psychopathology), and genetic (20 polymorphisms) data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions. PMID:24223551

Northwestern University Schizophrenia Data and Software Tool (NUSDAST).

PubMed

Wang, Lei; Kogan, Alex; Cobia, Derin; Alpert, Kathryn; Kolasny, Anthony; Miller, Michael I; Marcus, Daniel

2013-01-01

The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data), cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function), clinical (demographic, sibling relationship, SAPS and SANS psychopathology), and genetic (20 polymorphisms) data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions.

LSAH: a fast and efficient local surface feature for point cloud registration

NASA Astrophysics Data System (ADS)

Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi

2018-04-01

Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.

Functions of the human frontoparietal attention network: Evidence from neuroimaging

PubMed Central

Scolari, Miranda; Seidl-Rathkopf, Katharina N; Kastner, Sabine

2016-01-01

Human frontoparietal cortex has long been implicated as a source of attentional control. However, the mechanistic underpinnings of these control functions have remained elusive due to limitations of neuroimaging techniques that rely on anatomical landmarks to localize patterns of activation. The recent advent of topographic mapping via functional magnetic resonance imaging (fMRI) has allowed the reliable parcellation of the network into 18 independent subregions in individual subjects, thereby offering unprecedented opportunities to address a wide range of empirical questions as to how mechanisms of control operate. Here, we review the human neuroimaging literature that has begun to explore space-based, feature-based, object-based and category-based attentional control within the context of topographically defined frontoparietal cortex. PMID:27398396

A deformation of Sasakian structure in the presence of torsion and supergravity solutions

NASA Astrophysics Data System (ADS)

Houri, Tsuyoshi; Takeuchi, Hiroshi; Yasui, Yukinori

2013-07-01

A deformation of Sasakian structure in the presence of totally skew-symmetric torsion is discussed on odd-dimensional manifolds whose metric cones are Kähler with torsion. It is shown that such a geometry inherits similar properties to those of Sasakian geometry. As their example, we present an explicit expression of local metrics. It is also demonstrated that our example of the metrics admits the existence of hidden symmetry described by non-trivial odd-rank generalized closed conformal Killing-Yano tensors. Furthermore, using these metrics as an ansatz, we construct exact solutions in five-dimensional minimal gauged/ungauged supergravity and 11-dimensional supergravity. Finally, the global structures of the solutions are discussed. We obtain regular metrics on compact manifolds in five dimensions, which give natural generalizations of Sasaki-Einstein manifolds Yp, q and La, b, c. We also briefly discuss regular metrics on non-compact manifolds in 11 dimensions.

Psychophysics and Neuronal Bases of Sound Localization in Humans

PubMed Central

Ahveninen, Jyrki; Kopco, Norbert; Jääskeläinen, Iiro P.

2013-01-01

Localization of sound sources is a considerable computational challenge for the human brain. Whereas the visual system can process basic spatial information in parallel, the auditory system lacks a straightforward correspondence between external spatial locations and sensory receptive fields. Consequently, the question how different acoustic features supporting spatial hearing are represented in the central nervous system is still open. Functional neuroimaging studies in humans have provided evidence for a posterior auditory “where” pathway that encompasses non-primary auditory cortex areas, including the planum temporale (PT) and posterior superior temporal gyrus (STG), which are strongly activated by horizontal sound direction changes, distance changes, and movement. However, these areas are also activated by a wide variety of other stimulus features, posing a challenge for the interpretation that the underlying areas are purely spatial. This review discusses behavioral and neuroimaging studies on sound localization, and some of the competing models of representation of auditory space in humans. PMID:23886698

Low-Dimensional Statistics of Anatomical Variability via Compact Representation of Image Deformations.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2016-10-01

Using image-based descriptors to investigate clinical hypotheses and therapeutic implications is challenging due to the notorious "curse of dimensionality" coupled with a small sample size. In this paper, we present a low-dimensional analysis of anatomical shape variability in the space of diffeomorphisms and demonstrate its benefits for clinical studies. To combat the high dimensionality of the deformation descriptors, we develop a probabilistic model of principal geodesic analysis in a bandlimited low-dimensional space that still captures the underlying variability of image data. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than models based on the high-dimensional state-of-the-art approaches such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA).

Low-power adiabatic sequences for in-vivo localized two-dimensional chemical shift correlated MR spectroscopy

PubMed Central

Andronesi, Ovidiu C.; Ramadan, Saadallah; Mountford, Carolyn E.; Sorensen, A. Gregory

2011-01-01

Novel low-power adiabatic sequences are demonstrated for in-vivo localized two-dimensional (2D) correlated MR spectroscopy, such as COSY (Correlated Spectroscopy) and TOCSY (Total Correlated Spectroscopy). The design is based on three new elements for in-vivo 2D MRS: the use of gradient modulated constant adiabaticity GOIA-W(16,4) pulses for i) localization (COSY and TOCSY) and ii) mixing (TOCSY), and iii) the use of longitudinal mixing (z-filter) for magnetization transfer during TOCSY. GOIA-W(16,4) provides accurate signal localization, and more importantly, lowers the SAR for both TOCSY mixing and localization. Longitudinal mixing improves considerably (five-folds) the efficiency of TOCSY transfer. These are markedly different from previous 1D editing TOCSY sequences using spatially non-selective pulses and transverse mixing. Fully adiabatic (adiabatic mixing with adiabatic localization) and semi-adiabatic (adiabatic mixing with non-adiabatic localization) methods for 2D TOCSY are compared. Results are presented for simulations, phantoms, and in-vivo 2D spectra from healthy volunteers and patients with brain tumors obtained on 3T clinical platforms equipped with standard hardware. To the best of our knowledge this is the first demonstration of in-vivo adiabatic 2D TOCSY and fully adiabatic 2D COSY. It is expected that these methodological developments will advance the in-vivo applicability of multi(spectrally)dimensional MRS to reliably identify metabolic biomarkers. PMID:20890988

Neuroimaging of Central Sensitivity Syndromes: Key Insights from the Scientific Literature

PubMed Central

Walitt, Brian; Čeko, Marta; Gracely, John L.; Gracely, Richard H.

2016-01-01

Central sensitivity syndromes are characterized by distressing symptoms, such as pain and fatigue, in the absence of clinically obvious pathology. The scientific underpinnings of these disorders are not currently known. Modern neuroimaging techniques promise new insights into mechanisms mediating these postulated syndromes. We review the results of neuroimaging applied to five central sensitivity syndromes: fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, temporomandibular joint disorder, and vulvodynia syndrome. Neuroimaging studies of basal metabolism, anatomic constitution, molecular constituents, evoked neural activity, and treatment effect are compared across all of these syndromes. Evoked sensory paradigms reveal sensory augmentation to both painful and non-painful stimulation. This is a transformative observation for these syndromes, which were historically considered to be completely of hysterical or feigned in origin. However, whether sensory augmentation represents the cause of these syndromes, a predisposing factor, an endophenotype, or an epiphenomenon cannot be discerned from the current literature. Further, the result from cross-sectional neuroimaging studies of basal activity, anatomy, and molecular constituency are extremely heterogeneous within and between the syndromes. A defining neuroimaging “signature” cannot be discerned for any of the particular syndromes or for an over-arching central sensitization mechanism common to all of the syndromes. Several issues confound initial attempts to meaningfully measure treatment effects in these syndromes. At this time, the existence of “central sensitivity syndromes” is based more soundly on clinical and epidemiological evidence. A coherent picture of a “central sensitization” mechanism that bridges across all of these syndromes does not emerge from the existing scientific evidence. PMID:26717948

Computer implemented empirical mode decomposition method, apparatus, and article of manufacture for two-dimensional signals

NASA Technical Reports Server (NTRS)

Huang, Norden E. (Inventor)

2001-01-01

A computer implemented method of processing two-dimensional physical signals includes five basic components and the associated presentation techniques of the results. The first component decomposes the two-dimensional signal into one-dimensional profiles. The second component is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF's) from each profile based on local extrema and/or curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the profiles. In the third component, the IMF's of each profile are then subjected to a Hilbert Transform. The fourth component collates the Hilbert transformed IMF's of the profiles to form a two-dimensional Hilbert Spectrum. A fifth component manipulates the IMF's by, for example, filtering the two-dimensional signal by reconstructing the two-dimensional signal from selected IMF(s).

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies.

PubMed

Heggdal, Peder O Laugen; Brännström, Jonas; Aarstad, Hans Jørgen; Vassbotn, Flemming S; Specht, Karsten

2016-02-01

This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss. A literature search was performed in PubMed. Search criterions were peer reviewed original research papers in English completed by the 11th of March 2015. Twelve studies were found to use neuroimaging in subjects with unilateral hearing loss. An additional five papers not identified by the literature search were provided by a reviewer. Thus, a total of 17 studies were included in the review. Four different neuroimaging methods were used in these studies: Functional magnetic resonance imaging (fMRI) (n = 11), diffusion tensor imaging (DTI) (n = 4), T1/T2 volumetric images (n = 2), magnetic resonance spectroscopy (MRS) (n = 1). One study utilized two imaging methods (fMRI and T1 volumetric images). Neuroimaging techniques could provide valuable information regarding the effects of unilateral hearing loss on both auditory and non-auditory performance. fMRI-studies showing a bilateral BOLD-response in patients with unilateral hearing loss have not yet been followed by DTI studies confirming their microstructural correlates. In addition, the review shows that an auditory modality-specific deficit could affect multi-modal brain regions and their connections. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Local structure-based image decomposition for feature extraction with applications to face recognition.

PubMed

Qian, Jianjun; Yang, Jian; Xu, Yong

2013-09-01

This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.

Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment.

PubMed

Torgerson, Carinna M; Quinn, Catherine; Dinov, Ivo; Liu, Zhizhong; Petrosyan, Petros; Pelphrey, Kevin; Haselgrove, Christian; Kennedy, David N; Toga, Arthur W; Van Horn, John Darrell

2015-03-01

Under the umbrella of the National Database for Clinical Trials (NDCT) related to mental illnesses, the National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline workflow design and execution environment to enable large-scale analyses of cortical architecture and function via local, cluster, or "cloud"-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources. We discuss the utility of such database and workflow processing interactivity as a motivation for the sharing of additional primary data in ASD research and elsewhere.

Network localization of neurological symptoms from focal brain lesions

PubMed Central

Prasad, Sashank; Liu, Hesheng; Liu, Qi; Pascual-Leone, Alvaro; Caviness, Verne S.; Fox, Michael D.

2015-01-01

A traditional and widely used approach for linking neurological symptoms to specific brain regions involves identifying overlap in lesion location across patients with similar symptoms, termed lesion mapping. This approach is powerful and broadly applicable, but has limitations when symptoms do not localize to a single region or stem from dysfunction in regions connected to the lesion site rather than the site itself. A newer approach sensitive to such network effects involves functional neuroimaging of patients, but this requires specialized brain scans beyond routine clinical data, making it less versatile and difficult to apply when symptoms are rare or transient. In this article we show that the traditional approach to lesion mapping can be expanded to incorporate network effects into symptom localization without the need for specialized neuroimaging of patients. Our approach involves three steps: (i) transferring the three-dimensional volume of a brain lesion onto a reference brain; (ii) assessing the intrinsic functional connectivity of the lesion volume with the rest of the brain using normative connectome data; and (iii) overlapping lesion-associated networks to identify regions common to a clinical syndrome. We first tested our approach in peduncular hallucinosis, a syndrome of visual hallucinations following subcortical lesions long hypothesized to be due to network effects on extrastriate visual cortex. While the lesions themselves were heterogeneously distributed with little overlap in lesion location, 22 of 23 lesions were negatively correlated with extrastriate visual cortex. This network overlap was specific compared to other subcortical lesions (P < 10−5) and relative to other cortical regions (P < 0.01). Next, we tested for generalizability of our technique by applying it to three additional lesion syndromes: central post-stroke pain, auditory hallucinosis, and subcortical aphasia. In each syndrome, heterogeneous lesions that themselves had little overlap showed significant network overlap in cortical areas previously implicated in symptom expression (P < 10−4). These results suggest that (i) heterogeneous lesions producing similar symptoms share functional connectivity to specific brain regions involved in symptom expression; and (ii) publically available human connectome data can be used to incorporate these network effects into traditional lesion mapping approaches. Because the current technique requires no specialized imaging of patients it may prove a versatile and broadly applicable approach for localizing neurological symptoms in the setting of brain lesions. PMID:26264514

Supersymmetric interactions of a six-dimensional self-dual tensor and fixed-shape second quantized strings

NASA Astrophysics Data System (ADS)

Ganor, Ori J.

2018-02-01

"Curvepole (2,0)-theory" is a deformation of the (2,0)-theory with nonlocal interactions. A curvepole is defined as a two-dimensional generalization of a dipole. It is an object of fixed two-dimensional shape of which the boundary is a charged curve that interacts with a 2-form gauge field. Curvepole theory was previously only defined indirectly via M-theory. Here, we propose a supersymmetric Lagrangian, constructed explicitly up to quartic terms, for an "Abelian" curvepole theory, which is an interacting deformation of the free (2,0) tensor multiplet. This theory contains fields of which the quanta are curvepoles (i.e., fixed-shape strings). Supersymmetry is preserved (at least up to quartic terms) if the shape of the curvepoles is (two-dimensional) planar. This nonlocal six-dimensional quantum field theory may also serve as a UV completion for certain (local) five-dimensional gauge theories.

Server-based Approach to Web Visualization of Integrated Three-dimensional Brain Imaging Data

PubMed Central

Poliakov, Andrew V.; Albright, Evan; Hinshaw, Kevin P.; Corina, David P.; Ojemann, George; Martin, Richard F.; Brinkley, James F.

2005-01-01

The authors describe a client-server approach to three-dimensional (3-D) visualization of neuroimaging data, which enables researchers to visualize, manipulate, and analyze large brain imaging datasets over the Internet. All computationally intensive tasks are done by a graphics server that loads and processes image volumes and 3-D models, renders 3-D scenes, and sends the renderings back to the client. The authors discuss the system architecture and implementation and give several examples of client applications that allow visualization and analysis of integrated language map data from single and multiple patients. PMID:15561787

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.

Parsing dimensional vs diagnostic category-related patterns of reward circuitry function in behaviorally and emotionally dysregulated youth in the Longitudinal Assessment of Manic Symptoms study.

PubMed

Bebko, Genna; Bertocci, Michele A; Fournier, Jay C; Hinze, Amanda K; Bonar, Lisa; Almeida, Jorge R C; Perlman, Susan B; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A; Ciuffetelli, Gary; Rodriguez, Eric; Olino, Thomas; Forbes, Erika; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Arnold, L Eugene; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Phillips, Mary L

2014-01-01

Pediatric disorders characterized by behavioral and emotional dysregulation pose diagnostic and treatment challenges because of high comorbidity, suggesting that they may be better conceptualized dimensionally rather than categorically. Identifying neuroimaging measures associated with behavioral and emotional dysregulation in youth may inform understanding of underlying dimensional vs disorder-specific pathophysiologic features. To identify, in a large cohort of behaviorally and emotionally dysregulated youth, neuroimaging measures that (1) are associated with behavioral and emotional dysregulation pathologic dimensions (behavioral and emotional dysregulation measured with the Parent General Behavior Inventory 10-Item Mania Scale [PGBI-10M], mania, depression, and anxiety) or (2) differentiate diagnostic categories (bipolar spectrum disorders, attention-deficit/hyperactivity disorder, anxiety, and disruptive behavior disorders). A multisite neuroimaging study was conducted from February 1, 2011, to April 15, 2012, at 3 academic medical centers: University Hospitals Case Medical Center, Cincinnati Children's Hospital Medical Center, and University of Pittsburgh Medical Center. Participants included a referred sample of behaviorally and emotionally dysregulated youth from the Longitudinal Assessment of Manic Symptoms (LAMS) study (n = 85) and healthy youth (n = 20). Region-of-interest analyses examined relationships among prefrontal-ventral striatal reward circuitry during a reward paradigm (win, loss, and control conditions), symptom dimensions, and diagnostic categories. Regardless of diagnosis, higher PGBI-10M scores were associated with greater left middle prefrontal cortical activity (r = 0.28) and anxiety with greater right dorsal anterior cingulate cortical (r = 0.27) activity to win. The 20 highest (t = 2.75) and 20 lowest (t = 2.42) PGBI-10M-scoring youth showed significantly greater left middle prefrontal cortical activity to win compared with 20 healthy youth. Disruptive behavior disorders were associated with lower left ventrolateral prefrontal cortex activity to win (t = 2.68) (all P < .05, corrected). Greater PGBI-10M-related left middle prefrontal cortical activity and anxiety-related right dorsal anterior cingulate cortical activity to win may reflect heightened reward sensitivity and greater attention to reward in behaviorally and emotionally dysregulated youth regardless of diagnosis. Reduced left ventrolateral prefrontal cortex activity to win may reflect reward insensitivity in youth with disruptive behavior disorders. Despite a distinct reward-related neurophysiologic feature in disruptive behavior disorders, findings generally support a dimensional approach to studying neural mechanisms in behaviorally and emotionally dysregulated youth.

Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning.

PubMed

Janssen, Ronald J; Mourão-Miranda, Janaina; Schnack, Hugo G

2018-04-22

Psychiatric prognosis is a difficult problem. Making a prognosis requires looking far into the future, as opposed to making a diagnosis, which is concerned with the current state. During the follow-up period, many factors will influence the course of the disease. Combined with the usually scarcer longitudinal data and the variability in the definition of outcomes/transition, this makes prognostic predictions a challenging endeavor. Employing neuroimaging data in this endeavor introduces the additional hurdle of high dimensionality. Machine-learning techniques are especially suited to tackle this challenging problem. This review starts with a brief introduction to machine learning in the context of its application to clinical neuroimaging data. We highlight a few issues that are especially relevant for prediction of outcome and transition using neuroimaging. We then review the literature that discusses the application of machine learning for this purpose. Critical examination of the studies and their results with respect to the relevant issues revealed the following: 1) there is growing evidence for the prognostic capability of machine-learning-based models using neuroimaging; and 2) reported accuracies may be too optimistic owing to small sample sizes and the lack of independent test samples. Finally, we discuss options to improve the reliability of (prognostic) prediction models. These include new methodologies and multimodal modeling. Paramount, however, is our conclusion that future work will need to provide properly (cross-)validated accuracy estimates of models trained on sufficiently large datasets. Nevertheless, with the technological advances enabling acquisition of large databases of patients and healthy subjects, machine learning represents a powerful tool in the search for psychiatric biomarkers. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Combining Feature Extraction Methods to Assist the Diagnosis of Alzheimer's Disease.

PubMed

Segovia, F; Górriz, J M; Ramírez, J; Phillips, C

2016-01-01

Neuroimaging data as (18)F-FDG PET is widely used to assist the diagnosis of Alzheimer's disease (AD). Looking for regions with hypoperfusion/ hypometabolism, clinicians may predict or corroborate the diagnosis of the patients. Modern computer aided diagnosis (CAD) systems based on the statistical analysis of whole neuroimages are more accurate than classical systems based on quantifying the uptake of some predefined regions of interests (ROIs). In addition, these new systems allow determining new ROIs and take advantage of the huge amount of information comprised in neuroimaging data. A major branch of modern CAD systems for AD is based on multivariate techniques, which analyse a neuroimage as a whole, considering not only the voxel intensities but also the relations among them. In order to deal with the vast dimensionality of the data, a number of feature extraction methods have been successfully applied. In this work, we propose a CAD system based on the combination of several feature extraction techniques. First, some commonly used feature extraction methods based on the analysis of the variance (as principal component analysis), on the factorization of the data (as non-negative matrix factorization) and on classical magnitudes (as Haralick features) were simultaneously applied to the original data. These feature sets were then combined by means of two different combination approaches: i) using a single classifier and a multiple kernel learning approach and ii) using an ensemble of classifier and selecting the final decision by majority voting. The proposed approach was evaluated using a labelled neuroimaging database along with a cross validation scheme. As conclusion, the proposed CAD system performed better than approaches using only one feature extraction technique. We also provide a fair comparison (using the same database) of the selected feature extraction methods.

Neuroimaging findings in Joubert syndrome with C5orf42 gene mutations: A milder form of molar tooth sign and vermian hypoplasia.

PubMed

Enokizono, Mikako; Aida, Noriko; Niwa, Tetsu; Osaka, Hitoshi; Naruto, Takuya; Kurosawa, Kenji; Ohba, Chihiro; Suzuki, Toshifumi; Saitsu, Hirotomo; Goto, Tomohide; Matsumoto, Naomichi

2017-05-15

Little is known regarding neuroimaging-genotype correlations in Joubert syndrome (JBTS). To elucidate one of these correlations, we investigated the neuroimaging findings of JBTS patients with C5orf42 mutations. Neuroimaging findings in five JBTS patients with C5orf42 mutations were retrospectively assessed with regard to the infratentorial and supratentorial structures on T1-magnetization prepared rapid gradient echo (MPRAGE), T2-weighted images, and color-coded fractional anisotropy (FA) maps; the findings were compared to those in four JBTS patients with mutations in other genes (including three with AHI1 and one with TMEM67 mutations). In C5orf42-mutant patients, the infratentorial magnetic resonance (MR) images showed normal or minimally thickened and minimally elongated superior cerebellar peduncles (SCP), normal or minimally deepened interpeduncular fossa (IF), and mild vermian hypoplasia (VH). However, in other patients, all had severe abnormalities in the SCP and IF, and moderate to marked VH. Supratentorial abnormalities were found in one individual in other JBTS. In JBTS with all mutations, color-coded FA maps showed the absence of decussation of the SCP (DSCP). The morphological neuroimaging findings in C5orf42-mutant JBTS were distinctly mild and made diagnosis difficult. However, the absence of DSCP on color-coded FA maps may facilitate the diagnosis of JBTS. Copyright © 2017 Elsevier B.V. All rights reserved.

Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system.

PubMed

Chitnis, Danial; Cooper, Robert J; Dempsey, Laura; Powell, Samuel; Quaggia, Simone; Highton, David; Elwell, Clare; Hebden, Jeremy C; Everdell, Nicholas L

2016-10-01

We present the first three-dimensional, functional images of the human brain to be obtained using a fibre-less, high-density diffuse optical tomography system. Our technology consists of independent, miniaturized, silicone-encapsulated DOT modules that can be placed directly on the scalp. Four of these modules were arranged to provide up to 128, dual-wavelength measurement channels over a scalp area of approximately 60 × 65 mm 2 . Using a series of motor-cortex stimulation experiments, we demonstrate that this system can obtain high-quality, continuous-wave measurements at source-detector separations ranging from 14 to 55 mm in adults, in the presence of hair. We identify robust haemodynamic response functions in 5 out of 5 subjects, and present diffuse optical tomography images that depict functional haemodynamic responses that are well-localized in all three dimensions at both the individual and group levels. This prototype modular system paves the way for a new generation of wearable, wireless, high-density optical neuroimaging technologies.

Bilateral hippocampal atrophy in temporal lobe epilepsy: Effect of depressive symptoms and febrile seizures

PubMed Central

Finegersh, Andrey; Avedissian, Christina; Shamim, Sadat; Dustin, Irene; Thompson, Paul M.; Theodore, William H.

2011-01-01

Summary Purpose Neuroimaging studies suggest a history of febrile seizures, and depression, are associated with hippocampal volume reductions in patients with temporal lobe epilepsy (TLE). Methods We used radial atrophy mapping (RAM), a three-dimensional (3D) surface modeling tool, to measure hippocampal atrophy in 40 patients with unilateral TLE, with or without a history of febrile seizures and symptoms of depression. Multiple linear regression was used to single out the effects of covariates on local atrophy. Key Findings Subjects with a history of febrile seizures (n = 15) had atrophy in regions corresponding to the CA1 and CA3 subfields of the hippocampus contralateral to seizure focus (CHC) compared to those without a history of febrile seizures (n = 25). Subjects with Beck Depression Inventory II (BDI-II) score ≥14 (n = 11) had atrophy in the superoanterior portion of the CHC compared to subjects with BDI-II <14 (n = 29). Significance Contralateral hippocampal atrophy in TLE may be related to febrile seizures or depression. PMID:21269286

Pituitary tumours in adolescence: clinical behaviour and neuroimaging features of seven cases.

PubMed

Nishio, S; Morioka, T; Suzuki, S; Takeshita, I; Fukui, M; Iwaki, T

2001-05-01

The clinicopathologic features of seven paediatric patients with pituitary adenomas (2 male, 5 female; mean age 14.3 years) were reviewed. There were three non-functioning adenomas, three prolactinomas, and one growth hormone producing adenoma. Five patients presented with visual field deficits, and six patients had endocrine symptoms, which included menstrual irregularities in all female patients, pubertal delay in two females, and growth delay and gigantism in one case each. On neuroimaging studies, five adenomas showed parasellar extension, while the remaining two prolactinomas were intrasellar microadenomas. While two patients with prolactinomas received good results with bromocriptine treatment alone, the remaining five patients underwent either craniotomy or transsphenoidal surgery. Postoperatively, visual disturbances improved markedly in all patients. Two patients also received replacement hormonal therapy. While six patients have been stable for 3.6 years on average, one non-functioning tumour recurred 2 years after the initial transcranial subtotal resection of the tumour. Although there are still many unknowns concerning the biology and optimal treatments for paediatric pituitary adenomas, many of them are assumed to be relatively rapidly growing tumours, while others merely have an earlier tumour genesis than in adults. Copyright 2001 Harcourt Publishers Ltd.

Light-cone reduction vs. TsT transformations: a fluid dynamics perspective

NASA Astrophysics Data System (ADS)

Dutta, Suvankar; Krishna, Hare

2018-05-01

We compute constitutive relations for a charged (2+1) dimensional Schrödinger fluid up to first order in derivative expansion, using holographic techniques. Starting with a locally boosted, asymptotically AdS, 4 + 1 dimensional charged black brane geometry, we uplift that to ten dimensions and perform TsT transformations to obtain an effective five dimensional local black brane solution with asymptotically Schrödinger isometries. By suitably implementing the holographic techniques, we compute the constitutive relations for the effective fluid living on the boundary of this space-time and extract first order transport coefficients from these relations. Schrödinger fluid can also be obtained by reducing a charged relativistic conformal fluid over light-cone. It turns out that both the approaches result the same system at the end. Fluid obtained by light-cone reduction satisfies a restricted class of thermodynamics. Here, we see that the charged fluid obtained holographically also belongs to the same restricted class.

Tracking Brain Development and Dimensional Psychiatric Symptoms in Children: A Longitudinal Population-Based Neuroimaging Study.

PubMed

Muetzel, Ryan L; Blanken, Laura M E; van der Ende, Jan; El Marroun, Hanan; Shaw, Philip; Sudre, Gustavo; van der Lugt, Aad; Jaddoe, Vincent W V; Verhulst, Frank C; Tiemeier, Henning; White, Tonya

2018-01-01

Psychiatric symptomatology during childhood predicts persistent mental illness later in life. While neuroimaging methodologies are routinely applied cross-sectionally to the study of child and adolescent psychopathology, the nature of the relationship between childhood symptoms and the underlying neurodevelopmental processes remains unclear. The authors used a prospective population-based cohort to delineate the longitudinal relationship between childhood psychiatric problems and brain development. A total of 845 children participated in the study. Psychiatric symptoms were measured with the parent-rated Child Behavior Checklist at ages 6 and 10. MRI data were collected at ages 8 and 10. Cross-lagged panel models and linear mixed-effects models were used to determine the associations between psychiatric symptom ratings and quantitative anatomic and white matter microstructural measures over time. Higher ratings for externalizing and internalizing symptoms at baseline predicted smaller increases in both subcortical gray matter volume and global fractional anisotropy over time. The reverse relationship did not hold; thus, baseline measures of gray matter and white matter were not significantly related to changes in symptom ratings over time. Children presenting with behavioral problems at an early age show differential subcortical and white matter development. Most neuroimaging models tend to explain brain differences observed in psychopathology as an underlying (causal) neurobiological substrate. However, the present work suggests that future neuroimaging studies showing effects that are pathogenic in nature should additionally explore the possibility of the downstream effects of psychopathology on the brain.

Distinguishing between Unipolar Depression and Bipolar Depression: Current and Future Clinical and Neuroimaging Perspectives

PubMed Central

de Almeida, Jorge Renner Cardoso; Phillips, Mary Louise

2012-01-01

Differentiating bipolar disorder (BD) from recurrent unipolar depression (UD) is a major clinical challenge. Main reasons for this include the higher prevalence of depressive relative to hypo/manic symptoms during the course of BD illness and the high prevalence of subthreshold manic symptoms in both BD and UD depression. Identifying objective markers of BD might help improve accuracy in differentiating between BD and UD depression, to ultimately optimize clinical and functional outcome for all depressed individuals. Yet, only eight neuroimaging studies to date directly compared UD and BD depressed individuals. Findings from these studies suggest more widespread abnormalities in white matter connectivity and white matter hyperintensities in BD than UD depression, habenula volume reductions in BD but not UD depression, and differential patterns of functional abnormalities in emotion regulation and attentional control neural circuitry in the two depression types. These findings suggest different pathophysiologic processes, especially in emotion regulation, reward and attentional control neural circuitry in BD versus UD depression. This review thereby serves as a “call to action” to highlight the pressing need for more neuroimaging studies, using larger samples sizes, comparing BD and UD depressed individuals. These future studies should also include dimensional approaches, studies of at risk individuals, and more novel neuroimaging approaches, such as, connectivity analysis and machine learning. Ultimately, these approaches might provide biomarkers to identify individuals at future risk for BD versus UD, and biological targets for more personalized treatment and new treatment developments for BD and UD depression. PMID:22784485

Haptic fMRI: combining functional neuroimaging with haptics for studying the brain's motor control representation.

PubMed

Menon, Samir; Brantner, Gerald; Aholt, Chris; Kay, Kendrick; Khatib, Oussama

2013-01-01

A challenging problem in motor control neuroimaging studies is the inability to perform complex human motor tasks given the Magnetic Resonance Imaging (MRI) scanner's disruptive magnetic fields and confined workspace. In this paper, we propose a novel experimental platform that combines Functional MRI (fMRI) neuroimaging, haptic virtual simulation environments, and an fMRI-compatible haptic device for real-time haptic interaction across the scanner workspace (above torso ∼ .65×.40×.20m(3)). We implement this Haptic fMRI platform with a novel haptic device, the Haptic fMRI Interface (HFI), and demonstrate its suitability for motor neuroimaging studies. HFI has three degrees-of-freedom (DOF), uses electromagnetic motors to enable high-fidelity haptic rendering (>350Hz), integrates radio frequency (RF) shields to prevent electromagnetic interference with fMRI (temporal SNR >100), and is kinematically designed to minimize currents induced by the MRI scanner's magnetic field during motor displacement (<2cm). HFI possesses uniform inertial and force transmission properties across the workspace, and has low friction (.05-.30N). HFI's RF noise levels, in addition, are within a 3 Tesla fMRI scanner's baseline noise variation (∼.85±.1%). Finally, HFI is haptically transparent and does not interfere with human motor tasks (tested for .4m reaches). By allowing fMRI experiments involving complex three-dimensional manipulation with haptic interaction, Haptic fMRI enables-for the first time-non-invasive neuroscience experiments involving interactive motor tasks, object manipulation, tactile perception, and visuo-motor integration.

Decoding Dynamic Brain Patterns from Evoked Responses: A Tutorial on Multivariate Pattern Analysis Applied to Time Series Neuroimaging Data.

PubMed

Grootswagers, Tijl; Wardle, Susan G; Carlson, Thomas A

2017-04-01

Multivariate pattern analysis (MVPA) or brain decoding methods have become standard practice in analyzing fMRI data. Although decoding methods have been extensively applied in brain-computer interfaces, these methods have only recently been applied to time series neuroimaging data such as MEG and EEG to address experimental questions in cognitive neuroscience. In a tutorial style review, we describe a broad set of options to inform future time series decoding studies from a cognitive neuroscience perspective. Using example MEG data, we illustrate the effects that different options in the decoding analysis pipeline can have on experimental results where the aim is to "decode" different perceptual stimuli or cognitive states over time from dynamic brain activation patterns. We show that decisions made at both preprocessing (e.g., dimensionality reduction, subsampling, trial averaging) and decoding (e.g., classifier selection, cross-validation design) stages of the analysis can significantly affect the results. In addition to standard decoding, we describe extensions to MVPA for time-varying neuroimaging data including representational similarity analysis, temporal generalization, and the interpretation of classifier weight maps. Finally, we outline important caveats in the design and interpretation of time series decoding experiments.

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

Fermion masses and mixing in general warped extra dimensional models

NASA Astrophysics Data System (ADS)

Frank, Mariana; Hamzaoui, Cherif; Pourtolami, Nima; Toharia, Manuel

2015-06-01

We analyze fermion masses and mixing in a general warped extra dimensional model, where all the Standard Model (SM) fields, including the Higgs, are allowed to propagate in the bulk. In this context, a slightly broken flavor symmetry imposed universally on all fermion fields, without distinction, can generate the full flavor structure of the SM, including quarks, charged leptons and neutrinos. For quarks and charged leptons, the exponential sensitivity of their wave functions to small flavor breaking effects yield hierarchical masses and mixing as it is usual in warped models with fermions in the bulk. In the neutrino sector, the exponential wave-function factors can be flavor blind and thus insensitive to the small flavor symmetry breaking effects, directly linking their masses and mixing angles to the flavor symmetric structure of the five-dimensional neutrino Yukawa couplings. The Higgs must be localized in the bulk and the model is more successful in generalized warped scenarios where the metric background solution is different than five-dimensional anti-de Sitter (AdS5 ). We study these features in two simple frameworks, flavor complimentarity and flavor democracy, which provide specific predictions and correlations between quarks and leptons, testable as more precise data in the neutrino sector becomes available.

Evaluating mental workload of two-dimensional and three-dimensional visualization for anatomical structure localization.

PubMed

Foo, Jung-Leng; Martinez-Escobar, Marisol; Juhnke, Bethany; Cassidy, Keely; Hisley, Kenneth; Lobe, Thom; Winer, Eliot

2013-01-01

Visualization of medical data in three-dimensional (3D) or two-dimensional (2D) views is a complex area of research. In many fields 3D views are used to understand the shape of an object, and 2D views are used to understand spatial relationships. It is unclear how 2D/3D views play a role in the medical field. Using 3D views can potentially decrease the learning curve experienced with traditional 2D views by providing a whole representation of the patient's anatomy. However, there are challenges with 3D views compared with 2D. This current study expands on a previous study to evaluate the mental workload associated with both 2D and 3D views. Twenty-five first-year medical students were asked to localize three anatomical structures--gallbladder, celiac trunk, and superior mesenteric artery--in either 2D or 3D environments. Accuracy and time were taken as the objective measures for mental workload. The NASA Task Load Index (NASA-TLX) was used as a subjective measure for mental workload. Results showed that participants viewing in 3D had higher localization accuracy and a lower subjective measure of mental workload, specifically, the mental demand component of the NASA-TLX. Results from this study may prove useful for designing curricula in anatomy education and improving training procedures for surgeons.

Virtual Reality and Simulation in Neurosurgical Training.

PubMed

Bernardo, Antonio

2017-10-01

Recent biotechnological advances, including three-dimensional microscopy and endoscopy, virtual reality, surgical simulation, surgical robotics, and advanced neuroimaging, have continued to mold the surgeon-computer relationship. For developing neurosurgeons, such tools can reduce the learning curve, improve conceptual understanding of complex anatomy, and enhance visuospatial skills. We explore the current and future roles and application of virtual reality and simulation in neurosurgical training. Copyright © 2017 Elsevier Inc. All rights reserved.

Topology for Dominance for Network of Multi-Agent System

NASA Astrophysics Data System (ADS)

Szeto, K. Y.

2007-05-01

The resource allocation problem in evolving two-dimensional point patterns is investigated for the existence of good strategies for the construction of initial configuration that leads to fast dominance of the pattern by one single species, which can be interpreted as market dominance by a company in the context of multi-agent systems in econophysics. For hexagonal lattice, certain special topological arrangements of the resource in two-dimensions, such as rings, lines and clusters have higher probability of dominance, compared to random pattern. For more complex networks, a systematic way to search for a stable and dominant strategy of resource allocation in the changing environment is found by means of genetic algorithm. Five typical features can be summarized by means of the distribution function for the local neighborhood of friends and enemies as well as the local clustering coefficients: (1) The winner has more triangles than the loser has. (2) The winner likes to form clusters as the winner tends to connect with other winner rather than with losers; while the loser tends to connect with winners rather than losers. (3) The distribution function of friends as well as enemies for the winner is broader than the corresponding distribution function for the loser. (4) The connectivity at which the peak of the distribution of friends for the winner occurs is larger than that of the loser; while the peak values for friends for winners is lower. (5) The connectivity at which the peak of the distribution of enemies for the winner occurs is smaller than that of the loser; while the peak values for enemies for winners is lower. These five features appear to be general, at least in the context of two-dimensional hexagonal lattices of various sizes, hierarchical lattice, Voronoi diagrams, as well as high-dimensional random networks. These general local topological properties of networks are relevant to strategists aiming at dominance in evolving patterns when the interaction between the agents is local.

Defining Face Perception Areas in the Human Brain: A Large-Scale Factorial fMRI Face Localizer Analysis

ERIC Educational Resources Information Center

Rossion, Bruno; Hanseeuw, Bernard; Dricot, Laurence

2012-01-01

A number of human brain areas showing a larger response to faces than to objects from different categories, or to scrambled faces, have been identified in neuroimaging studies. Depending on the statistical criteria used, the set of areas can be overextended or minimized, both at the local (size of areas) and global (number of areas) levels. Here…

5D perspective on Higgs production at the boundary of a warped extra dimension

NASA Astrophysics Data System (ADS)

Malm, Raoul; Neubert, Matthias; Novotny, Kristiane; Schmell, Christoph

2014-01-01

A comprehensive, five-dimensional calculation of Higgs-boson production in gluon fusion is performed for both the minimal and the custodially protected Randall-Sundrum (RS) model, with Standard Model fields propagating in the bulk and the scalar sector confined on or near the IR brane. For the first time, an exact expression for the gg → h amplitude in terms of the five-dimensional fermion propagator is derived, which includes the full dependence on the Higgs-boson mass. Various results in the literature are reconciled and shown to correspond to different incarnations of the RS model, in which the Higgs field is either localized on the IR brane or is described in terms of a narrow bulk state. The results in the two scenarios differ in a qualitative way: the gg → h amplitude is suppressed in models where the scalar sector is localized on the IR brane, while it tends to be enhanced in bulk Higgs models. In both cases, effects of higher-dimensional operators contributing to the gg → h amplitude at tree level are shown to be numerically suppressed under reasonable assumptions. There is no smooth cross-over between the two scenarios, since the effective field-theory description breaks down in the transition region. A detailed phenomenological analysis of Higgs production in various RS scenarios is presented, and for each scenario the regions of parameter space already excluded by LHC data are derived.

U.S. Army Medical Department Journal (October-December 2006)

DTIC Science & Technology

2006-12-01

prioritize Soldiers with medical conditions who need additional neurophysiological and/or neuroimaging evaluations. If local national facilities are...of Enlightenment . Focused experimentation and solid hard work by an increasingly diverse range of organizations leads to a true understanding of the

Distinguishing between unipolar depression and bipolar depression: current and future clinical and neuroimaging perspectives.

PubMed

Cardoso de Almeida, Jorge Renner; Phillips, Mary Louise

2013-01-15

Differentiating bipolar disorder (BD) from recurrent unipolar depression (UD) is a major clinical challenge. Main reasons for this include the higher prevalence of depressive relative to hypo/manic symptoms during the course of BD illness and the high prevalence of subthreshold manic symptoms in both BD and UD depression. Identifying objective markers of BD might help improve accuracy in differentiating between BD and UD depression, to ultimately optimize clinical and functional outcome for all depressed individuals. Yet, only eight neuroimaging studies to date have directly compared UD and BD depressed individuals. Findings from these studies suggest more widespread abnormalities in white matter connectivity and white matter hyperintensities in BD than UD depression, habenula volume reductions in BD but not UD depression, and differential patterns of functional abnormalities in emotion regulation and attentional control neural circuitry in the two depression types. These findings suggest different pathophysiologic processes, especially in emotion regulation, reward, and attentional control neural circuitry in BD versus UD depression. This review thereby serves as a call to action to highlight the pressing need for more neuroimaging studies, using larger samples sizes, comparing BD and UD depressed individuals. These future studies should also include dimensional approaches, studies of at-risk individuals, and more novel neuroimaging approaches, such as connectivity analysis and machine learning. Ultimately, these approaches might provide biomarkers to identify individuals at future risk for BD versus UD and biological targets for more personalized treatment and new treatment developments for BD and UD depression. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

From Neurons to Brainpower: Cognitive Neuroscience and Brain-Based Learning

ERIC Educational Resources Information Center

Phillips, Janet M.

2005-01-01

We have learned more about the brain in the past five years than the previous 100. Neuroimaging, lesion studies, and animal studies have revealed the intricate inner workings of the brain and learning. Synaptogenesis, pruning, sensitive periods, and plasticity have all become accepted concepts of cognitive neuroscience that are now being applied…

Neural Coding for Effective Rehabilitation

PubMed Central

2014-01-01

Successful neurological rehabilitation depends on accurate diagnosis, effective treatment, and quantitative evaluation. Neural coding, a technology for interpretation of functional and structural information of the nervous system, has contributed to the advancements in neuroimaging, brain-machine interface (BMI), and design of training devices for rehabilitation purposes. In this review, we summarized the latest breakthroughs in neuroimaging from microscale to macroscale levels with potential diagnostic applications for rehabilitation. We also reviewed the achievements in electrocorticography (ECoG) coding with both animal models and human beings for BMI design, electromyography (EMG) interpretation for interaction with external robotic systems, and robot-assisted quantitative evaluation on the progress of rehabilitation programs. Future rehabilitation would be more home-based, automatic, and self-served by patients. Further investigations and breakthroughs are mainly needed in aspects of improving the computational efficiency in neuroimaging and multichannel ECoG by selection of localized neuroinformatics, validation of the effectiveness in BMI guided rehabilitation programs, and simplification of the system operation in training devices. PMID:25258708

Adherence to standard of care in the diagnosis and treatment of suspected bacterial meningitis.

PubMed

Chia, David; Yavari, Youness; Kirsanov, Eugeny; Aronin, Steven I; Sadigh, Majid

2015-01-01

Acute bacterial meningitis (ABM) is a rare but deadly neurological emergency. Accordingly, Infectious Diseases Society of America (IDSA) guidelines summarize current evidence into a straightforward algorithm for its management. The goal of this study is to evaluate the overall compliance with these guidelines in patients with suspected ABM. A retrospective cross-sectional study was conducted of adult patients who underwent lumbar puncture for suspected ABM to ascertain local adherence patterns to IDSA guidelines for bacterial meningitis. Primary outcomes included appropriate utilization of neuroimaging, blood cultures, antibiotics, corticosteroids, and lumbar puncture. In all, 160 patients were included in the study. Overall IDSA compliance was only 0.6%. Neuroimaging and blood cultures were appropriately utilized in 54.3% and 47.5% of patients, respectively. Steroids and antibiotics were appropriately administered in only 7.5% and 5.6% of patients, respectively. Adherence to IDSA guidelines is poor. Antibiotic choice is often incorrect, corticosteroids are rarely administered, and there is an overutilization of neuroimaging. © The Author(s) 2014.

Network localization of neurological symptoms from focal brain lesions.

PubMed

Boes, Aaron D; Prasad, Sashank; Liu, Hesheng; Liu, Qi; Pascual-Leone, Alvaro; Caviness, Verne S; Fox, Michael D

2015-10-01

A traditional and widely used approach for linking neurological symptoms to specific brain regions involves identifying overlap in lesion location across patients with similar symptoms, termed lesion mapping. This approach is powerful and broadly applicable, but has limitations when symptoms do not localize to a single region or stem from dysfunction in regions connected to the lesion site rather than the site itself. A newer approach sensitive to such network effects involves functional neuroimaging of patients, but this requires specialized brain scans beyond routine clinical data, making it less versatile and difficult to apply when symptoms are rare or transient. In this article we show that the traditional approach to lesion mapping can be expanded to incorporate network effects into symptom localization without the need for specialized neuroimaging of patients. Our approach involves three steps: (i) transferring the three-dimensional volume of a brain lesion onto a reference brain; (ii) assessing the intrinsic functional connectivity of the lesion volume with the rest of the brain using normative connectome data; and (iii) overlapping lesion-associated networks to identify regions common to a clinical syndrome. We first tested our approach in peduncular hallucinosis, a syndrome of visual hallucinations following subcortical lesions long hypothesized to be due to network effects on extrastriate visual cortex. While the lesions themselves were heterogeneously distributed with little overlap in lesion location, 22 of 23 lesions were negatively correlated with extrastriate visual cortex. This network overlap was specific compared to other subcortical lesions (P < 10(-5)) and relative to other cortical regions (P < 0.01). Next, we tested for generalizability of our technique by applying it to three additional lesion syndromes: central post-stroke pain, auditory hallucinosis, and subcortical aphasia. In each syndrome, heterogeneous lesions that themselves had little overlap showed significant network overlap in cortical areas previously implicated in symptom expression (P < 10(-4)). These results suggest that (i) heterogeneous lesions producing similar symptoms share functional connectivity to specific brain regions involved in symptom expression; and (ii) publically available human connectome data can be used to incorporate these network effects into traditional lesion mapping approaches. Because the current technique requires no specialized imaging of patients it may prove a versatile and broadly applicable approach for localizing neurological symptoms in the setting of brain lesions. © 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.

Three-Dimensional Computer-Assisted Two-Layer Elastic Models of the Face.

PubMed

Ueda, Koichi; Shigemura, Yuka; Otsuki, Yuki; Fuse, Asuka; Mitsuno, Daisuke

2017-11-01

To make three-dimensional computer-assisted elastic models for the face, we decided on five requirements: (1) an elastic texture like skin and subcutaneous tissue; (2) the ability to take pen marking for incisions; (3) the ability to be cut with a surgical knife; (4) the ability to keep stitches in place for a long time; and (5) a layered structure. After testing many elastic solvents, we have made realistic three-dimensional computer-assisted two-layer elastic models of the face and cleft lip from the computed tomographic and magnetic resonance imaging stereolithographic data. The surface layer is made of polyurethane and the inner layer is silicone. Using this elastic model, we taught residents and young doctors how to make several typical local flaps and to perform cheiloplasty. They could experience realistic simulated surgery and understand three-dimensional movement of the flaps.

Pontocerebellar hypoplasia type 6 caused by mutations in RARS2: definition of the clinical spectrum and molecular findings in five patients.

PubMed

Cassandrini, Denise; Cilio, Maria Roberta; Bianchi, Marzia; Doimo, Mara; Balestri, Martina; Tessa, Alessandra; Rizza, Teresa; Sartori, Geppo; Meschini, Maria Chiara; Nesti, Claudia; Tozzi, Giulia; Petruzzella, Vittoria; Piemonte, Fiorella; Bisceglia, Luigi; Bruno, Claudio; Dionisi-Vici, Carlo; D'Amico, Adele; Fattori, Fabiana; Carrozzo, Rosalba; Salviati, Leonardo; Santorelli, Filippo M; Bertini, Enrico

2013-01-01

Recessive mutations in the mitochondrial arginyl-transfer RNA synthetase (RARS2) gene have been associated with early onset encephalopathy with signs of oxidative phosphorylation defects classified as pontocerebellar hypoplasia 6. We describe clinical, neuroimaging and molecular features on five patients from three unrelated families who displayed mutations in RARS2. All patients rapidly developed a neonatal or early-infantile epileptic encephalopathy with intractable seizures. The long-term follow-up revealed a virtual absence of psychomotor development, progressive microcephaly, and feeding difficulties. Mitochondrial respiratory chain enzymes in muscle and fibroblasts were normal in two. Blood and CSF lactate was abnormally elevated in all five patients at early stages while appearing only occasionally abnormal with the progression of the disease. Cerebellar vermis hypoplasia with normal aspect of the cerebral and cerebellar hemispheres appeared within the first months of life at brain MRI. In three patients follow-up neuroimaging revealed a progressive pontocerebellar and cerebral cortical atrophy. Molecular investigations of RARS2 disclosed the c.25A>G/p.I9V and the c.1586+3A>T in family A, the c.734G>A/p.R245Q and the c.1406G>A/p.R469H in family B, and the c.721T>A/p.W241R and c.35A>G/p.Q12R in family C. Functional complementation studies in Saccharomyces cerevisiae showed that mutation MSR1-R531H (equivalent to human p.R469H) abolished respiration whereas the MSR1-R306Q strain (corresponding to p.R245Q) displayed a reduced growth on non-fermentable YPG medium. Although mutations functionally disrupted yeast we found a relatively well preserved arginine aminoacylation of mitochondrial tRNA. Clinical and neuroimaging findings are important clues to raise suspicion and to reach diagnostic accuracy for RARS2 mutations considering that biochemical abnormalities may be absent in muscle biopsy.

Temporary Hearing Threshold Shift in Healthy Volunteers with Hearing Protection Caused by Acoustic Noise Exposure during 3-T Multisequence MR Neuroimaging.

PubMed

Jin, Chao; Li, Huan; Li, Xianjun; Wang, Miaomiao; Liu, Congcong; Guo, Jianxin; Yang, Jian

2018-02-01

Purpose To determine whether a single 51-minute exposure to acoustic noise during 3-T multisequence magnetic resonance (MR) neuroimaging could affect the hearing threshold of healthy adults with earplugs and sponge mats as hearing protection. Materials and Methods With earplugs and motion-refraining sponge mats as hearing protection, 26 healthy young adults underwent 3-T MR neuroimaging imaging that included T1-weighted three-dimensional gradient-echo sequence, T2-weighted fast spin-echo sequence, diffusion-tensor imaging, diffusion-kurtosis imaging, T2*-weighted three-dimensional multiecho gradient-echo sequence, and blood oxygen level-dependent imaging. Automated auditory brainstem response (ABR) was used to measure the hearing thresholds within 24 hours before, within 20 minutes after, and 25 days after the MR examination. One-way repeated-measure analysis of variance with Bonferroni adjustment was used to compare automated ABR results among the three tests and partial η 2 (η p 2 ) was reported as a measure of effect size. Results Automated ABR results showed significantly increased mean threshold shift of 5.0 dB ± 8.1 (standard deviation) (left ear: 4.8 dB ± 9.2 [95% confidence interval: 1.09, 8.53], η p 2 = 0.221, P = .013; right ear: 5.2 dB ± 6.9 [95% confidence interval: 2.36, 8.02], η p 2 = 0.364, P = .001) immediately after the MR examination compared with the baseline study. This shift is below the temporary threshold shift of 40-50 dB that is associated with cochlea nerve changes. Automated ABR obtained at day 25 after MR imaging showed no significant differences from baseline (left ear: -2.3 dB ± 8.6 [95% confidence interval: -5.79, 1.78], η p 2 = 0.069, P = .185; right ear: 0.4 dB ± 7.3 [95% confidence interval: -3.35, 2.58], η p 2 = 0.003, P = .791). Conclusion A 3-T MR neuroimaging examination with the acoustic noise at equivalent sound pressure level of 103.5-111.3 dBA lasting 51 minutes can cause temporary hearing threshold shift in healthy volunteers with hearing protection. © RSNA, 2017.

Utilization of a multimedia PACS workstation for surgical planning of epilepsy

NASA Astrophysics Data System (ADS)

Soo Hoo, Kent; Wong, Stephen T.; Hawkins, Randall A.; Knowlton, Robert C.; Laxer, Kenneth D.; Rowley, Howard A.

1997-05-01

Surgical treatment of temporal lobe epilepsy requires the localization of the epileptogenic zone for surgical resection. Currently, clinicians utilize electroencephalography, various neuroimaging modalities, and psychological tests together to determine the location of this zone. We investigate how a multimedia neuroimaging workstation built on top of the UCSF Picture Archiving and Communication System can be used to aid surgical planning of epilepsy and related brain diseases. This usage demonstrates the ability of the workstation to retrieve image and textural data from PACS and other image sources, register multimodality images, visualize and render 3D data sets, analyze images, generate new image and text data from the analysis, and organize all data in a relational database management system.

Neuroimaging and clinical findings in a case of linear scleroderma en coup de sabre.

PubMed

Duman, Ikram E; Ekinci, Gazanfer

2018-06-01

Linear scleroderma "en coup de sabre" is a subset of localized scleroderma with band-like sclerotic lesions typically involving the frontoparietal regions of the scalp. En coup de sabre and Parry-Romberg syndrome are variants of linear morphea on the head and neck that can be associated with neurologic manifestations. On imaging, patients may have lesions in the cerebrum ipsilateral to the scalp abnormality. We present a case of an 8-year-old girl with a left frontoparietal "en coup de sabre" scalp lesion and describe the neuroimaging findings of frontoparietal white matter lesion discovered incidentally on routine magnetic resonance imaging. The patient had no neurologic symptoms given the lesion identified.

Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms.

PubMed

Zhang, Miaomiao; Wells, William M; Golland, Polina

2017-10-01

We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space. Copyright © 2017 Elsevier B.V. All rights reserved.

Fermion localization on a split brane

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

Chumbes, A. E. R.; Vasquez, A. E. O.; Hott, M. B.

2011-05-15

In this work we analyze the localization of fermions on a brane embedded in five-dimensional, warped and nonwarped, space-time. In both cases we use the same nonlinear theoretical model with a nonpolynomial potential featuring a self-interacting scalar field whose minimum energy solution is a soliton (a kink) which can be continuously deformed into a two-kink. Thus a single brane splits into two branes. The behavior of spin 1/2 fermions wave functions on the split brane depends on the coupling of fermions to the scalar field and on the geometry of the space-time.

PubMed Central

VANNI, S.; CASATI, C.; MORONI, F.; RISSO, M.; OTTAVIANI, M.; NAZERIAN, P.; GRIFONI, S.; VANNUCCHI, P.

2014-01-01

SUMMARY Vertigo is generally due to a benign disorder, but it is the most common symptom associated with misdiagnosis of stroke. In this pilot study, we preliminarily assessed the diagnostic performance of a structured bedside algorithm to differentiate central from non-central acute vertigo (AV). Adult patients presenting to a single Emergency Department with vertigo were evaluated with STANDING (SponTAneous Nystagmus, Direction, head Impulse test, standiNG) by one of five trained emergency physicians or evaluated ordinarily by the rest of the medical staff (control group). The gold standard was a complete audiologic evaluation by a clinicians who are experts in assessing dizzy patients and neuroimaging. Reliability, sensibility and specificity of STANDING were calculated. Moreover, to evaluate the potential clinical impact of STANDING, neuroimaging and hospitalisation rates were compared with control group. A total of 292 patients were included, and 48 (16.4%) had a diagnosis of central AV. Ninety-eight (33.4%) patients were evaluated with STANDING. The test had good interobserver agreement (k = 0.76), with very high sensitivity (100%, 95%CI 72.3-100%) and specificity (94.3%, 95%CI 90.7-94.3%). Furthermore, hospitalisation and neuroimaging test rates were lower in the STANDING than in the control group (27.6% vs. 50.5% and 31.6% vs. 71.1%, respectively). In conclusion, STANDING seems to be a promising simple structured bedside algorithm that in this preliminary study identified central AV with a very high sensitivity, and was associated with significant reduction of neuroimaging and hospitalisation rates. PMID:25762835

Comparison of three-dimensional multi-segmental foot models used in clinical gait laboratories.

PubMed

Nicholson, Kristen; Church, Chris; Takata, Colton; Niiler, Tim; Chen, Brian Po-Jung; Lennon, Nancy; Sees, Julie P; Henley, John; Miller, Freeman

2018-05-16

Many skin-mounted three-dimensional multi-segmented foot models are currently in use for gait analysis. Evidence regarding the repeatability of models, including between trial and between assessors, is mixed, and there are no between model comparisons of kinematic results. This study explores differences in kinematics and repeatability between five three-dimensional multi-segmented foot models. The five models include duPont, Heidelberg, Oxford Child, Leardini, and Utah. Hind foot, forefoot, and hallux angles were calculated with each model for ten individuals. Two physical therapists applied markers three times to each individual to assess within and between therapist variability. Standard deviations were used to evaluate marker placement variability. Locally weighted regression smoothing with alpha-adjusted serial T tests analysis was used to assess kinematic similarities. All five models had similar variability, however, the Leardini model showed high standard deviations in plantarflexion/dorsiflexion angles. P-value curves for the gait cycle were used to assess kinematic similarities. The duPont and Oxford models had the most similar kinematics. All models demonstrated similar marker placement variability. Lower variability was noted in the sagittal and coronal planes compared to rotation in the transverse plane, suggesting a higher minimal detectable change when clinically considering rotation and a need for additional research. Between the five models, the duPont and Oxford shared the most kinematic similarities. While patterns of movement were very similar between all models, offsets were often present and need to be considered when evaluating published data. Copyright © 2018 Elsevier B.V. All rights reserved.

Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review.

PubMed

Sarica, Alessia; Cerasa, Antonio; Quattrone, Aldo

2017-01-01

Objective: Machine learning classification has been the most important computational development in the last years to satisfy the primary need of clinicians for automatic early diagnosis and prognosis. Nowadays, Random Forest (RF) algorithm has been successfully applied for reducing high dimensional and multi-source data in many scientific realms. Our aim was to explore the state of the art of the application of RF on single and multi-modal neuroimaging data for the prediction of Alzheimer's disease. Methods: A systematic review following PRISMA guidelines was conducted on this field of study. In particular, we constructed an advanced query using boolean operators as follows: ("random forest" OR "random forests") AND neuroimaging AND ("alzheimer's disease" OR alzheimer's OR alzheimer) AND (prediction OR classification) . The query was then searched in four well-known scientific databases: Pubmed, Scopus, Google Scholar and Web of Science. Results: Twelve articles-published between the 2007 and 2017-have been included in this systematic review after a quantitative and qualitative selection. The lesson learnt from these works suggest that when RF was applied on multi-modal data for prediction of Alzheimer's disease (AD) conversion from the Mild Cognitive Impairment (MCI), it produces one of the best accuracies to date. Moreover, the RF has important advantages in terms of robustness to overfitting, ability to handle highly non-linear data, stability in the presence of outliers and opportunity for efficient parallel processing mainly when applied on multi-modality neuroimaging data, such as, MRI morphometric, diffusion tensor imaging, and PET images. Conclusions: We discussed the strengths of RF, considering also possible limitations and by encouraging further studies on the comparisons of this algorithm with other commonly used classification approaches, particularly in the early prediction of the progression from MCI to AD.

Experimental evidence for improved neuroimaging interpretation using three-dimensional graphic models.

PubMed

Ruisoto, Pablo; Juanes, Juan Antonio; Contador, Israel; Mayoral, Paula; Prats-Galino, Alberto

2012-01-01

Three-dimensional (3D) or volumetric visualization is a useful resource for learning about the anatomy of the human brain. However, the effectiveness of 3D spatial visualization has not yet been assessed systematically. This report analyzes whether 3D volumetric visualization helps learners to identify and locate subcortical structures more precisely than classical cross-sectional images based on a two dimensional (2D) approach. Eighty participants were assigned to each experimental condition: 2D cross-sectional visualization vs. 3D volumetric visualization. Both groups were matched for age, gender, visual-spatial ability, and previous knowledge of neuroanatomy. Accuracy in identifying brain structures, execution time, and level of confidence in the response were taken as outcome measures. Moreover, interactive effects between the experimental conditions (2D vs. 3D) and factors such as level of competence (novice vs. expert), image modality (morphological and functional), and difficulty of the structures were analyzed. The percentage of correct answers (hit rate) and level of confidence in responses were significantly higher in the 3D visualization condition than in the 2D. In addition, the response time was significantly lower for the 3D visualization condition in comparison with the 2D. The interaction between the experimental condition (2D vs. 3D) and difficulty was significant, and the 3D condition facilitated the location of difficult images more than the 2D condition. 3D volumetric visualization helps to identify brain structures such as the hippocampus and amygdala, more accurately and rapidly than conventional 2D visualization. This paper discusses the implications of these results with regards to the learning process involved in neuroimaging interpretation. Copyright © 2012 American Association of Anatomists.

A Model for Predicting Cognitive and Emotional Health from Structural and Functional Neurocircuitry Following Traumatic Brain Injury

DTIC Science & Technology

2017-10-01

Neuroimaging 2006 Reviewer, Journal of Abnormal Psychology 2006 Reviewer, Psychopharmacology 2006 Reviewer, Developmental Science 2006 Reviewer...This study will address this problem by collecting measures of white matter integrity and concomitant neuropsychological status at five time points...hypothesize that structural white matter tract disintegrity will underlie abnormalities in functional connectivity, neurocognitive performance and

Mental Imagery and Post-Traumatic Stress Disorder: A Neuroimaging and Experimental Psychopathology Approach to Intrusive Memories of Trauma

PubMed Central

Clark, Ian A.; Mackay, Clare E.

2015-01-01

This hypothesis and theory paper presents a pragmatic framework to help bridge the clinical presentation and neuroscience of intrusive memories following psychological trauma. Intrusive memories are a hallmark symptom of post-traumatic stress disorder (PTSD). However, key questions, including those involving etiology, remain. In particular, we know little about the brain mechanisms involved in why only some moments of the trauma return as intrusive memories while others do not. We first present an overview of the patient experience of intrusive memories and the neuroimaging studies that have investigated intrusive memories in PTSD patients. Next, one mechanism of how to model intrusive memories in the laboratory, the trauma film paradigm, is examined. In particular, we focus on studies combining the trauma film paradigm with neuroimaging. Stemming from the clinical presentation and our current understanding of the processes involved in intrusive memories, we propose a framework in which an intrusive memory comprises five component parts; autobiographical (trauma) memory, involuntary recall, negative emotions, attention hijacking, and mental imagery. Each component part is considered in turn, both behaviorally and from a brain imaging perspective. A mapping of these five components onto our understanding of the brain is described. Unanswered questions that exist in our understanding of intrusive memories are considered using the proposed framework. Overall, we suggest that mental imagery is key to bridging the experience, memory, and intrusive recollection of the traumatic event. Further, we suggest that by considering the brain mechanisms involved in the component parts of an intrusive memory, in particular mental imagery, we may be able to aid the development of a firmer bridge between patients’ experiences of intrusive memories and the clinical neuroscience behind them. PMID:26257660

Finding Imaging Patterns of Structural Covariance via Non-Negative Matrix Factorization

PubMed Central

Sotiras, Aristeidis; Resnick, Susan M.; Davatzikos, Christos

2015-01-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. PMID:25497684

The Role of Functional Neuroimaging in Pre-Surgical Epilepsy Evaluation

PubMed Central

Pittau, Francesca; Grouiller, Frédéric; Spinelli, Laurent; Seeck, Margitta; Michel, Christoph M.; Vulliemoz, Serge

2014-01-01

The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy. PMID:24715886

[Neuroimaging and Blood Biomarkers in Functional Prognosis after Stroke].

PubMed

Branco, João Paulo; Costa, Joana Santos; Sargento-Freitas, João; Oliveira, Sandra; Mendes, Bruno; Laíns, Jorge; Pinheiro, João

2016-11-01

Stroke remains one of the leading causes of morbidity and mortality around the world and it is associated with an important long-term functional disability. Some neuroimaging resources and certain peripheral blood or cerebrospinal fluid proteins can give important information about etiology, therapeutic approach, follow-up and functional prognosis in acute ischemic stroke patients. However, among the scientific community, there is currently more interest in the stroke vital prognosis over the functional prognosis. Predicting the functional prognosis during acute phase would allow more objective rehabilitation programs and better management of the available resources. The aim of this work is to review the potential role of acute phase neuroimaging and blood biomarkers as functional recovery predictors after ischemic stroke. Review of the literature published between 2005 and 2015, in English, using the terms "ischemic stroke", "neuroimaging" e "blood biomarkers". We included nine studies, based on abstract reading. Computerized tomography, transcranial doppler ultrasound and diffuse magnetic resonance imaging show potential predictive value, based on the blood flow study and the evaluation of stroke's volume and localization, especially when combined with the National Institutes of Health Stroke Scale. Several biomarkers have been studied as diagnostic, risk stratification and prognostic tools, namely the S100 calcium binding protein B, C-reactive protein, matrix metalloproteinases and cerebral natriuretic peptide. Although some biomarkers and neuroimaging techniques have potential predictive value, none of the studies were able to support its use, alone or in association, as a clinically useful functionality predictor model. All the evaluated markers were considered insufficient to predict functional prognosis at three months, when applied in the first hours after stroke. Additional studies are necessary to identify reliable predictive markers for functional prognosis after ischemic stroke.

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.

Engagement of large-scale networks is related to individual differences in inhibitory control

PubMed Central

Congdon, Eliza; Mumford, Jeanette A.; Cohen, Jessica R.; Galvan, Adriana; Aron, Adam R.; Xue, Gui; Miller, Eric; Poldrack, Russell A.

2010-01-01

Understanding which brain regions regulate the execution, and suppression, of goal-directed behavior has implications for a number of areas of research. In particular, understanding which brain regions engaged during tasks requiring the execution and inhibition of a motor response provides insight into the mechanisms underlying individual differences in response inhibition ability. However, neuroimaging studies examing the relation between activation and stopping have been inconsistent regarding the direction of the relationship, and also regarding the anatomical location of regions that correlate with behavior. These limitations likely arise from the relatively low power of vox-elwise correlations with small sample sizes. Here, we pooled data over five separate fMRI studies of the Stop-signal task in order to obtain a sufficiently large sample size to robustly detect brain/behavior correlations. In addition, rather than performing mass univariate correlation analysis across all voxels, we increased statistical power by reducing the dimensionality of the data set using independent components analysis and then examined correlations between behavior and the resulting component scores. We found that components reflecting activity in regions thought to be involved in stopping were associated with better stopping ability, while activity in a default-mode network was associated with poorer stopping ability across individuals. These results clearly show a relationship between individual differences in stopping ability in specific activated networks, including regions known to be critical for the behavior. The results also highlight the usefulness of using dimensionality reduction to increase the power to detect brain/behavior correlations in individual differences research. PMID:20600962

Gravity localization in sine-Gordon braneworlds

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

Cruz, W.T., E-mail: wilamicruz@gmail.com; Maluf, R.V., E-mail: r.v.maluf@fisica.ufc.br; Sousa, L.J.S., E-mail: luisjose@fisica.ufc.br

2016-01-15

In this work we study two types of five-dimensional braneworld models given by sine-Gordon potentials. In both scenarios, the thick brane is generated by a real scalar field coupled to gravity. We focus our investigation on the localization of graviton field and the behaviour of the massive spectrum. In particular, we analyse the localization of massive modes by means of a relative probability method in a Quantum Mechanics context. Initially, considering a scalar field sine-Gordon potential, we find a localized state to the graviton at zero mode. However, when we consider a double sine-Gordon potential, the brane structure is changedmore » allowing the existence of massive resonant states. The new results show how the existence of an internal structure can aid in the emergence of massive resonant modes on the brane.« less

Subcortical volume and cortical surface architecture in women with acute and remitted anorexia nervosa: An exploratory neuroimaging study.

PubMed

Miles, Amy E; Voineskos, Aristotle N; French, Leon; Kaplan, Allan S

2018-07-01

Anorexia nervosa (AN) is a highly heritable psychiatric disorder characterized by starvation and emaciation and associated with changes in brain structure. The precise nature of these changes remains unclear, as does their developmental time course and capacity for reversal with weight-restoration. In this comprehensive neuroimaging study, we sought to characterize these changes by measuring subcortical volume and cortical surface architecture in women with acute and remitted AN. Structural magnetic resonance imaging data was acquired from underweight women with a current diagnosis of AN (acAN: n = 23), weight-recovered women with a past diagnosis of AN (recAN: n = 24), and female controls (HC: n = 24). Subcortical segmentation and cortical surface reconstruction were performed with FreeSurfer 6.0.0, and group differences in regional volume and vertex-wise, cortex-wide thickness, surface area, and local gyrification index (LGI), a measure of folding, were tested with separate univariate analyses of covariance. Mean hippocampal and thalamic volumes were significantly reduced in acAN participants, as was mean cortical thickness in four frontal and temporal clusters. Mean LGI was significantly reduced in acAN and recAN participants in five frontal and parietal clusters. No significant group differences in cortical surface area were detected. Reductions in subcortical volume, cortical thickness, and right postcentral LGI were unique to women with acute AN, indicating state-dependence and pointing towards cellular remodeling and sulcal widening as consequences of disease manifestation. Reductions in bilateral frontal LGI were observed in women with acute and remitted AN, suggesting a role of atypical neurodevelopment in disease vulnerability. Copyright © 2018. Published by Elsevier Ltd.

Clinical and Electrographic Correlates of Bilateral Independent Periodic Discharges.

PubMed

Freund, Brin; Gugger, James J; Reynolds, Alexandra; Tatum, William O; Claassen, Jan; Kaplan, Peter W

2018-05-01

Periodic discharges (PDs) are EEG patterns denoting brain dysfunction and ictal tendency. Their exact meaning regarding etiology and outcomes is not well known. In particular, bilateral independent PDs (BIPDs) are poorly described. We performed a retrospective, multicenter study evaluating neuroimaging, epileptic, clinical, and EEG correlates of BIPDs. Twenty-five patients studied with a mean Glasgow Coma Scale 6.5 and modified Rankin scale 3.9 who underwent EEG monitoring, mean duration 287 hours (range 0.75-3,216). Most common causes of BIPDs were cardiac arrest, Central Nervous System infections, and acute/chronic ischemic/hemorrhagic stroke. Most had subcortical and cortical injuries on neuroimaging. Most of the PDs ranged from 0.5 to 2 Hz in frequency, were of multiple phase types, and localized to the frontal head regions. Eighteen of 25 patients had clinical or electrographic seizures. There was a trend toward seizures in those with BIPDs with a history of epilepsy (P = 0.08) and acute metabolic dysfunction (P = 0.08), particularly with coincident acute structural lesions (P = 0.05). Seizures were predicted by bilaterally symmetric frequencies (P = 0.02) and trended toward higher likelihood with PD frequency <2 Hz (P = 0.08). Two of 25 patients survived past discharge with modified Rankin scale <3. Cardiac arrest was associated with withdrawal of life-sustaining therapy (P < 0.001). BIPDs arise from acute and chronic neurologic injuries, often associated with metabolic dysfunction. Outcomes are poor in this population. Seizures are common, particularly in patients with PDs that are of a lower frequency or are symmetric in frequency. Further study is warranted to evaluate the association between BIPDs and seizures, as well as functional and longer term outcomes.

Perfusion MRI: The Five Most Frequently Asked Clinical Questions

PubMed Central

Essig, Marco; Nguyen, Thanh Binh; Shiroishi, Mark S.; Saake, Marc; Provenzale, James M.; Enterline, David S.; Anzalone, Nicoletta; Dörfler, Arnd; Rovira, Àlex; Wintermark, Max; Law, Meng

2013-01-01

OBJECTIVE This article addresses questions that radiologists frequently ask when planning, performing, processing, and interpreting MRI perfusion studies in CNS imaging. CONCLUSION Perfusion MRI is a promising tool in assessing stroke, brain tumors, and neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols. PMID:23971482

Two-Dimensional Nonlinear Finite Element Analysis of CMC Microstructures

NASA Technical Reports Server (NTRS)

Mital, Subodh K.; Goldberg, Robert K.; Bonacuse, Peter J.

2012-01-01

A research program has been developed to quantify the effects of the microstructure of a woven ceramic matrix composite and its variability on the effective properties and response of the material. In order to characterize and quantify the variations in the microstructure of a five harness satin weave, chemical vapor infiltrated (CVI) SiC/SiC composite material, specimens were serially sectioned and polished to capture images that detailed the fiber tows, matrix, and porosity. Open source quantitative image analysis tools were then used to isolate the constituents, from which two dimensional finite element models were generated which approximated the actual specimen section geometry. A simplified elastic-plastic model, wherein all stress above yield is redistributed to lower stress regions, is used to approximate the progressive damage behavior for each of the composite constituents. Finite element analyses under in-plane tensile loading were performed to examine how the variability in the local microstructure affected the macroscopic stress-strain response of the material as well as the local initiation and progression of damage. The macroscopic stress-strain response appeared to be minimally affected by the variation in local microstructure, but the locations where damage initiated and propagated appeared to be linked to specific aspects of the local microstructure.

Bi-level Multi-Source Learning for Heterogeneous Block-wise Missing Data

PubMed Central

Xiang, Shuo; Yuan, Lei; Fan, Wei; Wang, Yalin; Thompson, Paul M.; Ye, Jieping

2013-01-01

Bio-imaging technologies allow scientists to collect large amounts of high-dimensional data from multiple heterogeneous sources for many biomedical applications. In the study of Alzheimer's Disease (AD), neuroimaging data, gene/protein expression data, etc., are often analyzed together to improve predictive power. Joint learning from multiple complementary data sources is advantageous, but feature-pruning and data source selection are critical to learn interpretable models from high-dimensional data. Often, the data collected has block-wise missing entries. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), most subjects have MRI and genetic information, but only half have cerebrospinal fluid (CSF) measures, a different half has FDG-PET; only some have proteomic data. Here we propose how to effectively integrate information from multiple heterogeneous data sources when data is block-wise missing. We present a unified “bi-level” learning model for complete multi-source data, and extend it to incomplete data. Our major contributions are: (1) our proposed models unify feature-level and source-level analysis, including several existing feature learning approaches as special cases; (2) the model for incomplete data avoids imputing missing data and offers superior performance; it generalizes to other applications with block-wise missing data sources; (3) we present efficient optimization algorithms for modeling complete and incomplete data. We comprehensively evaluate the proposed models including all ADNI subjects with at least one of four data types at baseline: MRI, FDG-PET, CSF and proteomics. Our proposed models compare favorably with existing approaches. PMID:23988272

Bi-level multi-source learning for heterogeneous block-wise missing data.

PubMed

Xiang, Shuo; Yuan, Lei; Fan, Wei; Wang, Yalin; Thompson, Paul M; Ye, Jieping

2014-11-15

Bio-imaging technologies allow scientists to collect large amounts of high-dimensional data from multiple heterogeneous sources for many biomedical applications. In the study of Alzheimer's Disease (AD), neuroimaging data, gene/protein expression data, etc., are often analyzed together to improve predictive power. Joint learning from multiple complementary data sources is advantageous, but feature-pruning and data source selection are critical to learn interpretable models from high-dimensional data. Often, the data collected has block-wise missing entries. In the Alzheimer's Disease Neuroimaging Initiative (ADNI), most subjects have MRI and genetic information, but only half have cerebrospinal fluid (CSF) measures, a different half has FDG-PET; only some have proteomic data. Here we propose how to effectively integrate information from multiple heterogeneous data sources when data is block-wise missing. We present a unified "bi-level" learning model for complete multi-source data, and extend it to incomplete data. Our major contributions are: (1) our proposed models unify feature-level and source-level analysis, including several existing feature learning approaches as special cases; (2) the model for incomplete data avoids imputing missing data and offers superior performance; it generalizes to other applications with block-wise missing data sources; (3) we present efficient optimization algorithms for modeling complete and incomplete data. We comprehensively evaluate the proposed models including all ADNI subjects with at least one of four data types at baseline: MRI, FDG-PET, CSF and proteomics. Our proposed models compare favorably with existing approaches. © 2013 Elsevier Inc. All rights reserved.

Functional specializations in human cerebral cortex analyzed using the Visible Man surface-based atlas

NASA Technical Reports Server (NTRS)

Drury, H. A.; Van Essen, D. C.

1997-01-01

We used surface-based representations to analyze functional specializations in the human cerebral cortex. A computerized reconstruction of the cortical surface of the Visible Man digital atlas was generated and transformed to the Talairach coordinate system. This surface was also flattened and used to establish a surface-based coordinate system that respects the topology of the cortical sheet. The linkage between two-dimensional and three-dimensional representations allows the locations of published neuroimaging activation foci to be stereotaxically projected onto the Visible Man cortical flat map. An analysis of two activation studies related to the hearing and reading of music and of words illustrates how this approach permits the systematic estimation of the degree of functional segregation and of potential functional overlap for different aspects of sensory processing.

Differential Brain Development with Low and High IQ in Attention-Deficit/Hyperactivity Disorder

PubMed Central

de Zeeuw, Patrick; Schnack, Hugo G.; van Belle, Janna; Weusten, Juliette; van Dijk, Sarai; Langen, Marieke; Brouwer, Rachel M.; van Engeland, Herman; Durston, Sarah

2012-01-01

Attention-Deficit/Hyperactivity Disorder (ADHD) and intelligence (IQ) are both heritable phenotypes. Overlapping genetic effects have been suggested to influence both, with neuroimaging work suggesting similar overlap in terms of morphometric properties of the brain. Together, this evidence suggests that the brain changes characteristic of ADHD may vary as a function of IQ. This study investigated this hypothesis in a sample of 108 children with ADHD and 106 typically developing controls, who participated in a cross-sectional anatomical MRI study. A subgroup of 64 children also participated in a diffusion tensor imaging scan. Brain volumes, local cortical thickness and average cerebral white matter microstructure were analyzed in relation to diagnostic group and IQ. Dimensional analyses investigated possible group differences in the relationship between anatomical measures and IQ. Second, the groups were split into above and below median IQ subgroups to investigate possible differences in the trajectories of cortical development. Dimensionally, cerebral gray matter volume and cerebral white matter microstructure were positively associated with IQ for controls, but not for ADHD. In the analyses of the below and above median IQ subgroups, we found no differences from controls in cerebral gray matter volume in ADHD with below-median IQ, but a delay of cortical development in a number of regions, including prefrontal areas. Conversely, in ADHD with above-median IQ, there were significant reductions from controls in cerebral gray matter volume, but no local differences in the trajectories of cortical development. In conclusion, the basic relationship between IQ and neuroanatomy appears to be altered in ADHD. Our results suggest that there may be multiple brain phenotypes associated with ADHD, where ADHD combined with above median IQ is characterized by small, more global reductions in brain volume that are stable over development, whereas ADHD with below median IQ is associated more with a delay of cortical development. PMID:22536435

Differential Sources for 2 Neural Signatures of Target Detection: An Electrocorticography Study.

PubMed

Kam, J W Y; Szczepanski, S M; Canolty, R T; Flinker, A; Auguste, K I; Crone, N E; Kirsch, H E; Kuperman, R A; Lin, J J; Parvizi, J; Knight, R T

2018-01-01

Electrophysiology and neuroimaging provide conflicting evidence for the neural contributions to target detection. Scalp electroencephalography (EEG) studies localize the P3b event-related potential component mainly to parietal cortex, whereas neuroimaging studies report activations in both frontal and parietal cortices. We addressed this discrepancy by examining the sources that generate the target-detection process using electrocorticography (ECoG). We recorded ECoG activity from cortex in 14 patients undergoing epilepsy monitoring, as they performed an auditory or visual target-detection task. We examined target-related responses in 2 domains: high frequency band (HFB) activity and the P3b. Across tasks, we observed a greater proportion of electrodes that showed target-specific HFB power relative to P3b over frontal cortex, but their proportions over parietal cortex were comparable. Notably, there was minimal overlap in the electrodes that showed target-specific HFB and P3b activity. These results revealed that the target-detection process is characterized by at least 2 different neural markers with distinct cortical distributions. Our findings suggest that separate neural mechanisms are driving the differential patterns of activity observed in scalp EEG and neuroimaging studies, with the P3b reflecting EEG findings and HFB activity reflecting neuroimaging findings, highlighting the notion that target detection is not a unitary phenomenon. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Can emergency physicians accurately and reliably assess acute vertigo in the emergency department?

PubMed

Vanni, Simone; Nazerian, Peiman; Casati, Carlotta; Moroni, Federico; Risso, Michele; Ottaviani, Maddalena; Pecci, Rudi; Pepe, Giuseppe; Vannucchi, Paolo; Grifoni, Stefano

2015-04-01

To validate a clinical diagnostic tool, used by emergency physicians (EPs), to diagnose the central cause of patients presenting with vertigo, and to determine interrater reliability of this tool. A convenience sample of adult patients presenting to a single academic ED with isolated vertigo (i.e. vertigo without other neurological deficits) was prospectively evaluated with STANDING (SponTAneousNystagmus, Direction, head Impulse test, standiNG) by five trained EPs. The first step focused on the presence of spontaneous nystagmus, the second on the direction of nystagmus, the third on head impulse test and the fourth on gait. The local standard practice, senior audiologist evaluation corroborated by neuroimaging when deemed appropriate, was considered the reference standard. Sensitivity and specificity of STANDING were calculated. On the first 30 patients, inter-observer agreement among EPs was also assessed. Five EPs with limited experience in nystagmus assessment volunteered to participate in the present study enrolling 98 patients. Their average evaluation time was 9.9 ± 2.8 min (range 6-17). Central acute vertigo was suspected in 16 (16.3%) patients. There were 13 true positives, three false positives, 81 true negatives and one false negative, with a high sensitivity (92.9%, 95% CI 70-100%) and specificity (96.4%, 95% CI 93-38%) for central acute vertigo according to senior audiologist evaluation. The Cohen's kappas of the first, second, third and fourth steps of the STANDING were 0.86, 0.93, 0.73 and 0.78, respectively. The whole test showed a good inter-observer agreement (k = 0.76, 95% CI 0.45-1). In the hands of EPs, STANDING showed a good inter-observer agreement and accuracy validated against the local standard of care. © 2015 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

The utility of conductive plastic electrodes in prolonged ICU EEG monitoring.

PubMed

Das, Rohit R; Lucey, Brendan P; Chou, Sherry H-Y; Espinosa, Patricio S; Zamani, Amir A; Dworetzky, Barbara A; Bromfield, Edward B; Lee, Jong Woo

2009-01-01

We investigated the feasibility and utilization of conductive plastic electrodes (CPEs) in patients undergoing continuous video-electroencephalographic (EEG) monitoring in the intensive care unit (ICU), and assessed the quality of brain magnetic resonance imaging (MRI) and computed tomography (CT) images obtained during this period. A total of 54 patients were monitored. Seizures were recorded in 16 patients. Twenty-five patients had neuroimaging performed with electrodes in place; 15 MRI and 23 CT scans were performed. All patients had excellent quality anatomical images without clinically significant artifacts, and without any signs or symptoms that raised safety concerns. Recording quality of the EEG was indistinguishable to that achieved with standard gold electrodes. The use of CPEs allowed for uninterrupted EEG recording of patients who required urgent neuroimaging, and decreased the amount of time spent by the technologists required to remove and reattach leads.

The missing link: evolution of the primate cerebellum.

PubMed

MacLeod, Carol

2012-01-01

The cerebellum has too often been seen as the "little brain," subservient to the "big brain," the cerebrum. That is changing, as neuroimaging uncovers the cerebellum as the "missing link" in the neurological underpinnings of many cognitive domains. Connections between the neocortex and the cerebellum are now more precisely defined, with functionally localized areas of cerebellar cortex understood for cognitive tasks in humans. Comparative volumetric studies of the primate cerebellum have isolated some elements of circuitry, and our field is moving toward a better integration with the neurosciences in a systematic comparative framework. The next decade may show great advances, as relatively noninvasive techniques of neuroimaging have the potential to build a comparative model of the evolution of primate neurocircuitry. Copyright © 2012 Elsevier B.V. All rights reserved.

Atypical Neuroimaging Manifestations of Linear Scleroderma "en coup de sabre".

PubMed

M Allmendinger, Andrew; A Ricci, Joseph; S Desai, Naman; Viswanadhan, Narayan; Rodriguez, Diana

2015-01-01

Linear scleroderma "en coup de sabre" is a subset of localized scleroderma with band-like sclerotic lesions typically involving the fronto-parietal regions of the scalp. Patients often present with neurologic symptoms. On imaging, patients may have lesions in the cerebrum ipsilateral to the scalp abnormality. Infratentorial lesions and other lesions not closely associated with the overlying scalp abnormality, such as those found in the cerebellum, have been reported, but are extremely uncommon. We present a case of an 8-year-old boy with a left fronto-parietal "en coup de sabre" scalp lesion and describe the neuroimaging findings of a progressively enlarging left cerebellar lesion discovered incidentally on routine magnetic resonance imaging. Interestingly, the patient had no neurologic symptoms given the size of the mass identified.

Atypical Neuroimaging Manifestations of Linear Scleroderma “en coup de sabre”

PubMed Central

M. ALLMENDINGER, Andrew; A. RICCI, Joseph; S. DESAI, Naman; VISWANADHAN, Narayan; RODRIGUEZ, Diana

2015-01-01

Linear scleroderma “en coup de sabre” is a subset of localized scleroderma with band-like sclerotic lesions typically involving the fronto-parietal regions of the scalp. Patients often present with neurologic symptoms. On imaging, patients may have lesions in the cerebrum ipsilateral to the scalp abnormality. Infratentorial lesions and other lesions not closely associated with the overlying scalp abnormality, such as those found in the cerebellum, have been reported, but are extremely uncommon. We present a case of an 8-year-old boy with a left fronto-parietal “en coup de sabre” scalp lesion and describe the neuroimaging findings of a progressively enlarging left cerebellar lesion discovered incidentally on routine magnetic resonance imaging. Interestingly, the patient had no neurologic symptoms given the size of the mass identified. PMID:26401155

Holographic renormalization group and cosmology in theories with quasilocalized gravity

NASA Astrophysics Data System (ADS)

Csáki, Csaba; Erlich, Joshua; Hollowood, Timothy J.; Terning, John

2001-03-01

We study the long distance behavior of brane theories with quasilocalized gravity. The five-dimensional (5D) effective theory at large scales follows from a holographic renormalization group flow. As intuitively expected, the graviton is effectively four dimensional at intermediate scales and becomes five dimensional at large scales. However, in the holographic effective theory the essentially 4D radion dominates at long distances and gives rise to scalar antigravity. The holographic description shows that at large distances the Gregory-Rubakov-Sibiryakov (GRS) model is equivalent to the model recently proposed by Dvali, Gabadadze, and Porrati (DGP), where a tensionless brane is embedded into 5D Minkowski space, with an additional induced 4D Einstein-Hilbert term on the brane. In the holographic description the radion of the GRS model is automatically localized on the tensionless brane, and provides the ghostlike field necessary to cancel the extra graviton polarization of the DGP model. Thus, there is a holographic duality between these theories. This analysis provides physical insight into how the GRS model works at intermediate scales; in particular it sheds light on the size of the width of the graviton resonance, and also demonstrates how the holographic renormalization group can be used as a practical tool for calculations.

Holographic renormalization group and cosmology in theories with quasilocalized gravity

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

Csaki, Csaba; Erlich, Joshua; Hollowood, Timothy J.

2001-03-15

We study the long distance behavior of brane theories with quasilocalized gravity. The five-dimensional (5D) effective theory at large scales follows from a holographic renormalization group flow. As intuitively expected, the graviton is effectively four dimensional at intermediate scales and becomes five dimensional at large scales. However, in the holographic effective theory the essentially 4D radion dominates at long distances and gives rise to scalar antigravity. The holographic description shows that at large distances the Gregory-Rubakov-Sibiryakov (GRS) model is equivalent to the model recently proposed by Dvali, Gabadadze, and Porrati (DGP), where a tensionless brane is embedded into 5D Minkowskimore » space, with an additional induced 4D Einstein-Hilbert term on the brane. In the holographic description the radion of the GRS model is automatically localized on the tensionless brane, and provides the ghostlike field necessary to cancel the extra graviton polarization of the DGP model. Thus, there is a holographic duality between these theories. This analysis provides physical insight into how the GRS model works at intermediate scales; in particular it sheds light on the size of the width of the graviton resonance, and also demonstrates how the holographic renormalization group can be used as a practical tool for calculations.« less

A priori collaboration in population imaging: The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium.

PubMed

Adams, Hieab H H; Hilal, Saima; Schwingenschuh, Petra; Wittfeld, Katharina; van der Lee, Sven J; DeCarli, Charles; Vernooij, Meike W; Katschnig-Winter, Petra; Habes, Mohamad; Chen, Christopher; Seshadri, Sudha; van Duijn, Cornelia M; Ikram, M Kamran; Grabe, Hans J; Schmidt, Reinhold; Ikram, M Arfan

2015-12-01

Virchow-Robin spaces (VRS), or perivascular spaces, are compartments of interstitial fluid enclosing cerebral blood vessels and are potential imaging markers of various underlying brain pathologies. Despite a growing interest in the study of enlarged VRS, the heterogeneity in rating and quantification methods combined with small sample sizes have so far hampered advancement in the field. The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement (UNIVRSE) consortium was established with primary aims to harmonize rating and analysis (www.uconsortium.org). The UNIVRSE consortium brings together 13 (sub)cohorts from five countries, totaling 16,000 subjects and over 25,000 scans. Eight different magnetic resonance imaging protocols were used in the consortium. VRS rating was harmonized using a validated protocol that was developed by the two founding members, with high reliability independent of scanner type, rater experience, or concomitant brain pathology. Initial analyses revealed risk factors for enlarged VRS including increased age, sex, high blood pressure, brain infarcts, and white matter lesions, but this varied by brain region. Early collaborative efforts between cohort studies with respect to data harmonization and joint analyses can advance the field of population (neuro)imaging. The UNIVRSE consortium will focus efforts on other potential correlates of enlarged VRS, including genetics, cognition, stroke, and dementia.

Romans supergravity from five-dimensional holograms

NASA Astrophysics Data System (ADS)

Chang, Chi-Ming; Fluder, Martin; Lin, Ying-Hsuan; Wang, Yifan

2018-05-01

We study five-dimensional superconformal field theories and their holographic dual, matter-coupled Romans supergravity. On the one hand, some recently derived formulae allow us to extract the central charges from deformations of the supersymmetric five-sphere partition function, whose large N expansion can be computed using matrix model techniques. On the other hand, the conformal and flavor central charges can be extracted from the six-dimensional supergravity action, by carefully analyzing its embedding into type I' string theory. The results match on the two sides of the holographic duality. Our results also provide analytic evidence for the symmetry enhancement in five-dimensional superconformal field theories.

Multivariate neural biomarkers of emotional states are categorically distinct

PubMed Central

Kragel, Philip A.

2015-01-01

Understanding how emotions are represented neurally is a central aim of affective neuroscience. Despite decades of neuroimaging efforts addressing this question, it remains unclear whether emotions are represented as distinct entities, as predicted by categorical theories, or are constructed from a smaller set of underlying factors, as predicted by dimensional accounts. Here, we capitalize on multivariate statistical approaches and computational modeling to directly evaluate these theoretical perspectives. We elicited discrete emotional states using music and films during functional magnetic resonance imaging scanning. Distinct patterns of neural activation predicted the emotion category of stimuli and tracked subjective experience. Bayesian model comparison revealed that combining dimensional and categorical models of emotion best characterized the information content of activation patterns. Surprisingly, categorical and dimensional aspects of emotion experience captured unique and opposing sources of neural information. These results indicate that diverse emotional states are poorly differentiated by simple models of valence and arousal, and that activity within separable neural systems can be mapped to unique emotion categories. PMID:25813790

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes

PubMed Central

2013-01-01

Motivation Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. Results We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. Availability The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana. PMID:24564704

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

PubMed

Wang, Yue; Goh, Wilson; Wong, Limsoon; Montana, Giovanni

2013-01-01

Multivariate quantitative traits arise naturally in recent neuroimaging genetics studies, in which both structural and functional variability of the human brain is measured non-invasively through techniques such as magnetic resonance imaging (MRI). There is growing interest in detecting genetic variants associated with such multivariate traits, especially in genome-wide studies. Random forests (RFs) classifiers, which are ensembles of decision trees, are amongst the best performing machine learning algorithms and have been successfully employed for the prioritisation of genetic variants in case-control studies. RFs can also be applied to produce gene rankings in association studies with multivariate quantitative traits, and to estimate genetic similarities measures that are predictive of the trait. However, in studies involving hundreds of thousands of SNPs and high-dimensional traits, a very large ensemble of trees must be inferred from the data in order to obtain reliable rankings, which makes the application of these algorithms computationally prohibitive. We have developed a parallel version of the RF algorithm for regression and genetic similarity learning tasks in large-scale population genetic association studies involving multivariate traits, called PaRFR (Parallel Random Forest Regression). Our implementation takes advantage of the MapReduce programming model and is deployed on Hadoop, an open-source software framework that supports data-intensive distributed applications. Notable speed-ups are obtained by introducing a distance-based criterion for node splitting in the tree estimation process. PaRFR has been applied to a genome-wide association study on Alzheimer's disease (AD) in which the quantitative trait consists of a high-dimensional neuroimaging phenotype describing longitudinal changes in the human brain structure. PaRFR provides a ranking of SNPs associated to this trait, and produces pair-wise measures of genetic proximity that can be directly compared to pair-wise measures of phenotypic proximity. Several known AD-related variants have been identified, including APOE4 and TOMM40. We also present experimental evidence supporting the hypothesis of a linear relationship between the number of top-ranked mutated states, or frequent mutation patterns, and an indicator of disease severity. The Java codes are freely available at http://www2.imperial.ac.uk/~gmontana.

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data

PubMed Central

Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F

2007-01-01

Background Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. Results We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: . Conclusion MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine. PMID:17937818

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data.

PubMed

Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F

2007-10-15

Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: http://sig.biostr.washington.edu/projects/MindSeer. MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine.

The Perfect Neuroimaging-Genetics-Computation Storm: Collision of Petabytes of Data, Millions of Hardware Devices and Thousands of Software Tools

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Zamanyan, Alen; Torri, Federica; Macciardi, Fabio; Hobel, Sam; Moon, Seok Woo; Sung, Young Hee; Jiang, Zhiguo; Labus, Jennifer; Kurth, Florian; Ashe-McNalley, Cody; Mayer, Emeran; Vespa, Paul M.; Van Horn, John D.; Toga, Arthur W.

2013-01-01

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. PMID:23975276

Five-dimensional Yang-Mills-Einstein supergravity on orbifold spacetimes: From phenomenology to M -theory

NASA Astrophysics Data System (ADS)

McReynolds, Sean

Five-dimensional N = 2 Yang-Mills-Einstein supergravity and its couplings to hyper and tensor multiplets are considered on an orbifold spacetime of the form M4 x S1/Gamma, where Gamma is a discrete group. As is well known in such cases, supersymmetry is broken to N = 1 on the orbifold fixed planes, and chiral 4D theories can be obtained from bulk hypermultiplets (or from the coupling of fixed-plane supported fields). Five-dimensional gauge symmetries are broken by boundary conditions for the fields, which are equivalent to some set of Gamma-parity assignments in the orbifold theory, allowing for arbitrary rank reduction. Furthermore, Wilson lines looping from one boundary to the other can break bulk gauge groups, or give rise to vacuum expectation values for scalars on the boundaries, which can result in spontaneous breaking of boundary gauge groups. The broken gauge symmetries do not survive as global symmetries of the low energy theories below the compactification scale due to 4 D minimal couplings to gauge fields. Axionic fields are a generic feature, just as in any compactification of M-theory (or string theory for that matter), and we exhibit the form of this field and its role as the QCD axion, capable of resolving the strong CP problem. The main motivation for the orbifold theories here is taken to be orbifold-GUTS, wherein a unified gauge group is sought in higher dimensions while allowing the orbifold reduction to handle problems such as rapid proton decay, exotic matter, mass hierarchies, etc. To that end, we discuss the allowable minimal SU(5), SO(10) and E6 GUT theories with all fields living in five dimensions. It is argued that, within the class of homogeneous quaternionic scalar manifolds characterizing the hypermultiplet couplings in 5D, supergravity admits a restricted set of theories that yield minimal phenomenological field content. In addition, non-compact gaugings are a novel feature of supergravity theories, and in particular we consider the example of an SU(5,1) YMESGT in which all of the fields of the theory are connected by local (susy and gauge) transformations that are symmetries of the Lagrangian. Such non-compact gaugings allow a novel type of gauge-Higgs unification in higher dimensions. The possibility of boundary-localized fields is considered only via anomaly arguments. (Abstract shortened by UMI.)

TripAdvisor^{N-D}: A Tourism-Inspired High-Dimensional Space Exploration Framework with Overview and Detail.

PubMed

Nam, Julia EunJu; Mueller, Klaus

2013-02-01

Gaining a true appreciation of high-dimensional space remains difficult since all of the existing high-dimensional space exploration techniques serialize the space travel in some way. This is not so foreign to us since we, when traveling, also experience the world in a serial fashion. But we typically have access to a map to help with positioning, orientation, navigation, and trip planning. Here, we propose a multivariate data exploration tool that compares high-dimensional space navigation with a sightseeing trip. It decomposes this activity into five major tasks: 1) Identify the sights: use a map to identify the sights of interest and their location; 2) Plan the trip: connect the sights of interest along a specifyable path; 3) Go on the trip: travel along the route; 4) Hop off the bus: experience the location, look around, zoom into detail; and 5) Orient and localize: regain bearings in the map. We describe intuitive and interactive tools for all of these tasks, both global navigation within the map and local exploration of the data distributions. For the latter, we describe a polygonal touchpad interface which enables users to smoothly tilt the projection plane in high-dimensional space to produce multivariate scatterplots that best convey the data relationships under investigation. Motion parallax and illustrative motion trails aid in the perception of these transient patterns. We describe the use of our system within two applications: 1) the exploratory discovery of data configurations that best fit a personal preference in the presence of tradeoffs and 2) interactive cluster analysis via cluster sculpting in N-D.

Ice Accretion Roughness Measurements and Modeling

NASA Technical Reports Server (NTRS)

McClain, Stephen T.; Vargas, Mario; Tsao, Jen-Ching; Broeren, Andy P.; Lee, Sam

2017-01-01

Roughness on aircraft ice accretions is very important to the overall ice accretion process and to the resulting degradation in aircraft aerodynamic performance. Roughness enhances the local convection leading to more rapid ice accumulation rates, and roughness generates local flow perturbations that lead to higher skin friction. This paper presents 1) a review of the developments in ice shape three-dimensional laser scanning developed at NASA Glenn, 2) a review of the approach of McClain and Kreeger employed to characterize ice roughness evolution on an airfoil surface, and 3) a review of the experimental efforts that have been performed over the last five years to characterize, scale, and model ice roughness evolution physics.

Chaotic oscillator containing memcapacitor and meminductor and its dimensionality reduction analysis.

PubMed

Yuan, Fang; Wang, Guangyi; Wang, Xiaowei

2017-03-01

In this paper, smooth curve models of meminductor and memcapacitor are designed, which are generalized from a memristor. Based on these models, a new five-dimensional chaotic oscillator that contains a meminductor and memcapacitor is proposed. By dimensionality reducing, this five-dimensional system can be transformed into a three-dimensional system. The main work of this paper is to give the comparisons between the five-dimensional system and its dimensionality reduction model. To investigate dynamics behaviors of the two systems, equilibrium points and stabilities are analyzed. And the bifurcation diagrams and Lyapunov exponent spectrums are used to explore their properties. In addition, digital signal processing technologies are used to realize this chaotic oscillator, and chaotic sequences are generated by the experimental device, which can be used in encryption applications.

Incorporating Digisonde Traces into the Ionospheric Data Assimilation Three Dimensional (IDA3D) Algorithm

DTIC Science & Technology

2006-05-11

examined. These data were processed by the Automatic Real Time Ionogram Scaler with True Height ( ARTIST ) [Reinisch and Huang, 1983] program into electron...IDA3D. The data is locally available and previously quality checked. In addition, IDA3D maps using ARTIST -calculated profiles from hand scaled...ionograms are available for comparison. The first test run of the IDA3D used only O-mode autoscaled virtual height profiles from five different digisondes

Response assessment challenges in clinical trials of gliomas.

PubMed

Wen, Patrick Y; Norden, Andrew D; Drappatz, Jan; Quant, Eudocia

2010-01-01

Accurate, reproducible criteria for determining tumor response and progression after therapy are critical for optimal patient care and effective evaluation of novel therapeutic agents. Currently, the most widely used criteria for determining treatment response in gliomas is based on two-dimensional tumor measurements using neuroimaging studies (Macdonald criteria). In recent years, the limitation of these criteria, which only address the contrast-enhancing component of the tumor, have become increasingly apparent. This review discusses challenges that have emerged in assessing response in patients with gliomas and approaches being introduced to address them.

Individual differences in personality traits reflect structural variance in specific brain regions.

PubMed

Gardini, Simona; Cloninger, C Robert; Venneri, Annalena

2009-06-30

Personality dimensions such as novelty seeking (NS), harm avoidance (HA), reward dependence (RD) and persistence (PER) are said to be heritable, stable across time and dependent on genetic and neurobiological factors. Recently a better understanding of the relationship between personality traits and brain structures/systems has become possible due to advances in neuroimaging techniques. This Magnetic Resonance Imaging (MRI) study investigated if individual differences in these personality traits reflected structural variance in specific brain regions. A large sample of eighty five young adult participants completed the Three-dimensional Personality Questionnaire (TPQ) and had their brain imaged with MRI. A voxel-based correlation analysis was carried out between individuals' personality trait scores and grey matter volume values extracted from 3D brain scans. NS correlated positively with grey matter volume in frontal and posterior cingulate regions. HA showed a negative correlation with grey matter volume in orbito-frontal, occipital and parietal structures. RD was negatively correlated with grey matter volume in the caudate nucleus and in the rectal frontal gyrus. PER showed a positive correlation with grey matter volume in the precuneus, paracentral lobule and parahippocampal gyrus. These results indicate that individual differences in the main personality dimensions of NS, HA, RD and PER, may reflect structural variance in specific brain areas.

Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging

NASA Astrophysics Data System (ADS)

Reisman, Matthew David

As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization

PubMed Central

Mankiw, Catherine; Park, Min Tae M.; Reardon, P.K.; Fish, Ari M.; Clasen, Liv S.; Greenstein, Deanna; Blumenthal, Jonathan D.; Lerch, Jason P.; Chakravarty, M. Mallar

2017-01-01

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences—including their spatial distribution, potential biological determinants, and independence from brain volume variation—lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male–female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. PMID:28314818

Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization.

PubMed

Sotiras, Aristeidis; Resnick, Susan M; Davatzikos, Christos

2015-03-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. Copyright © 2014 Elsevier Inc. All rights reserved.

The clinical outcome and neuroimaging of acute encephalopathy after status epilepticus in Dravet syndrome.

PubMed

Tian, Xiaojuan; Ye, Jintang; Zeng, Qi; Zhang, Jing; Yang, Xiaoling; Liu, Aijie; Yang, Zhixian; Liu, Xiaoyan; Wu, Xiru; Zhang, Yuehua

2018-06-01

To analyze the clinical outcome and neuroimaging over a long duration follow-up in the currently largest series of acute encephalopathy after status epilepticus in patients with Dravet syndrome. Clinical and neuroimaging data of patients with Dravet syndrome with a history of acute encephalopathy (coma >24h) after status epilepticus from February 2005 to December 2016 at Peking University First Hospital were reviewed retrospectively. Thirty-five patients (15 males, 20 females) with a history of acute encephalopathy were enrolled from a total of 624 patients with Dravet syndrome (5.6%). The median onset age of acute encephalopathy was 3 years 1 month. The duration of status epilepticus varied between 40 minutes to 12 hours. Thirty-four patients had a high fever when status epilepticus occurred, and only one had a normal temperature. Coma lasted from 2 to 20 days. Twelve patients died and 23 survived with massive neurological regression. The median follow-up time was 2 years 1 month. Neuroimaging of 20 out of 23 survivors during the recovery phase showed diverse degrees of cortical atrophy with or without subcortical lesions. Acute encephalopathy after status epilepticus is more prone to occur in patients with Dravet syndrome who had a high fever. The mortality rate is high in severe cases. Survivors are left with severe neurological sequelae but often with either no seizure or low seizure frequency. Acute encephalopathy is more prone to occur in patients with Dravet syndrome with a high fever. The mortality rate is high for acute encephalopathy after status epilepticus in patients with Dravet syndrome. Survivors have neurological sequelae. © 2018 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.

Incorporating modern neuroscience findings to improve brain-computer interfaces: tracking auditory attention.

PubMed

Wronkiewicz, Mark; Larson, Eric; Lee, Adrian Kc

2016-10-01

Brain-computer interface (BCI) technology allows users to generate actions based solely on their brain signals. However, current non-invasive BCIs generally classify brain activity recorded from surface electroencephalography (EEG) electrodes, which can hinder the application of findings from modern neuroscience research. In this study, we use source imaging-a neuroimaging technique that projects EEG signals onto the surface of the brain-in a BCI classification framework. This allowed us to incorporate prior research from functional neuroimaging to target activity from a cortical region involved in auditory attention. Classifiers trained to detect attention switches performed better with source imaging projections than with EEG sensor signals. Within source imaging, including subject-specific anatomical MRI information (instead of using a generic head model) further improved classification performance. This source-based strategy also reduced accuracy variability across three dimensionality reduction techniques-a major design choice in most BCIs. Our work shows that source imaging provides clear quantitative and qualitative advantages to BCIs and highlights the value of incorporating modern neuroscience knowledge and methods into BCI systems.

Do people become more apathetic as they grow older? A longitudinal study in healthy individuals.

PubMed

Brodaty, Henry; Altendorf, Annette; Withall, Adrienne; Sachdev, Perminder

2010-05-01

The aim of this study was to determine levels, rates and progression of apathy in healthy older persons and to investigate factors associated with its progression. Seventy-six healthy elderly subjects, aged 58-85 years (mean 69.9), who were recruited by general advertisement and through local community groups, participated as a control group for a longitudinal study of stroke patients. Data were collected on demographic, psychological, neuropsychological and neuroimaging (MRI) variables and apathy was rated by informants on the Apathy Evaluation Scale (AES). Apathy scores and rates increased over 5 years, especially in men. Change of apathy was associated with informant ratings of cognitive decline in the years prior to baseline assessment but not to subsequent neuropsychological, neuroimaging or functional changes. Apathy increases with age in otherwise healthy community-dwelling individuals, particularly in men.

Integration of Network Topological and Connectivity Properties for Neuroimaging Classification

PubMed Central

Jie, Biao; Gao, Wei; Wang, Qian; Wee, Chong-Yaw

2014-01-01

Rapid advances in neuroimaging techniques have provided an efficient and noninvasive way for exploring the structural and functional connectivity of the human brain. Quantitative measurement of abnormality of brain connectivity in patients with neurodegenerative diseases, such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD), have also been widely reported, especially at a group level. Recently, machine learning techniques have been applied to the study of AD and MCI, i.e., to identify the individuals with AD/MCI from the healthy controls (HCs). However, most existing methods focus on using only a single property of a connectivity network, although multiple network properties, such as local connectivity and global topological properties, can potentially be used. In this paper, by employing multikernel based approach, we propose a novel connectivity based framework to integrate multiple properties of connectivity network for improving the classification performance. Specifically, two different types of kernels (i.e., vector-based kernel and graph kernel) are used to quantify two different yet complementary properties of the network, i.e., local connectivity and global topological properties. Then, multikernel learning (MKL) technique is adopted to fuse these heterogeneous kernels for neuroimaging classification. We test the performance of our proposed method on two different data sets. First, we test it on the functional connectivity networks of 12 MCI and 25 HC subjects. The results show that our method achieves significant performance improvement over those using only one type of network property. Specifically, our method achieves a classification accuracy of 91.9%, which is 10.8% better than those by single network-property-based methods. Then, we test our method for gender classification on a large set of functional connectivity networks with 133 infants scanned at birth, 1 year, and 2 years, also demonstrating very promising results. PMID:24108708

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: evidence of validity.

PubMed

Frisoni, Giovanni B; Jack, Clifford R; Bocchetta, Martina; Bauer, Corinna; Frederiksen, Kristian S; Liu, Yawu; Preboske, Gregory; Swihart, Tim; Blair, Melanie; Cavedo, Enrica; Grothe, Michel J; Lanfredi, Mariangela; Martinez, Oliver; Nishikawa, Masami; Portegies, Marileen; Stoub, Travis; Ward, Chadwich; Apostolova, Liana G; Ganzola, Rossana; Wolf, Dominik; Barkhof, Frederik; Bartzokis, George; DeCarli, Charles; Csernansky, John G; deToledo-Morrell, Leyla; Geerlings, Mirjam I; Kaye, Jeffrey; Killiany, Ronald J; Lehéricy, Stephane; Matsuda, Hiroshi; O'Brien, John; Silbert, Lisa C; Scheltens, Philip; Soininen, Hilkka; Teipel, Stefan; Waldemar, Gunhild; Fellgiebel, Andreas; Barnes, Josephine; Firbank, Michael; Gerritsen, Lotte; Henneman, Wouter; Malykhin, Nikolai; Pruessner, Jens C; Wang, Lei; Watson, Craig; Wolf, Henrike; deLeon, Mony; Pantel, Johannes; Ferrari, Clarissa; Bosco, Paolo; Pasqualetti, Patrizio; Duchesne, Simon; Duvernoy, Henri; Boccardi, Marina

2015-02-01

An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms. Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

The EADC-ADNI Harmonized Protocol for manual hippocampal segmentation on magnetic resonance: Evidence of validity

PubMed Central

Frisoni, Giovanni B.; Jack, Clifford R.; Bocchetta, Martina; Bauer, Corinna; Frederiksen, Kristian S.; Liu, Yawu; Preboske, Gregory; Swihart, Tim; Blair, Melanie; Cavedo, Enrica; Grothe, Michel J.; Lanfredi, Mariangela; Martinez, Oliver; Nishikawa, Masami; Portegies, Marileen; Stoub, Travis; Ward, Chadwich; Apostolova, Liana G.; Ganzola, Rossana; Wolf, Dominik; Barkhof, Frederik; Bartzokis, George; DeCarli, Charles; Csernansky, John G.; deToledo-Morrell, Leyla; Geerlings, Mirjam I.; Kaye, Jeffrey; Killiany, Ronald J.; Lehéricy, Stephane; Matsuda, Hiroshi; O'Brien, John; Silbert, Lisa C.; Scheltens, Philip; Soininen, Hilkka; Teipel, Stefan; Waldemar, Gunhild; Fellgiebel, Andreas; Barnes, Josephine; Firbank, Michael; Gerritsen, Lotte; Henneman, Wouter; Malykhin, Nikolai; Pruessner, Jens C.; Wang, Lei; Watson, Craig; Wolf, Henrike; deLeon, Mony; Pantel, Johannes; Ferrari, Clarissa; Bosco, Paolo; Pasqualetti, Patrizio; Duchesne, Simon; Duvernoy, Henri; Boccardi, Marina

2015-01-01

Background An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. Methods Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. Results The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). Conclusions The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms. PMID:25267715

Prostate Brachytherapy Seed Reconstruction with Gaussian Blurring and Optimal Coverage Cost

PubMed Central

Lee, Junghoon; Liu, Xiaofeng; Jain, Ameet K.; Song, Danny Y.; Burdette, E. Clif; Prince, Jerry L.; Fichtinger, Gabor

2009-01-01

Intraoperative dosimetry in prostate brachytherapy requires localization of the implanted radioactive seeds. A tomosynthesis-based seed reconstruction method is proposed. A three-dimensional volume is reconstructed from Gaussian-blurred projection images and candidate seed locations are computed from the reconstructed volume. A false positive seed removal process, formulated as an optimal coverage problem, iteratively removes “ghost” seeds that are created by tomosynthesis reconstruction. In an effort to minimize pose errors that are common in conventional C-arms, initial pose parameter estimates are iteratively corrected by using the detected candidate seeds as fiducials, which automatically “focuses” the collected images and improves successive reconstructed volumes. Simulation results imply that the implanted seed locations can be estimated with a detection rate of ≥ 97.9% and ≥ 99.3% from three and four images, respectively, when the C-arm is calibrated and the pose of the C-arm is known. The algorithm was also validated on phantom data sets successfully localizing the implanted seeds from four or five images. In a Phase-1 clinical trial, we were able to localize the implanted seeds from five intraoperative fluoroscopy images with 98.8% (STD=1.6) overall detection rate. PMID:19605321

Perfusion MRI: The Five Most Frequently Asked Technical Questions

PubMed Central

Essig, Marco; Shiroishi, Mark S.; Nguyen, Thanh Binh; Saake, Marc; Provenzale, James M.; Enterline, David; Anzalone, Nicoletta; Dörfler, Arnd; Rovira, Àlex; Wintermark, Max; Law, Meng

2013-01-01

OBJECTIVE This and its companion article address the 10 most frequently asked questions that radiologists face when planning, performing, processing, and interpreting different MR perfusion studies in CNS imaging. CONCLUSION Perfusion MRI is a promising tool in assessing stroke, brain tumors, and patients with neurodegenerative diseases. Most of the impediments that have limited the use of perfusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols. PMID:23255738

Modeling of Melt-Infiltrated SiC/SiC Composite Properties

NASA Technical Reports Server (NTRS)

Mital, Subodh K.; Bednarcyk, Brett A.; Arnold, Steven M.; Lang, Jerry

2009-01-01

The elastic properties of a two-dimensional five-harness melt-infiltrated silicon carbide fiber reinforced silicon carbide matrix (MI SiC/SiC) ceramic matrix composite (CMC) were predicted using several methods. Methods used in this analysis are multiscale laminate analysis, micromechanics-based woven composite analysis, a hybrid woven composite analysis, and two- and three-dimensional finite element analyses. The elastic properties predicted are in good agreement with each other as well as with the available measured data. However, the various methods differ from each other in three key areas: (1) the fidelity provided, (2) the efforts required for input data preparation, and (3) the computational resources required. Results also indicate that efficient methods are also able to provide a reasonable estimate of local stress fields.

Neuroimaging Week: A Novel, Engaging, and Effective Curriculum for Teaching Neuroimaging to Junior Psychiatric Residents

ERIC Educational Resources Information Center

Downar, Jonathan; Krizova, Adriana; Ghaffar, Omar; Zaretsky, Ari

2010-01-01

Objective: Neuroimaging techniques are increasingly important in psychiatric research and clinical practice, but few postgraduate psychiatry programs offer formal training in neuroimaging. To address this need, the authors developed a course to prepare psychiatric residents to use neuroimaging techniques effectively in independent practice.…

Intrasellar cysticercosis: a systematic review.

PubMed

Del Brutto, Oscar H; Del Brutto, Victor J

2013-09-01

The objective of this study was to review patients with intrasellar cysticercosis to outline the features of this form of neurocysticercosis. A MEDLINE and manual search of patients with intrasellar cysticercosis were done. Abstracted data included clinical manifestations, neuroimaging findings, therapy, and outcome. Twenty-three patients were reviewed. Ophthalmological disturbances, including diminution of visual acuity and visual field defects following a chiasmatic pattern, were recorded in 67 % of cases. Endocrine abnormalities were found in 56 % of patients (panhypopituitarism, hyperprolactinemia, diabetes insipidus, and isolated hypothyroidism). In addition, some patients complained of seizures or chronic headaches. Neuroimaging studies showed lesions confined to the sellar region in 47 % of cases. The remaining patients also had subarachnoid cysts associated or not with hydrocephalus, parenchymal brain cysts, or parenchymal brain calcifications. Thirteen patients underwent surgical resection of the sellar cyst through a craniotomy in nine cases and by the transsphenoidal approach in four. Visual acuity or visual field defects improved in only two of these patients. Five patients were treated with cysticidal drugs without improvement. Intrasellar cysticercosis is rare and probably under-recognized. Clinical manifestations resemble those caused by pituitary tumors, cysts, or other granulomatous lesions. Neuroimaging findings are of more value when intrasellar cysts are associated with other forms of neurocysticercosis, such as basal subarachnoid cysts or hydrocephalus. Prompt surgical resection is mandatory to reduce the risk of permanent loss of visual function. There seems to be no role for cysticidal drug therapy in these cases.

Geodesic congruences in warped spacetimes

NASA Astrophysics Data System (ADS)

Ghosh, Suman; Dasgupta, Anirvan; Kar, Sayan

2011-04-01

In this article, we explore the kinematics of timelike geodesic congruences in warped five-dimensional bulk spacetimes, with and without thick or thin branes. Beginning with geodesic flows in the Randall-Sundrum anti-de Sitter geometry without and with branes, we find analytical expressions for the expansion scalar and comment on the effects of including thin branes on its evolution. Later, we move on to congruences in more general warped bulk geometries with a cosmological thick brane and a time-dependent extra dimensional scale. Using analytical expressions for the velocity field, we interpret the expansion, shear and rotation (ESR) along the flows, as functions of the extra dimensional coordinate. The evolution of a cross-sectional area orthogonal to the congruence, as seen from a local observer’s point of view, is also shown graphically. Finally, the Raychaudhuri and geodesic equations in backgrounds with a thick brane are solved numerically in order to figure out the role of initial conditions (prescribed on the ESR) and spacetime curvature on the evolution of the ESR.

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

Bena, Iosif; Kraus, Per; Warner, Nicholas P.

We construct the most generic three-charge, three-dipole-charge, BPS black-ring solutions in a Taub-NUT background. These solutions depend on seven charges and six moduli, and interpolate between a four-dimensional black hole and a five-dimensional black ring. They are also instrumental in determining the correct microscopic description of the five-dimensional BPS black rings.

Neuroimaging for psychotherapy research: Current trends

PubMed Central

WEINGARTEN, CAROL P.; STRAUMAN, TIMOTHY J.

2014-01-01

Objective This article reviews neuroimaging studies that inform psychotherapy research. An introduction to neuroimaging methods is provided as background for the increasingly sophisticated breadth of methods and findings appearing in psychotherapy research. Method We compiled and assessed a comprehensive list of neuroimaging studies of psychotherapy outcome, along with selected examples of other types of studies that also are relevant to psychotherapy research. We emphasized magnetic resonance imaging (MRI) since it is the dominant neuroimaging modality in psychological research. Results We summarize findings from neuroimaging studies of psychotherapy outcome, including treatment for depression, obsessive-compulsive disorder (OCD), and schizophrenia. Conclusions The increasing use of neuroimaging methods in the study of psychotherapy continues to refine our understanding of both outcome and process. We suggest possible directions for future neuroimaging studies in psychotherapy research. PMID:24527694

Hawking radiation of five-dimensional charged black holes with scalar fields

NASA Astrophysics Data System (ADS)

Miao, Yan-Gang; Xu, Zhen-Ming

2017-09-01

We investigate the Hawking radiation cascade from the five-dimensional charged black hole with a scalar field coupled to higher-order Euler densities in a conformally invariant manner. We give the semi-analytic calculation of greybody factors for the Hawking radiation. Our analysis shows that the Hawking radiation cascade from this five-dimensional black hole is extremely sparse. The charge enhances the sparsity of the Hawking radiation, while the conformally coupled scalar field reduces this sparsity.

Communication and the primate brain: insights from neuroimaging studies in humans, chimpanzees and macaques.

PubMed

Wilson, Benjamin; Petkov, Christopher I

2011-04-01

Considerable knowledge is available on the neural substrates for speech and language from brain-imaging studies in humans, but until recently there was a lack of data for comparison from other animal species on the evolutionarily conserved brain regions that process species-specific communication signals. To obtain new insights into the relationship of the substrates for communication in primates, we compared the results from several neuroimaging studies in humans with those that have recently been obtained from macaque monkeys and chimpanzees. The recent work in humans challenges the longstanding notion of highly localized speech areas. As a result, the brain regions that have been identified in humans for speech and nonlinguistic voice processing show a striking general correspondence to how the brains of other primates analyze species-specific vocalizations or information in the voice, such as voice identity. The comparative neuroimaging work has begun to clarify evolutionary relationships in brain function, supporting the notion that the brain regions that process communication signals in the human brain arose from a precursor network of regions that is present in nonhuman primates and is used for processing species-specific vocalizations. We conclude by considering how the stage now seems to be set for comparative neurobiology to characterize the ancestral state of the network that evolved in humans to support language.

Speech problems affect more than one in two children with cerebral palsy: Swedish population-based study.

PubMed

Nordberg, A; Miniscalco, C; Lohmander, A; Himmelmann, K

2013-02-01

To describe speech ability in a population-based study of children with cerebral palsy (CP), in relation to CP subtype, motor function, cognitive level and neuroimaging findings. A retrospective chart review of 129 children (66 girls, 63 boys) with CP, born in 1999-2002, was carried out. Speech ability and background information, such as type of CP, motor function, cognitive level and neuroimaging data, were collected and analysed. Speech disorders were found in 21% of the children and were present in all types of CP. Forty-one per cent of the children with speech disorders also had mental retardation, and 42% were able to walk independently. A further 32% of the children were nonverbal, and maldevelopment and basal ganglia lesions were most common in this group. The remaining 47% had no speech disorders, and this group was most likely to display white matter lesions of immaturity. More than half of the children in this CP cohort had a speech disorder (21%) or were nonverbal (32%). Speech ability was related to the type of CP, gross motor function, the presence of mental retardation and the localization of brain maldevelopment and lesions. Neuroimaging results differed between the three speech ability groups. ©2012 The Author(s)/Acta Paediatrica ©2012 Foundation Acta Paediatrica.

NAPR: a Cloud-Based Framework for Neuroanatomical Age Prediction.

PubMed

Pardoe, Heath R; Kuzniecky, Ruben

2018-01-01

The availability of cloud computing services has enabled the widespread adoption of the "software as a service" (SaaS) approach for software distribution, which utilizes network-based access to applications running on centralized servers. In this paper we apply the SaaS approach to neuroimaging-based age prediction. Our system, named "NAPR" (Neuroanatomical Age Prediction using R), provides access to predictive modeling software running on a persistent cloud-based Amazon Web Services (AWS) compute instance. The NAPR framework allows external users to estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. As a demonstration of the NAPR approach, we have developed two age prediction models that were trained using healthy control data from the ABIDE, CoRR, DLBS and NKI Rockland neuroimaging datasets (total N = 2367, age range 6-89 years). The provided age prediction models were trained using (i) relevance vector machines and (ii) Gaussian processes machine learning methods applied to cortical thickness surfaces obtained using Freesurfer v5.3. We believe that this transparent approach to out-of-sample evaluation and comparison of neuroimaging age prediction models will facilitate the development of improved age prediction models and allow for robust evaluation of the clinical utility of these methods.

Insights from neuroenergetics into the interpretation of functional neuroimaging: an alternative empirical model for studying the brain's support of behavior

PubMed Central

Shulman, Robert G; Hyder, Fahmeed; Rothman, Douglas L

2014-01-01

Functional neuroimaging measures quantitative changes in neurophysiological parameters coupled to neuronal activity during observable behavior. These results have usually been interpreted by assuming that mental causation of behavior arises from the simultaneous actions of distinct psychological mechanisms or modules. However, reproducible localization of these modules in the brain using functional magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging has been elusive other than for sensory systems. In this paper, we show that neuroenergetic studies using PET, calibrated functional magnetic resonance imaging (fMRI), 13C magnetic resonance spectroscopy, and electrical recordings do not support the standard approach, which identifies the location of mental modules from changes in brain activity. Of importance in reaching this conclusion is that changes in neuronal activities underlying the fMRI signal are many times smaller than the high ubiquitous, baseline neuronal activity, or energy in resting, awake humans. Furthermore, the incremental signal depends on the baseline activity contradicting theoretical assumptions about linearity and insertion of mental modules. To avoid these problems, while making use of these valuable results, we propose that neuroimaging should be used to identify observable brain activities that are necessary for a person's observable behavior rather than being used to seek hypothesized mental processes. PMID:25160670

Can Neuroimaging Markers of Vascular Pathology Explain Cognitive Performance in Adults with Sickle Cell Anemia? A Review of the Literature

PubMed Central

Jorgensen, Dana R.; Rosano, Caterina; Novelli, Enrico M.

2017-01-01

Adults with homozygous sickle cell anemia have, on average, lower cognitive function than unaffected controls. The mechanisms underlying cognitive deterioration in this population are poorly understood, but cerebral small vessel disease (CSVD) is likely to be implicated. We conducted a systematic review using the Prisma Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of articles that included both measures of cognitive function and magnetic resonance imaging (MRI) neuroimaging markers of small vessel disease. While all five studies identified small vessel disease by MRI, only two of them found a significant relationship between structural changes and cognitive performance. Differences in methodologies and small sample sizes likely accounted for the discrepancies between the studies. We conclude that while MRI is a valuable tool to identify markers of CSVD in this population, larger studies are needed to definitely establish a link between MRI-detectable abnormalities and cognitive function in sickle cell anemia. PMID:27689914

Central nervous system immune reconstitution inflammatory syndrome in AIDS: experience of a Mexican neurological centre.

PubMed

Guevara-Silva, Erik A; Ramírez-Crescencio, María A; Soto-Hernández, José Luís; Cárdenas, Graciela

2012-09-01

Highly active antiretroviral therapy (HAART) restores the inflammatory immune response in AIDS patients and it may unmask previous subclinical infections or paradoxically exacerbate symptoms of opportunistic infections. Up to 25% of patients receiving HAART develop immune reconstitution inflammatory syndrome (IRIS). We describe six patients with IRIS central nervous system (CNSIRIS) manifestations emphasizing the relevance of CSF cultures and neuroimaging in early diagnosis and management. Patients with CNSIRIS were identified among hospitalized HIV-infected patients that started HAART from January 2002 through December 2007 at a referral neurological center in Mexico. One-hundred and forty-two HIV-infected patients with neurological signs were hospitalized, 64 of which had received HAART, and six (9.3%) developed CNSIRIS. Five patients were male. Two cases of tuberculosis, two of cryptococcosis, one of brain toxoplasmosis, and one possible PML case were found. IRIS onset occurred within 12 weeks of HAART in five patients. Anti-infective therapy was continued. In one case, HAART was temporarily suspended. In long-term follow-up the clinical condition improved in all patients. CNSIRIS associated to opportunistic infections appeared in 9% of patients receiving HAART. Interestingly, no cases of malignancy or neoplasm IRIS-related were found. Frequent clinical assessment and neuroimaging studies supported diagnosis and treatment. Risk factors were similar to those found in other series. Copyright © 2012 Elsevier B.V. All rights reserved.

Perception of affective and linguistic prosody: an ALE meta-analysis of neuroimaging studies

PubMed Central

Brown, Steven

2014-01-01

Prosody refers to the melodic and rhythmic aspects of speech. Two forms of prosody are typically distinguished: ‘affective prosody’ refers to the expression of emotion in speech, whereas ‘linguistic prosody’ relates to the intonation of sentences, including the specification of focus within sentences and stress within polysyllabic words. While these two processes are united by their use of vocal pitch modulation, they are functionally distinct. In order to examine the localization and lateralization of speech prosody in the brain, we performed two voxel-based meta-analyses of neuroimaging studies of the perception of affective and linguistic prosody. There was substantial sharing of brain activations between analyses, particularly in right-hemisphere auditory areas. However, a major point of divergence was observed in the inferior frontal gyrus: affective prosody was more likely to activate Brodmann area 47, while linguistic prosody was more likely to activate the ventral part of area 44. PMID:23934416

Visual Exploration of Genetic Association with Voxel-based Imaging Phenotypes in an MCI/AD Study

PubMed Central

Kim, Sungeun; Shen, Li; Saykin, Andrew J.; West, John D.

2010-01-01

Neuroimaging genomics is a new transdisciplinary research field, which aims to examine genetic effects on brain via integrated analyses of high throughput neuroimaging and genomic data. We report our recent work on (1) developing an imaging genomic browsing system that allows for whole genome and entire brain analyses based on visual exploration and (2) applying the system to the imaging genomic analysis of an existing MCI/AD cohort. Voxel-based morphometry is used to define imaging phenotypes. ANCOVA is employed to evaluate the effect of the interaction of genotypes and diagnosis in relation to imaging phenotypes while controlling for relevant covariates. Encouraging experimental results suggest that the proposed system has substantial potential for enabling discovery of imaging genomic associations through visual evaluation and for localizing candidate imaging regions and genomic regions for refined statistical modeling. PMID:19963597

Response assessment in neuro-oncology.

PubMed

Quant, Eudocia C; Wen, Patrick Y

2011-02-01

Accuracy and reproducibility in determining response to therapy and tumor progression can be difficult to achieve for nervous system tumors. Current response criteria vary depending on the pathology and have several limitations. Until recently, the most widely used criteria for gliomas were "Macdonald criteria," based on two-dimensional tumor measurements on neuroimaging studies. However, the Response Assessment in Neuro-Oncology (RANO) Working Group has published new recommendations in high-grade gliomas and is working on recommendations for other nervous system tumors. This article reviews current response criteria for high-grade glioma, low-grade glioma, brain metastasis, meningioma, and schwannoma.

A phenome-wide examination of neural and cognitive function.

PubMed

Poldrack, R A; Congdon, E; Triplett, W; Gorgolewski, K J; Karlsgodt, K H; Mumford, J A; Sabb, F W; Freimer, N B; London, E D; Cannon, T D; Bilder, R M

2016-12-06

This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.

Exertional headache as unusual presentation of the syndrome of an elongated styloid process.

PubMed

Maggioni, Ferdinando; Marchese-Ragona, Rosario; Mampreso, Edoardo; Mainardi, Federico; Zanchin, Giorgio

2009-05-01

We present the case of a 34-year-old man with a 2-year history of pain related to efforts in heavy lifting, beginning in the right ear and radiating to the neck and to the vertex. He underwent multiple negative neuroimaging examinations, until a 3-dimensional computerized tomography scan of the pharyngeal region evidenced an elongated styloid process. A diagnosis of Eagle's syndrome was made. The excision of the elongated styloid process was performed, resulting in complete and lasting pain relief. We focus on Eagle's syndrome and in particular on this atypical presentation.

Diffusion spectral imaging modules correlate with EEG LORETA neuroimaging modules.

PubMed

Thatcher, Robert W; North, Duane M; Biver, Carl J

2012-05-01

The purpose of this study was to test the hypothesis that the highest temporal correlations between 3-dimensional EEG current source density corresponds to anatomical Modules of high synaptic connectivity. Eyes closed and eyes open EEG was recorded from 19 scalp locations with a linked ears reference from 71 subjects age 13-42 years. LORETA was computed from 1 to 30 Hz in 2,394 cortical gray matter voxels that were grouped into six anatomical Modules corresponding to the ROIs in the Hagmann et al.'s [2008] diffusion spectral imaging (DSI) study. All possible cross-correlations between voxels within a DSI Module were compared with the correlations between Modules. The Hagmann et al. [ 2008] Module correlation structure was replicated in the correlation structure of EEG three-dimensional current source density. EEG Temporal correlation between brain regions is related to synaptic density as measured by diffusion spectral imaging. Copyright © 2011 Wiley-Liss, Inc.

Multivariate neural biomarkers of emotional states are categorically distinct.

PubMed

Kragel, Philip A; LaBar, Kevin S

2015-11-01

Understanding how emotions are represented neurally is a central aim of affective neuroscience. Despite decades of neuroimaging efforts addressing this question, it remains unclear whether emotions are represented as distinct entities, as predicted by categorical theories, or are constructed from a smaller set of underlying factors, as predicted by dimensional accounts. Here, we capitalize on multivariate statistical approaches and computational modeling to directly evaluate these theoretical perspectives. We elicited discrete emotional states using music and films during functional magnetic resonance imaging scanning. Distinct patterns of neural activation predicted the emotion category of stimuli and tracked subjective experience. Bayesian model comparison revealed that combining dimensional and categorical models of emotion best characterized the information content of activation patterns. Surprisingly, categorical and dimensional aspects of emotion experience captured unique and opposing sources of neural information. These results indicate that diverse emotional states are poorly differentiated by simple models of valence and arousal, and that activity within separable neural systems can be mapped to unique emotion categories. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Emergent gravity from a mass deformation in warped spacetime

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

Gherghetta, Tony; Peloso, Marco; Poppitz, Erich

2005-11-15

We consider a deformation of five-dimensional warped gravity with bulk and boundary mass terms to quadratic order in the action. We show that massless zero modes occur for special choices of the masses. The tensor zero mode is a smooth deformation of the Randall-Sundrum graviton wave function and can be localized anywhere in the bulk. There is also a vector zero mode with similar localization properties, which is decoupled from conserved sources at tree level. Interestingly, there are no scalar modes, and the model is ghost-free at the linearized level. When the tensor zero mode is localized near the IRmore » brane, the dual interpretation is a composite graviton describing an emergent (induced) theory of gravity at the IR scale. In this case Newton's law of gravity changes to a new power law below the millimeter scale, with an exponent that can even be irrational.« less

Multiresonance modes in sine–Gordon brane models

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

Cruz, W.T., E-mail: wilamicruz@gmail.com; Maluf, R.V., E-mail: r.v.maluf@fisica.ufc.br; Dantas, D.M., E-mail: davi@fisica.ufc.br

2016-12-15

In this work, we study the localization of the vector gauge field in two five-dimensional braneworlds generated by scalar fields coupled to gravity. The sine–Gordon like potentials are employed to produce different thick brane setups. A zero mode localized is obtained, and we show the existence of reverberations with the wave solutions indicating a quasi-localized massive mode. More interesting results are achieved when we propose a double sine–Gordon potential to the scalar field. The resulting thick brane shows a more detailed topology with the presence of an internal structure composed by two kinks. The massive spectrum of the gauge fieldmore » is revalued on this scenario revealing the existence of various resonant modes. Furthermore, we compute the corrections to Coulomb law coming from these massive KK vector modes in these thick scenarios, which is concluded that the dilaton parameter regulates these corrections.« less

DIS off glueballs from string theory: the role of the chiral anomaly and the Chern-Simons term

NASA Astrophysics Data System (ADS)

Kovensky, Nicolas; Michalski, Gustavo; Schvellinger, Martin

2018-04-01

We calculate the structure function F 3( x, q 2) of the hadronic tensor of deep inelastic scattering (DIS) of charged leptons from glueballs of N=4 SYM theory at strong coupling and at small values of the Bjorken parameter in the gauge/string theory duality framework. This is done in terms of type IIB superstring theory scattering amplitudes. From the AdS5 perspective, the relevant part of the scattering amplitude comes from the five-dimensional non-Abelian Chern-Simons terms in the SU(4) gauged supergravity obtained from dimensional reduction on S 5. From type IIB superstring theory we derive an effective Lagrangian describing the four-point interaction in the local approximation. The exponentially small regime of the Bjorken parameter is investigated using Pomeron techniques.

Multi-dimensional Upwind Fluctuation Splitting Scheme with Mesh Adaption for Hypersonic Viscous Flow. Degree awarded by Virginia Polytechnic Inst. and State Univ., 9 Nov. 2001

NASA Technical Reports Server (NTRS)

Wood, William A., III

2002-01-01

A multi-dimensional upwind fluctuation splitting scheme is developed and implemented for two-dimensional and axisymmetric formulations of the Navier-Stokes equations on unstructured meshes. Key features of the scheme are the compact stencil, full upwinding, and non-linear discretization which allow for second-order accuracy with enforced positivity. Throughout, the fluctuation splitting scheme is compared to a current state-of-the-art finite volume approach, a second-order, dual mesh upwind flux difference splitting scheme (DMFDSFV), and is shown to produce more accurate results using fewer computer resources for a wide range of test cases. A Blasius flat plate viscous validation case reveals a more accurate upsilon-velocity profile for fluctuation splitting, and the reduced artificial dissipation production is shown relative to DMFDSFV. Remarkably, the fluctuation splitting scheme shows grid converged skin friction coefficients with only five points in the boundary layer for this case. The second half of the report develops a local, compact, anisotropic unstructured mesh adaptation scheme in conjunction with the multi-dimensional upwind solver, exhibiting a characteristic alignment behavior for scalar problems. The adaptation strategy is extended to the two-dimensional and axisymmetric Navier-Stokes equations of motion through the concept of fluctuation minimization.

Differences in protein expression among five species of stream stonefly (Plecoptera) along a latitudinal gradient in Japan.

PubMed

Gamboa, Maribet; Tsuchiya, Maria Claret; Matsumoto, Suguru; Iwata, Hisato; Watanabe, Kozo

2017-11-01

Proteome variation among natural populations along an environmental gradient may provide insights into how the biological functions of species are related to their local adaptation. We investigated protein expression in five stream stonefly species from four geographic regions along a latitudinal gradient in Japan with varying climatic conditions. The extracted proteins were separated by two-dimensional gel electrophoresis and identified by matrix-assisted laser desorption/ionization of time-of-flight (MALDI TOF/TOF), yielding 446 proteins. Low interspecies variation in the proteome profiles was observed among five species within geographical regions, presumably due to the co-occurring species sharing the environments. However, large spatial variations in protein expression were found among four geographic regions, suggesting strong regulation of protein expression in heterogeneous environments, where the spatial variations were positively correlated with water temperature. We identified 21 unique proteins expressed specifically in a geographical region and six common proteins expressed throughout all regions. In warmer regions, metabolic proteins were upregulated, whereas proteins related to cold stress, the photoperiod, and mating were downregulated. Oxygen-related and energy-production proteins were upregulated in colder regions with higher altitudes. Thus, our proteomic approach is useful for identifying and understanding important biological functions related to local adaptations by populations of stoneflies. © 2017 Wiley Periodicals, Inc.

Long-Latency Reductions in Gamma Power Predict Hemodynamic Changes That Underlie the Negative BOLD Signal

PubMed Central

Harris, Samuel; Bruyns-Haylett, Michael; Kennerley, Aneurin; Zheng, Ying; Martin, Chris; Jones, Myles; Redgrave, Peter; Berwick, Jason

2015-01-01

Studies that use prolonged periods of sensory stimulation report associations between regional reductions in neural activity and negative blood oxygenation level-dependent (BOLD) signaling. However, the neural generators of the negative BOLD response remain to be characterized. Here, we use single-impulse electrical stimulation of the whisker pad in the anesthetized rat to identify components of the neural response that are related to “negative” hemodynamic changes in the brain. Laminar multiunit activity and local field potential recordings of neural activity were performed concurrently with two-dimensional optical imaging spectroscopy measuring hemodynamic changes. Repeated measurements over multiple stimulation trials revealed significant variations in neural responses across session and animal datasets. Within this variation, we found robust long-latency decreases (300 and 2000 ms after stimulus presentation) in gamma-band power (30–80 Hz) in the middle-superficial cortical layers in regions surrounding the activated whisker barrel cortex. This reduction in gamma frequency activity was associated with corresponding decreases in the hemodynamic responses that drive the negative BOLD signal. These findings suggest a close relationship between BOLD responses and neural events that operate over time scales that outlast the initiating sensory stimulus, and provide important insights into the neurophysiological basis of negative neuroimaging signals. PMID:25788681

Long-latency reductions in gamma power predict hemodynamic changes that underlie the negative BOLD signal.

PubMed

Boorman, Luke; Harris, Samuel; Bruyns-Haylett, Michael; Kennerley, Aneurin; Zheng, Ying; Martin, Chris; Jones, Myles; Redgrave, Peter; Berwick, Jason

2015-03-18

Studies that use prolonged periods of sensory stimulation report associations between regional reductions in neural activity and negative blood oxygenation level-dependent (BOLD) signaling. However, the neural generators of the negative BOLD response remain to be characterized. Here, we use single-impulse electrical stimulation of the whisker pad in the anesthetized rat to identify components of the neural response that are related to "negative" hemodynamic changes in the brain. Laminar multiunit activity and local field potential recordings of neural activity were performed concurrently with two-dimensional optical imaging spectroscopy measuring hemodynamic changes. Repeated measurements over multiple stimulation trials revealed significant variations in neural responses across session and animal datasets. Within this variation, we found robust long-latency decreases (300 and 2000 ms after stimulus presentation) in gamma-band power (30-80 Hz) in the middle-superficial cortical layers in regions surrounding the activated whisker barrel cortex. This reduction in gamma frequency activity was associated with corresponding decreases in the hemodynamic responses that drive the negative BOLD signal. These findings suggest a close relationship between BOLD responses and neural events that operate over time scales that outlast the initiating sensory stimulus, and provide important insights into the neurophysiological basis of negative neuroimaging signals. Copyright © 2015 Boorman et al.

Stereoelectroencephalography: Indication and Efficacy

PubMed Central

IIDA, Koji; OTSUBO, Hiroshi

2017-01-01

Stereoelectroencephalography (SEEG) is a method for invasive study of patients with refractory epilepsy. Localization of the epileptogenic zone in SEEG relied on the hypothesis of anatomo-electro-clinical analysis limited by X-ray, analog electroencephalography (EEG), and seizure semiology in the 1950s. Modern neuroimaging studies and digital video-EEG have developed the hypothesis aiming at more precise localization of the epileptic network. Certain clinical scenarios favor SEEG over subdural EEG (SDEEG). SEEG can cover extensive areas of bilateral hemispheres with highly accurate sampling from sulcal areas and deep brain structures. A hybrid technique of SEEG and subdural strip electrode placement has been reported to overcome the SEEG limitations of poor functional mapping. Technological advances including acquisition of three-dimensional angiography and magnetic resonance image (MRI) in frameless conditions, advanced multimodal planning, and robot-assisted implantation have contributed to the accuracy and safety of electrode implantation in a simplified fashion. A recent meta-analysis of the safety of SEEG concluded the low value of the pooled prevalence for all complications. The complications of SEEG were significantly less than those of SDEEG. The removal of electrodes for SEEG was much simpler than for SDEEG and allowed sufficient time for data analysis, discussion, and consensus for both patients and physicians before the proceeding treatment. Furthermore, SEEG is applicable as a therapeutic alternative for deep-seated lesions, e.g., nodular heterotopia, in nonoperative epilepsies using SEEG-guided radiofrequency thermocoagulation. We review the SEEG method with technological advances for planning and implantation of electrodes. We highlight the indication and efficacy, advantages and disadvantages of SEEG compared with SDEEG. PMID:28637943

Anxiety in healthy humans is associated with orbital frontal chemistry.

PubMed

Grachev, I D; Apkarian, A V

2000-09-01

The present study examines relationships between regional brain chemistry (as identified by localized in vivo three-dimensional single-voxel proton magnetic resonance spectroscopy (1H-MRS) and anxiety (as measured by the State-Trait Anxiety Inventory) in 16 healthy subjects. The relative concentrations of N-Acetyl aspartate, choline, glutamate, glutamine, gamma-aminobutyric acid, inositol, glucose and lactate were measured relative to creatine within six 8-cm3 brain voxels localized to: thalamus, cingulate, insula, sensorimotor, dorsolateral prefrontal, and orbital frontal cortices (OFC) in the left hemisphere. Analysis of variance, across brain regions, chemicals, and high and low anxiety groups, showed a relationship between anxiety and chemical composition of OFC, with high anxiety subjects demonstrating 32% increase in overall chemical concentrations within OFC, as compared to the lower anxiety group (F= 60.8, P < 10(-7)). Other brain regions, including cingulate, showed no detectable anxiety dependence. The combination of the state and trait anxiety was highly correlated with the concentration of OFC chemicals (r2 = 0.98), and N-Acetyl aspartate in OFC was identified as the strongest chemical marker for anxiety (changed by 43.2% between the two anxiety groups, F = 21.5, P = 0.000005). The results provide direct evidence that the OFC chemistry is associated with anxiety in healthy humans. The method can be used as a neuroimaging/behavioral tool for documentation of OFC chemistry changes in relation to anxiety per se and anxiety disorders. The presented relationship between regional brain chemistry and anxiety reflects the functional/behavioral state of the brain, pointing to possible mechanisms of the neurobiology of anxiety.

IIB duals of D = 3 {N} = 4 circular quivers

NASA Astrophysics Data System (ADS)

Assel, Benjamin; Bachas, Costas; Estes, John; Gomis, Jaume

2012-12-01

We construct the type-IIB AdS4 ⋉ K supergravity solutions which are dual to the three-dimensional {N} = 4 superconformal field theories that arise as infrared fixed points of circular-quiver gauge theories. These superconformal field theories are labeled by a triple ( {ρ, hat{ρ},L} ) subject to constraints, where ρ and hat{ρ} are two partitions of a number N, and L is a positive integer. We show that in the limit of large L the localized five- branes in our solutions are effectively smeared, and these type-IIB solutions are dual to the near-horizon geometry of M-theory M2-branes at a {{{{{{C}}^4}}} / {{( {{Z_k}× {Z_{widehat{k}}}} )}} .} orbifold singularity. Our IIB solutions resolve the singularity into localized five-brane throats, without breaking the conformal symmetry. The constraints satisfied by the triple ( {ρ, hat{ρ},L} ) , together with the enhanced non-abelian flavour symmetries of the superconformal field theories are precisely reproduced by the type-IIB supergravity solutions. As a bonus, we uncover a novel type of "orbifold equivalence" between different quantum field theories and provide quantitative evidence for this equivalence.

Neuroimaging training among neuropsychologists: A survey of the state of current training and recommendations for trainees

PubMed Central

Benitez, Andreana; Hassenstab, Jason; Bangen, Katherine J.

2013-01-01

Neuroimaging has gained widespread use in neuropsychological research and practice. However, there are neither established guidelines on how neuropsychologists might become competent researchers or consumers of neuroimaging data, nor any published studies describing the state of neuroimaging training among neuropsychologists. We report the results of two online surveys, one of 13 expert neuropsychologist-neuroimagers, whose responses informed the formulation of a second, larger survey to neuropsychologists-at-large that were a random selection of a third of the members of the International Neuropsychological Society and American Academy of Clinical Neuropsychology. 237 doctoral-level neuropsychologists, or 15.3% of potential participants, provided complete responses. Most respondents (69.2%) received training in neuroimaging, mostly at the post-doctoral level, largely through independent study, clinical conferences, instruction by clinical supervisors, and individualized mentoring, on topics such as neuroimaging modalities in neurology, neuroanatomy, and the appropriate information to glean from neuroradiology reports. Of the remaining respondents who did not receive training in neuroimaging, 64.4% indicated that such training would be very or extremely beneficial to one’s career as a neuropsychologist. Both neuropsychologist-neuroimagers and neuropsychologists-at-large provided specific recommendations for training. Findings from this initial effort will guide trainees who seek to develop competence in neuroimaging, and inform future formulations of neuropsychological training. PMID:24215451

Higgs decay into two photons in a warped extra dimension

NASA Astrophysics Data System (ADS)

Hahn, Juliane; Hörner, Clara; Malm, Raoul; Neubert, Matthias; Novotny, Kristiane; Schmell, Christoph

2014-05-01

A detailed five-dimensional calculation of the Higgs-boson decay into two photons is performed in both the minimal and the custodially protected Randall-Sundrum (RS) model, where the Standard Model (SM) fields propagate in the bulk and the scalar sector lives on or near the IR brane. It is explicitly shown that the gauge invariance of the sum of diagrams involving bosonic fields in the SM also applies to the case of these RS scenarios. An exact expression for the amplitude in terms of the five-dimensional (5D) gauge-boson and fermion propagators is presented, which includes the full dependence on the Higgs-boson mass. Closed expressions for the 5D -boson propagators in the minimal and the custodial RS model are derived, which are valid to all orders in . In contrast to the fermion case, the result for the bosonic contributions to the amplitude is insensitive to the details of the localization of the Higgs profile on or near the IR brane. The various RS predictions for the rate of the process are compared with the latest LHC data, and exclusion regions for the RS model parameters are derived.

Holographic self-tuning of the cosmological constant

NASA Astrophysics Data System (ADS)

Charmousis, Christos; Kiritsis, Elias; Nitti, Francesco

2017-09-01

We propose a brane-world setup based on gauge/gravity duality in which the four-dimensional cosmological constant is set to zero by a dynamical self-adjustment mechanism. The bulk contains Einstein gravity and a scalar field. We study holographic RG flow solutions, with the standard model brane separating an infinite volume UV region and an IR region of finite volume. For generic values of the brane vacuum energy, regular solutions exist such that the four-dimensional brane is flat. Its position in the bulk is determined dynamically by the junction conditions. Analysis of linear fluctuations shows that a regime of 4-dimensional gravity is possible at large distances, due to the presence of an induced gravity term. The graviton acquires an effective mass, and a five-dimensional regime may exist at large and/or small scales. We show that, for a broad choice of potentials, flat-brane solutions are manifestly stable and free of ghosts. We compute the scalar contribution to the force between brane-localized sources and show that, in certain models, the vDVZ discontinuity is absent and the effective interaction at short distances is mediated by two transverse graviton helicities.

Maximal violation of a bipartite three-setting, two-outcome Bell inequality using infinite-dimensional quantum systems

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

Pal, Karoly F.; Vertesi, Tamas

2010-08-15

The I{sub 3322} inequality is the simplest bipartite two-outcome Bell inequality beyond the Clauser-Horne-Shimony-Holt (CHSH) inequality, consisting of three two-outcome measurements per party. In the case of the CHSH inequality the maximal quantum violation can already be attained with local two-dimensional quantum systems; however, there is no such evidence for the I{sub 3322} inequality. In this paper a family of measurement operators and states is given which enables us to attain the maximum quantum value in an infinite-dimensional Hilbert space. Further, it is conjectured that our construction is optimal in the sense that measuring finite-dimensional quantum systems is not enoughmore » to achieve the true quantum maximum. We also describe an efficient iterative algorithm for computing quantum maximum of an arbitrary two-outcome Bell inequality in any given Hilbert space dimension. This algorithm played a key role in obtaining our results for the I{sub 3322} inequality, and we also applied it to improve on our previous results concerning the maximum quantum violation of several bipartite two-outcome Bell inequalities with up to five settings per party.« less

Higher-order gravity in higher dimensions: geometrical origins of four-dimensional cosmology?

NASA Astrophysics Data System (ADS)

Troisi, Antonio

2017-03-01

Determining the cosmological field equations is still very much debated and led to a wide discussion around different theoretical proposals. A suitable conceptual scheme could be represented by gravity models that naturally generalize Einstein theory like higher-order gravity theories and higher-dimensional ones. Both of these two different approaches allow one to define, at the effective level, Einstein field equations equipped with source-like energy-momentum tensors of geometrical origin. In this paper, the possibility is discussed to develop a five-dimensional fourth-order gravity model whose lower-dimensional reduction could provide an interpretation of cosmological four-dimensional matter-energy components. We describe the basic concepts of the model, the complete field equations formalism and the 5-D to 4-D reduction procedure. Five-dimensional f( R) field equations turn out to be equivalent, on the four-dimensional hypersurfaces orthogonal to the extra coordinate, to an Einstein-like cosmological model with three matter-energy tensors related with higher derivative and higher-dimensional counter-terms. By considering the gravity model with f(R)=f_0R^n the possibility is investigated to obtain five-dimensional power law solutions. The effective four-dimensional picture and the behaviour of the geometrically induced sources are finally outlined in correspondence to simple cases of such higher-dimensional solutions.

Resonance fluorescence based two- and three-dimensional atom localization

NASA Astrophysics Data System (ADS)

Wahab, Abdul; Rahmatullah; Qamar, Sajid

2016-06-01

Two- and three-dimensional atom localization in a two-level atom-field system via resonance fluorescence is suggested. For the two-dimensional localization, the atom interacts with two orthogonal standing-wave fields, whereas for the three-dimensional atom localization, the atom interacts with three orthogonal standing-wave fields. The effect of the detuning and phase shifts associated with the corresponding standing-wave fields is investigated. A precision enhancement in position measurement of the single atom can be noticed via the control of the detuning and phase shifts.

A robust sparse-modeling framework for estimating schizophrenia biomarkers from fMRI.

PubMed

Dillon, Keith; Calhoun, Vince; Wang, Yu-Ping

2017-01-30

Our goal is to identify the brain regions most relevant to mental illness using neuroimaging. State of the art machine learning methods commonly suffer from repeatability difficulties in this application, particularly when using large and heterogeneous populations for samples. We revisit both dimensionality reduction and sparse modeling, and recast them in a common optimization-based framework. This allows us to combine the benefits of both types of methods in an approach which we call unambiguous components. We use this to estimate the image component with a constrained variability, which is best correlated with the unknown disease mechanism. We apply the method to the estimation of neuroimaging biomarkers for schizophrenia, using task fMRI data from a large multi-site study. The proposed approach yields an improvement in both robustness of the estimate and classification accuracy. We find that unambiguous components incorporate roughly two thirds of the same brain regions as sparsity-based methods LASSO and elastic net, while roughly one third of the selected regions differ. Further, unambiguous components achieve superior classification accuracy in differentiating cases from controls. Unambiguous components provide a robust way to estimate important regions of imaging data. Copyright © 2016 Elsevier B.V. All rights reserved.

Five-dimensional Myers-Perry black holes cannot be overspun in gedanken experiments

NASA Astrophysics Data System (ADS)

An, Jincheng; Shan, Jieru; Zhang, Hongbao; Zhao, Suting

2018-05-01

We apply the new version of a gedanken experiment designed recently by Sorce and Wald to overspin the five-dimensional Myers-Perry black holes. As a result, the extremal black holes cannot be overspun at the linear order. On the other hand, although the nearly extremal black holes could be overspun at the linear order, this process is shown to be prohibited by the quadratic order correction. Thus, no violation of the weak cosmic censorship conjecture occurs around the five-dimensional Myers-Perry black holes.

Streamlined, Inexpensive 3D Printing of the Brain and Skull.

PubMed

Naftulin, Jason S; Kimchi, Eyal Y; Cash, Sydney S

2015-01-01

Neuroimaging technologies such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) collect three-dimensional data (3D) that is typically viewed on two-dimensional (2D) screens. Actual 3D models, however, allow interaction with real objects such as implantable electrode grids, potentially improving patient specific neurosurgical planning and personalized clinical education. Desktop 3D printers can now produce relatively inexpensive, good quality prints. We describe our process for reliably generating life-sized 3D brain prints from MRIs and 3D skull prints from CTs. We have integrated a standardized, primarily open-source process for 3D printing brains and skulls. We describe how to convert clinical neuroimaging Digital Imaging and Communications in Medicine (DICOM) images to stereolithography (STL) files, a common 3D object file format that can be sent to 3D printing services. We additionally share how to convert these STL files to machine instruction gcode files, for reliable in-house printing on desktop, open-source 3D printers. We have successfully printed over 19 patient brain hemispheres from 7 patients on two different open-source desktop 3D printers. Each brain hemisphere costs approximately $3-4 in consumable plastic filament as described, and the total process takes 14-17 hours, almost all of which is unsupervised (preprocessing = 4-6 hr; printing = 9-11 hr, post-processing = <30 min). Printing a matching portion of a skull costs $1-5 in consumable plastic filament and takes less than 14 hr, in total. We have developed a streamlined, cost-effective process for 3D printing brain and skull models. We surveyed healthcare providers and patients who confirmed that rapid-prototype patient specific 3D models may help interdisciplinary surgical planning and patient education. The methods we describe can be applied for other clinical, research, and educational purposes.

Converging evidence for an impact of a functional NOS gene variation on anxiety-related processes

PubMed Central

Haaker, Jan; Glotzbach-Schoon, Evelyn; Schümann, Dirk; Andreatta, Marta; Mechias, Marie-Luise; Raczka, Karolina; Gartmann, Nina; Büchel, Christian; Mühlberger, Andreas; Pauli, Paul; Reif, Andreas; Kalisch, Raffael; Lonsdorf, Tina B.

2016-01-01

Abstract Being a complex phenotype with substantial heritability, anxiety and related phenotypes are characterized by a complex polygenic basis. Thereby, one candidate pathway is neuronal nitric oxide (NO) signaling, and accordingly, rodent studies have identified NO synthase (NOS-I), encoded by NOS1, as a strong molecular candidate for modulating anxiety and hippocampus-dependent learning processes. Using a multi-dimensional and -methodological replication approach, we investigated the impact of a functional promoter polymorphism (NOS1-ex1f-VNTR) on human anxiety-related phenotypes in a total of 1019 healthy controls in five different studies. Homozygous carriers of the NOS1-ex1f short-allele displayed enhanced trait anxiety, worrying and depression scores. Furthermore, short-allele carriers were characterized by increased anxious apprehension during contextual fear conditioning. While autonomous measures (fear-potentiated startle) provided only suggestive evidence for a modulatory role of NOS1-ex1f-VNTR on (contextual) fear conditioning processes, neural activation at the amygdala/anterior hippocampus junction was significantly increased in short-allele carriers during context conditioning. Notably, this could not be attributed to morphological differences. In accordance with data from a plethora of rodent studies, we here provide converging evidence from behavioral, subjective, psychophysiological and neuroimaging studies in large human cohorts that NOS-I plays an important role in anxious apprehension but provide only limited evidence for a role in (contextual) fear conditioning. PMID:26746182

A Neuropsychiatric Analysis of the Cotard Delusion.

PubMed

Sahoo, Aradhana; Josephs, Keith A

2018-01-01

Cotard's syndrome, a condition in which the patient denies his or her own existence or the existence of body parts, is a rare illness that has been reported in association with several neuropsychiatric diagnoses. The majority of published literature on the topic is in the form of case reports, many of which are several years old. The authors evaluated associated diagnoses, neuroimaging, and treatments recorded in patients diagnosed with Cotard's syndrome at their institution. A search of the Mayo Clinic database for patients with mention of signs and symptoms associated with Cotard's in their records between 1996 and 2016 was conducted. The electronic medical records of the identified patients were then reviewed for evidence of a true diagnosis of Cotard's. Clinical and neuroimaging data were also recorded for these patients. The search identified 18 patients, 14 of whom had Cotard delusions. Two of the 14 were excluded due to them being under age 18. The resulting 12 patients had a median age of 52 years (range: 30-85 years). On neuroimaging, four patients exhibited frontal lobe changes, four demonstrated generalized volume loss, and five had ischemic changes; seven patients demonstrated right-sided or bilateral hemisphere lesions. Treatments included ECT, pharmacotherapy, behavioral therapy, psychotherapy, rehydration, and removal of offending drugs. To conclude, Cotard delusions occur in the context of a relatively wide spectrum of neurological, psychiatric, and medical disorders and present with various neural changes. Nondominant hemisphere lesions may play a role in the pathophysiology. A number of effective treatments are available.

Gray matter abnormalities in opioid-dependent patients: A neuroimaging meta-analysis.

PubMed

Wollman, Scott C; Alhassoon, Omar M; Hall, Matthew G; Stern, Mark J; Connors, Eric J; Kimmel, Christine L; Allen, Kenneth E; Stephan, Rick A; Radua, Joaquim

2017-09-01

Prior research utilizing whole-brain neuroimaging techniques has identified structural differences in gray matter in opioid-dependent individuals. However, the results have been inconsistent. The current study meta-analytically examines the neuroimaging findings of studies published before 2016 comparing opioid-dependent individuals to drug-naïve controls. Exhaustive search of five databases yielded 12 studies that met inclusion criteria. Anisotropic Effect-Size Seed-Based d Mapping (AES-SDM) was used to analyze the data extracted by three independent researchers. Voxel-based AES-SDM distinguishes increases and decreases in brain matter significant at the whole-brain level. AES-SDM identified the fronto-temporal region, bilaterally, as being the primary site of gray matter deficits associated with opioid use. Moderator analysis revealed that length of opioid use was negatively associated with gray matter in the left cerebellar vermis and the right Rolandic operculum, including the insula. Meta-regression revealed no remaining significant areas of gray matter reductions, except in the precuneus, following longer abstinence from opioids. Opioid-dependent individuals had significantly less gray matter in several regions that play a key role in cognitive and affective processing. The findings provide evidence that opioid dependence may result in the breakdown of two distinct yet highly overlapping structural and functional systems. These are the fronto-cerebellar system that might be more responsible for impulsivity, compulsive behaviors, and affective disturbances and the fronto-insular system that might account more for the cognitive and decision-making impairments.

Functional brain imaging in neuropsychology over the past 25 years.

PubMed

Roalf, David R; Gur, Ruben C

2017-11-01

Outline effects of functional neuroimaging on neuropsychology over the past 25 years. Functional neuroimaging methods and studies will be described that provide a historical context, offer examples of the utility of neuroimaging in specific domains, and discuss the limitations and future directions of neuroimaging in neuropsychology. Tracking the history of publications on functional neuroimaging related to neuropsychology indicates early involvement of neuropsychologists in the development of these methodologies. Initial progress in neuropsychological application of functional neuroimaging has been hampered by costs and the exposure to ionizing radiation. With rapid evolution of functional methods-in particular functional MRI (fMRI)-neuroimaging has profoundly transformed our knowledge of the brain. Its current applications span the spectrum of normative development to clinical applications. The field is moving toward applying sophisticated statistical approaches that will help elucidate distinct neural activation networks associated with specific behavioral domains. The impact of functional neuroimaging on clinical neuropsychology is more circumscribed, but the prospects remain enticing. The theoretical insights and empirical findings of functional neuroimaging have been led by many neuropsychologists and have transformed the field of behavioral neuroscience. Thus far they have had limited effects on the clinical practices of neuropsychologists. Perhaps it is time to add training in functional neuroimaging to the clinical neuropsychologist's toolkit and from there to the clinic or bedside. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Kaluza-Klein cosmology from five-dimensional Lovelock-Cartan theory

NASA Astrophysics Data System (ADS)

Castillo-Felisola, Oscar; Corral, Cristóbal; del Pino, Simón; Ramírez, Francisca

2016-12-01

We study the Kaluza-Klein dimensional reduction of the Lovelock-Cartan theory in five-dimensional spacetime, with a compact dimension of S1 topology. We find cosmological solutions of the Friedmann-Robertson-Walker class in the reduced spacetime. The torsion and the fields arising from the dimensional reduction induce a nonvanishing energy-momentum tensor in four dimensions. We find solutions describing expanding, contracting, and bouncing universes. The model shows a dynamical compactification of the extra dimension in some regions of the parameter space.

Towards structured sharing of raw and derived neuroimaging data across existing resources

PubMed Central

Keator, D.B.; Helmer, K.; Steffener, J.; Turner, J.A.; Van Erp, T.G.M.; Gadde, S.; Ashish, N.; Burns, G.A.; Nichols, B.N.

2013-01-01

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery. PMID:23727024

Risk patterns and correlated brain activities. Multidimensional statistical analysis of FMRI data in economic decision making study.

PubMed

van Bömmel, Alena; Song, Song; Majer, Piotr; Mohr, Peter N C; Heekeren, Hauke R; Härdle, Wolfgang K

2014-07-01

Decision making usually involves uncertainty and risk. Understanding which parts of the human brain are activated during decisions under risk and which neural processes underly (risky) investment decisions are important goals in neuroeconomics. Here, we analyze functional magnetic resonance imaging (fMRI) data on 17 subjects who were exposed to an investment decision task from Mohr, Biele, Krugel, Li, and Heekeren (in NeuroImage 49, 2556-2563, 2010b). We obtain a time series of three-dimensional images of the blood-oxygen-level dependent (BOLD) fMRI signals. We apply a panel version of the dynamic semiparametric factor model (DSFM) presented in Park, Mammen, Wolfgang, and Borak (in Journal of the American Statistical Association 104(485), 284-298, 2009) and identify task-related activations in space and dynamics in time. With the panel DSFM (PDSFM) we can capture the dynamic behavior of the specific brain regions common for all subjects and represent the high-dimensional time-series data in easily interpretable low-dimensional dynamic factors without large loss of variability. Further, we classify the risk attitudes of all subjects based on the estimated low-dimensional time series. Our classification analysis successfully confirms the estimated risk attitudes derived directly from subjects' decision behavior.

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems

PubMed Central

Tuo, Shouheng; Yong, Longquan; Deng, Fang’an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application. PMID:28403224

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

PubMed

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an; Li, Yanhai; Lin, Yong; Lu, Qiuju

2017-01-01

Harmony Search (HS) and Teaching-Learning-Based Optimization (TLBO) as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

PubMed

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2016-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future.

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects

PubMed Central

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2017-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future. PMID:28167896

DataViewer3D: An Open-Source, Cross-Platform Multi-Modal Neuroimaging Data Visualization Tool

PubMed Central

Gouws, André; Woods, Will; Millman, Rebecca; Morland, Antony; Green, Gary

2008-01-01

Integration and display of results from multiple neuroimaging modalities [e.g. magnetic resonance imaging (MRI), magnetoencephalography, EEG] relies on display of a diverse range of data within a common, defined coordinate frame. DataViewer3D (DV3D) is a multi-modal imaging data visualization tool offering a cross-platform, open-source solution to simultaneous data overlay visualization requirements of imaging studies. While DV3D is primarily a visualization tool, the package allows an analysis approach where results from one imaging modality can guide comparative analysis of another modality in a single coordinate space. DV3D is built on Python, a dynamic object-oriented programming language with support for integration of modular toolkits, and development of cross-platform software for neuroimaging. DV3D harnesses the power of the Visualization Toolkit (VTK) for two-dimensional (2D) and 3D rendering, calling VTK's low level C++ functions from Python. Users interact with data via an intuitive interface that uses Python to bind wxWidgets, which in turn calls the user's operating system dialogs and graphical user interface tools. DV3D currently supports NIfTI-1, ANALYZE™ and DICOM formats for MRI data display (including statistical data overlay). Formats for other data types are supported. The modularity of DV3D and ease of use of Python allows rapid integration of additional format support and user development. DV3D has been tested on Mac OSX, RedHat Linux and Microsoft Windows XP. DV3D is offered for free download with an extensive set of tutorial resources and example data. PMID:19352444

Multimodal MRI for early diabetic mild cognitive impairment: study protocol of a prospective diagnostic trial.

PubMed

Yu, Ying; Sun, Qian; Yan, Lin-Feng; Hu, Yu-Chuan; Nan, Hai-Yan; Yang, Yang; Liu, Zhi-Cheng; Wang, Wen; Cui, Guang-Bin

2016-08-24

Type 2 diabetes mellitus (T2DM) is a risk factor for dementia. Mild cognitive impairment (MCI), an intermediary state between normal cognition and dementia, often occurs during the prodromal diabetic stage, making early diagnosis and intervention of MCI very important. Latest neuroimaging techniques revealed some underlying microstructure alterations for diabetic MCI, from certain aspects. But there still lacks an integrated multimodal MRI system to detect early neuroimaging changes in diabetic MCI patients. Thus, we intended to conduct a diagnostic trial using multimodal MRI techniques to detect early diabetic MCI that is determined by the Montreal Cognitive Assessment (MoCA). In this study, healthy controls, prodromal diabetes and diabetes subjects (53 subjects/group) aged 40-60 years will be recruited from the physical examination center of Tangdu Hospital. The neuroimaging and psychometric measurements will be repeated at a 0.5 year-interval for 2.5 years' follow-up. The primary outcome measures are 1) Microstructural and functional alterations revealed with multimodal MRI scans including structure magnetic resonance imaging (sMRI), resting state functional magnetic resonance imaging (rs-fMRI), diffusion kurtosis imaging (DKI), and three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL); 2) Cognition evaluation with MoCA. The second outcome measures are obesity, metabolic characteristics, lifestyle and quality of life. The study will provide evidence for the potential use of multimodal MRI techniques with psychometric evaluation in diagnosing MCI at prodromal diabetic stage so as to help decision making in early intervention and improve the prognosis of T2DM. This study has been registered to ClinicalTrials.gov ( NCT02420470 ) on April 2, 2015 and published on July 29, 2015.

Usefulness of the advanced neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state images for gamma knife radiosurgery and planning microsurgical procedures for skull base tumors.

PubMed

Hayashi, Motohiro; Chernov, Mikhail F; Tamura, Noriko; Yomo, Shoji; Tamura, Manabu; Horiba, Ayako; Izawa, Masahiro; Muragaki, Yoshihiro; Iseki, Hiroshi; Okada, Yoshikazu; Ivanov, Pavel; Régis, Jean; Takakura, Kintomo

2013-01-01

Gamma Knife radiosurgery (GKS) is currently performed with 0.1 mm preciseness, which can be designated microradiosurgery. It requires advanced methods for visualizing the target, which can be effectively attained by a neuroimaging protocol based on plain and gadolinium-enhanced constructive interference in steady state (CISS) images. Since 2003, the following thin-sliced images are routinely obtained before GKS of skull base lesions in our practice: axial CISS, gadolinium-enhanced axial CISS, gadolinium-enhanced axial modified time-of-flight (TOF), and axial computed tomography (CT). Fusion of "bone window" CT and magnetic resonance imaging (MRI), and detailed three-dimensional (3D) delineation of the anatomical structures are performed with the Leksell GammaPlan (Elekta Instruments AB). Recently, a similar technique has been also applied to evaluate neuroanatomy before open microsurgical procedures. Plain CISS images permit clear visualization of the cranial nerves in the subarachnoid space. Gadolinium-enhanced CISS images make the tumor "lucid" but do not affect the signal intensity of the cranial nerves, so they can be clearly delineated in the vicinity to the lesion. Gadolinium-enhanced TOF images are useful for 3D evaluation of the interrelations between the neoplasm and adjacent vessels. Fusion of "bone window" CT and MRI scans permits simultaneous assessment of both soft tissue and bone structures and allows 3D estimation and correction of MRI distortion artifacts. Detailed understanding of the neuroanatomy based on application of the advanced neuroimaging protocol permits performance of highly conformal and selective radiosurgical treatment. It also allows precise planning of the microsurgical procedures for skull base tumors.

Neural correlates of attention and arousal: insights from electrophysiology, functional neuroimaging and psychopharmacology.

PubMed

Coull, J T

1998-07-01

Attention and arousal are multi-dimensional psychological processes, which interact closely with one another. The neural substrates of attention, as well as the interaction between arousal and attention, are discussed in this review. After a brief discussion of psychological and neuropsychological theories of attention, event-related potential correlates of attention are discussed. Essentially, attention acts to modulate stimulus-induced electrical potentials (N100/P100, P300, N400), rather than generating any unique potentials of its own. Functional neuroimaging studies of attentional orienting, selective attention, divided attention and sustained attention (and its inter-dependence on underlying levels of arousal) are then reviewed. A distinction is drawn between the brain areas which are crucially involved in the top-down modulation of attention (the 'sources' of attention) and those sensory-association areas whose activity is modulated by attention (the 'sites' of attentional expression). Frontal and parietal (usually right-lateralised) cortices and thalamus are most often associated with the source of attentional modulation. Also, the use of functional neuroimaging to test explicit hypotheses about psychological theories of attention is emphasised. These experimental paradigms form the basis for a 'new generation' of functional imaging studies which exploit the dynamic aspect of imaging and demonstrate how it can be used as more than just a 'brain mapping' device. Finally, a review of psychopharmacological studies in healthy human volunteers outlines the contributions of the noradrenergic, cholinergic and dopaminergic neurotransmitter systems to the neurochemical modulation of human attention and arousal. While, noradrenergic and cholinergic systems are involved in 'low-level' aspects of attention (e.g. attentional orienting), the dopaminergic system is associated with more 'executive' aspects of attention such as attentional set-shifting or working memory.

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization.

PubMed

Mankiw, Catherine; Park, Min Tae M; Reardon, P K; Fish, Ari M; Clasen, Liv S; Greenstein, Deanna; Giedd, Jay N; Blumenthal, Jonathan D; Lerch, Jason P; Chakravarty, M Mallar; Raznahan, Armin

2017-05-24

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences-including their spatial distribution, potential biological determinants, and independence from brain volume variation-lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male-female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. Copyright © 2017 the authors 0270-6474/17/375222-11$15.00/0.

High-dimensional atom localization via spontaneously generated coherence in a microwave-driven atomic system.

PubMed

Wang, Zhiping; Chen, Jinyu; Yu, Benli

2017-02-20

We investigate the two-dimensional (2D) and three-dimensional (3D) atom localization behaviors via spontaneously generated coherence in a microwave-driven four-level atomic system. Owing to the space-dependent atom-field interaction, it is found that the detecting probability and precision of 2D and 3D atom localization behaviors can be significantly improved via adjusting the system parameters, the phase, amplitude, and initial population distribution. Interestingly, the atom can be localized in volumes that are substantially smaller than a cubic optical wavelength. Our scheme opens a promising way to achieve high-precision and high-efficiency atom localization, which provides some potential applications in high-dimensional atom nanolithography.

Multilocality and fusion rules on the generalized structure functions in two-dimensional and three-dimensional Navier-Stokes turbulence.

PubMed

Gkioulekas, Eleftherios

2016-09-01

Using the fusion-rules hypothesis for three-dimensional and two-dimensional Navier-Stokes turbulence, we generalize a previous nonperturbative locality proof to multiple applications of the nonlinear interactions operator on generalized structure functions of velocity differences. We call this generalization of nonperturbative locality to multiple applications of the nonlinear interactions operator "multilocality." The resulting cross terms pose a new challenge requiring a new argument and the introduction of a new fusion rule that takes advantage of rotational symmetry. Our main result is that the fusion-rules hypothesis implies both locality and multilocality in both the IR and UV limits for the downscale energy cascade of three-dimensional Navier-Stokes turbulence and the downscale enstrophy cascade and inverse energy cascade of two-dimensional Navier-Stokes turbulence. We stress that these claims relate to nonperturbative locality of generalized structure functions on all orders and not the term-by-term perturbative locality of diagrammatic theories or closure models that involve only two-point correlation and response functions.

What do patients with epilepsy tell us about language dynamics? A review of fMRI studies.

PubMed

Baciu, Monica; Perrone-Bertolotti, Marcela

2015-01-01

The objective of this review is to resume major neuroimaging findings on language organization and plasticity in patients with focal and refractory epilepsy, to discuss the effect of modulatory variables that should be considered alongside patterns of reorganization, and to propose possible models of language reorganization. The focal and refractory epilepsy provides a real opportunity to investigate various types of language reorganization in different conditions. The 'chronic' condition (induced by the epileptogenic zone or EZ) is associated with either recruitment of homologous regions of the opposite hemisphere or recruitment of intrahemispheric, nonlinguistic regions. In the 'acute' condition (neurosurgery and EZ resection), the initial interhemispheric shift (induced by the chronic EZ) could follow a reverse direction, back to the initial hemisphere. These different patterns depend on several modulatory factors and are associated with various levels of language performance. As a neuroimaging tool, functional magnetic resonance imaging enables the detailed investigation of both hemispheres simultaneously and allows for comparison with healthy controls, potentially creating a more comprehensive and more realistic picture of brain-language relations. Importantly, functional neuroimaging approaches demonstrate a good degree of concordance on a theoretical level, but also a considerable degree of individual variability, attesting to the clinical importance with these methods to establish, empirically, language localization in individual patients. Overall, the unique features of epilepsy, combined with ongoing advances in technology, promise further improvement in understanding of language substrate.

Neuromarketing: the hope and hype of neuroimaging in business.

PubMed

Ariely, Dan; Berns, Gregory S

2010-04-01

The application of neuroimaging methods to product marketing - neuromarketing - has recently gained considerable popularity. We propose that there are two main reasons for this trend. First, the possibility that neuroimaging will become cheaper and faster than other marketing methods; and second, the hope that neuroimaging will provide marketers with information that is not obtainable through conventional marketing methods. Although neuroimaging is unlikely to be cheaper than other tools in the near future, there is growing evidence that it may provide hidden information about the consumer experience. The most promising application of neuroimaging methods to marketing may come before a product is even released - when it is just an idea being developed.

Neuromarketing: the hope and hype of neuroimaging in business

PubMed Central

Ariely, Dan; Berns, Gregory S.

2010-01-01

The application of neuroimaging methods to product marketing — neuromarketing — has recently gained considerable popularity. We propose that there are two main reasons for this trend. First, the possibility that neuroimaging will become cheaper and faster than other marketing methods; and second, the hope that neuroimaging will provide marketers with information that is not obtainable through conventional marketing methods. Although neuroimaging is unlikely to be cheaper than other tools in the near future, there is growing evidence that it may provide hidden information about the consumer experience. The most promising application of neuroimaging methods to marketing may come before a product is even released — when it is just an idea being developed. PMID:20197790

Brain alterations in low-frequency fluctuations across multiple bands in obsessive compulsive disorder.

PubMed

Giménez, Mònica; Guinea-Izquierdo, Andrés; Villalta-Gil, Victoria; Martínez-Zalacaín, Ignacio; Segalàs, Cinto; Subirà, Marta; Real, Eva; Pujol, Jesús; Harrison, Ben J; Haro, Josep Maria; Sato, Joao R; Hoexter, Marcelo Q; Cardoner, Narcís; Alonso, Pino; Menchón, José Manuel; Soriano-Mas, Carles

2017-12-01

The extent of functional abnormalities in frontal-subcortical circuits in obsessive-compulsive disorder (OCD) is still unclear. Although neuroimaging studies, in general, and resting-state functional Magnetic Resonance Imaging (rs-fMRI), in particular, have provided relevant information regarding such alterations, rs-fMRI studies have been typically limited to the analysis of between-region functional connectivity alterations at low-frequency signal fluctuations (i.e., <0.08 Hz). Conversely, the local attributes of Blood Oxygen Level Dependent (BOLD) signal across different frequency bands have been seldom studied, although they may provide valuable information. Here, we evaluated local alterations in low-frequency fluctuations across different oscillation bands in OCD. Sixty-five OCD patients and 50 healthy controls underwent an rs-fMRI assessment. Alterations in the fractional amplitude of low-frequency fluctuations (fALFF) were evaluated, voxel-wise, across four different bands (from 0.01 Hz to 0.25 Hz). OCD patients showed decreased fALFF values in medial orbitofrontal regions and increased fALFF values in the dorsal-medial prefrontal cortex (DMPFC) at frequency bands <0.08 Hz. This pattern was reversed at higher frequencies, where increased fALFF values also appeared in medial temporal lobe structures and medial thalamus. Clinical variables (i.e., symptom-specific severities) were associated with fALFF values across the different frequency bands. Our findings provide novel evidence about the nature and regional distribution of functional alterations in OCD, which should contribute to refine neurobiological models of the disorder. We suggest that the evaluation of the local attributes of BOLD signal across different frequency bands may be a sensitive approach to further characterize brain functional alterations in psychiatric disorders.

Systematic Redaction for Neuroimage Data

PubMed Central

Matlock, Matt; Schimke, Nakeisha; Kong, Liang; Macke, Stephen; Hale, John

2013-01-01

In neuroscience, collaboration and data sharing are undermined by concerns over the management of protected health information (PHI) and personal identifying information (PII) in neuroimage datasets. The HIPAA Privacy Rule mandates measures for the preservation of subject privacy in neuroimaging studies. Unfortunately for the researcher, the management of information privacy is a burdensome task. Wide scale data sharing of neuroimages is challenging for three primary reasons: (i) A dearth of tools to systematically expunge PHI/PII from neuroimage data sets, (ii) a facility for tracking patient identities in redacted datasets has not been produced, and (iii) a sanitization workflow remains conspicuously absent. This article describes the XNAT Redaction Toolkit—an integrated redaction workflow which extends a popular neuroimage data management toolkit to remove PHI/PII from neuroimages. Quickshear defacing is also presented as a complementary technique for deidentifying the image data itself. Together, these tools improve subject privacy through systematic removal of PII/PHI. PMID:24179597

What do people with dementia and their carers want to know about neuroimaging for dementia?

PubMed

Featherstone, Hannah; Butler, Marie-Louise; Ciblis, Aurelia; Bokde, Arun L; Mullins, Paul G; McNulty, Jonathan P

2017-05-01

Neuroimaging forms an important part of dementia diagnosis. Provision of information on neuroimaging to people with dementia and their carers may aid understanding of the pathological, physiological and psychosocial changes of the disease, and increase understanding of symptoms. This qualitative study aimed to investigate participants' knowledge of the dementia diagnosis pathway, their understanding of neuroimaging and its use in diagnosis, and to determine content requirements for a website providing neuroimaging information. Structured interviews and a focus group were conducted with carers and people with dementia. The findings demonstrate an unmet need for information on neuroimaging both before and after the examination. Carers were keen to know about neuroimaging at a practical and technical level to help avoid diagnosis denial. People with dementia requested greater information, but with a caveat to avoid overwhelming detail, and were less likely to favour an Internet resource.

Neuroimaging: A Window to the Neurological Foundations of Learning and Behavior in Children.

ERIC Educational Resources Information Center

Lyon, G. Reid, Ed.; Rumsey, Judith M., Ed.

This book presents 11 papers on the use of neuroimaging technology in brain-related disorders. The text contains full-color neuroimaging scans and provides both theoretical and methodological explanations of the various neuroimaging techniques and their application to developmental disorders in children. The papers are grouped into three sections,…

Ethical and Legal Implications of the Methodological Crisis in Neuroimaging.

PubMed

Kellmeyer, Philipp

2017-10-01

Currently, many scientific fields such as psychology or biomedicine face a methodological crisis concerning the reproducibility, replicability, and validity of their research. In neuroimaging, similar methodological concerns have taken hold of the field, and researchers are working frantically toward finding solutions for the methodological problems specific to neuroimaging. This article examines some ethical and legal implications of this methodological crisis in neuroimaging. With respect to ethical challenges, the article discusses the impact of flawed methods in neuroimaging research in cognitive and clinical neuroscience, particularly with respect to faulty brain-based models of human cognition, behavior, and personality. Specifically examined is whether such faulty models, when they are applied to neurological or psychiatric diseases, could put patients at risk, and whether this places special obligations on researchers using neuroimaging. In the legal domain, the actual use of neuroimaging as evidence in United States courtrooms is surveyed, followed by an examination of ways that the methodological problems may create challenges for the criminal justice system. Finally, the article reviews and promotes some promising ideas and initiatives from within the neuroimaging community for addressing the methodological problems.

Breaking the cycles of poverty: Strategies, achievements, and lessons learned in Los Cuatro Santos, Nicaragua, 1990–2014

PubMed Central

Blandón, Elmer Zelaya; Källestål, Carina; Peña, Rodolfo; Perez, Wilton; Berglund, Staffan; Contreras, Mariela; Persson, Lars-Åke

2017-01-01

ABSTRACT Background: In a post-war frontier area in north-western Nicaragua that was severely hit by Hurricane Mitch in 1998, local stakeholders embarked on and facilitated multi-dimensional development initiatives to break the cycles of poverty. Objective: The aim of this paper is to describe the process of priority-setting, and the strategies, guiding principles, activities, achievements, and lessons learned in these local development efforts from 1990 to 2014 in the Cuatro Santos area, Nicaragua. Methods: Data were derived from project records and a Health and Demographic Surveillance System that was initiated in 2004. The area had 25,893 inhabitants living in 5,966 households in 2014. Results: A participatory process with local stakeholders and community representatives resulted in a long-term strategic plan. Guiding principles were local ownership, political reconciliation, consensus decision-making, social and gender equity, an environmental and public health perspective, and sustainability. Local data were used in workshops with communities to re-prioritise and formulate new goals. The interventions included water and sanitation, house construction, microcredits, environmental protection, school breakfasts, technical training, university scholarships, home gardening, breastfeeding promotion, and maternity waiting homes. During the last decade, the proportion of individuals living in poverty was reduced from 79 to 47%. Primary school enrolment increased from 70 to 98% after the start of the school breakfast program. Under-five mortality was around 50 per 1,000 live births in 1990 and again peaked after Hurricane Mitch and was approaching 20 per 1,000 in 2014. Several of the interventions have been scaled up as national programs. Conclusions: The lessons learned from the Cuatro Santos initiative underline the importance of a bottom-up approach and local ownership of the development process, the value of local data for monitoring and evaluation, and the need for multi-dimensional local interventions to break the cycles of poverty and gain better health and welfare. PMID:28136698

Breaking the cycles of poverty: Strategies, achievements, and lessons learned in Los Cuatro Santos, Nicaragua, 1990-2014.

PubMed

Blandón, Elmer Zelaya; Källestål, Carina; Peña, Rodolfo; Perez, Wilton; Berglund, Staffan; Contreras, Mariela; Persson, Lars-Åke

2017-01-01

In a post-war frontier area in north-western Nicaragua that was severely hit by Hurricane Mitch in 1998, local stakeholders embarked on and facilitated multi-dimensional development initiatives to break the cycles of poverty. The aim of this paper is to describe the process of priority-setting, and the strategies, guiding principles, activities, achievements, and lessons learned in these local development efforts from 1990 to 2014 in the Cuatro Santos area, Nicaragua. Data were derived from project records and a Health and Demographic Surveillance System that was initiated in 2004. The area had 25,893 inhabitants living in 5,966 households in 2014. A participatory process with local stakeholders and community representatives resulted in a long-term strategic plan. Guiding principles were local ownership, political reconciliation, consensus decision-making, social and gender equity, an environmental and public health perspective, and sustainability. Local data were used in workshops with communities to re-prioritise and formulate new goals. The interventions included water and sanitation, house construction, microcredits, environmental protection, school breakfasts, technical training, university scholarships, home gardening, breastfeeding promotion, and maternity waiting homes. During the last decade, the proportion of individuals living in poverty was reduced from 79 to 47%. Primary school enrolment increased from 70 to 98% after the start of the school breakfast program. Under-five mortality was around 50 per 1,000 live births in 1990 and again peaked after Hurricane Mitch and was approaching 20 per 1,000 in 2014. Several of the interventions have been scaled up as national programs. The lessons learned from the Cuatro Santos initiative underline the importance of a bottom-up approach and local ownership of the development process, the value of local data for monitoring and evaluation, and the need for multi-dimensional local interventions to break the cycles of poverty and gain better health and welfare.

Knowledge-Guided Robust MRI Brain Extraction for Diverse Large-Scale Neuroimaging Studies on Humans and Non-Human Primates

PubMed Central

Wang, Yaping; Nie, Jingxin; Yap, Pew-Thian; Li, Gang; Shi, Feng; Geng, Xiujuan; Guo, Lei; Shen, Dinggang

2014-01-01

Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55∼90 years of age, multi-site, various diagnosis groups), OASIS dataset with over 400 subjects (18∼96 years of age, wide age range, various diagnosis groups), and NIH pediatrics dataset with 150 subjects (5∼18 years of age, multi-site, wide age range as a complementary age group to the adult dataset). The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness. PMID:24489639

Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury

PubMed Central

Bigler, Erin D.

2016-01-01

The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology perspective could represent a significant advancement for the field. PMID:27555810

Data-driven approaches in the investigation of social perception

PubMed Central

Adolphs, Ralph; Nummenmaa, Lauri; Todorov, Alexander; Haxby, James V.

2016-01-01

The complexity of social perception poses a challenge to traditional approaches to understand its psychological and neurobiological underpinnings. Data-driven methods are particularly well suited to tackling the often high-dimensional nature of stimulus spaces and of neural representations that characterize social perception. Such methods are more exploratory, capitalize on rich and large datasets, and attempt to discover patterns often without strict hypothesis testing. We present four case studies here: behavioural studies on face judgements, two neuroimaging studies of movies, and eyetracking studies in autism. We conclude with suggestions for particular topics that seem ripe for data-driven approaches, as well as caveats and limitations. PMID:27069045

2-D to 3-D global/local finite element analysis of cross-ply composite laminates

NASA Technical Reports Server (NTRS)

Thompson, D. Muheim; Griffin, O. Hayden, Jr.

1990-01-01

An example of two-dimensional to three-dimensional global/local finite element analysis of a laminated composite plate with a hole is presented. The 'zoom' technique of global/local analysis is used, where displacements of the global/local interface from the two-dimensional global model are applied to the edges of the three-dimensional local model. Three different hole diameters, one, three, and six inches, are considered in order to compare the effect of hole size on the three-dimensional stress state around the hole. In addition, three different stacking sequences are analyzed for the six inch hole case in order to study the effect of stacking sequence. The existence of a 'critical' hole size, where the interlaminar stresses are maximum, is indicated. Dispersion of plies at the same angle, as opposed to clustering, is found to reduce the magnitude of some interlaminar stress components and increase others.

Shadows of rotating five-dimensional charged EMCS black holes

NASA Astrophysics Data System (ADS)

Amir, Muhammed; Singh, Balendra Pratap; Ghosh, Sushant G.

2018-05-01

Higher-dimensional theories admit astrophysical objects like supermassive black holes, which are rather different from standard ones, and their gravitational lensing features deviate from general relativity. It is well known that a black hole shadow is a dark region due to the falling geodesics of photons into the black hole and, if detected, a black hole shadow could be used to determine which theory of gravity is consistent with observations. Measurements of the shadow sizes around the black holes can help to evaluate various parameters of the black hole metric. We study the shapes of the shadow cast by the rotating five-dimensional charged Einstein-Maxwell-Chern-Simons (EMCS) black holes, which is characterized by four parameters, i.e., mass, two spins, and charge, in which the spin parameters are set equal. We integrate the null geodesic equations and derive an analytical formula for the shadow of the five-dimensional EMCS black hole, in turn, to show that size of black hole shadow is affected due to charge as well as spin. The shadow is a dark zone covered by a deformed circle, and the size of the shadow decreases with an increase in the charge q when compared with the five-dimensional Myers-Perry black hole. Interestingly, the distortion increases with charge q. The effect of these parameters on the shape and size of the naked singularity shadow of the five-dimensional EMCS black hole is also discussed.

The effect of intracortical bone pin application on kinetics and tibiocalcaneal kinematics of walking gait.

PubMed

Maiwald, Christian; Arndt, Anton; Nester, Chris; Jones, Richard; Lundberg, Arne; Wolf, Peter

2017-02-01

Bone anchored markers using intracortical bone pins are one of the few available methods for analyzing skeletal motion during human gait in-vivo without errors induced by soft tissue artifacts. However, bone anchored markers require local anesthesia and may alter the motor control and motor output during gait. The purpose of this study was to examine the effect of local anesthesia and the use of bone anchored markers on typical gait analysis variables. Five subjects were analyzed in two different gait analysis sessions. In the first session, a protocol with skin markers was used. In the second session, bone anchored markers were added after local anesthesia was applied. For both sessions, three dimensional infrared kinematics of the calcaneus and tibia segments, ground reaction forces, and plantar pressure data were collected. 95% confidence intervals and boxplots were used to compare protocols and assess the data distribution and data variability for each subject. Although considerable variation was found between subjects, within-subject comparison of the two protocols revealed non-systematic effects on the target variables. Two of the five subjects walked at reduced gait speed during the bone pin session, which explained the between-session differences found in kinetic and kinematic variables. The remaining three subjects did not systematically alter their gait pattern between the two sessions. Results support the hypothesis that local anesthesia and the presence of bone pins still allow a valid gait pattern to be analyzed. Copyright © 2016 Elsevier B.V. All rights reserved.

Quasi-two-dimensional spin correlations in the triangular lattice bilayer spin glass LuCoGaO 4

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

Fritsch, Katharina; Ross, Kathyrn A.; Granroth, Garrett E.

Here we present a single-crystal time-of-flight neutron scattering study of the static and dynamic spin correlations in LuCoGaO 4, a quasi-two-dimensional dilute triangular lattice antiferromagnetic spin-glass material. This system is based on Co 2+ ions that are randomly distributed on triangular bilayers within the YbFe 2O 4 type, hexagonal crystal structure. Antiferromagnetic short-range two-dimensional correlations at wave vectors Q = (1/3,1/3, L) develop within the bilayers at temperatures as high as |Θ CW| ~100 K and extend over roughly five unit cells at temperatures below T g = 19 K. These two-dimensional static correlations are observed as diffuse rods ofmore » neutron scattering intensity along c * and display a continuous spin freezing process in their energy dependence. Aside from exhibiting these typical spin-glass characteristics, this insulating material reveals a novel gapped magnetic resonant spin excitation at ΔE ~12 meV localized around Q = (1 / 3, 1 / 3,L) . The temperature dependence of the spin gap associated with this two-dimensional excitation correlates with the evolution of the static correlations into the spin-glass state ground state. Lastly, we associate it with the effect of the staggered exchange field acting on the S eff = 1/2 Ising-like doublet of the Co 2+ moments.« less

Quasi-two-dimensional spin correlations in the triangular lattice bilayer spin glass LuCoGaO 4

DOE PAGES

Fritsch, Katharina; Ross, Kathyrn A.; Granroth, Garrett E.; ...

2017-09-13

Here we present a single-crystal time-of-flight neutron scattering study of the static and dynamic spin correlations in LuCoGaO 4, a quasi-two-dimensional dilute triangular lattice antiferromagnetic spin-glass material. This system is based on Co 2+ ions that are randomly distributed on triangular bilayers within the YbFe 2O 4 type, hexagonal crystal structure. Antiferromagnetic short-range two-dimensional correlations at wave vectors Q = (1/3,1/3, L) develop within the bilayers at temperatures as high as |Θ CW| ~100 K and extend over roughly five unit cells at temperatures below T g = 19 K. These two-dimensional static correlations are observed as diffuse rods ofmore » neutron scattering intensity along c * and display a continuous spin freezing process in their energy dependence. Aside from exhibiting these typical spin-glass characteristics, this insulating material reveals a novel gapped magnetic resonant spin excitation at ΔE ~12 meV localized around Q = (1 / 3, 1 / 3,L) . The temperature dependence of the spin gap associated with this two-dimensional excitation correlates with the evolution of the static correlations into the spin-glass state ground state. Lastly, we associate it with the effect of the staggered exchange field acting on the S eff = 1/2 Ising-like doublet of the Co 2+ moments.« less

Treatment-responsive limbic encephalitis identified by neuropil antibodies: MRI and PET correlates

PubMed Central

Ances, Beau M.; Vitaliani, Roberta; Taylor, Robert A.; Liebeskind, David S.; Voloschin, Alfredo; Houghton, David J.; Galetta, Steven L.; Dichter, Marc; Alavi, Abass; Rosenfeld, Myrna R.; Dalmau, Josep

2007-01-01

We report seven patients, six from a single institution, who developed subacute limbic encephalitis initially considered of uncertain aetiology. Four patients presented with symptoms of hippocampal dysfunction (i.e. severe short-term memory loss) and three with extensive limbic dysfunction (i.e. confusion, seizures and suspected psychosis). Brain MRI and [18F]fluorodeoxyglucose (FDG)-PET complemented each other but did not overlap in 50% of the patients. Combining both tests, all patients had temporal lobe abnormalities, five with additional areas involved. In one patient, FDG hyperactivity in the brainstem that was normal on MRI correlated with central hypoventilation; in another case, hyperactivity in the cerebellum anticipated ataxia. All patients had abnormal CSF: six pleocytosis, six had increased protein concentration, and three of five examined had oligoclonal bands. A tumour was identified and removed in four patients (mediastinal teratoma, thymoma, thymic carcinoma and thyroid cancer) and not treated in one (ovarian teratoma). An immunohistochemical technique that facilitates the detection of antibodies to cell surface or synaptic proteins demonstrated that six patients had antibodies to the neuropil of hippocampus or cerebellum, and one to intraneuronal antigens. Only one of the neuropil antibodies corresponded to voltage-gated potassium channel (VGKC) antibodies; the other five (two with identical specificity) reacted with antigens concentrated in areas of high dendritic density or synaptic-enriched regions of the hippocampus or cerebellum. Preliminary characterization of these antigens indicates that they are diverse and expressed on the neuronal cell membrane and dendrites; they do not co-localize with VGKCs, but partially co-localize with spinophilin. A target autoantigen in one of the patients co-localizes with a cell surface protein involved in hippocampal dendritic development. All patients except the one with antibodies to intracellular antigens had dramatic clinical and neuroimaging responses to immunotherapy or tumour resection; two patients had neurological relapse and improved with immunotherapy. Overall, the phenotype associated with the novel neuropil antibodies includes dominant behavioural and psychiatric symptoms and seizures that often interfere with the evaluation of cognition and memory, and brain MRI or FDG-PET abnormalities less frequently restricted to the medial temporal lobes than in patients with classical paraneoplastic or VGKC antibodies. When compared with patients with VGKC antibodies, patients with these novel antibodies are more likely to have CSF inflammatory abnormalities and systemic tumours (teratoma and thymoma), and they do not develop SIADH-like hyponatraemia. Although most autoantigens await characterization, all share intense expression by the neuropil of hippocampus, with patterns of immunolabelling characteristic enough to suggest the diagnosis of these disorders and predict response to treatment. PMID:15888538

Intrinsic gray-matter connectivity of the brain in adults with autism spectrum disorder

PubMed Central

Ecker, Christine; Ronan, Lisa; Feng, Yue; Daly, Eileen; Murphy, Clodagh; Ginestet, Cedric E.; Brammer, Michael; Fletcher, Paul C.; Bullmore, Edward T.; Suckling, John; Baron-Cohen, Simon; Williams, Steve; Loth, Eva; Murphy, Declan G. M.; Bailey, A. J.; Baron-Cohen, S.; Bolton, P. F.; Bullmore, E. T.; Carrington, S.; Chakrabarti, B.; Daly, E. M.; Deoni, S. C.; Ecker, C.; Happe, F.; Henty, J.; Jezzard, P.; Johnston, P.; Jones, D. K.; Lai, M. C.; Lombardo, M. V.; Madden, A.; Mullins, D.; Murphy, C. M.; Murphy, D. G.; Pasco, G.; Sadek, S.; Spain, D.; Steward, R.; Suckling, J.; Wheelwright, S.; Williams, S. C.

2013-01-01

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions that are accompanied by atypical brain connectivity. So far, in vivo evidence for atypical structural brain connectivity in ASD has mainly been based on neuroimaging studies of cortical white matter. However, genetic studies suggest that abnormal connectivity in ASD may also affect neural connections within the cortical gray matter. Such intrinsic gray-matter connections are inherently more difficult to describe in vivo but may be inferred from a variety of surface-based geometric features that can be measured using magnetic resonance imaging. Here, we present a neuroimaging study that examines the intrinsic cortico-cortical connectivity of the brain in ASD using measures of “cortical separation distances” to assess the global and local intrinsic “wiring costs” of the cortex (i.e., estimated length of horizontal connections required to wire the cortex within the cortical sheet). In a sample of 68 adults with ASD and matched controls, we observed significantly reduced intrinsic wiring costs of cortex in ASD, both globally and locally. Differences in global and local wiring cost were predominantly observed in fronto-temporal regions and also significantly predicted the severity of social and repetitive symptoms (respectively). Our study confirms that atypical cortico-cortical “connectivity” in ASD is not restricted to the development of white-matter connections but may also affect the intrinsic gray-matter architecture (and connectivity) within the cortical sheet. Thus, the atypical connectivity of the brain in ASD is complex, affecting both gray and white matter, and forms part of the core neural substrates underlying autistic symptoms. PMID:23878213

Intrinsic gray-matter connectivity of the brain in adults with autism spectrum disorder.

PubMed

Ecker, Christine; Ronan, Lisa; Feng, Yue; Daly, Eileen; Murphy, Clodagh; Ginestet, Cedric E; Brammer, Michael; Fletcher, Paul C; Bullmore, Edward T; Suckling, John; Baron-Cohen, Simon; Williams, Steve; Loth, Eva; Murphy, Declan G M

2013-08-06

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions that are accompanied by atypical brain connectivity. So far, in vivo evidence for atypical structural brain connectivity in ASD has mainly been based on neuroimaging studies of cortical white matter. However, genetic studies suggest that abnormal connectivity in ASD may also affect neural connections within the cortical gray matter. Such intrinsic gray-matter connections are inherently more difficult to describe in vivo but may be inferred from a variety of surface-based geometric features that can be measured using magnetic resonance imaging. Here, we present a neuroimaging study that examines the intrinsic cortico-cortical connectivity of the brain in ASD using measures of "cortical separation distances" to assess the global and local intrinsic "wiring costs" of the cortex (i.e., estimated length of horizontal connections required to wire the cortex within the cortical sheet). In a sample of 68 adults with ASD and matched controls, we observed significantly reduced intrinsic wiring costs of cortex in ASD, both globally and locally. Differences in global and local wiring cost were predominantly observed in fronto-temporal regions and also significantly predicted the severity of social and repetitive symptoms (respectively). Our study confirms that atypical cortico-cortical "connectivity" in ASD is not restricted to the development of white-matter connections but may also affect the intrinsic gray-matter architecture (and connectivity) within the cortical sheet. Thus, the atypical connectivity of the brain in ASD is complex, affecting both gray and white matter, and forms part of the core neural substrates underlying autistic symptoms.

Brain mapping in cognitive disorders: a multidisciplinary approach to learning the tools and applications of functional neuroimaging

PubMed Central

Kelley, Daniel J; Johnson, Sterling C

2007-01-01

Background With rapid advances in functional imaging methods, human studies that feature functional neuroimaging techniques are increasing exponentially and have opened a vast arena of new possibilities for understanding brain function and improving the care of patients with cognitive disorders in the clinical setting. There is a growing need for medical centers to offer clinically relevant functional neuroimaging courses that emphasize the multifaceted and multidisciplinary nature of this field. In this paper, we describe the implementation of a functional neuroimaging course focusing on cognitive disorders that might serve as a model for other medical centers. We identify key components of an active learning course design that impact student learning gains in methods and issues pertaining to functional neuroimaging that deserve consideration when optimizing the medical neuroimaging curriculum. Methods Learning gains associated with the course were assessed using polychoric correlation analysis of responses to the SALG (Student Assessment of Learning Gains) instrument. Results Student gains in the functional neuroimaging of cognition as assessed by the SALG instrument were strongly associated with several aspects of the course design. Conclusion Our implementation of a multidisciplinary and active learning functional neuroimaging course produced positive learning outcomes. Inquiry-based learning activities and an online learning environment contributed positively to reported gains. This functional neuroimaging course design may serve as a useful model for other medical centers. PMID:17953758

Perception of affective and linguistic prosody: an ALE meta-analysis of neuroimaging studies.

PubMed

Belyk, Michel; Brown, Steven

2014-09-01

Prosody refers to the melodic and rhythmic aspects of speech. Two forms of prosody are typically distinguished: 'affective prosody' refers to the expression of emotion in speech, whereas 'linguistic prosody' relates to the intonation of sentences, including the specification of focus within sentences and stress within polysyllabic words. While these two processes are united by their use of vocal pitch modulation, they are functionally distinct. In order to examine the localization and lateralization of speech prosody in the brain, we performed two voxel-based meta-analyses of neuroimaging studies of the perception of affective and linguistic prosody. There was substantial sharing of brain activations between analyses, particularly in right-hemisphere auditory areas. However, a major point of divergence was observed in the inferior frontal gyrus: affective prosody was more likely to activate Brodmann area 47, while linguistic prosody was more likely to activate the ventral part of area 44. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Neuroimaging in epilepsy.

PubMed

Sidhu, Meneka Kaur; Duncan, John S; Sander, Josemir W

2018-05-17

Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments. The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy. Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.

The implications of brain connectivity in the neuropsychology of autism

PubMed Central

Maximo, Jose O.; Cadena, Elyse J.; Kana, Rajesh K.

2014-01-01

Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a biomarker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate. PMID:24496901

Complex biomarker discovery in neuroimaging data: Finding a needle in a haystack☆

PubMed Central

Atluri, Gowtham; Padmanabhan, Kanchana; Fang, Gang; Steinbach, Michael; Petrella, Jeffrey R.; Lim, Kelvin; MacDonald, Angus; Samatova, Nagiza F.; Doraiswamy, P. Murali; Kumar, Vipin

2013-01-01

Neuropsychiatric disorders such as schizophrenia, bipolar disorder and Alzheimer's disease are major public health problems. However, despite decades of research, we currently have no validated prognostic or diagnostic tests that can be applied at an individual patient level. Many neuropsychiatric diseases are due to a combination of alterations that occur in a human brain rather than the result of localized lesions. While there is hope that newer imaging technologies such as functional and anatomic connectivity MRI or molecular imaging may offer breakthroughs, the single biomarkers that are discovered using these datasets are limited by their inability to capture the heterogeneity and complexity of most multifactorial brain disorders. Recently, complex biomarkers have been explored to address this limitation using neuroimaging data. In this manuscript we consider the nature of complex biomarkers being investigated in the recent literature and present techniques to find such biomarkers that have been developed in related areas of data mining, statistics, machine learning and bioinformatics. PMID:24179856

The Status of the Quality Control in Acupuncture-Neuroimaging Studies

PubMed Central

Qiu, Ke; Jing, Miaomiao; Liu, Xiaoyan; Gao, Feifei; Liang, Fanrong; Zeng, Fang

2016-01-01

Using neuroimaging techniques to explore the central mechanism of acupuncture gains increasing attention, but the quality control of acupuncture-neuroimaging study remains to be improved. We searched the PubMed Database during 1995 to 2014. The original English articles with neuroimaging scan performed on human beings were included. The data involved quality control including the author, sample size, characteristics of the participant, neuroimaging technology, and acupuncture intervention were extracted and analyzed. The rigorous inclusion and exclusion criteria are important guaranty for the participants' homogeneity. The standard operation process of acupuncture and the stricter requirement for acupuncturist play significant role in quality control. More attention should be paid to the quality control in future studies to improve the reproducibility and reliability of the acupuncture-neuroimaging studies. PMID:27242911

Parsing brain activity with fMRI and mixed designs: what kind of a state is neuroimaging in?

PubMed

Donaldson, David I

2004-08-01

Neuroimaging is often pilloried for providing little more than pretty pictures that simply show where activity occurs in the brain. Strong critics (notably Uttal) have even argued that neuroimaging is nothing more than a modern day version of phrenology: destined to fail, and fundamentally uninformative. Here, I make the opposite case, arguing that neuroimaging is in a vibrant and healthy state of development. As recent investigations of memory illustrate, when used well, neuroimaging goes beyond asking 'where' activity is occurring, to ask questions concerned more with 'what' functional role the activity reflects.

Recognition of Simple 3D Geometrical Objects under Partial Occlusion

NASA Astrophysics Data System (ADS)

Barchunova, Alexandra; Sommer, Gerald

In this paper we present a novel procedure for contour-based recognition of partially occluded three-dimensional objects. In our approach we use images of real and rendered objects whose contours have been deformed by a restricted change of the viewpoint. The preparatory part consists of contour extraction, preprocessing, local structure analysis and feature extraction. The main part deals with an extended construction and functionality of the classifier ensemble Adaptive Occlusion Classifier (AOC). It relies on a hierarchical fragmenting algorithm to perform a local structure analysis which is essential when dealing with occlusions. In the experimental part of this paper we present classification results for five classes of simple geometrical figures: prism, cylinder, half cylinder, a cube, and a bridge. We compare classification results for three classical feature extractors: Fourier descriptors, pseudo Zernike and Zernike moments.

High Frequency of Neuroimaging Abnormalities Among Pediatric Patients With Sepsis Who Undergo Neuroimaging.

PubMed

Sandquist, Mary K; Clee, Mark S; Patel, Smruti K; Howard, Kelli A; Yunger, Toni; Nagaraj, Usha D; Jones, Blaise V; Fei, Lin; Vadivelu, Sudhakar; Wong, Hector R

2017-07-01

This study was intended to describe and correlate the neuroimaging findings in pediatric patients after sepsis. Retrospective chart review. Single tertiary care PICU. Patients admitted to Cincinnati Children's Hospital Medical Center with a discharge diagnosis of sepsis or septic shock between 2004 and 2013 were crossmatched with patients who underwent neuroimaging during the same time period. All neuroimaging studies that occurred during or subsequent to a septic event were reviewed, and all new imaging findings were recorded and classified. As many patients experienced multiple septic events and/or had multiple neuroimaging studies after sepsis, our statistical analysis utilized the most recent or "final" imaging study available for each patient so that only brain imaging findings that persisted were included. A total of 389 children with sepsis and 1,705 concurrent or subsequent neuroimaging studies were included in the study. Median age at first septic event was 3.4 years (interquartile range, 0.7-11.5). Median time from first sepsis event to final neuroimaging was 157 days (interquartile range, 10-1,054). The most common indications for final imaging were follow-up (21%), altered mental status (18%), and fever/concern for infection (15%). Sixty-three percentage (n = 243) of final imaging studies demonstrated abnormal findings, the most common of which were volume loss (39%) and MRI signal and/or CT attenuation abnormalities (21%). On multivariable logistic regression, highest Pediatric Risk of Mortality score and presence of oncologic diagnosis/organ transplantation were independently associated with any abnormal final neuroimaging study findings (odds ratio, 1.032; p = 0.048 and odds ratio, 1.632; p = 0.041), although early timing of neuroimaging demonstrated a negative association (odds ratio, 0.606; p = 0.039). The most common abnormal finding of volume loss was independently associated with highest Pediatric Risk of Mortality score (odds ratio, 1.037; p = 0.016) and oncologic diagnosis/organ transplantation (odds ratio, 2.207; p = 0.001) and was negatively associated with early timing of neuroimaging (odds ratio, 0.575; p = 0.037). The majority of pediatric patients with sepsis and concurrent or subsequent neuroimaging have abnormal neuroimaging findings. The implications of this high incidence for long-term neurologic outcomes and follow-up require further exploration.

Local metrics admitting a principal Killing-Yano tensor with torsion

NASA Astrophysics Data System (ADS)

Houri, Tsuyoshi; Kubizňák, David; Warnick, Claude M.; Yasui, Yukinori

2012-08-01

In this paper we initiate a classification of local metrics admitting the principal Killing-Yano tensor with a skew-symmetric torsion. It is demonstrated that in such spacetimes rank-2 Killing tensors occur naturally and mutually commute. We reduce the classification problem to that of solving a set of partial differential equations, and we present some solutions to these PDEs. In even dimensions, three types of local metrics are obtained: one of them naturally generalizes the torsion-less case while the others occur only when the torsion is present. In odd dimensions, we obtain more varieties of local metrics. The explicit metrics constructed in this paper are not the most general possible admitting the required symmetry; nevertheless, it is demonstrated that they cover a wide variety of solutions of various supergravities, such as the Kerr-Sen black holes of (un-)gauged Abelian heterotic supergravity, the Chong-Cvetic-Lü-Pope black hole solution of five-dimensional minimal supergravity or the Kähler with torsion manifolds. The relation between generalized Killing-Yano tensors and various torsion Killing spinors is also discussed.

Size-Independent Exciton Localization Efficiency in Colloidal CdSe/CdS Core/Crown Nanosheet Type-I Heterostructures.

PubMed

Li, Qiuyang; Wu, Kaifeng; Chen, Jinquan; Chen, Zheyuan; McBride, James R; Lian, Tianquan

2016-03-22

CdSe/CdS core/crown nanoplatelet type I heterostructures are a class of two-dimensional materials with atomically precise thickness and many potential optoelectronic applications. It remains unclear how the precise thickness and lack of energy disorder affect the properties of exciton transport in these materials. By steady-state photoluminescence excitation spectroscopy and ultrafast transient absorption spectroscopy, we show that in five CdSe/CdS core/crown structures with the same core and increasing crown size (with thickness of ∼1.8 nm, width of ∼11 nm, and length from 20 to 40 nm), the crown-to-core exciton localization efficiency is independent of crown size and increases with photon energy above the band edge (from 70% at 400 nm to ∼100% at 370 nm), while the localization time increases with the crown size. These observations can be understood by a model that accounts for the competition of in-plane exciton diffusion and selective hole trapping at the core/crown interface. Our findings suggest that the exciton localization efficiency can be further improved by reducing interfacial defects.

Loss anticipation and outcome during the Monetary Incentive Delay Task: a neuroimaging systematic review and meta-analysis

PubMed Central

Dugré, Jules R.; Dumais, Alexandre; Bitar, Nathalie

2018-01-01

Background Reward seeking and avoidance of punishment are key motivational processes. Brain-imaging studies often use the Monetary Incentive Delay Task (MIDT) to evaluate motivational processes involved in maladaptive behavior. Although the bulk of research has been done on the MIDT reward events, little is known about the neural basis of avoidance of punishment. Therefore, we conducted a meta-analysis of brain activations during anticipation and receipt of monetary losses in healthy controls. Methods All functional neuro-imaging studies using the MIDT in healthy controls were retrieved using PubMed, Google Scholar & EMBASE databases. Functional neuro-imaging data was analyzed using the Seed-based d Mapping Software. Results Thirty-five studies met the inclusion criteria, comprising 699 healthy adults. In both anticipation and loss outcome phases, participants showed large and robust activations in the bilateral striatum, (anterior) insula, and anterior cingulate gyrus relatively to Loss > Neutral contrast. Although relatively similar activation patterns were observed during the two event types, they differed in the pattern of prefrontal activations: ventro-lateral prefrontal activations were observed during loss anticipation, while medial prefrontal activations were observed during loss receipt. Discussion Considering that previous meta-analyses highlighted activations in the medial prefrontal cortex/anterior cingulate cortex, the anterior insula and the ventral striatum, the current meta-analysis highlighted the potential specificity of the ventro-lateral prefrontal regions, the median cingulate cortex and the amygdala in the loss events. Future studies can rely on these latter results to examine the neural correlates of loss processing in psychiatric populations characterized by harm avoidance or insensitivity to punishment. PMID:29761060

Loss anticipation and outcome during the Monetary Incentive Delay Task: a neuroimaging systematic review and meta-analysis.

PubMed

Dugré, Jules R; Dumais, Alexandre; Bitar, Nathalie; Potvin, Stéphane

2018-01-01

Reward seeking and avoidance of punishment are key motivational processes. Brain-imaging studies often use the Monetary Incentive Delay Task (MIDT) to evaluate motivational processes involved in maladaptive behavior. Although the bulk of research has been done on the MIDT reward events, little is known about the neural basis of avoidance of punishment. Therefore, we conducted a meta-analysis of brain activations during anticipation and receipt of monetary losses in healthy controls. All functional neuro-imaging studies using the MIDT in healthy controls were retrieved using PubMed, Google Scholar & EMBASE databases. Functional neuro-imaging data was analyzed using the Seed-based d Mapping Software. Thirty-five studies met the inclusion criteria, comprising 699 healthy adults. In both anticipation and loss outcome phases, participants showed large and robust activations in the bilateral striatum, (anterior) insula, and anterior cingulate gyrus relatively to Loss > Neutral contrast. Although relatively similar activation patterns were observed during the two event types, they differed in the pattern of prefrontal activations: ventro-lateral prefrontal activations were observed during loss anticipation, while medial prefrontal activations were observed during loss receipt. Considering that previous meta-analyses highlighted activations in the medial prefrontal cortex/anterior cingulate cortex, the anterior insula and the ventral striatum, the current meta-analysis highlighted the potential specificity of the ventro-lateral prefrontal regions, the median cingulate cortex and the amygdala in the loss events. Future studies can rely on these latter results to examine the neural correlates of loss processing in psychiatric populations characterized by harm avoidance or insensitivity to punishment.

Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches.

PubMed

Wang, Jiaojian; Yang, Yong; Fan, Lingzhong; Xu, Jinping; Li, Changhai; Liu, Yong; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2015-01-01

The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions. © 2014 Wiley Periodicals, Inc.

“Can It Read My Mind?” – What Do the Public and Experts Think of the Current (Mis)Uses of Neuroimaging?

PubMed Central

Wardlaw, Joanna M.; O'Connell, Garret; Shuler, Kirsten; DeWilde, Janet; Haley, Jane; Escobar, Oliver; Murray, Shaun; Rae, Robert; Jarvie, Donald; Sandercock, Peter; Schafer, Burkhard

2011-01-01

Emerging applications of neuroimaging outside medicine and science have received intense public exposure through the media. Media misrepresentations can create a gulf between public and scientific understanding of the capabilities of neuroimaging and raise false expectations. To determine the extent of this effect and determine public opinions on acceptable uses and the need for regulation, we designed an electronic survey to obtain anonymous opinions from as wide a range of members of the public and neuroimaging experts as possible. The surveys ran from 1st June to 30 September 2010, asked 10 and 21 questions, respectively, about uses of neuroimaging outside traditional medical diagnosis, data storage, science communication and potential methods of regulation. We analysed the responses using descriptive statistics; 660 individuals responded to the public and 303 individuals responded to the expert survey. We found evidence of public skepticism about the use of neuroimaging for applications such as lie detection or to determine consumer preferences and considerable disquiet about use by employers or government and about how their data would be stored and used. While also somewhat skeptical about new applications of neuroimaging, experts grossly underestimated how often neuroimaging had been used as evidence in court. Although both the public and the experts rated highly the importance of a better informed public in limiting the inappropriate uses to which neuroimaging might be put, opinions differed on the need for, and mechanism of, actual regulation. Neuroscientists recognized the risks of inaccurate reporting of neuroimaging capabilities in the media but showed little motivation to engage with the public. The present study also emphasizes the need for better frameworks for scientific engagement with media and public education. PMID:21991367

Data sharing in neuroimaging research

PubMed Central

Poline, Jean-Baptiste; Breeze, Janis L.; Ghosh, Satrajit; Gorgolewski, Krzysztof; Halchenko, Yaroslav O.; Hanke, Michael; Haselgrove, Christian; Helmer, Karl G.; Keator, David B.; Marcus, Daniel S.; Poldrack, Russell A.; Schwartz, Yannick; Ashburner, John; Kennedy, David N.

2012-01-01

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging. PMID:22493576

Five-Dimensional Gauged Supergravity with Higher Derivatives

NASA Astrophysics Data System (ADS)

Hanaki, Kentaro

This thesis summarizes the recent developments on the study of five-dimensional gauged supergravity with higher derivative terms, emphasizing in particular the application to understanding the hydrodynamic properties of gauge theory plasma via the AdS/CFT correspondence. We first review how the ungauged and gauged five-dimensional supergravity actions with higher derivative terms can be constructed using the off-shell superconformal formalism. Then we relate the gauged supergravity to four-dimensional gauge theory using the AdS/CFT correspondence and extract the physical quantities associated with gauge theory plasma from the dual classical supergravity computations. We put a particular emphasis on the discussion of the conjectured lower bound for the shear viscosity over entropy density ratio proposed by Kovtun, Son and Starinets, and discuss how higher derivative terms in supergravity and the introduction of chemical potential for the R-charge affect this bound.

A three-dimensional laser vibration measurement technology realized on five laser beam and its calibration

NASA Astrophysics Data System (ADS)

Li, Lu-Ke; Zhang, Shen-Feng

2018-03-01

Put forward a kind of three-dimensional vibration information technology of vibrating object by the mean of five laser beam of He-Ne laser, and with the help of three-way sensor, measure the three-dimensional laser vibration developed by above mentioned technology. The technology based on the Doppler principle of interference and signal demodulation technology, get the vibration information of the object, through the algorithm processing, extract the three-dimensional vibration information of space objects, and can achieve the function of angle calibration of five beam in the space, which avoid the effects of the mechanical installation error, greatly improve the accuracy of measurement. With the help of a & B K4527 contact three axis sensor, measure and calibrate three-dimensional laser vibrometer, which ensure the accuracy of the measurement data. Summarize the advantages and disadvantages of contact and non-contact sensor, and analysis the future development trends of the sensor industry.

The WCA reference system for four- and five-dimensional Lennard-Jones fluids

NASA Astrophysics Data System (ADS)

Bishop, Marvin

1988-05-01

The WCA reference system is investigated for four- and five-dimensional Lennard-Jones fluids by molecular dynamics simulations. It is found that the WCA prescription for the scaling of the reference system to a hard hypersphere one is a very good approximation in the fluid region.

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond.

PubMed

Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco

2017-01-01

The existence of so-called 'basic emotions' and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment.

Multimodal neuroimaging of frontal white matter microstructure in early phase schizophrenia: the impact of early adolescent cannabis use

PubMed Central

2013-01-01

Background A disturbance in connectivity between different brain regions, rather than abnormalities within the separate regions themselves, could be responsible for the clinical symptoms and cognitive dysfunctions observed in schizophrenia. White matter, which comprises axons and their myelin sheaths, provides the physical foundation for functional connectivity in the brain. Myelin sheaths are located around the axons and provide insulation through the lipid membranes of oligodendrocytes. Empirical data suggests oligodendroglial dysfunction in schizophrenia, based on findings of abnormal myelin maintenance and repair in regions of deep white matter. The aim of this in vivo neuroimaging project is to assess the impact of early adolescent onset of regular cannabis use on brain white matter tissue integrity, and to differentiate this impact from the white matter abnormalities associated with schizophrenia. The ultimate goal is to determine the liability of early adolescent use of cannabis on brain white matter, in a vulnerable brain. Methods/Design Young adults with schizophrenia at the early stage of the illness (less than 5 years since diagnosis) will be the focus of this project. Four magnetic resonance imaging measurements will be used to assess different cellular aspects of white matter: a) diffusion tensor imaging, b) localized proton magnetic resonance spectroscopy with a focus on the neurochemical N-acetylaspartate, c) the transverse relaxation time constants of regional tissue water, d) and of N-acetylaspartate. These four neuroimaging indices will be assessed within the same brain region of interest, that is, a large white matter fibre bundle located in the frontal region, the left superior longitudinal fasciculus. Discussion We will expand our knowledge regarding current theoretical models of schizophrenia with a more comprehensive multimodal neuroimaging approach to studying the underlying cellular abnormalities of white matter, while taking into consideration the important confounding variable of early adolescent onset of regular cannabis use. PMID:24131511

Multimodal neuroimaging of frontal white matter microstructure in early phase schizophrenia: the impact of early adolescent cannabis use.

PubMed

Bernier, Denise; Cookey, Jacob; McAllindon, David; Bartha, Robert; Hanstock, Christopher C; Newman, Aaron J; Stewart, Sherry H; Tibbo, Philip G

2013-10-17

A disturbance in connectivity between different brain regions, rather than abnormalities within the separate regions themselves, could be responsible for the clinical symptoms and cognitive dysfunctions observed in schizophrenia. White matter, which comprises axons and their myelin sheaths, provides the physical foundation for functional connectivity in the brain. Myelin sheaths are located around the axons and provide insulation through the lipid membranes of oligodendrocytes. Empirical data suggests oligodendroglial dysfunction in schizophrenia, based on findings of abnormal myelin maintenance and repair in regions of deep white matter. The aim of this in vivo neuroimaging project is to assess the impact of early adolescent onset of regular cannabis use on brain white matter tissue integrity, and to differentiate this impact from the white matter abnormalities associated with schizophrenia. The ultimate goal is to determine the liability of early adolescent use of cannabis on brain white matter, in a vulnerable brain. Young adults with schizophrenia at the early stage of the illness (less than 5 years since diagnosis) will be the focus of this project. Four magnetic resonance imaging measurements will be used to assess different cellular aspects of white matter: a) diffusion tensor imaging, b) localized proton magnetic resonance spectroscopy with a focus on the neurochemical N-acetylaspartate, c) the transverse relaxation time constants of regional tissue water, d) and of N-acetylaspartate. These four neuroimaging indices will be assessed within the same brain region of interest, that is, a large white matter fibre bundle located in the frontal region, the left superior longitudinal fasciculus. We will expand our knowledge regarding current theoretical models of schizophrenia with a more comprehensive multimodal neuroimaging approach to studying the underlying cellular abnormalities of white matter, while taking into consideration the important confounding variable of early adolescent onset of regular cannabis use.

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

Five-dimensional imaging of freezing emulsions with solute effects.

PubMed

Dedovets, Dmytro; Monteux, Cécile; Deville, Sylvain

2018-04-20

The interaction of objects with a moving solidification front is a common feature of many industrial and natural processes such as metal processing, the growth of single crystals, the cryopreservation of cells, or the formation of sea ice. Interaction of solidification fronts with objects leads to different outcomes, from total rejection of the objects to their complete engulfment. We imaged the freezing of emulsions in five dimensions (space, time, and solute concentration) with confocal microscopy. We showed that the solute induces long-range interactions that determine the solidification microstructure. The local increase of solute concentration enhances premelting, which controls the engulfment of droplets by the front and the evolution of grain boundaries. Freezing emulsions may be a good analog of many solidification systems where objects interact with a solidification interface. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Neuroimaging Endophenotypes in Autism Spectrum Disorder

PubMed Central

Mahajan, Rajneesh; Mostofsky, Stewart H.

2015-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has a strong genetic basis, and is heterogeneous in its etiopathogenesis and clinical presentation. Neuroimaging studies, in concert with neuropathological and clinical research, have been instrumental in delineating trajectories of development in children with ASD. Structural neuroimaging has revealed ASD to be a disorder with general and regional brain enlargement, especially in the frontotemporal cortices, while functional neuroimaging studies have highlighted diminished connectivity, especially between frontal-posterior regions. The diverse and specific neuroimaging findings may represent potential neuroendophenotypes, and may offer opportunities to further understand the etiopathogenesis of ASD, predict treatment response and lead to the development of new therapies. PMID:26234701

CBRAIN: a web-based, distributed computing platform for collaborative neuroimaging research

PubMed Central

Sherif, Tarek; Rioux, Pierre; Rousseau, Marc-Etienne; Kassis, Nicolas; Beck, Natacha; Adalat, Reza; Das, Samir; Glatard, Tristan; Evans, Alan C.

2014-01-01

The Canadian Brain Imaging Research Platform (CBRAIN) is a web-based collaborative research platform developed in response to the challenges raised by data-heavy, compute-intensive neuroimaging research. CBRAIN offers transparent access to remote data sources, distributed computing sites, and an array of processing and visualization tools within a controlled, secure environment. Its web interface is accessible through any modern browser and uses graphical interface idioms to reduce the technical expertise required to perform large-scale computational analyses. CBRAIN's flexible meta-scheduling has allowed the incorporation of a wide range of heterogeneous computing sites, currently including nine national research High Performance Computing (HPC) centers in Canada, one in Korea, one in Germany, and several local research servers. CBRAIN leverages remote computing cycles and facilitates resource-interoperability in a transparent manner for the end-user. Compared with typical grid solutions available, our architecture was designed to be easily extendable and deployed on existing remote computing sites with no tool modification, administrative intervention, or special software/hardware configuration. As October 2013, CBRAIN serves over 200 users spread across 53 cities in 17 countries. The platform is built as a generic framework that can accept data and analysis tools from any discipline. However, its current focus is primarily on neuroimaging research and studies of neurological diseases such as Autism, Parkinson's and Alzheimer's diseases, Multiple Sclerosis as well as on normal brain structure and development. This technical report presents the CBRAIN Platform, its current deployment and usage and future direction. PMID:24904400

CBRAIN: a web-based, distributed computing platform for collaborative neuroimaging research.

PubMed

Sherif, Tarek; Rioux, Pierre; Rousseau, Marc-Etienne; Kassis, Nicolas; Beck, Natacha; Adalat, Reza; Das, Samir; Glatard, Tristan; Evans, Alan C

2014-01-01

The Canadian Brain Imaging Research Platform (CBRAIN) is a web-based collaborative research platform developed in response to the challenges raised by data-heavy, compute-intensive neuroimaging research. CBRAIN offers transparent access to remote data sources, distributed computing sites, and an array of processing and visualization tools within a controlled, secure environment. Its web interface is accessible through any modern browser and uses graphical interface idioms to reduce the technical expertise required to perform large-scale computational analyses. CBRAIN's flexible meta-scheduling has allowed the incorporation of a wide range of heterogeneous computing sites, currently including nine national research High Performance Computing (HPC) centers in Canada, one in Korea, one in Germany, and several local research servers. CBRAIN leverages remote computing cycles and facilitates resource-interoperability in a transparent manner for the end-user. Compared with typical grid solutions available, our architecture was designed to be easily extendable and deployed on existing remote computing sites with no tool modification, administrative intervention, or special software/hardware configuration. As October 2013, CBRAIN serves over 200 users spread across 53 cities in 17 countries. The platform is built as a generic framework that can accept data and analysis tools from any discipline. However, its current focus is primarily on neuroimaging research and studies of neurological diseases such as Autism, Parkinson's and Alzheimer's diseases, Multiple Sclerosis as well as on normal brain structure and development. This technical report presents the CBRAIN Platform, its current deployment and usage and future direction.

Neuroimaging classification of progression patterns in glioblastoma: a systematic review.

PubMed

Piper, Rory J; Senthil, Keerthi K; Yan, Jiun-Lin; Price, Stephen J

2018-03-30

Our primary objective was to report the current neuroimaging classification systems of spatial patterns of progression in glioblastoma. In addition, we aimed to report the terminology used to describe 'progression' and to assess the compliance with the Response Assessment in Neuro-Oncology (RANO) Criteria. We conducted a systematic review to identify all neuroimaging studies of glioblastoma that have employed a categorical classification system of spatial progression patterns. Our review was registered with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) registry. From the included 157 results, we identified 129 studies that used labels of spatial progression patterns that were not based on radiation volumes (Group 1) and 50 studies that used labels that were based on radiation volumes (Group 2). In Group 1, we found 113 individual labels and the most frequent were: local/localised (58%), distant/distal (51%), diffuse (20%), multifocal (15%) and subependymal/subventricular zone (15%). We identified 13 different labels used to refer to 'progression', of which the most frequent were 'recurrence' (99%) and 'progression' (92%). We identified that 37% (n = 33/90) of the studies published following the release of the RANO classification were adherent compliant with the RANO criteria. Our review reports significant heterogeneity in the published systems used to classify glioblastoma spatial progression patterns. Standardization of terminology and classification systems used in studying progression would increase the efficiency of our research in our attempts to more successfully treat glioblastoma.

Variations of the Functional Brain Network Efficiency in a Young Clinical Sample within the Autism Spectrum: A fNIRS Investigation.

PubMed

Li, Yanwei; Yu, Dongchuan

2018-01-01

Autism is a neurodevelopmental disorder with dimensional behavioral symptoms and various damages in the structural and functional brain. Previous neuroimaging studies focused on exploring the differences of brain development between individuals with and without autism spectrum disorders (ASD). However, few of them have attempted to investigate the individual differences of the brain features among subjects within the Autism spectrum. Our main goal was to explore the individual differences of neurodevelopment in young children with Autism by testing for the association between the functional network efficiency and levels of autistic behaviors, as well as the association between the functional network efficiency and age. Forty-six children with Autism (ages 2.0-8.9 years old) participated in the current study, with levels of autistic behaviors evaluated by their parents. The network efficiency (global and local network efficiency) were obtained from the functional networks based on the oxy-, deoxy-, and total-Hemoglobin series, respectively. Results indicated that the network efficiency decreased with age in young children with Autism in the deoxy- and total-Hemoglobin-based-networks, and children with a relatively higher level of autistic behaviors showed decreased network efficiency in the oxy-hemoglobin-based network. Results suggest individual differences of brain development in young children within the Autism spectrum, providing new insights into the psychopathology of ASD.

The neuroimaging of sacred values.

PubMed

Vilarroya, Oscar; Hilferty, Joseph

2013-09-01

Sacred (or protected) values (SVs) constitute core beliefs that define primary reference groups. There is significant research on SVs at a behavioral level, but their neural underpinnings are just beginning to be discovered. In this paper, we highlight the current state of neuroimaging research concerning SVs. Given that SVs are considered to be strongly motivated by moral principles, we first provide an outline of the neural circuits that have been found to be involved in moral cognition. We then review various neuroimaging studies that have explored the notion of SVs. Specifically, we concentrate on neuroimaging studies dealing with intergroup bias and those that focus on social norms, since these are two basic dimensions of SVs that have been studied with neuroimaging techniques. Finally, we review two studies that have directly addressed SVs with neuroimaging techniques, and we offer suggestions for further avenues of study. © 2013 New York Academy of Sciences.

Pituitary gland in psychiatric disorders: a review of neuroimaging findings.

PubMed

Atmaca, Murad

2014-08-01

In this paper, it was reviewed neuroimaging results of the pituitary gland in psychiatric disorders, particularly schizophrenia, mood disorders, anxiety disorders, and somatoform disorders. The author made internet search in detail by using PubMed database including the period between 1980 and 2012 October. It was included in the articles in English, Turkish and French languages on pituitary gland in psychiatric disorders through structural or functional neuroimaging results. After searching mentioned in the Methods section in detail, investigations were obtained on pituitary gland neuroimaging in a variety of psychiatric disorders. There have been so limited investigations on pituitary neuroimaging in psychiatric disorders including major psychiatric illnesses like schizophrenia and mood disorders. Current findings are so far from the generalizability of the results. For this reason, it is required to perform much more neuroimaging studies of pituitary gland in all psychiatric disorders to reach the diagnostic importance of measuring it.

Neuroimaging of Pain: Human Evidence and Clinical Relevance of Central Nervous System Processes and Modulation.

PubMed

Martucci, Katherine T; Mackey, Sean C

2018-06-01

Neuroimaging research has demonstrated definitive involvement of the central nervous system in the development, maintenance, and experience of chronic pain. Structural and functional neuroimaging has helped elucidate central nervous system contributors to chronic pain in humans. Neuroimaging of pain has provided a tool for increasing our understanding of how pharmacologic and psychologic therapies improve chronic pain. To date, findings from neuroimaging pain research have benefitted clinical practice by providing clinicians with an educational framework to discuss the biopsychosocial nature of pain with patients. Future advances in neuroimaging-based therapeutics (e.g., transcranial magnetic stimulation, real-time functional magnetic resonance imaging neurofeedback) may provide additional benefits for clinical practice. In the future, with standardization and validation, brain imaging could provide objective biomarkers of chronic pain, and guide treatment for personalized pain management. Similarly, brain-based biomarkers may provide an additional predictor of perioperative prognoses.

A Review on the Bioinformatics Tools for Neuroimaging

PubMed Central

MAN, Mei Yen; ONG, Mei Sin; Mohamad, Mohd Saberi; DERIS, Safaai; SULONG, Ghazali; YUNUS, Jasmy; CHE HARUN, Fauzan Khairi

2015-01-01

Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system. PMID:27006633

Neuroimaging findings in treatment-resistant schizophrenia: a systematic review

PubMed Central

Nakajima, Shinichiro; Takeuchi, Hiroyoshi; Plitman, Eric; Fervaha, Gagan; Gerretsen, Philip; Caravaggio, Fernando; Chung, Jun Ku; Iwata, Yusuke; Remington, Gary; Graff-Guerrero, Ariel

2015-01-01

Background Recent developments in neuroimaging have advanced understanding biological mechanisms underlying schizophrenia. However, neuroimaging correlates of treatment-resistant schizophrenia (TRS) and superior effects of clozapine on TRS remain unclear. Methods Systematic search was performed to identify neuroimaging characteristics unique to TRS and ultra-resistant schizophrenia (i.e. clozapine-resistant [URS]), and clozapine's efficacy in TRS using Embase, Medline, and PsychInfo. Search terms included (schizophreni*) and (resistan* OR refractory OR clozapine) and (ASL OR CT OR DTI OR FMRI OR MRI OR MRS OR NIRS OR PET OR SPECT). Results 25 neuroimaging studies have investigated TRS and effects of clozapine. Only 5 studies have compared TRS and non-TRS, collectively providing no replicated neuroimaging finding specific to TRS. Studies comparing TRS and healthy controls suggest hypometabolism in the prefrontal cortex, hypermetabolism in the basal ganglia, and structural anomalies in the corpus callosum contribute to TRS. Clozapine may increase prefrontal hypoactivation in TRS although this was not related to clinical improvement; in contrast, evidence has suggested a link between clozapine efficacy and decreased metabolism in the basal ganglia and thalamus. Conclusion Existing literature does not elucidate neuroimaging correlates specific to TRS or URS, which, if present, might also shed light on clozapine's efficacy in TRS. This said, leads from other lines of investigation, including the glutamatergic system can prove useful in guiding future neuroimaging studies focused on, in particular, the frontocortical-basal ganglia-thalamic circuits. Critical to the success of this work will be precise subtyping of study subjects based on treatment response/nonresponse and the use of multimodal neuroimaging. PMID:25684554

Killing Forms on the Five-Dimensional Einstein-Sasaki Y(p, q) Spaces

NASA Astrophysics Data System (ADS)

Visinescu, Mihai

2012-12-01

We present the complete set of Killing-Yano tensors on the five-dimensional Einstein-Sasaki Y(p, q) spaces. Two new Killing-Yano tensors are identified, associated with the complex volume form of the Calabi-Yau metric cone. The corresponding hidden symmetries are not anomalous and the geodesic equations are superintegrable.

Development and verification of global/local analysis techniques for laminated composites

NASA Technical Reports Server (NTRS)

Thompson, Danniella Muheim; Griffin, O. Hayden, Jr.

1991-01-01

A two-dimensional to three-dimensional global/local finite element approach was developed, verified, and applied to a laminated composite plate of finite width and length containing a central circular hole. The resulting stress fields for axial compression loads were examined for several symmetric stacking sequences and hole sizes. Verification was based on comparison of the displacements and the stress fields with those accepted trends from previous free edge investigations and a complete three-dimensional finite element solution of the plate. The laminates in the compression study included symmetric cross-ply, angle-ply and quasi-isotropic stacking sequences. The entire plate was selected as the global model and analyzed with two-dimensional finite elements. Displacements along a region identified as the global/local interface were applied in a kinematically consistent fashion to independent three-dimensional local models. Local areas of interest in the plate included a portion of the straight free edge near the hole, and the immediate area around the hole. Interlaminar stress results obtained from the global/local analyses compares well with previously reported trends, and some new conclusions about interlaminar stress fields in plates with different laminate orientations and hole sizes are presented for compressive loading. The effectiveness of the global/local procedure in reducing the computational effort required to solve these problems is clearly demonstrated through examination of the computer time required to formulate and solve the linear, static system of equations which result for the global and local analyses to those required for a complete three-dimensional formulation for a cross-ply laminate. Specific processors used during the analyses are described in general terms. The application of this global/local technique is not limited software system, and was developed and described in as general a manner as possible.

Converging evidence for an impact of a functional NOS gene variation on anxiety-related processes.

PubMed

Kuhn, Manuel; Haaker, Jan; Glotzbach-Schoon, Evelyn; Schümann, Dirk; Andreatta, Marta; Mechias, Marie-Luise; Raczka, Karolina; Gartmann, Nina; Büchel, Christian; Mühlberger, Andreas; Pauli, Paul; Reif, Andreas; Kalisch, Raffael; Lonsdorf, Tina B

2016-05-01

Being a complex phenotype with substantial heritability, anxiety and related phenotypes are characterized by a complex polygenic basis. Thereby, one candidate pathway is neuronal nitric oxide (NO) signaling, and accordingly, rodent studies have identified NO synthase (NOS-I), encoded by NOS1, as a strong molecular candidate for modulating anxiety and hippocampus-dependent learning processes. Using a multi-dimensional and -methodological replication approach, we investigated the impact of a functional promoter polymorphism (NOS1-ex1f-VNTR) on human anxiety-related phenotypes in a total of 1019 healthy controls in five different studies. Homozygous carriers of the NOS1-ex1f short-allele displayed enhanced trait anxiety, worrying and depression scores. Furthermore, short-allele carriers were characterized by increased anxious apprehension during contextual fear conditioning. While autonomous measures (fear-potentiated startle) provided only suggestive evidence for a modulatory role of NOS1-ex1f-VNTR on (contextual) fear conditioning processes, neural activation at the amygdala/anterior hippocampus junction was significantly increased in short-allele carriers during context conditioning. Notably, this could not be attributed to morphological differences. In accordance with data from a plethora of rodent studies, we here provide converging evidence from behavioral, subjective, psychophysiological and neuroimaging studies in large human cohorts that NOS-I plays an important role in anxious apprehension but provide only limited evidence for a role in (contextual) fear conditioning. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Categorizing Cortical Dysplasia Lesions for Surgical Outcome Using Network Functional Connectivity

NASA Astrophysics Data System (ADS)

Bdaiwi, Abdullah Sarray

Lesion-symptom mapping is a powerful and broadly applicable approach that is used for linking neurological symptoms to specific brain regions. Traditionally, it involves identifying overlap in lesion location across patients with similar symptoms. This approach has limitations when symptoms do not localize to a single region or when lesions do not tend to overlap. In this thesis, we show that we can expand the traditional approach of lesion mapping to incorporate network effects into symptom localization without the need for specialized neuroimaging of patients. Our approach involves assessing the functional connectivity of each lesion volume with the rest of the typical healthy brain using a database of healthy pediatric brain imaging data (C-MIND), available at CCHMC. Our study included 24 subjects that had cortical dysplasia lesions and underwent surgery for seizures that did not respond to drug therapy. We tested our approach using healthy brain imaging data across all ages (2-18 years old) and using age & gender specific groupings of data. The analysis sought categorization of lesion connectivity based on five subject characteristics: gender, cortical dysplasia pathology, epilepsy syndrome, scalp EEG pattern and surgical outcome. Our primary analysis focused on surgical outcome. The results showed that there are some substantial connectivity differences in the outcome analysis. Lesions with stronger connectivity to default mode and attention/motor networks tended to result in poorer surgical outcomes. This result could be expanded with a larger set of data with the ultimate goal of allowing examination of lesions of cortical dysplasia patients and predicting their seizure outcomes.

Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?

PubMed

Madhyastha, Tara M; Koh, Natalie; Day, Trevor K M; Hernández-Fernández, Moises; Kelley, Austin; Peterson, Daniel J; Rajan, Sabreena; Woelfer, Karl A; Wolf, Jonathan; Grabowski, Thomas J

2017-01-01

The contribution of this paper is to identify and describe current best practices for using Amazon Web Services (AWS) to execute neuroimaging workflows "in the cloud." Neuroimaging offers a vast set of techniques by which to interrogate the structure and function of the living brain. However, many of the scientists for whom neuroimaging is an extremely important tool have limited training in parallel computation. At the same time, the field is experiencing a surge in computational demands, driven by a combination of data-sharing efforts, improvements in scanner technology that allow acquisition of images with higher image resolution, and by the desire to use statistical techniques that stress processing requirements. Most neuroimaging workflows can be executed as independent parallel jobs and are therefore excellent candidates for running on AWS, but the overhead of learning to do so and determining whether it is worth the cost can be prohibitive. In this paper we describe how to identify neuroimaging workloads that are appropriate for running on AWS, how to benchmark execution time, and how to estimate cost of running on AWS. By benchmarking common neuroimaging applications, we show that cloud computing can be a viable alternative to on-premises hardware. We present guidelines that neuroimaging labs can use to provide a cluster-on-demand type of service that should be familiar to users, and scripts to estimate cost and create such a cluster.

Three-dimensional fluoroscopic navigation-assisted surgery for tumors in patients with tumor-induced osteomalacia in the bones.

PubMed

Kobayashi, Hiroshi; Akiyama, Toru; Okuma, Tomotake; Shinoda, Yusuke; Oka, Hiroyuki; Ito, Nobuaki; Fukumoto, Seiji; Tanaka, Sakae; Kawano, Hirotaka

2017-12-01

Tumor-induced osteomalacia (TIO) is a rare paraneoplastic syndrome usually caused by phosphaturic mesenchymal tumors. Segmental resection has been recommended for these tumors in the bones because curettage was found to be associated with a high local recurrence rate. Navigation-assisted surgery provides radiological information to guide the surgeon during surgery. No previous study has reported on the efficacy of navigation-assisted surgery for tumors in patients with TIO. Therefore, the present study aimed to evaluate the efficacy of navigation-assisted surgery for tumors in patients with TIO. The study included seven patients with TIO who were treated between January 2003 and December 2014 at our hospital. All patients underwent surgical treatment with or without the use of a 3-dimensional (3D) fluoroscopy-based navigation system. The laboratory data and oncological outcomes were evaluated. The follow-up period was 8-128 months. The tumors were located at the femur (n = 4), ischium, spine and ilium (n = 1). Of the seven patients, five underwent navigation-assisted surgery and two underwent surgery without navigation assistance. In the two patients who underwent surgery without navigation assistance, a complete cure was not obtained and osteomalacia did not resolve. One of these two patients and the other five patients who underwent navigation-assisted surgery, one patient had incomplete resection due to massive invasion of the tumor into the spinal canal, but five patients achieved complete excision and recovered from osteomalacia. Navigation-assisted surgery using a 3D fluoroscopy-based navigation system is effective for tumors in patients with TIO.

Straight velocity boundaries in the lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Latt, Jonas; Chopard, Bastien; Malaspinas, Orestis; Deville, Michel; Michler, Andreas

2008-05-01

Various ways of implementing boundary conditions for the numerical solution of the Navier-Stokes equations by a lattice Boltzmann method are discussed. Five commonly adopted approaches are reviewed, analyzed, and compared, including local and nonlocal methods. The discussion is restricted to velocity Dirichlet boundary conditions, and to straight on-lattice boundaries which are aligned with the horizontal and vertical lattice directions. The boundary conditions are first inspected analytically by applying systematically the results of a multiscale analysis to boundary nodes. This procedure makes it possible to compare boundary conditions on an equal footing, although they were originally derived from very different principles. It is concluded that all five boundary conditions exhibit second-order accuracy, consistent with the accuracy of the lattice Boltzmann method. The five methods are then compared numerically for accuracy and stability through benchmarks of two-dimensional and three-dimensional flows. None of the methods is found to be throughout superior to the others. Instead, the choice of a best boundary condition depends on the flow geometry, and on the desired trade-off between accuracy and stability. From the findings of the benchmarks, the boundary conditions can be classified into two major groups. The first group comprehends boundary conditions that preserve the information streaming from the bulk into boundary nodes and complete the missing information through closure relations. Boundary conditions in this group are found to be exceptionally accurate at low Reynolds number. Boundary conditions of the second group replace all variables on boundary nodes by new values. They exhibit generally much better numerical stability and are therefore dedicated for use in high Reynolds number flows.

[Neuropsychological evaluation of a case of organic personality disorder due to penetrating brain injury].

PubMed

Sanz de la Torre, J C; Pérez-Ríos, M

1996-06-01

In this paper, an organic personality disorder case by penetrating brain injury, predominantly localized in the right frontal lobe, is presented. Neuropsychological and neuroimaging (CT scan studies) were performed. We assessed the main cognitive aspect: orientation, attention, memory, intelligence, language, visual-spatial functioning, motor functioning, executive functioning and personality. The results obtained, point out disorders in the patient's behavior and in the executive functions. Likewise, other cognitive functions as: attention, memory, language and visual-spatial functioning, show specific deficits.

Red flag findings in children with headaches: Prevalence and association with emergency department neuroimaging.

PubMed

Tsze, Daniel S; Ochs, Julie B; Gonzalez, Ariana E; Dayan, Peter S

2018-01-01

Background Clinicians appear to obtain emergent neuroimaging for children with headaches based on the presence of red flag findings. However, little data exists regarding the prevalence of these findings in emergency department populations, and whether the identification of red flag findings is associated with potentially unnecessary emergency department neuroimaging. Objectives We aimed to determine the prevalence of red flag findings and their association with neuroimaging in otherwise healthy children presenting with headaches to the emergency department. Our secondary aim was to determine the prevalence of emergent intracranial abnormalities in this population. Methods A prospective cohort study of otherwise healthy children 2-17 years of age presenting to an urban pediatric emergency department with non-traumatic headaches was undertaken. Emergency department physicians completed a standardized form to document headache descriptors and characteristics, associated symptoms, and physical and neurological exam findings. Children who did not receive emergency department neuroimaging received 4-month telephone follow-up. Outcomes included emergency department neuroimaging and the presence of emergent intracranial abnormalities. Results We enrolled 224 patients; 197 (87.9%) had at least one red flag finding on history. Several red flag findings were reported by more than a third of children, including: Headache waking from sleep (34.8%); headache present with or soon after waking (39.7%); or headaches increasing in frequency, duration and severity (40%, 33.1%, and 46.3%). Thirty-three percent of children received emergency department neuroimaging. The prevalence of emergent intracranial abnormalities was 1% (95% CI 0.1, 3.6). Abnormal neurological exam, extreme pain intensity of presenting headache, vomiting, and positional symptoms were independently associated with emergency department neuroimaging. Conclusions Red flag findings are common in children presenting with headaches to the emergency department. The presence of red flag findings is associated with emergency department neuroimaging, although the risk of emergent intracranial abnormalities is low. Many children with headaches may be receiving unnecessary neuroimaging due to the high prevalence of non-specific red flag findings.

Ictal and interictal electric source imaging in presurgical evaluation: a prospective study.

PubMed

Sharma, Praveen; Scherg, Michael; Pinborg, Lars H; Fabricius, Martin; Rubboli, Guido; Pedersen, Birthe; Leffers, Anne-Mette; Uldall, Peter; Jespersen, Bo; Brennum, Jannick; Mølby Henriksen, Otto; Beniczky, Sándor

2018-05-11

Accurate localization of the epileptic focus is essential for surgical treatment of patients with drug- resistant epilepsy. EEG source imaging (ESI) is increasingly used in presurgical evaluation. However, most previous studies analysed interictal discharges. Prospective studies comparing feasibility and accuracy of interictal (II) and ictal (IC) ESI are lacking. We prospectively analysed long-term video EEG recordings (LTM) of patients admitted for presurgical evaluation. We performed ESI of II and IC signals, using two methods: equivalent current dipole (ECD) and distributed source model (DSM). LTM recordings employed the standard 25-electrode array (including inferior temporal electrodes). An age-matched template head-model was used for source analysis. Results were compared with intracranial recordings (ICR), conventional neuroimaging methods (MRI, PET, SPECT) and outcome one year after surgery. Eighty-seven consecutive patients were analysed. ECD gave a significantly higher proportion of patients with localised focal abnormalities (94%) compared to MRI (70%), PET (66%) and SPECT (64%). Agreement between the ESI methods and ICR was moderate to substantial (k=0.56-0.79). Fifty-four patients were operated (47 for more than one year ago) and 62% of them became seizure-free. Localization accuracy of II-ESI was 51% for DSM and 57% for ECD; for IC-ESI this was 51% (DSM) and 62% (ECD). The differences between the ESI methods were not significant. Differences in localization accuracy between ESI and MRI (55%), PET (33%) and SPECT (40%) were not significant. II and IC ESI of LTM-data have high feasibility and their localisation accuracy is similar to the conventional neuroimaging methods. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Cancer Trials Ireland (ICORG) 06-34: A multi-centre clinical trial using three-dimensional conformal radiation therapy to reduce the toxicity of palliative radiation for lung cancer.

PubMed

McDermott, Ronan L; Armstrong, John G; Thirion, Pierre; Dunne, Mary; Finn, Marie; Small, Cormac; Byrne, Mary; O'Shea, Carmel; O'Sullivan, Lydia; Shannon, Aoife; Kelly, Emma; Hacking, Dayle J

2018-05-01

Cancer Trials Ireland (ICORG) 06-34: A multi-centre clinical trial using three-dimensional conformal radiation therapy to reduce the toxicity of palliative radiation for lung cancer. NCT01176487. Trials of radiation therapy for the palliation of intra-thoracic symptoms from locally advanced non-small cell lung cancer (NSCLC) have concentrated on optimising fractionation and dose schedules. In these trials, the rates of oesophagitis induced by this "palliative" therapy have been unacceptably high. In contrast, this non-randomised, single-arm trial was designed to assess if more technically advanced treatment techniques would result in equivalent symptom relief and reduce the side-effect of symptomatic oesophagitis. Thirty-five evaluable patients with symptomatic locally advanced or metastatic NSCLC were treated using a three-dimensional conformal technique (3-DCRT) and standardised dose regimens of 39 Gy in 13 fractions, 20 Gy in 5 fractions or 17 Gy in 2 fractions. Treatment plans sought to minimise oesophageal dose. Oesophagitis was recorded during treatment, at two weeks, one month and three months following radiation therapy and 3-6 monthly thereafter. Mean dose to the irradiated oesophagus was calculated for all treatment plans. Five patients (14%) had experienced grade 2 oesophagitis or dysphagia or both during treatment and 2 other patients had these side effects at the 2-week follow-up. At follow-up of one month after therapy, there was no grade two or higher oesophagitis or dysphagia reported. 22 patients were eligible for assessment of late toxicity. Five of these patients reported oesophagitis or dysphagia (one had grade 3 dysphagia, two had grade 2 oesophagitis, one of whom also had grade 2 dysphagia). Quality of Life (QoL) data at baseline and at 1-month follow up were available for 20 patients. At 1-month post radiation therapy, these patients had slightly less trouble taking a short walk, less shortness of breath, did not feel as weak, had better appetite and generally had a better overall quality of life than they did at baseline. They did report being slightly more tired. This trial is the first of its kind showing that 3-DCRT provides patients with lower rates of oesophageal toxicity whilst yielding acceptable rates of symptom control. (Sponsored by Cancer Trials Ireland (ICORG) Study number 06-34, the Friends of St. Luke's and the St. Luke's Institute of Cancer Research.). Copyright © 2018 Elsevier B.V. All rights reserved.

Cognitive neuroimaging: cognitive science out of the armchair.

PubMed

de Zubicaray, Greig I

2006-04-01

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.

Neuropsychological and neuroimaging underpinnings of schizoaffective disorder: a systematic review.

PubMed

Madre, M; Canales-Rodríguez, E J; Ortiz-Gil, J; Murru, A; Torrent, C; Bramon, E; Perez, V; Orth, M; Brambilla, P; Vieta, E; Amann, B L

2016-07-01

The neurobiological basis and nosological status of schizoaffective disorder remains elusive and controversial. This study provides a systematic review of neurocognitive and neuroimaging findings in the disorder. A comprehensive literature search was conducted via PubMed, ScienceDirect, Scopus and Web of Knowledge (from 1949 to 31st March 2015) using the keyword 'schizoaffective disorder' and any of the following terms: 'neuropsychology', 'cognition', 'structural neuroimaging', 'functional neuroimaging', 'multimodal', 'DTI' and 'VBM'. Only studies that explicitly examined a well defined sample, or subsample, of patients with schizoaffective disorder were included. Twenty-two of 43 neuropsychological and 19 of 51 neuroimaging articles fulfilled inclusion criteria. We found a general trend towards schizophrenia and schizoaffective disorder being related to worse cognitive performance than bipolar disorder. Grey matter volume loss in schizoaffective disorder is also more comparable to schizophrenia than to bipolar disorder which seems consistent across further neuroimaging techniques. Neurocognitive and neuroimaging abnormalities in schizoaffective disorder resemble more schizophrenia than bipolar disorder. This is suggestive for schizoaffective disorder being a subtype of schizophrenia or being part of the continuum spectrum model of psychosis, with schizoaffective disorder being more skewed towards schizophrenia than bipolar disorder. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Responsible Reporting: Neuroimaging News in the Age of Responsible Research and Innovation.

PubMed

de Jong, Irja Marije; Kupper, Frank; Arentshorst, Marlous; Broerse, Jacqueline

2016-08-01

Besides offering opportunities in both clinical and non-clinical domains, the application of novel neuroimaging technologies raises pressing dilemmas. 'Responsible Research and Innovation' (RRI) aims to stimulate research and innovation activities that take ethical and social considerations into account from the outset. We previously identified that Dutch neuroscientists interpret "responsible innovation" as educating the public on neuroimaging technologies via the popular press. Their aim is to mitigate (neuro)hype, an aim shared with the wider emerging RRI community. Here, we present results of a media-analysis undertaken to establish whether the body of articles in the Dutch popular press presents balanced conversations on neuroimaging research to the public. We found that reporting was mostly positive and framed in terms of (healthcare) progress. There was rarely a balance between technology opportunities and limitations, and even fewer articles addressed societal or ethical aspects of neuroimaging research. Furthermore, neuroimaging metaphors seem to favour oversimplification. Current reporting is therefore more likely to enable hype than to mitigate it. How can neuroscientists, given their self-ascribed social responsibility, address this conundrum? We make a case for a collective and shared responsibility among neuroscientists, journalists and other stakeholders, including funders, committed to responsible reporting on neuroimaging research.

Multichannel wearable system dedicated for simultaneous electroencephalography/near-infrared spectroscopy real-time data acquisitions

NASA Astrophysics Data System (ADS)

Lareau, Etienne; Lesage, Frederic; Pouliot, Philippe; Nguyen, Dang; Le Lan, Jerome; Sawan, Mohamad

2011-09-01

Functional neuroimaging is becoming a valuable tool in cognitive research and clinical applications. The clinical context brings specific constraints that include the requirement of a high channel count to cover the whole head, high sensitivity for single event detection, and portability for long-term bedside monitoring. For epilepsy and stroke monitoring, the combination of electroencephalography (EEG) and functional near-infrared spectroscopy (NIRS) is expected to provide useful clinical information, and efforts have been deployed to create prototypes able to simultaneously acquire both measurement modalities. However, to the best of our knowledge, existing systems lack portability, NIRS sensitivity, or have low channel count. We present a battery-powered, portable system with potentially up to 32 EEG channels, 32 NIRS light sources, and 32 detectors. Avalanche photodiodes allow for high NIRS sensitivity and the autonomy of the system is over 24 h. A reduced channel count prototype with 8 EEG channels, 8 sources, and 8 detectors was tested on phantoms. Further validation was done on five healthy adults using a visual stimulation protocol to detect local hemodynamic changes and visually evoked potentials. Results show good concordance with literature regarding functional activations and suggest sufficient performance for clinical use, provided some minor adjustments were made.

A self-organizing Lagrangian particle method for adaptive-resolution advection-diffusion simulations

NASA Astrophysics Data System (ADS)

Reboux, Sylvain; Schrader, Birte; Sbalzarini, Ivo F.

2012-05-01

We present a novel adaptive-resolution particle method for continuous parabolic problems. In this method, particles self-organize in order to adapt to local resolution requirements. This is achieved by pseudo forces that are designed so as to guarantee that the solution is always well sampled and that no holes or clusters develop in the particle distribution. The particle sizes are locally adapted to the length scale of the solution. Differential operators are consistently evaluated on the evolving set of irregularly distributed particles of varying sizes using discretization-corrected operators. The method does not rely on any global transforms or mapping functions. After presenting the method and its error analysis, we demonstrate its capabilities and limitations on a set of two- and three-dimensional benchmark problems. These include advection-diffusion, the Burgers equation, the Buckley-Leverett five-spot problem, and curvature-driven level-set surface refinement.

Epi-Two-Dimensional Fluid Flow: A New Topological Paradigm for Dimensionality

NASA Astrophysics Data System (ADS)

Yoshida, Z.; Morrison, P. J.

2017-12-01

While a variety of fundamental differences are known to separate two-dimensional (2D) and three-dimensional (3D) fluid flows, it is not well understood how they are related. Conventionally, dimensional reduction is justified by an a priori geometrical framework; i.e., 2D flows occur under some geometrical constraint such as shallowness. However, deeper inquiry into 3D flow often finds the presence of local 2D-like structures without such a constraint, where 2D-like behavior may be identified by the integrability of vortex lines or vanishing local helicity. Here we propose a new paradigm of flow structure by introducing an intermediate class, termed epi-two-dimensional flow, and thereby build a topological bridge between 2D and 3D flows. The epi-2D property is local and is preserved in fluid elements obeying ideal (inviscid and barotropic) mechanics; a local epi-2D flow may be regarded as a "particle" carrying a generalized enstrophy as its charge. A finite viscosity may cause "fusion" of two epi-2D particles, generating helicity from their charges giving rise to 3D flow.

Combined Loadings and Cross-Dimensional Loadings Timeliness of Presentation of Financial Statements of Local Government

NASA Astrophysics Data System (ADS)

Muda, I.; Dharsuky, A.; Siregar, H. S.; Sadalia, I.

2017-03-01

This study examines the pattern of readiness dimensional accuracy of financial statements of local government in North Sumatra with a routine pattern of two (2) months after the fiscal year ends and patterns of at least 3 (three) months after the fiscal year ends. This type of research is explanatory survey with quantitative methods. The population and the sample used is of local government officials serving local government financial reports. Combined Analysis And Cross-Loadings Loadings are used with statistical tools WarpPLS. The results showed that there was a pattern that varies above dimensional accuracy of the financial statements of local government in North Sumatra.

Spinors fields in co-dimension one braneworlds

NASA Astrophysics Data System (ADS)

Mendes, W. M.; Alencar, G.; Landim, R. R.

2018-02-01

In this work we analyze the zero mode localization and resonances of 1/2-spin fermions in co-dimension one Randall-Sundrum braneworld scenarios. We consider delta-like, domain walls and deformed domain walls membranes. Beyond the influence of the spacetime dimension D we also consider three types of couplings: (i) the standard Yukawa coupling with the scalar field and parameter η 1, (ii) a Yukawa-dilaton coupling with two parameters η 2 and λ and (iii) a dilaton derivative coupling with parameter h. Together with the deformation parameter s, we end up with five free parameter to be considered. For the zero mode we find that the localization is dependent of D, because the spinorial representation changes when the bulk dimensionality is odd or even and must be treated separately. For case (i) we find that in odd dimensions only one chirality can be localized and for even dimension a massless Dirac spinor is trapped over the brane. In the cases (ii) and (iii) we find that for some values of the parameters, both chiralities can be localized in odd dimensions and for even dimensions we obtain that the massless Dirac spinor is trapped over the brane. We also calculated numerically resonances for cases (ii) and (iii) by using the transfer matrix method. We find that, for deformed defects, the increasing of D induces a shift in the peaks of resonances. For a given λ with domain walls, we find that the resonances can show up by changing the spacetime dimensionality. For example, the same case in D = 5 do not induces resonances but when we consider D = 10 one peak of resonance is found. Therefore the introduction of more dimensions, diversely from the bosonic case, can change drastically the zero mode and resonances in fermion fields.

Microstructure from ferroelastic transitions using strain pseudospin clock models in two and three dimensions: A local mean-field analysis

NASA Astrophysics Data System (ADS)

Vasseur, Romain; Lookman, Turab; Shenoy, Subodh R.

2010-09-01

We show how microstructure can arise in first-order ferroelastic structural transitions, in two and three spatial dimensions, through a local mean-field approximation of their pseudospin Hamiltonians, that include anisotropic elastic interactions. Such transitions have symmetry-selected physical strains as their NOP -component order parameters, with Landau free energies that have a single zero-strain “austenite” minimum at high temperatures, and spontaneous-strain “martensite” minima of NV structural variants at low temperatures. The total free energy also has gradient terms, and power-law anisotropic effective interactions, induced by “no-dislocation” St Venant compatibility constraints. In a reduced description, the strains at Landau minima induce temperature dependent, clocklike ZNV+1 Hamiltonians, with NOP -component strain-pseudospin vectors S⃗ pointing to NV+1 discrete values (including zero). We study elastic texturing in five such first-order structural transitions through a local mean-field approximation of their pseudospin Hamiltonians, that include the power-law interactions. As a prototype, we consider the two-variant square/rectangle transition, with a one-component pseudospin taking NV+1=3 values of S=0,±1 , as in a generalized Blume-Capel model. We then consider transitions with two-component (NOP=2) pseudospins: the equilateral to centered rectangle (NV=3) ; the square to oblique polygon (NV=4) ; the triangle to oblique (NV=6) transitions; and finally the three-dimensional (3D) cubic to tetragonal transition (NV=3) . The local mean-field solutions in two-dimensional and 3D yield oriented domain-wall patterns as from continuous-variable strain dynamics, showing the discrete-variable models capture the essential ferroelastic texturings. Other related Hamiltonians illustrate that structural transitions in materials science can be the source of interesting spin models in statistical mechanics.

Comparison of Toxicity Between Intensity-Modulated Radiotherapy and 3-Dimensional Conformal Radiotherapy for Locally Advanced Non-small-cell Lung Cancer.

PubMed

Ling, Diane C; Hess, Clayton B; Chen, Allen M; Daly, Megan E

2016-01-01

The role of intensity-modulated radiotherapy (IMRT) in reducing treatment-related toxicity for locally advanced non-small-cell lung cancer (NSCLC) remains incompletely defined. We compared acute toxicity and oncologic outcomes in a large cohort of patients treated with IMRT or 3-dimensional conformal radiotherapy (3-DCRT), with or without elective nodal irradiation (ENI). A single-institution retrospective review was performed evaluating 145 consecutive patients with histologically confirmed stage III NSCLC treated with definitive chemoradiotherapy. Sixty-five (44.8%) were treated with 3-DCRT using ENI, 43 (30.0%) with 3-DCRT using involved-field radiotherapy (IFRT), and 37 (25.5%) with IMRT using IFRT. All patients received concurrent chemotherapy. Comparison of acute toxicities by treatment technique (IMRT vs. 3-DCRT) and extent of nodal irradiation (3-DCRT-IFRT vs. 3-DCRT-ENI) was performed for grade 2 or higher esophagitis or pneumonitis, number of acute hospitalizations, incidence of opioid requirement, percutaneous endoscopic gastrostomy utilization, and percentage weight loss during treatment. Local control and overall survival were analyzed by the Kaplan-Meier method. We identified no significant differences in any measures of acute toxicity by treatment technique or extent of nodal irradiation. There was a trend toward lower rates of grade 2 or higher pneumonitis among IMRT patients compared to 3-DCRT patients (5.4% vs. 23.0%; P = .065). Local control and overall survival were similar between cohorts. Acute and subacute toxicities were similar for patients treated with IMRT and with 3-DCRT with or without ENI, with a nonsignificant trend toward a reduction in pneumonitis with IMRT. Larger studies are needed to better define which patients will benefit from IMRT. Copyright © 2016 Elsevier Inc. All rights reserved.

Cross-ply laminates with holes in compression - Straight free-edge stresses determined by two- to three-dimensional global/local finite element analysis

NASA Technical Reports Server (NTRS)

Thompson, Danniella Muheim; Griffin, O. Hayden, Jr.; Vidussoni, Marco A.

1990-01-01

A practical example of applying two- to three-dimensional (2- to 3-D) global/local finite element analysis to laminated composites is presented. Cross-ply graphite/epoxy laminates of 0.1-in. (0.254-cm) thickness with central circular holes ranging from 1 to 6 in. (2.54 to 15.2 cm) in diameter, subjected to in-plane compression were analyzed. Guidelines for full three-dimensional finite element analysis and two- to three-dimensional global/local analysis of interlaminar stresses at straight free edges of laminated composites are included. The larger holes were found to reduce substantially the interlaminar stresses at the straight free-edge in proximity to the hole. Three-dimensional stress results were obtained for thin laminates which require prohibitive computer resources for full three-dimensional analyses of comparative accuracy.

Cosmology and the large-mass problem of the five-dimensional Kaluza-Klein theory

NASA Astrophysics Data System (ADS)

Lukács, B.; Pacher, T.

1985-12-01

It is shown that in five-dimensional Kaluza-Klein theories the large-mass problem leads to circulus vitiosus: the huge recent e2/G value produces the large mass problem, which restricts the ratio e2/Gm2 to the order of unity, in contradiction with the present 1040 value for elementary particles.

Charged black lens in de Sitter space

NASA Astrophysics Data System (ADS)

Tomizawa, Shinya

2018-02-01

We obtain a charged black lens solution in the five-dimensional Einstein-Maxwell-Chern-Simons theory with a positive cosmological constant. It is shown that the solution obtained here describes the formation of a black hole with the spatial cross section of a sphere from that of the lens space of L (n ,1 ) in five-dimensional de Sitter space.

Revisiting the ADT mass of the five-dimensional rotating black holes with squashed horizons

NASA Astrophysics Data System (ADS)

Peng, Jun-Jin

2017-10-01

We evaluate the Abbott-Deser-Tekin (ADT) mass of the five-dimensional rotating black holes with squashed horizons on two different on-shell reference backgrounds, which are the flat background and the boundary matched Kaluza-Klein (KK) monopole. The mass on the former, identified with the one on the background of the asymptotic geometry, differs from the mass on the latter by that of the KK monopole. However, each mass satisfies the first law of black hole thermodynamics. To test the results in five dimensions, we compute the mass in the context of the dimensionally reduced theory. Finally, in contrast with the original ADT formulation, its off-shell generalisation is applied to calculate the mass as well.

Childhood-Onset Schizophrenia: Insights from Neuroimaging Studies

ERIC Educational Resources Information Center

Gogtay, Nitin; Rapoport, Judith L.

2008-01-01

The use of longitudinal neuroimaging to study the developmental perspectives of brain pathology in children with childhood-onset schizophrenia (COS) is described. Structural neuroimaging is capable of providing evidence of neurobiological specificity of COS to distinguish it from other brain abnormalities seen in neuropsychiatric illnesses like…

Neuroimaging in mental health care: voices in translation

PubMed Central

Borgelt, Emily L.; Buchman, Daniel Z.; Illes, Judy

2012-01-01

Images of brain function, popularly called “neuroimages,” have become a mainstay of contemporary communication about neuroscience and mental health. Paralleling media coverage of neuroimaging research and the high visibility of clinics selling scans is pressure from sponsors to move basic research about brain function along the translational pathway. Indeed, neuroimaging may offer benefits to mental health care: early or tailored intervention, opportunities for education and planning, and access to resources afforded by objectification of disorder. However, risks of premature technology transfer, such as misinterpretation, misrepresentation, and increased stigmatization, could compromise patient care. The insights of stakeholder groups about neuroimaging for mental health care are a largely untapped resource of information and guidance for translational efforts. We argue that the insights of key stakeholders—including researchers, healthcare providers, patients, and families—have an essential role to play upstream in professional, critical, and ethical discourse surrounding neuroimaging in mental health. Here we integrate previously orthogonal lines of inquiry involving stakeholder research to describe the translational landscape as well as challenges on its horizon. PMID:23097640

Integration of a neuroimaging processing pipeline into a pan-canadian computing grid

NASA Astrophysics Data System (ADS)

Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.

2012-02-01

The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.

Seeing responsibility: can neuroimaging teach us anything about moral and legal responsibility?

PubMed

Wasserman, David; Johnston, Josephine

2014-01-01

As imaging technologies help us understand the structure and function of the brain, providing insight into human capabilities as basic as vision and as complex as memory, and human conditions as impairing as depression and as fraught as psychopathy, some have asked whether they can also help us understand human agency. Specifically, could neuroimaging lead us to reassess the socially significant practice of assigning and taking responsibility? While responsibility itself is not a psychological process open to investigation through neuroimaging, decision-making is. Over the past decade, different researchers and scholars have sought to use neuroimaging (or the results of neuroimaging studies) to investigate what is going on in the brain when we make decisions. The results of this research raise the question whether neuroscience-especially now that it includes neuroimaging-can and should alter our understandings of responsibility and our related practice of holding people responsible. It is this question that we investigate here. © 2014 by The Hastings Center.

Nonlinearity-aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI measures.

PubMed

Cao, Peng; Liu, Xiaoli; Yang, Jinzhu; Zhao, Dazhe; Huang, Min; Zhang, Jian; Zaiane, Osmar

2017-12-01

Alzheimer's disease (AD) has been not only a substantial financial burden to the health care system but also an emotional burden to patients and their families. Making accurate diagnosis of AD based on brain magnetic resonance imaging (MRI) is becoming more and more critical and emphasized at the earliest stages. However, the high dimensionality and imbalanced data issues are two major challenges in the study of computer aided AD diagnosis. The greatest limitations of existing dimensionality reduction and over-sampling methods are that they assume a linear relationship between the MRI features (predictor) and the disease status (response). To better capture the complicated but more flexible relationship, we propose a multi-kernel based dimensionality reduction and over-sampling approaches. We combined Marginal Fisher Analysis with ℓ 2,1 -norm based multi-kernel learning (MKMFA) to achieve the sparsity of region-of-interest (ROI), which leads to simultaneously selecting a subset of the relevant brain regions and learning a dimensionality transformation. Meanwhile, a multi-kernel over-sampling (MKOS) was developed to generate synthetic instances in the optimal kernel space induced by MKMFA, so as to compensate for the class imbalanced distribution. We comprehensively evaluate the proposed models for the diagnostic classification (binary class and multi-class classification) including all subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. The experimental results not only demonstrate the proposed method has superior performance over multiple comparable methods, but also identifies relevant imaging biomarkers that are consistent with prior medical knowledge. Copyright © 2017 Elsevier Ltd. All rights reserved.

Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?

PubMed Central

Madhyastha, Tara M.; Koh, Natalie; Day, Trevor K. M.; Hernández-Fernández, Moises; Kelley, Austin; Peterson, Daniel J.; Rajan, Sabreena; Woelfer, Karl A.; Wolf, Jonathan; Grabowski, Thomas J.

2017-01-01

The contribution of this paper is to identify and describe current best practices for using Amazon Web Services (AWS) to execute neuroimaging workflows “in the cloud.” Neuroimaging offers a vast set of techniques by which to interrogate the structure and function of the living brain. However, many of the scientists for whom neuroimaging is an extremely important tool have limited training in parallel computation. At the same time, the field is experiencing a surge in computational demands, driven by a combination of data-sharing efforts, improvements in scanner technology that allow acquisition of images with higher image resolution, and by the desire to use statistical techniques that stress processing requirements. Most neuroimaging workflows can be executed as independent parallel jobs and are therefore excellent candidates for running on AWS, but the overhead of learning to do so and determining whether it is worth the cost can be prohibitive. In this paper we describe how to identify neuroimaging workloads that are appropriate for running on AWS, how to benchmark execution time, and how to estimate cost of running on AWS. By benchmarking common neuroimaging applications, we show that cloud computing can be a viable alternative to on-premises hardware. We present guidelines that neuroimaging labs can use to provide a cluster-on-demand type of service that should be familiar to users, and scripts to estimate cost and create such a cluster. PMID:29163119

Neuroimaging and Drug Taking in Primates Abbreviated title: Neuroimaging and Drug taking

PubMed Central

Murnane, Kevin S.; Howell, Leonard L.

2011-01-01

Rationale Neuroimaging techniques have led to significant advances in our understanding of the neurobiology of drug-taking and the treatment of drug addiction in humans. Neuroimaging approaches provide a powerful translational approach that can link findings from humans and laboratory animals. Objective This review describes the utility of neuroimaging toward understanding the neurobiological basis of drug taking, and documents the close concordance that can be achieved among neuroimaging, neurochemical and behavioral endpoints. Results The study of drug interactions with dopamine and serotonin transporters in vivo has identified pharmacological mechanisms of action associated with the abuse liability of stimulants. Neuroimaging has identified the extended limbic system, including the prefrontal cortex and anterior cingulate, as important neuronal circuitry that underlies drug taking. The ability to conduct within-subject, longitudinal assessments of brain chemistry and neuronal function has enhanced our efforts to document long-term changes in dopamine D2 receptors, monoamine transporters, and prefrontal metabolism due to chronic drug exposure. Dysregulation of dopamine function and brain metabolic changes in areas involved in reward circuitry have been linked to drug-taking behavior, cognitive impairment and treatment response. Conclusions Experimental designs employing neuroimaging should consider well-documented determinants of drug taking, including pharmacokinetic considerations, subject history and environmental variables. Methodological issues to consider include limited molecular probes, lack of neurochemical specificity in brain activation studies, and the potential influence of anesthetics in animal studies. Nevertheless, these integrative approaches should have important implications for understanding drug-taking behavior and the treatment of drug addiction. PMID:21360099

Neural modeling and functional neuroimaging.

PubMed

Horwitz, B; Sporns, O

1994-01-01

Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America. Copyright © 1994 Wiley-Liss, Inc.

Three-dimensional silicon inverse photonic quasicrystals for infrared wavelengths.

PubMed

Ledermann, Alexandra; Cademartiri, Ludovico; Hermatschweiler, Martin; Toninelli, Costanza; Ozin, Geoffrey A; Wiersma, Diederik S; Wegener, Martin; von Freymann, Georg

2006-12-01

Quasicrystals are a class of lattices characterized by a lack of translational symmetry. Nevertheless, the points of the lattice are deterministically arranged, obeying rotational symmetry. Thus, we expect properties that are different from both crystals and glasses. Indeed, naturally occurring electronic quasicrystals (for example, AlPdMn metal alloys) show peculiar electronic, vibrational and physico-chemical properties. Regarding artificial quasicrystals for electromagnetic waves, three-dimensional (3D) structures have recently been realized at GHz frequencies and 2D structures have been reported for the near-infrared region. Here, we report on the first fabrication and characterization of 3D quasicrystals for infrared frequencies. Using direct laser writing combined with a silicon inversion procedure, we achieve high-quality silicon inverse icosahedral structures. Both polymeric and silicon quasicrystals are characterized by means of electron microscopy and visible-light Laue diffraction. The diffraction patterns of structures with a local five-fold real-space symmetry axis reveal a ten-fold symmetry as required by theory for 3D structures.

Experimental studies of flow separation and stalling on two-dimensional airfoils at low speeds. Phase 2: Studies with Fowler flap extended

NASA Technical Reports Server (NTRS)

Seetharam, H. C.; Wentz, W. H., Jr.

1975-01-01

Results were given on experimental studies of flow separation and stalling on a two-dimensional GA(W)-1 17 percent thick airfoil with an extended Fowler flap. Experimental velocity profiles obtained from a five tube probe survey with optimum flap gap and overlap setting (flap at 40 deg) are shown at various stations above, below, and behind the airfoil/flap combination for various angles of attack. The typical zones of steady flow, intermittent turbulence, and large scale turbulence were obtained from a hot wire anemometer survey and are depicted graphically for an angle of attack of 12.5 deg. Local skin friction distributions were obtained and are given for various angles of attack. Computer plots of the boundary layer profiles are shown for the case of the flap at 40 deg. Static pressure contours are also given. A GA(W)-2 section model was fabricated with 30 percent Fowler flaps and with pressure tabs.

Streamlined, Inexpensive 3D Printing of the Brain and Skull

PubMed Central

Cash, Sydney S.

2015-01-01

Neuroimaging technologies such as Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) collect three-dimensional data (3D) that is typically viewed on two-dimensional (2D) screens. Actual 3D models, however, allow interaction with real objects such as implantable electrode grids, potentially improving patient specific neurosurgical planning and personalized clinical education. Desktop 3D printers can now produce relatively inexpensive, good quality prints. We describe our process for reliably generating life-sized 3D brain prints from MRIs and 3D skull prints from CTs. We have integrated a standardized, primarily open-source process for 3D printing brains and skulls. We describe how to convert clinical neuroimaging Digital Imaging and Communications in Medicine (DICOM) images to stereolithography (STL) files, a common 3D object file format that can be sent to 3D printing services. We additionally share how to convert these STL files to machine instruction gcode files, for reliable in-house printing on desktop, open-source 3D printers. We have successfully printed over 19 patient brain hemispheres from 7 patients on two different open-source desktop 3D printers. Each brain hemisphere costs approximately $3–4 in consumable plastic filament as described, and the total process takes 14–17 hours, almost all of which is unsupervised (preprocessing = 4–6 hr; printing = 9–11 hr, post-processing = <30 min). Printing a matching portion of a skull costs $1–5 in consumable plastic filament and takes less than 14 hr, in total. We have developed a streamlined, cost-effective process for 3D printing brain and skull models. We surveyed healthcare providers and patients who confirmed that rapid-prototype patient specific 3D models may help interdisciplinary surgical planning and patient education. The methods we describe can be applied for other clinical, research, and educational purposes. PMID:26295459

Neuroimaging correlates of parent ratings of working memory in typically developing children

PubMed Central

Mahone, E. Mark; Martin, Rebecca; Kates, Wendy R.; Hay, Trisha; Horská, Alena

2009-01-01

The purpose of the present study was to investigate construct validity of parent ratings of working memory in children, using a multi-trait/multi-method design including neuroimaging, rating scales, and performance-based measures. Thirty-five typically developing children completed performance-based tests of working memory and nonexecutive function (EF) skills, received volumetric MRI, and were rated by parents on both EF-specific and broad behavior rating scales. After controlling for total cerebral volume and age, parent ratings of working memory were significantly correlated with frontal gray, but not temporal, parietal, or occipital gray, or any lobar white matter volumes. Performance-based measures of working memory were also moderately correlated with frontal lobe gray matter volume; however, non-EF parent ratings and non-EF performance-based measures were not correlated with frontal lobe volumes. Results provide preliminary support for the convergent and discriminant validity of parent ratings of working memory, and emphasize their utility in exploring brain–behavior relationships in children. Rating scales that directly examine EF skills may potentially have ecological validity, not only for “everyday” function, but also as correlates of brain volume. PMID:19128526

An Observational Study to Assess Brain MRI Change and Disease Progression in Multiple Sclerosis Clinical Practice-The MS-MRIUS Study.

PubMed

Zivadinov, Robert; Khan, Nasreen; Medin, Jennie; Christoffersen, Pia; Price, Jennifer; Korn, Jonathan R; Bonzani, Ian; Dwyer, Michael G; Bergsland, Niels; Carl, Ellen; Silva, Diego; Weinstock-Guttman, Bianca

2017-05-01

To describe methodology, interim baseline, and longitudinal magnetic resonance imaging (MRI) acquisition parameter characteristics of the multiple sclerosis clinical outcome and MRI in the United States (MS-MRIUS). The MS-MRIUS is an ongoing longitudinal and retrospective study of MS patients on fingolimod. Clinical and brain MRI image scan data were collected from 600 patients across 33 MS centers in the United States. MRI brain outcomes included change in whole-brain volume, lateral ventricle volume, T2- and T1-lesion volumes, and new/enlarging T2 and gadolinium-enhancing lesions. Interim baseline and longitudinal MRI acquisition parameters results are presented for 252 patients. Mean age was 44 years and 81% were female. Forty percent of scans had 3-dimensional (3D) T1 sequence in the preindex period, increasing to 50% in the postindex period. Use of 2-dimensional (2D) T1 sequence decreased over time from 85% in the preindex period to 65% in the postindex. About 95% of the scans with FLAIR and 2D T1-WI were considered acceptable or good quality compared to 99-100% with 3D T1-WI. There were notable changes in MRI hardware, software, and coil (39.5% in preindex to index and 50% in index to postindex). MRI sequence parameters (orientation, thickness, or protocol) differed for 36%, 29%, and 20% of index/postindex scans for FLAIR, 2D T1-WI, and 3D T1-WI, respectively. The MS-MRIUS study linked the clinical and brain MRI outcomes into an integrated database to create a cohort of fingolimod patients in real-world practice. Variability was observed in MRI acquisition protocols overtime. © 2016 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.

Pydpiper: a flexible toolkit for constructing novel registration pipelines.

PubMed

Friedel, Miriam; van Eede, Matthijs C; Pipitone, Jon; Chakravarty, M Mallar; Lerch, Jason P

2014-01-01

Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available software package that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines "out-of-the-box." In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code.

Pydpiper: a flexible toolkit for constructing novel registration pipelines

PubMed Central

Friedel, Miriam; van Eede, Matthijs C.; Pipitone, Jon; Chakravarty, M. Mallar; Lerch, Jason P.

2014-01-01

Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available software package that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines “out-of-the-box.” In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code. PMID:25126069

Three dimensional canonical singularity and five dimensional N = 1 SCFT

NASA Astrophysics Data System (ADS)

Xie, Dan; Yau, Shing-Tung

2017-06-01

We conjecture that every three dimensional canonical singularity defines a five dimensional N = 1 SCFT. Flavor symmetry can be found from singularity structure: non-abelian flavor symmetry is read from the singularity type over one dimensional singular locus. The dimension of Coulomb branch is given by the number of compact crepant divisors from a crepant resolution of singularity. The detailed structure of Coulomb branch is described as follows: a) a chamber of Coulomb branch is described by a crepant resolution, and this chamber is given by its Nef cone and the prepotential is computed from triple intersection numbers; b) Crepant resolution is not unique and different resolutions are related by flops; Nef cones from crepant resolutions form a fan which is claimed to be the full Coulomb branch.

The value of real-time three-dimensional transesophageal echocardiography in the assessment of paravalvular leak origin following prosthetic mitral valve replacement.

PubMed

Yildiz, Mustafa; Duran, Nilüfer Ekşi; Gökdeniz, Tayyar; Kaya, Hasan; Ozkan, Mehmet

2009-09-01

Two-dimensional (2D) echocardiographic approaches are not sufficient to determine the origin of paravalvular leak (PVL) that occurs after prosthetic mitral valve replacement (MVR). In this study, we investigated the role of real-time three-dimensional transesophageal echocardiography (RT-3D TEE) in detecting the origin and size of PVL occurring after prosthetic MVR. The study included 13 patients (7 females; 6 males; mean age 56+/-10 years; range 37 to 71 years) who developed PVL within a mean of 8.3+/-3.8 years following mechanical prosthetic MVR. Nine patients (69.2%) had atrial fibrillation, and four patients (30.8%) had normal sinus rhythm. Four patients (30.8%) had hemolysis. Paravalvular leak was mild, moderate, and severe in two, six, and five patients, respectively. Real-time 3D TEE was performed using a 3D matrix-array TEE transducer immediately after detection of PVL on 2D TEE examination. Localization of PVL was made using a clock-wise format in relation to the aortic valve and the size of dehiscence was measured. The mean PVL width measured by 2D TEE was 3.00+/-0.92 mm. The mean length of dehiscence was 13.6+/-8.8 mm, and the mean width was 3.88+/-2.04 mm on RT-3D TEE. The PVLs were mainly localized in the posterior and anterior annular positions between 12 to 03 hours (n=7) and 06 to 09 hours (n=3) on RT-3D TEE, respectively, which corresponded to the posteromedial or anterolateral sectors of the posterior annulus. Considering that only the width of the PVL defect can be assessed by 2D TEE, delineation by RT-3D TEE includes the localization of PVL together with the length and width of the defect.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

Hidden conformal symmetry of rotating black holes in minimal five-dimensional gauged supergravity

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

Setare, M. R.; Kamali, V.

2010-10-15

In the present paper we show that for a low frequency limit the wave equation of a massless scalar field in the background of nonextremal charged rotating black holes in five-dimensional minimal gauged and ungauged supergravity can be written as the Casimir of an SL(2,R) symmetry. Our result shows that the entropy of the black hole is reproduced by the Cardy formula. Also the absorption cross section is consistent with the finite temperature absorption cross section for a two-dimensional conformal field theory.

Assessment of three-dimensional inviscid codes and loss calculations for turbine aerodynamic computations

NASA Technical Reports Server (NTRS)

Povinelli, L. A.

1984-01-01

An assessment of several three dimensional inviscid turbine aerodynamic computer codes and loss models used at the NASA Lewis Research Center is presented. Five flow situations are examined, for which both experimental data and computational results are available. The five flows form a basis for the evaluation of the computational procedures. It was concluded that stator flows may be calculated with a high degree of accuracy, whereas, rotor flow fields are less accurately determined. Exploitation of contouring, learning, bowing, and sweeping will require a three dimensional viscous analysis technique.

Dimensional models of personality: the five-factor model and the DSM-5

PubMed Central

Trull, Timothy J.; Widiger, Thomas A.

2013-01-01

It is evident that the classification of personality disorder is shifting toward a dimensional trait model and, more specifically, the five-factor model (FFM). The purpose of this paper is to provide an overview of the FFM of personality disorder. It will begin with a description of this dimensional model of normal and abnormal personality functioning, followed by a comparison with a proposal for future revisions to DSM-5 and a discussion of its potential advantages as an integrative hierarchical model of normal and abnormal personality structure. PMID:24174888

Incremental online learning in high dimensions.

PubMed

Vijayakumar, Sethu; D'Souza, Aaron; Schaal, Stefan

2005-12-01

Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high-dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models. In order to stay computationally efficient and numerically robust, each local model performs the regression analysis with a small number of univariate regressions in selected directions in input space in the spirit of partial least squares regression. We discuss when and how local learning techniques can successfully work in high-dimensional spaces and review the various techniques for local dimensionality reduction before finally deriving the LWPR algorithm. The properties of LWPR are that it (1) learns rapidly with second-order learning methods based on incremental training, (2) uses statistically sound stochastic leave-one-out cross validation for learning without the need to memorize training data, (3) adjusts its weighting kernels based on only local information in order to minimize the danger of negative interference of incremental learning, (4) has a computational complexity that is linear in the number of inputs, and (5) can deal with a large number of-possibly redundant-inputs, as shown in various empirical evaluations with up to 90 dimensional data sets. For a probabilistic interpretation, predictive variance and confidence intervals are derived. To our knowledge, LWPR is the first truly incremental spatially localized learning method that can successfully and efficiently operate in very high-dimensional spaces.

Radiologically occult medulloblastoma with hydrocephalus: case report.

PubMed

Honma, Hirokuni; Ogiwara, Hideki

2017-09-01

There have been no reports of occult medulloblastoma nor noncommunicating hydrocephalus due to radiologically occult brain tumors. Herein, we report radiologically occult medulloblastoma with noncommunicating hydrocephalus. A 3-year-old boy presented with macrocephaly, visual field constriction, and papilledema. Neuroimagings showed enlargement of the ventricles without any mass lesions. The CT cisternography did not show influx of the contrast into the ventricles, which suggested local cerebrospinal fluid (CSF) circulatory disturbance at the outlet of the fourth ventricle. Due to possible obstructive nature of hydrocephalus, endoscopic third ventriculostomy (ETV) was performed. Three months after the ETV, he presented with repeated vomiting. Neuroimagings showed a 3-cm fourth ventricular mass with progressive hydrocephalus. Surgical resection was performed, which revealed the pathology was medulloblastoma. We report the case of radiologically occult medulloblastoma which was demonstrated radiologically in the follow-up period of ETV for noncommunicating hydrocephalus of uncertain etiology. This is the first description of a radiologically occult medulloblastoma and also the first description of an occult brain tumor with noncommunicating hydrocephalus. The occult brain tumor may be included in the etiology of hydrocephalus.

Believers' estimates of God's beliefs are more egocentric than estimates of other people's beliefs

PubMed Central

Epley, Nicholas; Converse, Benjamin A.; Delbosc, Alexa; Monteleone, George A.; Cacioppo, John T.

2009-01-01

People often reason egocentrically about others' beliefs, using their own beliefs as an inductive guide. Correlational, experimental, and neuroimaging evidence suggests that people may be even more egocentric when reasoning about a religious agent's beliefs (e.g., God). In both nationally representative and more local samples, people's own beliefs on important social and ethical issues were consistently correlated more strongly with estimates of God's beliefs than with estimates of other people's beliefs (Studies 1–4). Manipulating people's beliefs similarly influenced estimates of God's beliefs but did not as consistently influence estimates of other people's beliefs (Studies 5 and 6). A final neuroimaging study demonstrated a clear convergence in neural activity when reasoning about one's own beliefs and God's beliefs, but clear divergences when reasoning about another person's beliefs (Study 7). In particular, reasoning about God's beliefs activated areas associated with self-referential thinking more so than did reasoning about another person's beliefs. Believers commonly use inferences about God's beliefs as a moral compass, but that compass appears especially dependent on one's own existing beliefs. PMID:19955414

Cognitive Neuroimaging: Cognitive Science out of the Armchair

ERIC Educational Resources Information Center

de Zubicaray, Greig I.

2006-01-01

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some…

Neuroimaging of Cognitive Load in Instructional Multimedia

ERIC Educational Resources Information Center

Whelan, Robert R.

2007-01-01

This paper reviews research literature on cognitive load measurement in learning and neuroimaging, and describes a mapping between the main elements of cognitive load theory and findings in functional neuroanatomy. It is argued that these findings may lead to the improved measurement of cognitive load using neuroimaging. The paper describes how…

Turner Syndrome: Neuroimaging Findings--Structural and Functional

ERIC Educational Resources Information Center

Mullaney, Ronan; Murphy, Declan

2009-01-01

Neuroimaging studies of Turner syndrome can advance our understanding of the X chromosome in brain development, and the modulatory influence of endocrine factors. There is increasing evidence from neuroimaging studies that TX individuals have significant differences in the anatomy, function, and metabolism of a number of brain regions; including…

Multilingual Processing in the Brain

ERIC Educational Resources Information Center

van den Noort, Maurits; Struys, Esli; Kim, Kayoung; Bosch, Peggy; Mondt, Katrien; van Kralingen, Rosalinde; Lee, Mikyoung; van de Craen, Piet

2014-01-01

In this paper, in contrast to previous neuroimaging literature reviews on first language (L1) and second language (L2), the focus was only on neuroimaging studies that were directly conducted on multilingual participants. In total, 14 neuroimaging studies were included in our study such as 10 functional magnetic resonance imaging, 1 positron…

A very simple, re-executable neuroimaging publication

PubMed Central

Ghosh, Satrajit S.; Poline, Jean-Baptiste; Keator, David B.; Halchenko, Yaroslav O.; Thomas, Adam G.; Kessler, Daniel A.; Kennedy, David N.

2017-01-01

Reproducible research is a key element of the scientific process. Re-executability of neuroimaging workflows that lead to the conclusions arrived at in the literature has not yet been sufficiently addressed and adopted by the neuroimaging community. In this paper, we document a set of procedures, which include supplemental additions to a manuscript, that unambiguously define the data, workflow, execution environment and results of a neuroimaging analysis, in order to generate a verifiable re-executable publication. Re-executability provides a starting point for examination of the generalizability and reproducibility of a given finding. PMID:28781753

Heterogeneity of neuroanatomical patterns in prodromal Alzheimer's disease: links to cognition, progression and biomarkers.

PubMed

Dong, Aoyan; Toledo, Jon B; Honnorat, Nicolas; Doshi, Jimit; Varol, Erdem; Sotiras, Aristeidis; Wolk, David; Trojanowski, John Q; Davatzikos, Christos

2017-03-01

See Coulthard and Knight (doi:10.1093/aww335) for a scientific commentary on this article.Individuals with mild cognitive impairment and Alzheimer's disease clinical diagnoses can display significant phenotypic heterogeneity. This variability likely reflects underlying genetic, environmental and neuropathological differences. Characterizing this heterogeneity is important for precision diagnostics, personalized predictions, and recruitment of relatively homogeneous sets of patients into clinical trials. In this study, we apply state-of-the-art semi-supervised machine learning methods to the Alzheimer's disease Neuroimaging cohort (ADNI) to elucidate the heterogeneity of neuroanatomical differences between subjects with mild cognitive impairment (n = 530) and Alzheimer's disease (n = 314) and cognitively normal individuals (n = 399), thereby adding to an increasing literature aiming to establish neuroanatomical and neuropathological (e.g. amyloid and tau deposition) dimensions in Alzheimer's disease and its prodromal stages. These dimensional approaches aim to provide surrogate measures of heterogeneous underlying pathologic processes leading to cognitive impairment. We relate these neuroimaging patterns to cerebrospinal fluid biomarkers, white matter hyperintensities, cognitive and clinical measures, and longitudinal trajectories. We identified four such atrophy patterns: (i) individuals with largely normal neuroanatomical profiles, who also turned out to have the least abnormal cognitive and cerebrospinal fluid biomarker profiles and the slowest clinical progression during follow-up; (ii) individuals with classical Alzheimer's disease neuroanatomical, cognitive, cerebrospinal fluid biomarkers and clinical profile, who presented the fastest clinical progression; (iii) individuals with a diffuse pattern of atrophy with relatively less pronounced involvement of the medial temporal lobe, abnormal cerebrospinal fluid amyloid-β1-42 values, and proportionally greater executive impairment; and (iv) individuals with notably focal involvement of the medial temporal lobe and a slow steady progression, likely representing in early Alzheimer's disease stages. These four atrophy patterns effectively define a 4-dimensional categorization of neuroanatomical alterations in mild cognitive impairment and Alzheimer's disease that can complement existing dimensional approaches for staging Alzheimer's disease using a variety of biomarkers, which offer the potential for enabling precision diagnostics and prognostics, as well as targeted patient recruitment of relatively homogeneous subgroups of subjects for clinical trials. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Visual Systems for Interactive Exploration and Mining of Large-Scale Neuroimaging Data Archives

PubMed Central

Bowman, Ian; Joshi, Shantanu H.; Van Horn, John D.

2012-01-01

While technological advancements in neuroimaging scanner engineering have improved the efficiency of data acquisition, electronic data capture methods will likewise significantly expedite the populating of large-scale neuroimaging databases. As they do and these archives grow in size, a particular challenge lies in examining and interacting with the information that these resources contain through the development of compelling, user-driven approaches for data exploration and mining. In this article, we introduce the informatics visualization for neuroimaging (INVIZIAN) framework for the graphical rendering of, and dynamic interaction with the contents of large-scale neuroimaging data sets. We describe the rationale behind INVIZIAN, detail its development, and demonstrate its usage in examining a collection of over 900 T1-anatomical magnetic resonance imaging (MRI) image volumes from across a diverse set of clinical neuroimaging studies drawn from a leading neuroimaging database. Using a collection of cortical surface metrics and means for examining brain similarity, INVIZIAN graphically displays brain surfaces as points in a coordinate space and enables classification of clusters of neuroanatomically similar MRI images and data mining. As an initial step toward addressing the need for such user-friendly tools, INVIZIAN provides a highly unique means to interact with large quantities of electronic brain imaging archives in ways suitable for hypothesis generation and data mining. PMID:22536181

Single-Particle Mobility Edge in a One-Dimensional Quasiperiodic Optical Lattice

NASA Astrophysics Data System (ADS)

Lüschen, Henrik P.; Scherg, Sebastian; Kohlert, Thomas; Schreiber, Michael; Bordia, Pranjal; Li, Xiao; Das Sarma, S.; Bloch, Immanuel

2018-04-01

A single-particle mobility edge (SPME) marks a critical energy separating extended from localized states in a quantum system. In one-dimensional systems with uncorrelated disorder, a SPME cannot exist, since all single-particle states localize for arbitrarily weak disorder strengths. However, in a quasiperiodic system, the localization transition can occur at a finite detuning strength and SPMEs become possible. In this Letter, we find experimental evidence for the existence of such a SPME in a one-dimensional quasiperiodic optical lattice. Specifically, we find a regime where extended and localized single-particle states coexist, in good agreement with theoretical simulations, which predict a SPME in this regime.

Discovering Planetary Nebula Geometries: Explorations with a Hierarchy of Models

NASA Technical Reports Server (NTRS)

Huyser, Karen A.; Knuth, Kevin H.; Fischer, Bernd; Schumann, Johann; Granquist-Fraser, Domhnull; Hajian, Arsen R.

2004-01-01

Astronomical objects known as planetary nebulae (PNe) consist of a shell of gas expelled by an aging medium-sized star as it makes its transition from a red giant to a white dwarf. In many cases this gas shell can be approximately described as a prolate ellipsoid. Knowledge of the physics of ionization processes in this gaseous shell enables us to construct a model in three dimensions (3D) called the Ionization-Bounded Prolate Ellipsoidal Shell model (IBPES model). Using this model we can generate synthetic nebular images, which can be used in conjunction with Hubble Space Telescope (HST) images of actual PNe to perform Bayesian model estimation. Since the IBPES model is characterized by thirteen parameters, model estimation requires the search of a 13-dimensional parameter space. The 'curse of dimensionality,' compounded by a computationally intense forward problem, makes forward searches extremely time-consuming and frequently causes them to become trapped in local solutions. We find that both the speed and of the search can be improved by judiciously reducing the dimensionality of the search space. Our basic approach employs a hierarchy of models of increasing complexity that converges to the IBPES model. Earlier studies establish that a hierarchical sequence converges more quickly, and to a better solution, than a search relying only on the most complex model. Here we report results for a hierarchy of five models. The first three models treat the nebula as a 2D image, while the last two models explore its characteristics as a 3D object and enable us to characterize the physics of the nebula. This five-model hierarchy is applied to HST images of ellipsoidal PNe to estimate their geometric properties and gas density profiles.

Fission dynamics with microscopic level densities

NASA Astrophysics Data System (ADS)

Randrup, Jørgen; Ward, Daniel; Carlsson, Gillis; Døssing, Thomas; Möller, Peter; Åberg, Sven

2018-03-01

Working within the Langevin framework of nuclear shape dynamics, we study the dependence of the evolution on the degree of excitation. As the excitation energy of the fissioning system is increased, the pairing correlations and the shell effects diminish and the effective potential-energy surface becomes ever more liquid-drop like. This feature can be included in the treatment in a formally well-founded manner by using the local level densities as a basis for the shape evolution. This is particularly easy to understand and implement in the Metropolis treatment where the evolution is simulated by means of a random walk on the five-dimensional lattice of shapes for which the potential energy has been tabulated. Because the individual steps between two neighboring lattice sites are decided on the basis of the ratio of the statistical weights, what is needed is the ratio of the local level densities for those shapes, evaluated at the associated local excitation energies. For this purpose, we adapt a recently developed combinatorial method for calculating level densities which employs the same single-particle levels as those that were used for the calculation of the pairing and shell contributions to the macroscopic-microscopic deformation-energy surface. For each nucleus under consideration, the level density (for a fixed total angular momentum) is calculated microscopically for each of the over five million shapes given in the three-quadratic-surface parametrization. This novel treatment, which introduces no new parameters, is illustrated for the fission fragment mass distributions for selected uranium and plutonium cases.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Clinical correlates of graph theory findings in temporal lobe epilepsy.

PubMed

Haneef, Zulfi; Chiang, Sharon

2014-11-01

Temporal lobe epilepsy (TLE) is considered a brain network disorder, additionally representing the most common form of pharmaco-resistant epilepsy in adults. There is increasing evidence that seizures in TLE arise from abnormal epileptogenic networks, which extend beyond the clinico-radiologically determined epileptogenic zone and may contribute to the failure rate of 30-50% following epilepsy surgery. Graph theory allows for a network-based representation of TLE brain networks using several neuroimaging and electrophysiologic modalities, and has potential to provide clinicians with clinically useful biomarkers for diagnostic and prognostic purposes. We performed a review of the current state of graph theory findings in TLE as they pertain to localization of the epileptogenic zone, prediction of pre- and post-surgical seizure frequency and cognitive performance, and monitoring cognitive decline in TLE. Although different neuroimaging and electrophysiologic modalities have yielded occasionally conflicting results, several potential biomarkers have been characterized for identifying the epileptogenic zone, pre-/post-surgical seizure prediction, and assessing cognitive performance. For localization, graph theory measures of centrality have shown the most potential, including betweenness centrality, outdegree, and graph index complexity, whereas for prediction of seizure frequency, measures of synchronizability have shown the most potential. The utility of clustering coefficient and characteristic path length for assessing cognitive performance in TLE is also discussed. Future studies integrating data from multiple modalities and testing predictive models are needed to clarify findings and develop graph theory for its clinical utility. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Clinical correlates of graph theory findings in temporal lobe epilepsy

PubMed Central

Haneef, Zulfi; Chiang, Sharon

2014-01-01

Purpose Temporal lobe epilepsy (TLE) is considered a brain network disorder, additionally representing the most common form of pharmaco-resistant epilepsy in adults. There is increasing evidence that seizures in TLE arise from abnormal epileptogenic networks, which extend beyond the clinico-radiologically determined epileptogenic zone and may contribute to the failure rate of 30–50% following epilepsy surgery. Graph theory allows for a network-based representation of TLE brain networks using several neuroimaging and electrophysiologic modalities, and has potential to provide clinicians with clinically useful biomarkers for diagnostic and prognostic purposes. Methods We performed a review of the current state of graph theory findings in TLE as they pertain to localization of the epileptogenic zone, prediction of pre- and post-surgical seizure frequency and cognitive performance, and monitoring cognitive decline in TLE. Results Although different neuroimaging and electrophysiologic modalities have yielded occasionally conflicting results, several potential biomarkers have been characterized for identifying the epileptogenic zone, pre-/post-surgical seizure prediction, and assessing cognitive performance. For localization, graph theory measures of centrality have shown the most potential, including betweenness centrality, outdegree, and graph index complexity, whereas for prediction of seizure frequency, measures of synchronizability have shown the most potential. The utility of clustering coefficient and characteristic path length for assessing cognitive performance in TLE is also discussed. Conclusions Future studies integrating data from multiple modalities and testing predictive models are needed to clarify findings and develop graph theory for its clinical utility. PMID:25127370

Mapping the fundamental niches of two freshwater microalgae, Chlorella vulgaris (Trebouxiophyceae) and Peridinium cinctum (Dinophyceae), in 5-dimensional ion space

USDA-ARS?s Scientific Manuscript database

A five dimensional experimental design, i.e. a five component ion mixture design for nitrate, phosphate, potassium, sodium and chloride projected across a total ion concentration gradient of 1-30 mM was utilized to map the ion-based, scenopoetic, or ‘Grinnellian’, niche space for two freshwater alga...

Can cognitive models explain brain activation during word and pseudoword reading? A meta-analysis of 36 neuroimaging studies.

PubMed

Taylor, J S H; Rastle, Kathleen; Davis, Matthew H

2013-07-01

Reading in many alphabetic writing systems depends on both item-specific knowledge used to read irregular words (sew, yacht) and generative spelling-sound knowledge used to read pseudowords (tew, yash). Research into the neural basis of these abilities has been directed largely by cognitive accounts proposed by the dual-route cascaded and triangle models of reading. We develop a framework that enables predictions for neural activity to be derived from cognitive models of reading using 2 principles: (a) the extent to which a model component or brain region is engaged by a stimulus and (b) how much effort is exerted in processing that stimulus. To evaluate the derived predictions, we conducted a meta-analysis of 36 neuroimaging studies of reading using the quantitative activation likelihood estimation technique. Reliable clusters of activity are localized during word versus pseudoword and irregular versus regular word reading and demonstrate a great deal of convergence between the functional organization of the reading system put forward by cognitive models and the neural systems activated during reading tasks. Specifically, left-hemisphere activation clusters are revealed reflecting orthographic analysis (occipitotemporal cortex), lexical and/or semantic processing (anterior fusiform, middle temporal gyrus), spelling-sound conversion (inferior parietal cortex), and phonological output resolution (inferior frontal gyrus). Our framework and results establish that cognitive models of reading are relevant for interpreting neuroimaging studies and that neuroscientific studies can provide data relevant for advancing cognitive models. This article thus provides a firm empirical foundation from which to improve integration between cognitive and neural accounts of the reading process. 2013 APA, all rights reserved

Representation of the five- and six-dimensional harmonic oscillators in a u(5) ⊃ so(5) ⊃ so(3) basis

NASA Astrophysics Data System (ADS)

Rowe, D. J.

1994-06-01

The duality that exists between the two subgroups SU(1,1) and O(5) of Sp(5,R) to construct basis states for the five-dimensional harmonic oscillator which simultaneously reduce the Sp(5,R)⊇U(5)⊇O(5)⊇SO(3) and Sp(5,R)⊇ SU(1,1)⊇U(1) subgroup chains is used. It is shown that the vector-coherent-state wave functions of the fundamental five-dimensional SO(5) irrep [1,0] realize the traceless bosons introduced by Lohe and Hurst to classify the irreps of the orthogonal groups and employed in Chacon, Moshinsky, and Sharp's construction of a basis for the five-dimensional harmonic oscillator. Moreover, it is shown that VCS theory provides a simple mechanism for constructing matrix elements of the traceless boson operators. These matrix elements are used to extend the VCS representations of SO(5) in an SO(3) basis, given in a previous paper, to irreps of U(5) in an SO(5)⊇ SO(3) basis. The extension to U(6)⊇U(5)⊇SO(5)⊇SO(3) is also given.

Local brain connectivity across development in autism spectrum disorder: A cross-sectional investigation

PubMed Central

Dajani, Dina R.; Uddin, Lucina Q.

2015-01-01

Lay Abstract There is a general consensus that autism spectrum disorder (ASD) is accompanied by alterations in brain connectivity. Much of the neuroimaging work has focused on assessing long-range connectivity disruptions in ASD. However, evidence from both animal models and postmortem examination of the human brain suggests that local connections may also be disrupted in individuals with ASD. Here we investigated the development of local connectivity across three age cohorts of individuals with ASD and typically developing (TD) individuals. We find that in typical development, children exhibit high levels of local connectivity across the brain, while adolescents exhibit lower levels of local connectivity, similar to adult levels. On the other hand, children with ASD exhibit marginally lower local connectivity than TD children, and adolescents and adults with ASD exhibit levels of local connectivity comparable to that observed in neurotypical individuals. During all developmental stages -- childhood, adolescence, and adulthood -- individuals with ASD exhibited lower local connectivity in brain regions involved in sensory processing and higher local connectivity in brain regions involved in complex information processing. Further, higher local connectivity in ASD corresponded to more severe ASD symptomatology. Thus we demonstrate that local connectivity is disrupted in autism across development, with the most pronounced differences occurring in childhood. Scientific Abstract There is a general consensus that autism spectrum disorder (ASD) is accompanied by alterations in brain connectivity. Much of the neuroimaging work has focused on assessing long-range connectivity disruptions in ASD. However, evidence from both animal models and postmortem examination of the human brain suggests that local connections may also be disrupted in individuals with the disorder. Here we investigated how regional homogeneity (ReHo), a measure of similarity of a voxel’s timeseries to its nearest neighbors, varies across age in individuals with ASD and typically developing (TD) individuals using a cross-sectional design. Resting-state fMRI data obtained from a publicly available database were analyzed to determine group differences in ReHo between three age cohorts: children, adolescents, and adults. In typical development, ReHo across the entire brain was higher in children than in adolescents and adults. In contrast, children with ASD exhibited marginally lower ReHo than TD children, while adolescents and adults with ASD exhibited similar levels of local connectivity as age-matched neurotypical individuals. During all developmental stages, individuals with ASD exhibited lower local connectivity in sensory processing brain regions and higher local connectivity in complex information processing regions. Further, higher local connectivity in ASD corresponded to more severe ASD symptomatology. These results demonstrate that local connectivity is disrupted in ASD across development, with the most pronounced differences occurring in childhood. Developmental changes in ReHo do not mirror findings from fMRI studies of long-range connectivity in ASD, pointing to a need for more nuanced accounts of brain connectivity alterations in the disorder. PMID:26058882

Local polynomial chaos expansion for linear differential equations with high dimensional random inputs

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

Chen, Yi; Jakeman, John; Gittelson, Claude

2015-01-08

In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. Furthermore, the local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained frommore » the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In our paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.« less

Ultrafast Brain MRI: Clinical Deployment and Comparison to Conventional Brain MRI at 3T.

PubMed

Prakkamakul, Supada; Witzel, Thomas; Huang, Susie; Boulter, Daniel; Borja, Maria J; Schaefer, Pamela; Rosen, Bruce; Heberlein, Keith; Ratai, Eva; Gonzalez, Gilberto; Rapalino, Otto

2016-09-01

To compare an ultrafast brain magnetic resonance imaging (MRI) protocol to the conventional protocol in motion-prone inpatient clinical settings. This retrospective study was HIPAA compliant and approved by the Institutional Review Board with waived inform consent. Fifty-nine inpatients (30 males, 29 females; mean age 55.1, range 23-93 years)who underwent 3-Tesla brain MRI using ultrafast and conventional protocols, both including five sequences, were included in the study. The total scan time for five ultrafast sequences was 4 minutes 59 seconds. The ideal conventional acquisition time was 10 minutes 32 seconds but the actual acquisition took 15-20 minutes. The average scan times for ultrafast localizers, T1-weighted, T2-weighted, fluid-attenuated inversion recovery (FLAIR), diffusion-weighted, T2*-weighted sequences were 14, 41, 62, 96, 80, 6 seconds, respectively. Two blinded neuroradiologists independently assessed three aspects: (1) image quality, (2) gray-white matter (GM-WM) differentiation, and (3) diagnostic concordance for the detection of six clinically relevant imaging findings. Wilcoxon signed-rank test was used to compare image quality and GM-WM scores. Interobserver reproducibility was calculated. The ultrafast T1-weighted sequence demonstrated significantly better image quality (P = .005) and GM-WM differentiation (P < .001) compared to the conventional sequence. There was high agreement (>85%) between both protocols for the detection of mass-like lesion, hemorrhage, diffusion restriction, WM FLAIR hyperintensities, subarachnoid FLAIR hyperintensities, and hydrocephalus. The ultrafast protocol achieved at least comparable image quality and high diagnostic concordance compared to the conventional protocol. This fast protocol can be a viable option to replace the conventional protocol in motion-prone inpatient clinical settings. Copyright © 2016 by the American Society of Neuroimaging.

Phonon-induced localization of electron states in quasi-one-dimensional systems

NASA Astrophysics Data System (ADS)

Xiong, Ye

2007-02-01

It is shown that hot phonons with random phases can cause localization of electron states in quasi-one-dimensional systems. Owing to the nature of long-range correlation of the disorder induced by phonons, only the states at edges of one-dimensional (1D) subbands are localized, and the states inside the 1D subbands are still extended. As a result, the conductance exhibits gradual quantum steps in varying the gate potential. By increasing the temperature the degree of localization increases. In the localization regime the distribution of Lyapunov exponent (LE) is Gaussian and the relation of the mean-value and standard variance of LE to the system size obeys the single-parameter hypothesis. The mean value of LE can be used as an order parameter to distinguish the local and extended states.

Rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD) syndrome may have a hypothalamus-periaqueductal gray localization.

PubMed

Chow, Cristelle; Fortier, Marielle Valerie; Das, Lena; Menon, Anuradha P; Vasanwala, Rashida; Lam, Joyce C M; Ng, Zhi Min; Ling, Simon Robert; Chan, Derrick W S; Choong, Chew Thye; Liew, Wendy K M; Thomas, Terrence

2015-05-01

Anatomical localization of the rapid-onset obesity with hypothalamic dysfunction, hypoventilation, and autonomic dysregulation (ROHHAD) syndrome has proved elusive. Most patients had neuroimaging after cardiorespiratory collapse, revealing a range of ischemic lesions. A 15-year-old obese boy with an acute febrile encephalopathy had hypoventilation, autonomic dysfunction, visual hallucinations, hyperekplexia, and disordered body temperature, and saltwater regulation. These features describe the ROHHAD syndrome. Cerebrospinal fluid analysis showed pleocytosis, elevated neopterins, and oligoclonal bands, and serology for systemic and antineuronal antibodies was negative. He improved after receiving intravenous steroids, immunoglobulins, and long-term mycophenolate. Screening for neural crest tumors was negative. Magnetic resonance imaging of the brain early in his illness showed focal inflammation in the periaqueductal gray matter and hypothalamus. This unique localization explains almost all symptoms of this rare autoimmune encephalitis. Copyright © 2015 Elsevier Inc. All rights reserved.

Localization, correlation, and visualization of electroencephalographic surface electrodes and brain anatomy in epilepsy studies

NASA Astrophysics Data System (ADS)

Brinkmann, Benjamin H.; O'Brien, Terence J.; Robb, Richard A.; Sharbrough, Frank W.

1997-05-01

Advances in neuroimaging have enhanced the clinician's ability to localize the epileptogenic zone in focal epilepsy, but 20-50 percent of these cases still remain unlocalized. Many sophisticated modalities have been used to study epilepsy, but scalp electrode recorded electroencephalography is particularly useful due to its noninvasive nature and excellent temporal resolution. This study is aimed at specific locations of scalp electrode EEG information for correlation with anatomical structures in the brain. 3D position localizing devices commonly used in virtual reality systems are used to digitize the coordinates of scalp electrodes in a standard clinical configuration. The electrode coordinates are registered with a high- resolution MRI dataset using a robust surface matching algorithm. Volume rendering can then be used to visualize the electrodes and electrode potentials interpolated over the scalp. The accuracy of the coordinate registration is assessed quantitatively with a realistic head phantom.

Pre-seizure state identified by diffuse optical tomography

PubMed Central

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

2014-01-01

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

Intergenerational Neuroimaging of Human Brain Circuitry

PubMed Central

Ho, Tiffany C.; Sanders, Stephan J.; Gotlib, Ian H.; Hoeft, Fumiko

2016-01-01

Neuroscientists are increasingly using advanced neuroimaging methods to elucidate the intergenerational transmission of human brain circuitry. This new line of work promises to shed insight into the ontogeny of complex behavioral traits, including psychiatric disorders, and possible mechanisms of transmission. Here, we highlight recent intergenerational neuroimaging studies and provide recommendations for future work. PMID:27623194

Neuroimaging and Research into Second Language Acquisition

ERIC Educational Resources Information Center

Sabourin, Laura

2009-01-01

Neuroimaging techniques are becoming not only more and more sophisticated but are also coming to be increasingly accessible to researchers. One thing that one should take note of is the potential of neuroimaging research within second language acquisition (SLA) to contribute to issues pertaining to the plasticity of the adult brain and to general…

A Numerical Analysis on a Compact Heat Exchanger in Aluminum Foam

NASA Astrophysics Data System (ADS)

Buonomo, B.; Ercole, D.; Manca, O.; Nardini, S.

2016-09-01

A numerical investigation on a compact heat exchanger in aluminum foam is carried out. The governing equations in two-dimensional steady state regime are written in local thermal non-equilibrium (LTNE). The geometrical domain under investigation is made up of a plate in aluminum foam with inside a single array of five circular tubes. The presence of the open-celled metal foam is modeled as a porous media by means of the Darcy-Forchheimer law. The foam has a porosity of 0.93 with 20 pores per inch and the LTNE assumption is used to simulate the heat transfer between metal foam and air. The compact heat exchanger at different air flow rates is studied with an assigned surface tube temperature. The results in terms of local heat transfer coefficient and Nusselt number on the external surface of the tubes are given. Moreover, local air temperature and velocity profiles in the smaller cross section, between two consecutive tubes, as a function of Reynolds number are showed. The performance evaluation criteria (PEC) is assessed in order to evaluate the effectiveness of the metal foam.

Imaging genetics approach to predict progression of Parkinson's diseases.

PubMed

Mansu Kim; Seong-Jin Son; Hyunjin Park

2017-07-01

Imaging genetics is a tool to extract genetic variants associated with both clinical phenotypes and imaging information. The approach can extract additional genetic variants compared to conventional approaches to better investigate various diseased conditions. Here, we applied imaging genetics to study Parkinson's disease (PD). We aimed to extract significant features derived from imaging genetics and neuroimaging. We built a regression model based on extracted significant features combining genetics and neuroimaging to better predict clinical scores of PD progression (i.e. MDS-UPDRS). Our model yielded high correlation (r = 0.697, p <; 0.001) and low root mean squared error (8.36) between predicted and actual MDS-UPDRS scores. Neuroimaging (from 123 I-Ioflupane SPECT) predictors of regression model were computed from independent component analysis approach. Genetic features were computed using image genetics approach based on identified neuroimaging features as intermediate phenotypes. Joint modeling of neuroimaging and genetics could provide complementary information and thus have the potential to provide further insight into the pathophysiology of PD. Our model included newly found neuroimaging features and genetic variants which need further investigation.

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories

PubMed Central

Neu, Scott C.; Crawford, Karen L.; Toga, Arthur W.

2012-01-01

Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead. PMID:22470336

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories.

PubMed

Neu, Scott C; Crawford, Karen L; Toga, Arthur W

2012-01-01

Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead.

Real-time fMRI: a tool for local brain regulation.

PubMed

Caria, Andrea; Sitaram, Ranganatha; Birbaumer, Niels

2012-10-01

Real-time fMRI permits simultaneous measurement and observation of brain activity during an ongoing task. One of the most challenging applications of real-time fMRI in neuroscientific and clinical research is the possibility of acquiring volitional control of localized brain activity using real-time fMRI-based neurofeedback protocols. Real-time fMRI allows the experimenter to noninvasively manipulate brain activity as an independent variable to observe the effects on behavior. Real-time fMRI neurofeedback studies demonstrated that learned control of the local brain activity leads to specific changes in behavior. Here, the authors describe the implementation and application of real-time fMRI with particular emphasis on the self-regulation of local brain activity and the investigation of brain-function relationships. Real-time fMRI represents a promising new approach to cognitive neuroscience that could complement traditional neuroimaging techniques by providing more causal insights into the functional role of circumscribed brain regions in behavior.

Vacuum solutions of five dimensional Einstein equations generated by inverse scattering method. II. Production of the black ring solution

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

Tomizawa, Shinya; Nozawa, Masato

2006-06-15

We study vacuum solutions of five-dimensional Einstein equations generated by the inverse scattering method. We reproduce the black ring solution which was found by Emparan and Reall by taking the Euclidean Levi-Civita metric plus one-dimensional flat space as a seed. This transformation consists of two successive processes; the first step is to perform the three-solitonic transformation of the Euclidean Levi-Civita metric with one-dimensional flat space as a seed. The resulting metric is the Euclidean C-metric with extra one-dimensional flat space. The second is to perform the two-solitonic transformation by taking it as a new seed. Our result may serve asmore » a stepping stone to find new exact solutions in higher dimensions.« less

Terminology development towards harmonizing multiple clinical neuroimaging research repositories.

PubMed

Turner, Jessica A; Pasquerello, Danielle; Turner, Matthew D; Keator, David B; Alpert, Kathryn; King, Margaret; Landis, Drew; Calhoun, Vince D; Potkin, Steven G; Tallis, Marcelo; Ambite, Jose Luis; Wang, Lei

2015-07-01

Data sharing and mediation across disparate neuroimaging repositories requires extensive effort to ensure that the different domains of data types are referred to by commonly agreed upon terms. Within the SchizConnect project, which enables querying across decentralized databases of neuroimaging, clinical, and cognitive data from various studies of schizophrenia, we developed a model for each data domain, identified common usable terms that could be agreed upon across the repositories, and linked them to standard ontological terms where possible. We had the goal of facilitating both the current user experience in querying and future automated computations and reasoning regarding the data. We found that existing terminologies are incomplete for these purposes, even with the history of neuroimaging data sharing in the field; and we provide a model for efforts focused on querying multiple clinical neuroimaging repositories.

Terminology development towards harmonizing multiple clinical neuroimaging research repositories

PubMed Central

Turner, Jessica A.; Pasquerello, Danielle; Turner, Matthew D.; Keator, David B.; Alpert, Kathryn; King, Margaret; Landis, Drew; Calhoun, Vince D.; Potkin, Steven G.; Tallis, Marcelo; Ambite, Jose Luis; Wang, Lei

2015-01-01

Data sharing and mediation across disparate neuroimaging repositories requires extensive effort to ensure that the different domains of data types are referred to by commonly agreed upon terms. Within the SchizConnect project, which enables querying across decentralized databases of neuroimaging, clinical, and cognitive data from various studies of schizophrenia, we developed a model for each data domain, identified common usable terms that could be agreed upon across the repositories, and linked them to standard ontological terms where possible. We had the goal of facilitating both the current user experience in querying and future automated computations and reasoning regarding the data. We found that existing terminologies are incomplete for these purposes, even with the history of neuroimaging data sharing in the field; and we provide a model for efforts focused on querying multiple clinical neuroimaging repositories. PMID:26688838

Catlas: An magnetic resonance imaging-based three-dimensional cortical atlas and tissue probability maps for the domestic cat (Felis catus).

PubMed

Stolzberg, Daniel; Wong, Carmen; Butler, Blake E; Lomber, Stephen G

2017-10-15

Brain atlases play an important role in effectively communicating results from neuroimaging studies in a standardized coordinate system. Furthermore, brain atlases extend analysis of functional magnetic resonance imaging (MRI) data by delineating regions of interest over which to evaluate the extent of functional activation as well as measures of inter-regional connectivity. Here, we introduce a three-dimensional atlas of the cat cerebral cortex based on established cytoarchitectonic and electrophysiological findings. In total, 71 cerebral areas were mapped onto the gray matter (GM) of an averaged T1-weighted structural MRI acquired at 7 T from eight adult domestic cats. In addition, a nonlinear registration procedure was used to generate a common template brain as well as GM, white matter, and cerebral spinal fluid tissue probability maps to facilitate tissue segmentation as part of the standard preprocessing pipeline for MRI data analysis. The atlas and associated files can also be used for planning stereotaxic surgery and for didactic purposes. © 2017 Wiley Periodicals, Inc.

'Where' depends on 'what': a differential functional anatomy for position discrimination in one- versus two-dimensions.

PubMed

Fink, G R; Marshall, J C; Weiss, P H; Shah, N J; Toni, I; Halligan, P W; Zilles, K

2000-01-01

Line bisection is widely used as a clinical test of spatial cognition in patients with left visuospatial neglect after right hemisphere lesion. Surprisingly, many neglect patients who show severe impairment on marking the center of horizontal lines can accurately mark the center of squares. That these patients with left neglect are also typically poor at judging whether lines are correctly prebisected implies that the deficit can be perceptual rather than motoric. These findings suggest a differential neural basis for one- and two-dimensional visual position discrimination that we investigated with functional neuroimaging (fMRI). Normal subjects judged whether, in premarked lines or squares, the mark was placed centrally. Line center judgements differentially activated right parietal cortex, while square center judgements differentially activated the lingual gyrus bilaterally. These distinct neural bases for one- and two-dimensional visuospatial judgements help explain the observed clinical dissociations by showing that as a stimulus becomes a better, more 'object-like' gestalt, the ventral visuoperceptive route assumes more responsibility for assessing position within the object.

Experimental Observation of Two-Dimensional Anderson Localization with the Atomic Kicked Rotor.

PubMed

Manai, Isam; Clément, Jean-François; Chicireanu, Radu; Hainaut, Clément; Garreau, Jean Claude; Szriftgiser, Pascal; Delande, Dominique

2015-12-11

Dimension 2 is expected to be the lower critical dimension for Anderson localization in a time-reversal-invariant disordered quantum system. Using an atomic quasiperiodic kicked rotor-equivalent to a two-dimensional Anderson-like model-we experimentally study Anderson localization in dimension 2 and we observe localized wave function dynamics. We also show that the localization length depends exponentially on the disorder strength and anisotropy and is in quantitative agreement with the predictions of the self-consistent theory for the 2D Anderson localization.

Neuroimaging and Anxiety: the Neural Substrates of Pathological and Non-pathological Anxiety.

PubMed

Taylor, James M; Whalen, Paul J

2015-06-01

Advances in the use of noninvasive neuroimaging to study the neural correlates of pathological and non-pathological anxiety have shone new light on the underlying neural bases for both the development and manifestation of anxiety. This review summarizes the most commonly observed neural substrates of the phenotype of anxiety. We focus on the neuroimaging paradigms that have shown promise in exposing this relevant brain circuitry. In this way, we offer a broad overview of how anxiety is studied in the neuroimaging laboratory and the key findings that offer promise for future research and a clearer understanding of anxiety.

Quantitative magnetic resonance imaging in traumatic brain injury.

PubMed

Bigler, E D

2001-04-01

Quantitative neuroimaging has now become a well-established method for analyzing magnetic resonance imaging in traumatic brain injury (TBI). A general review of studies that have examined quantitative changes following TBI is presented. The consensus of quantitative neuroimaging studies is that most brain structures demonstrate changes in volume or surface area after injury. The patterns of atrophy are consistent with the generalized nature of brain injury and diffuse axonal injury. Various clinical caveats are provided including how quantitative neuroimaging findings can be used clinically and in predicting rehabilitation outcome. The future of quantitative neuroimaging also is discussed.

Neural Correlates of Visual Perceptual Expertise: Evidence from Cognitive Neuroscience Using Functional Neuroimaging

ERIC Educational Resources Information Center

Gegenfurtner, Andreas; Kok, Ellen M.; van Geel, Koos; de Bruin, Anique B. H.; Sorger, Bettina

2017-01-01

Functional neuroimaging is a useful approach to study the neural correlates of visual perceptual expertise. The purpose of this paper is to review the functional-neuroimaging methods that have been implemented in previous research in this context. First, we will discuss research questions typically addressed in visual expertise research. Second,…

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond

PubMed Central

Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco

2017-01-01

The existence of so-called ‘basic emotions’ and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment. PMID:28883803

Local elasticity map and plasticity in a model Lennard-Jones glass.

PubMed

Tsamados, Michel; Tanguy, Anne; Goldenberg, Chay; Barrat, Jean-Louis

2009-08-01

In this work we calculate the local elastic moduli in a weakly polydispersed two-dimensional Lennard-Jones glass undergoing a quasistatic shear deformation at zero temperature. The numerical method uses coarse-grained microscopic expressions for the strain, displacement, and stress fields. This method allows us to calculate the local elasticity tensor and to quantify the deviation from linear elasticity (local Hooke's law) at different coarse-graining scales. From the results a clear picture emerges of an amorphous material with strongly spatially heterogeneous elastic moduli that simultaneously satisfies Hooke's law at scales larger than a characteristic length scale of the order of five interatomic distances. At this scale, the glass appears as a composite material composed of a rigid scaffolding and of soft zones. Only recently calculated in nonhomogeneous materials, the local elastic structure plays a crucial role in the elastoplastic response of the amorphous material. For a small macroscopic shear strain, the structures associated with the nonaffine displacement field appear directly related to the spatial structure of the elastic moduli. Moreover, for a larger macroscopic shear strain we show that zones of low shear modulus concentrate most of the strain in the form of plastic rearrangements. The spatiotemporal evolution of this local elasticity map and its connection with long term dynamical heterogeneity as well as with the plasticity in the material is quantified. The possibility to use this local parameter as a predictor of subsequent local plastic activity is also discussed.

Preserved local but disrupted contextual figure-ground influences in an individual with abnormal function of intermediate visual areas

PubMed Central

Brooks, Joseph L.; Gilaie-Dotan, Sharon; Rees, Geraint; Bentin, Shlomo; Driver, Jon

2012-01-01

Visual perception depends not only on local stimulus features but also on their relationship to the surrounding stimulus context, as evident in both local and contextual influences on figure-ground segmentation. Intermediate visual areas may play a role in such contextual influences, as we tested here by examining LG, a rare case of developmental visual agnosia. LG has no evident abnormality of brain structure and functional neuroimaging showed relatively normal V1 function, but his intermediate visual areas (V2/V3) function abnormally. We found that contextual influences on figure-ground organization were selectively disrupted in LG, while local sources of figure-ground influences were preserved. Effects of object knowledge and familiarity on figure-ground organization were also significantly diminished. Our results suggest that the mechanisms mediating contextual and familiarity influences on figure-ground organization are dissociable from those mediating local influences on figure-ground assignment. The disruption of contextual processing in intermediate visual areas may play a role in the substantial object recognition difficulties experienced by LG. PMID:22947116

Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers

PubMed Central

Crosson, Bruce; Ford, Anastasia; McGregor, Keith M.; Meinzer, Marcus; Cheshkov, Sergey; Li, Xiufeng; Walker-Batson, Delaina; Briggs, Richard W.

2010-01-01

Functional neuroimaging and related neuroimaging techniques are becoming important tools for rehabilitation research. Functional neuroimaging techniques can be used to determine the effects of brain injury or disease on brain systems related to cognition and behavior and to determine how rehabilitation changes brain systems. These techniques include: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), and transcranial magnetic stimulation (TMS). Related diffusion weighted magnetic resonance imaging techniques (DWI), including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), can quantify white matter integrity. With the proliferation of these imaging techniques in rehabilitation research, it is critical that rehabilitation researchers, as well as consumers of rehabilitation research, become familiar with neuroimaging techniques, what they can offer, and their strengths and weaknesses The purpose to this review is to provide such an introduction to these neuroimaging techniques. PMID:20593321

Structural neuroimaging in neuropsychology: History and contemporary applications.

PubMed

Bigler, Erin D

2017-11-01

Neuropsychology's origins began long before there were any in vivo methods to image the brain. That changed with the advent of computed tomography in the 1970s and magnetic resonance imaging in the early 1980s. Now computed tomography and magnetic resonance imaging are routinely a part of neuropsychological investigations with an increasing number of sophisticated methods for image analysis. This review examines the history of neuroimaging utilization in neuropsychological investigations, highlighting the basic methods that go into image quantification and the various metrics that can be derived. Neuroimaging methods and limitations for identify what constitutes a lesion are discussed. Likewise, the influence of various demographic and developmental factors that influence quantification of brain structure are reviewed. Neuroimaging is an integral part of 21st Century neuropsychology. The importance of neuroimaging to advancing neuropsychology is emphasized. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Neuroimaging of epilepsy

PubMed Central

Cendes, Fernando; Theodore, William H.; Brinkmann, Benjamin H.; Sulc, Vlastimil; Cascino, Gregory D.

2017-01-01

Imaging is pivotal in the evaluation and management of patients with seizure disorders. Elegant structural neuroimaging with magnetic resonance imaging (MRI) may assist in determining the etiology of focal epilepsy and demonstrating the anatomical changes associated with seizure activity. The high diagnostic yield of MRI to identify the common pathological findings in individuals with focal seizures including mesial temporal sclerosis, vascular anomalies, low-grade glial neoplasms and malformations of cortical development has been demonstrated. Positron emission tomography (PET) is the most commonly performed interictal functional neuroimaging technique that may reveal a focal hypometabolic region concordant with seizure onset. Single photon emission computed tomography (SPECT) studies may assist performance of ictal neuroimaging in patients with pharmacoresistant focal epilepsy being considered for neurosurgical treatment. This chapter highlights neuroimaging developments and innovations, and provides a comprehensive overview of the imaging strategies used to improve the care and management of people with epilepsy. PMID:27430454

Dynamic adaptive chemistry with operator splitting schemes for reactive flow simulations

NASA Astrophysics Data System (ADS)

Ren, Zhuyin; Xu, Chao; Lu, Tianfeng; Singer, Michael A.

2014-04-01

A numerical technique that uses dynamic adaptive chemistry (DAC) with operator splitting schemes to solve the equations governing reactive flows is developed and demonstrated. Strang-based splitting schemes are used to separate the governing equations into transport fractional substeps and chemical reaction fractional substeps. The DAC method expedites the numerical integration of reaction fractional substeps by using locally valid skeletal mechanisms that are obtained using the directed relation graph (DRG) reduction method to eliminate unimportant species and reactions from the full mechanism. Second-order temporal accuracy of the Strang-based splitting schemes with DAC is demonstrated on one-dimensional, unsteady, freely-propagating, premixed methane/air laminar flames with detailed chemical kinetics and realistic transport. The use of DAC dramatically reduces the CPU time required to perform the simulation, and there is minimal impact on solution accuracy. It is shown that with DAC the starting species and resulting skeletal mechanisms strongly depend on the local composition in the flames. In addition, the number of retained species may be significant only near the flame front region where chemical reactions are significant. For the one-dimensional methane/air flame considered, speed-up factors of three and five are achieved over the entire simulation for GRI-Mech 3.0 and USC-Mech II, respectively. Greater speed-up factors are expected for larger chemical kinetics mechanisms.

Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity.

PubMed

Ewert, Siobhan; Plettig, Philip; Li, Ningfei; Chakravarty, M Mallar; Collins, D Louis; Herrington, Todd M; Kühn, Andrea A; Horn, Andreas

2018-04-15

Three-dimensional atlases of subcortical brain structures are valuable tools to reference anatomy in neuroscience and neurology. For instance, they can be used to study the position and shape of the three most common deep brain stimulation (DBS) targets, the subthalamic nucleus (STN), internal part of the pallidum (GPi) and ventral intermediate nucleus of the thalamus (VIM) in spatial relationship to DBS electrodes. Here, we present a composite atlas based on manual segmentations of a multimodal high resolution brain template, histology and structural connectivity. In a first step, four key structures were defined on the template itself using a combination of multispectral image analysis and manual segmentation. Second, these structures were used as anchor points to coregister a detailed histological atlas into standard space. Results show that this approach significantly improved coregistration accuracy over previously published methods. Finally, a sub-segmentation of STN and GPi into functional zones was achieved based on structural connectivity. The result is a composite atlas that defines key nuclei on the template itself, fills the gaps between them using histology and further subdivides them using structural connectivity. We show that the atlas can be used to segment DBS targets in single subjects, yielding more accurate results compared to priorly published atlases. The atlas will be made publicly available and constitutes a resource to study DBS electrode localizations in combination with modern neuroimaging methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Neuronal Correlates of Individual Differences in the Big Five Personality Traits: Evidences from Cortical Morphology and Functional Homogeneity.

PubMed

Li, Ting; Yan, Xu; Li, Yuan; Wang, Junjie; Li, Qiang; Li, Hong; Li, Junfeng

2017-01-01

There have been many neuroimaging studies of human personality traits, and it have already provided glimpse into the neurobiology of complex traits. And most of previous studies adopt voxel-based morphology (VBM) analysis to explore the brain-personality mechanism from two levels (vertex and regional based), the findings are mixed with great inconsistencies and the brain-personality relations are far from a full understanding. Here, we used a new method of surface-based morphology (SBM) analysis, which provides better alignment of cortical landmarks to generate about the associations between cortical morphology and the personality traits across 120 healthy individuals at both vertex and regional levels. While to further reveal local functional correlates of the morphology-personality relationships, we related surface-based functional homogeneity measures to the regions identified in the regional-based SBM correlation. Vertex-wise analysis revealed that people with high agreeableness exhibited larger areas in the left superior temporal gyrus. Based on regional parcellation we found that extroversion was negatively related with the volume of the left lateral occipito-temporal gyrus and agreeableness was negatively associated with the sulcus depth of the left superior parietal lobule. Moreover, increased regional homogeneity in the left lateral occipito-temporal gyrus is related to the scores of extroversion, and increased regional homogeneity in the left superior parietal lobule is related to the scores of agreeableness. These findings provide supporting evidence of a link between personality and brain structural mysteries with a method of SBM, and further suggest that local functional homogeneity of personality traits has neurobiological relevance that is likely based on anatomical substrates.

Overview of Three-Dimensional Atomic-Resolution Holography and Imaging Techniques: Recent Advances in Local-Structure Science

NASA Astrophysics Data System (ADS)

Daimon, Hiroshi

2018-06-01

Local three-dimensional (3D) atomic arrangements without periodicity have not been able to be studied until recently. Recently, several holographies and related techniques have been developed to reveal the 3D atomic arrangement around specific atoms with no translational symmetry. This review gives an overview of these new local 3D atomic imaging techniques.

Development of a Localized Low-Dimensional Approach to Turbulence Simulation

NASA Astrophysics Data System (ADS)

Juttijudata, Vejapong; Rempfer, Dietmar; Lumley, John

2000-11-01

Our previous study has shown that the localized low-dimensional model derived from a projection of Navier-Stokes equations onto a set of one-dimensional scalar POD modes, with boundary conditions at y^+=40, can predict wall turbulence accurately for short times while failing to give a stable long-term solution. The structures obtained from the model and later studies suggest our boundary conditions from DNS are not consistent with the solution from the localized model resulting in an injection of energy at the top boundary. In the current study, we develop low-dimensional models using one-dimensional scalar POD modes derived from an explicitly filtered DNS. This model problem has exact no-slip boundary conditions at both walls while the locality of the wall layer is still retained. Furthermore, the interaction between wall and core region is attenuated via an explicit filter which allows us to investigate the quality of the model without requiring complicated modeling of the top boundary conditions. The full-channel model gives reasonable wall turbulence structures as well as long-term turbulent statistics while still having difficulty with the prediction of the mean velocity profile farther from the wall. We also consider a localized model with modified boundary conditions in the last part of our study.

Linking neuroimaging signals to behavioral responses in single cases: Challenges and opportunities.

PubMed

Sander, Tilmann H; Zhou, Bin

2016-09-01

Despite rapid progress both in psychology and neuroimaging, there is still a convergence gap between the results of these two scientific disciplines. This is particularly unsatisfactory, as the variability between single subjects needs to be understood both for basic science and for patient diagnostics in, for example, the field of age-related cognitive changes. Active and passive behaviors are the observables in psychology and can be studied alone or in combination with the neuroimaging approach. Various physical signatures of brain activity are the observables in neuroimaging and can be measured concurrent with behaviors. Despite the intrinsic relationship between behaviors and the corresponding neuroimaging patterns and the obvious advantages in integrating behavioral and neuroimaging measurements, the results of combined studies can be difficult to interpret. Experiments are often optimized to yield either a novel behavioral or a novel physiological result, but rarely designed for a better match between the two. Since integrating the results is probably a key to future progress in clinical psychology and basic research, an attempt is made here to identify some difficulties and to provide some ideas for future research. © 2016 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

The Shepherd's Crook Sign: A New Neuroimaging Pareidolia in Joubert Syndrome.

PubMed

Manley, Andrew T; Maertens, Paul M

2015-01-01

By pareidolically recognizing specific patterns indicative of particular diseases, neuroimagers reinforce their mnemonic strategies and improve their neuroimaging diagnostic skills. Joubert Syndrome (JS) is an autosomal recessive disorder characterized clinically by mental retardation, episodes of abnormal deep and rapid breathing, abnormal eye movements, and ataxia. Many neuroimaging signs characteristic of JS have been reported. In retrospective case study, two consanguineous neonates diagnosed with JS were evaluated with brain magnetic resonance imaging (MRI), computed tomography (CT), and neurosonography. Both cranial ultrasound and MRI of the brain showed the characteristic molar tooth sign. There was a shepherd's crook in the sagittal views of the posterior fossa where the shaft of the crook is made by the brainstem and the pons. The arc of the crook is made by the abnormal superior cerebellar peduncle and cerebellar hemisphere. By ultrasound, the shepherd's crook sign was seen through the posterior fontanelle only. CT imaging also showed the shepherd's crook sign. Neuroimaging diagnosis of JS, which already involves the pareidolical recognition of specific patterns indicative of the disease, can be improved by recognition of the shepherd's crook sign on MRI, CT, and cranial ultrasound. Copyright © 2014 by the American Society of Neuroimaging.

Annual Research Review: Understudied populations within the autism spectrum – current trends and future directions in neuroimaging research

PubMed Central

Jack, Allison; Pelphrey, Kevin

2017-01-01

Background Autism spectrum disorders (ASDs) are a heterogeneous group of neurodevelopmental conditions that vary in both etiology and phenotypic expression. Expressions of ASD characterized by a more severe phenotype, including autism with intellectual disability (ASD+ID), autism with a history of developmental regression (ASD+R), and minimally verbal autism (ASD+MV) are understudied generally, and especially in the domain of neuroimaging. However, neuroimaging methods are a potentially powerful tool for understanding the etiology of these ASD subtypes. Scope and Methodology This review evaluates existing neuroimaging research on ASD+MV, ASD+ID, and ASD+R, identified by a search of the literature using the PubMed database, and discusses methodological, theoretical, and practical considerations for future research involving neuroimaging assessment of these populations. Findings There is a paucity of neuroimaging research on ASD+ID, ASD+MV, and ASD+R, and what findings do exist are often contradictory, or so sparse as to be ungeneralizable. We suggest that while greater sample sizes and more studies are necessary, more important would be a paradigm shift toward multimodal (e.g., imaging genetics) approaches that allow for the characterization of heterogeneity within etiologically diverse samples. PMID:28102566

[Functional neuroimaging in the diagnosis of patients with Parkinsonism: Update and recommendations for clinical use].

PubMed

Arbizu, J; Luquin, M R; Abella, J; de la Fuente-Fernández, R; Fernandez-Torrón, R; García-Solís, D; Garrastachu, P; Jiménez-Hoyuela, J M; Llaneza, M; Lomeña, F; Lorenzo-Bosquet, C; Martí, M J; Martinez-Castrillo, J C; Mir, P; Mitjavila, M; Ruiz-Martínez, J; Vela, L

2014-01-01

Functional Neuroimaging has been traditionally used in research for patients with different Parkinsonian syndromes. However, the emergence of commercial radiotracers together with the availability of single photon emission computed tomography (SPECT) and, more recently, positron emission tomography (PET) have made them available for clinical practice. Particularly, the development of clinical evidence achieved by functional neuroimaging techniques over the past two decades have motivated a progressive inclusion of several biomarkers in the clinical diagnostic criteria for neurodegenerative diseases that occur with Parkinsonism. However, the wide range of radiotracers designed to assess the involvement of different pathways in the neurodegenerative process underlying Parkinsonian syndromes (dopaminergic nigrostriatal pathway integrity, basal ganglia and cortical neuronal activity, myocardial sympathetic innervation), and the different neuroimaging techniques currently available (scintigraphy, SPECT and PET), have generated some controversy concerning the best neuroimaging test that should be indicated for the differential diagnosis of Parkinsonism. In this article, a panel of nuclear medicine and neurology experts has evaluated the functional neuroimaging techniques emphazising practical considerations related to the diagnosis of patients with uncertain origin parkinsonism and the assessment Parkinson's disease progression. Copyright © 2014 Elsevier España, S.L. and SEMNIM. All rights reserved.

Computerized lung cancer malignancy level analysis using 3D texture features

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang; Zhang, Jianying; Qian, Wei

2016-03-01

Based on the likelihood of malignancy, the nodules are classified into five different levels in Lung Image Database Consortium (LIDC) database. In this study, we tested the possibility of using threedimensional (3D) texture features to identify the malignancy level of each nodule. Five groups of features were implemented and tested on 172 nodules with confident malignancy levels from four radiologists. These five feature groups are: grey level co-occurrence matrix (GLCM) features, local binary pattern (LBP) features, scale-invariant feature transform (SIFT) features, steerable features, and wavelet features. Because of the high dimensionality of our proposed features, multidimensional scaling (MDS) was used for dimension reduction. RUSBoost was applied for our extracted features for classification, due to its advantages in handling imbalanced dataset. Each group of features and the final combined features were used to classify nodules highly suspicious for cancer (level 5) and moderately suspicious (level 4). The results showed that the area under the curve (AUC) and accuracy are 0.7659 and 0.8365 when using the finalized features. These features were also tested on differentiating benign and malignant cases, and the reported AUC and accuracy were 0.8901 and 0.9353.

Warped AdS 6 × S 2 in Type IIB supergravity III. Global solutions with seven-branes

NASA Astrophysics Data System (ADS)

D'Hoker, Eric; Gutperle, Michael; Uhlemann, Christoph F.

2017-11-01

We extend our previous construction of global solutions to Type IIB super-gravity that are invariant under the superalgebra F(4) and are realized on a spacetime of the form AdS 6 × S 2 warped over a Riemann surface Σ by allowing the supergravity fields to have non-trivial SL(2, ℝ) monodromy at isolated punctures on Σ. We obtain explicit solutions for the case where Σ is a disc, and the monodromy generators are parabolic elements of SL(2, ℝ) physically corresponding to the monodromy allowed in Type IIB string theory. On the boundary of Σ the solutions exhibit singularities at isolated points which correspond to semi-infinite five-branes, as is familiar from the global solutions without monodromy. In the interior of Σ, the solutions are everywhere regular, except at the punctures where SL(2, ℝ) monodromy resides and which physically correspond to the locations of [ p, q] seven-branes. The solutions have a compelling physical interpretation corresponding to fully localized five-brane intersections with additional seven-branes, and provide candidate holographic duals to the five-dimensional superconformal field theories realized on such intersections.

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing.

PubMed

Shatil, Anwar S; Younas, Sohail; Pourreza, Hossein; Figley, Chase R

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

Heads in the Cloud: A Primer on Neuroimaging Applications of High Performance Computing

PubMed Central

Shatil, Anwar S.; Younas, Sohail; Pourreza, Hossein; Figley, Chase R.

2015-01-01

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications. PMID:27279746

Pure spinal multiple sclerosis: A possible novel entity within the multiple sclerosis disease spectrum.

PubMed

Schee, Jie Ping; Viswanathan, Shanthi

2018-05-01

We identified five female patients retrospectively with relapsing short-segment partial myelitis whose clinical and paraclinical features were suggestive of cord involvement of multiple sclerosis (MS)-type albeit not rigidly fulfilling the 2017 McDonald criteria. Notably, these patients had not developed any typical MS-like brain lesions despite repeated neuroimaging assessments over years. Comprehensive work-up for differential diagnoses of MS and other causes of transverse myelitis particularly neuromyelitis optica spectrum disorders had been consistently negative on longitudinal follow-up. Thus, we postulate a possible entity of pure spinal MS which may represent a novel forme fruste within the MS disease spectrum.

Intracranial complications of Serratia marcescens infection in neonates.

PubMed

Madide, Ayanda; Smith, Johan

2016-03-15

Even though Serratia marcescens is not one of the most common causes of infection in neonates, it is associated with grave morbidity and mortality. We describe the evolution of brain parenchymal affectation observed in association with S. marcescens infection in neonates. This retrospective case series details brain ultrasound findings of five neonates with hospital-acquired S. marcescens infection. Neonatal S. marcescens infection with or without associated meningitis can be complicated by brain parenchymal affectation, leading to cerebral abscess formation. It is recommended that all neonates with this infection should undergo neuro-imaging more than once before discharge from hospital; this can be achieved using bedside ultrasonography.

A Neuroimaging Web Services Interface as a Cyber Physical System for Medical Imaging and Data Management in Brain Research: Design Study

PubMed Central

2018-01-01

Background Structural and functional brain images are essential imaging modalities for medical experts to study brain anatomy. These images are typically visually inspected by experts. To analyze images without any bias, they must be first converted to numeric values. Many software packages are available to process the images, but they are complex and difficult to use. The software packages are also hardware intensive. The results obtained after processing vary depending on the native operating system used and its associated software libraries; data processed in one system cannot typically be combined with data on another system. Objective The aim of this study was to fulfill the neuroimaging community’s need for a common platform to store, process, explore, and visualize their neuroimaging data and results using Neuroimaging Web Services Interface: a series of processing pipelines designed as a cyber physical system for neuroimaging and clinical data in brain research. Methods Neuroimaging Web Services Interface accepts magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and functional magnetic resonance imaging. These images are processed using existing and custom software packages. The output is then stored as image files, tabulated files, and MySQL tables. The system, made up of a series of interconnected servers, is password-protected and is securely accessible through a Web interface and allows (1) visualization of results and (2) downloading of tabulated data. Results All results were obtained using our processing servers in order to maintain data validity and consistency. The design is responsive and scalable. The processing pipeline started from a FreeSurfer reconstruction of Structural magnetic resonance imaging images. The FreeSurfer and regional standardized uptake value ratio calculations were validated using Alzheimer’s Disease Neuroimaging Initiative input images, and the results were posted at the Laboratory of Neuro Imaging data archive. Notable leading researchers in the field of Alzheimer’s Disease and epilepsy have used the interface to access and process the data and visualize the results. Tabulated results with unique visualization mechanisms help guide more informed diagnosis and expert rating, providing a truly unique multimodal imaging platform that combines magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and resting state functional magnetic resonance imaging. A quality control component was reinforced through expert visual rating involving at least 2 experts. Conclusions To our knowledge, there is no validated Web-based system offering all the services that Neuroimaging Web Services Interface offers. The intent of Neuroimaging Web Services Interface is to create a tool for clinicians and researchers with keen interest on multimodal neuroimaging. More importantly, Neuroimaging Web Services Interface significantly augments the Alzheimer’s Disease Neuroimaging Initiative data, especially since our data contain a large cohort of Hispanic normal controls and Alzheimer’s Disease patients. The obtained results could be scrutinized visually or through the tabulated forms, informing researchers on subtle changes that characterize the different stages of the disease. PMID:29699962

Online 3D Ear Recognition by Combining Global and Local Features.

PubMed

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.

Online 3D Ear Recognition by Combining Global and Local Features

PubMed Central

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%. PMID:27935955

Successful correction of tibial bone deformity through multiple surgical procedures, liquid nitrogen-pretreated bone tumor autograft, three-dimensional external fixation, and internal fixation in a patient with primary osteosarcoma: a case report.

PubMed

Takeuchi, Akihiko; Yamamoto, Norio; Shirai, Toshiharu; Nishida, Hideji; Hayashi, Katsuhiro; Watanabe, Koji; Miwa, Shinji; Tsuchiya, Hiroyuki

2015-12-07

In a previous report, we described a method of reconstruction using tumor-bearing autograft treated by liquid nitrogen for malignant bone tumor. Here we present the first case of bone deformity correction following a tumor-bearing frozen autograft via three-dimensional computerized reconstruction after multiple surgeries. A 16-year-old female student presented with pain in the left lower leg and was diagnosed with a low-grade central tibial osteosarcoma. Surgical bone reconstruction was performed using a tumor-bearing frozen autograft. Bone union was achieved at 7 months after the first surgical procedure. However, local tumor recurrence and lung metastases occurred 2 years later, at which time a second surgical procedure was performed. Five years later, the patient developed a 19° varus deformity and underwent a third surgical procedure, during which an osteotomy was performed using the Taylor Spatial Frame three-dimensional external fixation technique. A fourth corrective surgical procedure was performed in which internal fixation was achieved with a locking plate. Two years later, and 10 years after the initial diagnosis of tibial osteosarcoma, the bone deformity was completely corrected, and the patient's limb function was good. We present the first report in which a bone deformity due to a primary osteosarcoma was corrected using a tumor-bearing frozen autograft, followed by multiple corrective surgical procedures that included osteotomy, three-dimensional external fixation, and internal fixation.

A Non Local Electron Heat Transport Model for Multi-Dimensional Fluid Codes

NASA Astrophysics Data System (ADS)

Schurtz, Guy

2000-10-01

Apparent inhibition of thermal heat flow is one of the most ancient problems in computational Inertial Fusion and flux-limited Spitzer-Harm conduction has been a mainstay in multi-dimensional hydrodynamic codes for more than 25 years. Theoretical investigation of the problem indicates that heat transport in laser produced plasmas has to be considered as a non local process. Various authors contributed to the non local theory and proposed convolution formulas designed for practical implementation in one-dimensional fluid codes. Though the theory, confirmed by kinetic calculations, actually predicts a reduced heat flux, it fails to explain the very small limiters required in two-dimensional simulations. Fokker-Planck simulations by Epperlein, Rickard and Bell [PRL 61, 2453 (1988)] demonstrated that non local effects could lead to a strong reduction of heat flow in two dimensions, even in situations where a one-dimensional analysis suggests that the heat flow is nearly classical. We developed at CEA/DAM a non local electron heat transport model suitable for implementation in our two-dimensional radiation hydrodynamic code FCI2. This model may be envisionned as the first step of an iterative solution of the Fokker-Planck equations; it takes the mathematical form of multigroup diffusion equations, the solution of which yields both the heat flux and the departure of the electron distribution function to the Maxwellian. Although direct implementation of the model is straightforward, formal solutions of it can be expressed in convolution form, exhibiting a three-dimensional tensor propagator. Reduction to one dimension retrieves the original formula of Luciani, Mora and Virmont [PRL 51, 1664 (1983)]. Intense magnetic fields may be generated by thermal effects in laser targets; these fields, as well as non local effects, will inhibit electron conduction. We present simulations where both effects are taken into account and shortly discuss the coupling strategy between them.

A face-selective ventral occipito-temporal map of the human brain with intracerebral potentials

PubMed Central

Jonas, Jacques; Jacques, Corentin; Liu-Shuang, Joan; Brissart, Hélène; Colnat-Coulbois, Sophie; Maillard, Louis; Rossion, Bruno

2016-01-01

Human neuroimaging studies have identified a network of distinct face-selective regions in the ventral occipito-temporal cortex (VOTC), with a right hemispheric dominance. To date, there is no evidence for this hemispheric and regional specialization with direct measures of brain activity. To address this gap in knowledge, we recorded local neurophysiological activity from 1,678 contact electrodes implanted in the VOTC of a large group of epileptic patients (n = 28). They were presented with natural images of objects at a rapid fixed rate (six images per second: 6 Hz), with faces interleaved as every fifth stimulus (i.e., 1.2 Hz). High signal-to-noise ratio face-selective responses were objectively (i.e., exactly at the face stimulation frequency) identified and quantified throughout the whole VOTC. Face-selective responses were widely distributed across the whole VOTC, but also spatially clustered in specific regions. Among these regions, the lateral section of the right middle fusiform gyrus showed the largest face-selective response by far, offering, to our knowledge, the first supporting evidence of two decades of neuroimaging observations with direct neural measures. In addition, three distinct regions with a high proportion of face-selective responses were disclosed in the right ventral anterior temporal lobe, a region that is undersampled in neuroimaging because of magnetic susceptibility artifacts. A high proportion of contacts responding only to faces (i.e., “face-exclusive” responses) were found in these regions, suggesting that they contain populations of neurons involved in dedicated face-processing functions. Overall, these observations provide a comprehensive mapping of visual category selectivity in the whole human VOTC with direct neural measures. PMID:27354526

How Configural Is the Configural Superiority Effect? A Neuroimaging Investigation of Emergent Features in Visual Cortex

PubMed Central

Fox, Olivia M.; Harel, Assaf; Bennett, Kevin B.

2017-01-01

The perception of a visual stimulus is dependent not only upon local features, but also on the arrangement of those features. When stimulus features are perceptually well organized (e.g., symmetric or parallel), a global configuration with a high degree of salience emerges from the interactions between these features, often referred to as emergent features. Emergent features can be demonstrated in the Configural Superiority Effect (CSE): presenting a stimulus within an organized context relative to its presentation in a disarranged one results in better performance. Prior neuroimaging work on the perception of emergent features regards the CSE as an “all or none” phenomenon, focusing on the contrast between configural and non-configural stimuli. However, it is still not clear how emergent features are processed between these two endpoints. The current study examined the extent to which behavioral and neuroimaging markers of emergent features are responsive to the degree of configurality in visual displays. Subjects were tasked with reporting the anomalous quadrant in a visual search task while being scanned. Degree of configurality was manipulated by incrementally varying the rotational angle of low-level features within the stimulus arrays. Behaviorally, we observed faster response times with increasing levels of configurality. These behavioral changes were accompanied by increases in response magnitude across multiple visual areas in occipito-temporal cortex, primarily early visual cortex and object-selective cortex. Our findings suggest that the neural correlates of emergent features can be observed even in response to stimuli that are not fully configural, and demonstrate that configural information is already present at early stages of the visual hierarchy. PMID:28167924

Dimensional stabilization of southern pines

Treesearch

E.T. Choong; H.M. Barnes

1969-01-01

The effectiveness of five dimensional stabilizing agents and three impregnation methods on southern pine was determined. Four southern pine species were studies in order to determine the effect of wood factors. The best dimensional stability was obtained when the wood was preswollen and the chemical was impregnated by a diffusion process. In general, polyethylene...

An Overview of Software for Conducting Dimensionality Assessment in Multidimensional Models

ERIC Educational Resources Information Center

Svetina, Dubravka; Levy, Roy

2012-01-01

An overview of popular software packages for conducting dimensionality assessment in multidimensional models is presented. Specifically, five popular software packages are described in terms of their capabilities to conduct dimensionality assessment with respect to the nature of analysis (exploratory or confirmatory), types of data (dichotomous,…

[18F]-Fluoro-Deoxy-Glucose Positron Emission Tomography Scan Should Be Obtained Early in Cases of Autoimmune Encephalitis

PubMed Central

Sarwal, A.; Hantus, S.

2016-01-01

Introduction. Autoimmune encephalitis (AE) is a clinically challenging diagnosis with nonspecific neurological symptoms. Prompt diagnosis is important and often relies on neuroimaging. We present a case series of AE highlighting the importance of an early [18F]-fluoro-deoxy-glucose positron emission tomography (FDG-PET) scan. Methods. Retrospective review of seven consecutive cases of autoimmune encephalitis. Results. All patients had both magnetic resonance imaging (MRI) and FDG-PET scans. Initial clinical presentations included altered mental status and/or new onset seizures. Six cases had serum voltage-gated potassium channel (VGKC) antibody and one had serum N-methyl-D-aspartate (NMDA) antibody. MRI of brain showed mesial temporal lobe hyperintensity in five cases of VGKC. The other two patients with VGKC or NMDA AE had restiform body hyperintensity on MRI brain or a normal MRI, respectively. Mesial temporal lobe hypermetabolism was noted in three cases on FDG-PET, despite initial unremarkable MRI. Malignancy workup was negative in all patients. Conclusion. A high index of suspicion for AE should be maintained in patients presenting with cognitive symptoms, seizures, and limbic changes on neuroimaging. In cases with normal initial brain MRI, FDG-PET can be positive. Additionally, extralimbic hyperintensity on MRI may also be observed. PMID:27559482

Neural correlates of somatoform disorders from a meta-analytic perspective on neuroimaging studies.

PubMed

Boeckle, Markus; Schrimpf, Marlene; Liegl, Gregor; Pieh, Christoph

2016-01-01

Somatoform disorders (SD) are common medical disorders with prevalence rates between 3.5% and 18.4%, depending on country and medical setting. SD as outlined in the ICD-10 exhibits various biological, social, and psychological pathogenic factors. Little is known about the neural correlates of SD. The aims of this meta-analysis are to identify neuronal areas that are involved in SD and consistently differ between patients and healthy controls. We conducted a systematic literature research on neuroimaging studies of SD. Ten out of 686 studies fulfilled the inclusion criteria and were analyzed using activation likelihood estimation. Five neuronal areas differ between patients with SD and healthy controls namely the premotor and supplementary motor cortexes, the middle frontal gyrus, the anterior cingulate cortex, the insula, and the posterior cingulate cortex. These areas seem to have a particular importance for the occurrence of SD. Out of the ten studies two did not contribute to any of the clusters. Our results seem to largely overlap with the circuit network model of somatosensory amplification for SD. It is conceivable that functional disorders, independent of the clinical impression, show similar neurobiological processes. While overlaps do occur it is necessary to understand single functional somatic syndromes and their aetiology for future research, terminology, and treatment guidelines.

Experiment of flow regime map and local condensing heat transfer coefficients inside three dimensional inner microfin tubes

NASA Astrophysics Data System (ADS)

Du, Yang; Xin, Ming Dao

1999-03-01

This paper developed a new type of three dimensional inner microfin tube. The experimental results of the flow patterns for the horizontal condensation inside these tubes are reported in the paper. The flow patterns for the horizontal condensation inside the new made tubes are divided into annular flow, stratified flow and intermittent flow within the test conditions. The experiments of the local heat transfer coefficients for the different flow patterns have been systematically carried out. The experiments of the local heat transfer coefficients changing with the vapor dryness fraction have also been carried out. As compared with the heat transfer coefficients of the two dimensional inner microfin tubes, those of the three dimensional inner microfin tubes increase 47-127% for the annular flow region, 38-183% for the stratified flow and 15-75% for the intermittent flow, respectively. The enhancement factor of the local heat transfer coefficients is from 1.8-6.9 for the vapor dryness fraction from 0.05 to 1.

Neurovascular and neuroimaging effects of the hallucinogenic serotonin receptor agonist psilocin in the rat brain

PubMed Central

Spain, Aisling; Howarth, Clare; Khrapitchev, Alexandre A.; Sharp, Trevor; Sibson, Nicola R.; Martin, Chris

2015-01-01

The development of pharmacological magnetic resonance imaging (phMRI) has presented the opportunity for investigation of the neurophysiological effects of drugs in vivo. Psilocin, a hallucinogen metabolised from psilocybin, was recently reported to evoke brain region-specific, phMRI signal changes in humans. The present study investigated the effects of psilocin in a rat model using phMRI and then probed the relationship between neuronal and haemodynamic responses using a multimodal measurement preparation. Psilocin (2 mg/kg or 0.03 mg/kg i.v.) or vehicle was administered to rats (N = 6/group) during either phMRI scanning or concurrent imaging of cortical blood flow and recording of local field potentials. Compared to vehicle controls psilocin (2 mg/kg) evoked phMRI signal increases in a number of regions including olfactory and limbic areas and elements of the visual system. PhMRI signal decreases were seen in other regions including somatosensory and motor cortices. Investigation of neurovascular coupling revealed that whilst neuronal responses (local field potentials) to sensory stimuli were decreased in amplitude by psilocin administration, concurrently measured haemodynamic responses (cerebral blood flow) were enhanced. The present findings show that psilocin evoked region-specific changes in phMRI signals in the rat, confirming recent human data. However, the results also suggest that the haemodynamic signal changes underlying phMRI responses reflect changes in both neuronal activity and neurovascular coupling. This highlights the importance of understanding the neurovascular effects of pharmacological manipulations for interpreting haemodynamic neuroimaging data. PMID:26192543

Individual differences in brain structure and resting brain function underlie cognitive styles: evidence from the Embedded Figures Test.

PubMed

Hao, Xin; Wang, Kangcheng; Li, Wenfu; Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Qinglin

2013-01-01

Cognitive styles can be characterized as individual differences in the way people perceive, think, solve problems, learn, and relate to others. Field dependence/independence (FDI) is an important and widely studied dimension of cognitive styles. Although functional imaging studies have investigated the brain activation of FDI cognitive styles, the combined structural and functional correlates with individual differences in a large sample have never been investigated. In the present study, we investigated the neural correlates of individual differences in FDI cognitive styles by analyzing the correlations between Embedded Figures Test (EFT) score and structural neuroimaging data [regional gray matter volume (rGMV) was assessed using voxel-based morphometry (VBM)]/functional neuroimaging data [resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF)] throughout the whole brain. Results showed that the increased rGMV in the left inferior parietal lobule (IPL) was associated with the EFT score, which might be the structural basis of effective local processing. Additionally, a significant positive correlation between ALFF and EFT score was found in the fronto-parietal network, including the left inferior parietal lobule (IPL) and the medial prefrontal cortex (mPFC). We speculated that the left IPL might be associated with superior feature identification, and mPFC might be related to cognitive inhibition of global processing bias. These results suggested that the underlying neuroanatomical and functional bases were linked to the individual differences in FDI cognitive styles and emphasized the important contribution of superior local processing ability and cognitive inhibition to field-independent style.

Individual Differences in Brain Structure and Resting Brain Function Underlie Cognitive Styles: Evidence from the Embedded Figures Test

PubMed Central

Hao, Xin; Wang, Kangcheng; Li, Wenfu; Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Qinglin

2013-01-01

Cognitive styles can be characterized as individual differences in the way people perceive, think, solve problems, learn, and relate to others. Field dependence/independence (FDI) is an important and widely studied dimension of cognitive styles. Although functional imaging studies have investigated the brain activation of FDI cognitive styles, the combined structural and functional correlates with individual differences in a large sample have never been investigated. In the present study, we investigated the neural correlates of individual differences in FDI cognitive styles by analyzing the correlations between Embedded Figures Test (EFT) score and structural neuroimaging data [regional gray matter volume (rGMV) was assessed using voxel-based morphometry (VBM)] / functional neuroimaging data [resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF)] throughout the whole brain. Results showed that the increased rGMV in the left inferior parietal lobule (IPL) was associated with the EFT score, which might be the structural basis of effective local processing. Additionally, a significant positive correlation between ALFF and EFT score was found in the fronto-parietal network, including the left inferior parietal lobule (IPL) and the medial prefrontal cortex (mPFC). We speculated that the left IPL might be associated with superior feature identification, and mPFC might be related to cognitive inhibition of global processing bias. These results suggested that the underlying neuroanatomical and functional bases were linked to the individual differences in FDI cognitive styles and emphasized the important contribution of superior local processing ability and cognitive inhibition to field-independent style. PMID:24348991

The Association of PTSD Symptom Severity with Localized Hippocampus and Amygdala Abnormalities

PubMed Central

Akiki, Teddy J.; Averill, Christopher L.; Wrocklage, Kristen M.; Schweinsburg, Brian; Scott, J. Cobb; Martini, Brenda; Averill, Lynnette A.; Southwick, Steven M.; Krystal, John H.; Abdallah, Chadi G.

2017-01-01

Background The hippocampus and amygdala have been repeatedly implicated in the psychopathology of posttraumatic stress disorder (PTSD). While numerous structural neuroimaging studies examined these two structures in PTSD, these analyses have largely been limited to volumetric measures. Recent advances in vertex-based neuroimaging methods have made it possible to identify specific locations of subtle morphometric changes within a structure of interest. Methods In this cross-sectional study, we used high-resolution magnetic resonance imaging to examine the relationship between PTSD symptomatology, as measured using the Clinician Administered PTSD Scale for the DSM-IV (CAPS), and structural shape of the hippocampus and amygdala using vertex-wise shape analyses in a group of combat-exposed US Veterans (N = 69). Results Following correction for multiple comparisons and controlling for age and cranial volume, we found that participants with more severe PTSD symptoms showed an indentation in the anterior half of the right hippocampus and an indentation in the dorsal region of the right amygdala (corresponding to the centromedial amygdala). Post hoc analysis using stepwise regression suggest that among PTSD symptom clusters, arousal symptoms explain most of the variance in the hippocampal abnormality, whereas re-experiencing symptoms explain most of the variance in the amygdala abnormality. Conclusion The results provide evidence of localized abnormalities in the anterior hippocampus and centromedial amygdala in combat-exposed US Veterans suffering from PTSD symptoms. This novel finding provides a more fine-grained analysis of structural abnormalities in PTSD and may be informative for understanding the neurobiology of the disorder. PMID:28825050

Automatic Semantic Facilitation in Anterior Temporal Cortex Revealed through Multimodal Neuroimaging

PubMed Central

Gramfort, Alexandre; Hämäläinen, Matti S.; Kuperberg, Gina R.

2013-01-01

A core property of human semantic processing is the rapid, facilitatory influence of prior input on extracting the meaning of what comes next, even under conditions of minimal awareness. Previous work has shown a number of neurophysiological indices of this facilitation, but the mapping between time course and localization—critical for separating automatic semantic facilitation from other mechanisms—has thus far been unclear. In the current study, we used a multimodal imaging approach to isolate early, bottom-up effects of context on semantic memory, acquiring a combination of electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) measurements in the same individuals with a masked semantic priming paradigm. Across techniques, the results provide a strikingly convergent picture of early automatic semantic facilitation. Event-related potentials demonstrated early sensitivity to semantic association between 300 and 500 ms; MEG localized the differential neural response within this time window to the left anterior temporal cortex, and fMRI localized the effect more precisely to the left anterior superior temporal gyrus, a region previously implicated in semantic associative processing. However, fMRI diverged from early EEG/MEG measures in revealing semantic enhancement effects within frontal and parietal regions, perhaps reflecting downstream attempts to consciously access the semantic features of the masked prime. Together, these results provide strong evidence that automatic associative semantic facilitation is realized as reduced activity within the left anterior superior temporal cortex between 300 and 500 ms after a word is presented, and emphasize the importance of multimodal neuroimaging approaches in distinguishing the contributions of multiple regions to semantic processing. PMID:24155321

Category-Selectivity in Human Visual Cortex Follows Cortical Topology: A Grouped icEEG Study

PubMed Central

Conner, Christopher Richard; Whaley, Meagan Lee; Baboyan, Vatche George; Tandon, Nitin

2016-01-01

Neuroimaging studies suggest that category-selective regions in higher-order visual cortex are topologically organized around specific anatomical landmarks: the mid-fusiform sulcus (MFS) in the ventral temporal cortex (VTC) and lateral occipital sulcus (LOS) in the lateral occipital cortex (LOC). To derive precise structure-function maps from direct neural signals, we collected intracranial EEG (icEEG) recordings in a large human cohort (n = 26) undergoing implantation of subdural electrodes. A surface-based approach to grouped icEEG analysis was used to overcome challenges from sparse electrode coverage within subjects and variable cortical anatomy across subjects. The topology of category-selectivity in bilateral VTC and LOC was assessed for five classes of visual stimuli—faces, animate non-face (animals/body-parts), places, tools, and words—using correlational and linear mixed effects analyses. In the LOC, selectivity for living (faces and animate non-face) and non-living (places and tools) classes was arranged in a ventral-to-dorsal axis along the LOS. In the VTC, selectivity for living and non-living stimuli was arranged in a latero-medial axis along the MFS. Written word-selectivity was reliably localized to the intersection of the left MFS and the occipito-temporal sulcus. These findings provide direct electrophysiological evidence for topological information structuring of functional representations within higher-order visual cortex. PMID:27272936

Machine learning for the assessment of Alzheimer's disease through DTI

NASA Astrophysics Data System (ADS)

Lella, Eufemia; Amoroso, Nicola; Bellotti, Roberto; Diacono, Domenico; La Rocca, Marianna; Maggipinto, Tommaso; Monaco, Alfonso; Tangaro, Sabina

2017-09-01

Digital imaging techniques have found several medical applications in the development of computer aided detection systems, especially in neuroimaging. Recent advances in Diffusion Tensor Imaging (DTI) aim to discover biological markers for the early diagnosis of Alzheimer's disease (AD), one of the most widespread neurodegenerative disorders. We explore here how different supervised classification models provide a robust support to the diagnosis of AD patients. We use DTI measures, assessing the structural integrity of white matter (WM) fiber tracts, to reveal patterns of disrupted brain connectivity. In particular, we provide a voxel-wise measure of fractional anisotropy (FA) and mean diffusivity (MD), thus identifying the regions of the brain mostly affected by neurodegeneration, and then computing intensity features to feed supervised classification algorithms. In particular, we evaluate the accuracy of discrimination of AD patients from healthy controls (HC) with a dataset of 80 subjects (40 HC, 40 AD), from the Alzheimer's Disease Neurodegenerative Initiative (ADNI). In this study, we compare three state-of-the-art classification models: Random Forests, Naive Bayes and Support Vector Machines (SVMs). We use a repeated five-fold cross validation framework with nested feature selection to perform a fair comparison between these algorithms and evaluate the information content they provide. Results show that AD patterns are well localized within the brain, thus DTI features can support the AD diagnosis.

The Layer of Kevlar Angle-interlock Woven Fabric Effect on the Tensile Properties of Composite Materials

NASA Astrophysics Data System (ADS)

Xie, Wan-Chen; Guo, Xu-Yi; Yan, Tao; Zhang, Shang-Yong

2017-09-01

This article is based on the structure of three-dimensional angle-interlock longitudinal.The 3-layer, 5-layer, 7-layer and 9-layer of angle-interlock 3D fabrics are woven on sample weaving machine respectively with the 1500D Kevlar fiber twist filament produced by United States DuPont. At the same time, Kevlar plain weave fabric is woven, and three, five, seven and nine layers’ fabric are to be compared. In the process of VARTM composite technology, epoxy resin is matrix material, acetone is diluent, triethylene tetramine is curing agent and the five different fabrics are the reinforced materials respectively. Finally, eight different three-dimensional woven fabric composites were prepared. In this paper, the tensile properties of eight kinds of three-dimensional woven fabric composites were tested respectively.Finally, it is concluded that the five-layer angle-interlock woven fabric prepared by Kevlar fiber shows the best tensile property.

Numerical investigation on aluminum foam application in a tubular heat exchanger

NASA Astrophysics Data System (ADS)

Buonomo, Bernardo; di Pasqua, Anna; Ercole, Davide; Manca, Oronzio; Nardini, Sergio

2018-02-01

A numerical study has been conducted to examine the thermal and fluiddynamic behaviors of a tubular heat exchanger in aluminum foam. A plate in metal foam with a single array of five circular tubes is the geometrical domain under examination. Darcy-Forchheimer flow model and the thermal non-equilibrium energy model are used to execute two-dimensional simulations on metal foam heat exchanger. The foam is characterized by porosity and (number) pores per inch respectively equal to 0.935 and 20. Different air flow rates are imposed to the entrance of the heat exchanger with an assigned surface tube temperature. The results are provided in terms of local heat transfer coefficient and Nusselt number evaluated on the external surface of the tubes. Furthermore, local air temperature and velocity profiles in the smaller cross section, between two consecutive tubes are given. Finally, the Energy Performance Ratio (EPR) is evaluated in order to demonstrate the effectiveness of the metal foam.

EMC3-EIRENE modelling of toroidally-localized divertor gas injection experiments on Alcator C-Mod

DOE PAGES

Lore, Jeremy D.; Reinke, M. L.; LaBombard, Brian; ...

2014-09-30

Experiments on Alcator C-Mod with toroidally and poloidally localized divertor nitrogen injection have been modeled using the three-dimensional edge transport code EMC3-EIRENE to elucidate the mechanisms driving measured toroidal asymmetries. In these experiments five toroidally distributed gas injectors in the private flux region were sequentially activated in separate discharges resulting in clear evidence of toroidal asymmetries in radiated power and nitrogen line emission as well as a ~50% toroidal modulation in electron pressure at the divertor target. The pressure modulation is qualitatively reproduced by the modelling, with the simulation yielding a toroidal asymmetry in the heat flow to the outermore » strike point. Finally, toroidal variation in impurity line emission is qualitatively matched in the scrape-off layer above the strike point, however kinetic corrections and cross-field drifts are likely required to quantitatively reproduce impurity behavior in the private flux region and electron temperatures and densities directly in front of the target.« less

Legal and ethical issues in neuroimaging research: human subjects protection, medical privacy, and the public communication of research results.

PubMed

Kulynych, Jennifer

2002-12-01

Humans subjects research entails significant legal and ethical obligations. Neuroimaging researchers must be familiar with the requirements of human subjects protection, including evolving standards for the protection of privacy and the disclosure of risk in "non-therapeutic" research. Techniques for creating veridical surface renderings from volumetric anatomical imaging data raise new privacy concerns, particularly under the federal medical privacy regulation. Additionally, neuroimaging researchers must consider their obligation to communicate research results responsibly. The emerging field of neuroethics should strive to raise awareness of these issues and to involve neuroimaging researchers in the legal, ethical, and policy debates that currently surround human subjects research.

Two-dimensional Anderson-Hubbard model in the DMFT + {Sigma} approximation

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

Kuchinskii, E. Z., E-mail: kuchinsk@iep.uran.ru; Kuleeva, N. A.; Nekrasov, I. A.

The density of states, the dynamic (optical) conductivity, and the phase diagram of the paramagnetic two-dimensional Anderson-Hubbard model with strong correlations and disorder are analyzed within the generalized dynamical mean field theory (DMFT + {Sigma} approximation). Strong correlations are accounted by the DMFT, while disorder is taken into account via the appropriate generalization of the self-consistent theory of localization. We consider the two-dimensional system with the rectangular 'bare' density of states (DOS). The DMFT effective single-impurity problem is solved by numerical renormalization group (NRG). The 'correlated metal,' Mott insulator, and correlated Anderson insulator phases are identified from the evolution ofmore » the density of states, optical conductivity, and localization length, demonstrating both Mott-Hubbard and Anderson metal-insulator transitions in two-dimensional systems of finite size, allowing us to construct the complete zero-temperature phase diagram of the paramagnetic Anderson-Hubbard model. The localization length in our approximation is practically independent of the strength of Hubbard correlations. But the divergence of the localization length in a finite-size two-dimensional system at small disorder signifies the existence of an effective Anderson transition.« less

Sampling design for groundwater solute transport: Tests of methods and analysis of Cape Cod tracer test data

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.; Garabedian, Stephen P.

1991-01-01

Tests of a one-dimensional sampling design methodology on measurements of bromide concentration collected during the natural gradient tracer test conducted by the U.S. Geological Survey on Cape Cod, Massachusetts, demonstrate its efficacy for field studies of solute transport in groundwater and the utility of one-dimensional analysis. The methodology was applied to design of sparse two-dimensional networks of fully screened wells typical of those often used in engineering practice. In one-dimensional analysis, designs consist of the downstream distances to rows of wells oriented perpendicular to the groundwater flow direction and the timing of sampling to be carried out on each row. The power of a sampling design is measured by its effectiveness in simultaneously meeting objectives of model discrimination, parameter estimation, and cost minimization. One-dimensional models of solute transport, differing in processes affecting the solute and assumptions about the structure of the flow field, were considered for description of tracer cloud migration. When fitting each model using nonlinear regression, additive and multiplicative error forms were allowed for the residuals which consist of both random and model errors. The one-dimensional single-layer model of a nonreactive solute with multiplicative error was judged to be the best of those tested. Results show the efficacy of the methodology in designing sparse but powerful sampling networks. Designs that sample five rows of wells at five or fewer times in any given row performed as well for model discrimination as the full set of samples taken up to eight times in a given row from as many as 89 rows. Also, designs for parameter estimation judged to be good by the methodology were as effective in reducing the variance of parameter estimates as arbitrary designs with many more samples. Results further showed that estimates of velocity and longitudinal dispersivity in one-dimensional models based on data from only five rows of fully screened wells each sampled five or fewer times were practically equivalent to values determined from moments analysis of the complete three-dimensional set of 29,285 samples taken during 16 sampling times.

Entanglement Entropy in Two-Dimensional String Theory.

PubMed

Hartnoll, Sean A; Mazenc, Edward A

2015-09-18

To understand an emergent spacetime is to understand the emergence of locality. Entanglement entropy is a powerful diagnostic of locality, because locality leads to a large amount of short distance entanglement. Two-dimensional string theory is among the very simplest instances of an emergent spatial dimension. We compute the entanglement entropy in the large-N matrix quantum mechanics dual to two-dimensional string theory in the semiclassical limit of weak string coupling. We isolate a logarithmically large, but finite, contribution that corresponds to the short distance entanglement of the tachyon field in the emergent spacetime. From the spacetime point of view, the entanglement is regulated by a nonperturbative "graininess" of space.

[Symptoms and lesion localization in visual agnosia].

PubMed

Suzuki, Kyoko

2004-11-01

There are two cortical visual processing streams, the ventral and dorsal stream. The ventral visual stream plays the major role in constructing our perceptual representation of the visual world and the objects within it. Disturbance of visual processing at any stage of the ventral stream could result in impairment of visual recognition. Thus we need systematic investigations to diagnose visual agnosia and its type. Two types of category-selective visual agnosia, prosopagnosia and landmark agnosia, are different from others in that patients could recognize a face as a face and buildings as buildings, but could not identify an individual person or building. Neuronal bases of prosopagnosia and landmark agnosia are distinct. Importance of the right fusiform gyrus for face recognition was confirmed by both clinical and neuroimaging studies. Landmark agnosia is related to lesions in the right parahippocampal gyrus. Enlarged lesions including both the right fusiform and parahippocampal gyri can result in prosopagnosia and landmark agnosia at the same time. Category non-selective visual agnosia is related to bilateral occipito-temporal lesions, which is in agreement with the results of neuroimaging studies that revealed activation of the bilateral occipito-temporal during object recognition tasks.

What the cognitive neurosciences mean to me.

PubMed

Pereira, Alfredo

2007-01-01

Cognitive Neuroscience is an interdisciplinary area of research that combines measurement of brain activity (mostly by means of neuroimaging) with a simultaneous performance of cognitive tasks by human subjects. These investigations have been successful in the task of connecting the sciences of the brain (Neurosciences) and the sciences of the mind (Cognitive Sciences). Advances on this kind of research provide a map of localization of cognitive functions in the human brain. Do these results help us to understand how mind relates to the brain? In my view, the results obtained by the Cognitive Neurosciences lead to new investigations in the domain of Molecular Neurobiology, aimed at discovering biophysical mechanisms that generate the activity measured by neuroimaging instruments. In this context, I argue that the understanding of how ionic/molecular processes support cognition and consciousness cannot be made by means of the standard reductionist explanations. Knowledge of ionic/molecular mechanisms can contribute to our understanding of the human mind as long as we assume an alternative form of explanation, based on psycho-physical similarities, together with an ontological view of mentality and spirituality as embedded in physical nature (and not outside nature, as frequently assumed in western culture).

What The Cognitive Neurosciences Mean To Me

PubMed Central

Pereira, Alfredo

2007-01-01

Cognitive Neuroscience is an interdisciplinary area of research that combines measurement of brain activity (mostly by means of neuroimaging) with a simultaneous performance of cognitive tasks by human subjects. These investigations have been successful in the task of connecting the sciences of the brain (Neurosciences) and the sciences of the mind (Cognitive Sciences). Advances on this kind of research provide a map of localization of cognitive functions in the human brain. Do these results help us to understand how mind relates to the brain? In my view, the results obtained by the Cognitive Neurosciences lead to new investigations in the domain of Molecular Neurobiology, aimed at discovering biophysical mechanisms that generate the activity measured by neuroimaging instruments. In this context, I argue that the understanding of how ionic/molecular processes support cognition and consciousness cannot be made by means of the standard reductionist explanations. Knowledge of ionic/molecular mechanisms can contribute to our understanding of the human mind as long as we assume an alternative form of explanation, based on psycho-physical similarities, together with an ontological view of mentality and spirituality as embedded in physical nature (and not outside nature, as frequently assumed in western culture). PMID:22058629

Neuroimaging Findings from Childhood Onset Schizophrenia Patients and their Non-Psychotic Siblings

PubMed Central

Ordóñez, Anna E.; Luscher, Zoe; Gogtay, Nitin

2015-01-01

Childhood onset schizophrenia (COS), with onset of psychosis before age 13, is a rare form of schizophrenia that represents a more severe and chronic form of the adult onset illness. In this review we examine structural and functional magnetic resonance imaging (MRI) studies of COS and non-psychotic siblings of COS patients in the context of studies of schizophrenia as a whole. Studies of COS to date reveal progressive loss of gray matter volume and cortical thinning, ventricular enlargement, progressive decline in cerebellar volume and a significant but fixed deficit in hippocampal volume. COS is also associated with a slower rate of white matter growth and disrupted local connectivity strength. Sibling studies indicate that non-psychotic siblings of COS patients share many of these brain abnormalities, including decreased cortical thickness and disrupted white matter growth, yet these abnormalities normalize with age. Cross-sectional and longitudinal neuroimaging studies remain some of the few methods for assessing human brain function and play a pivotal role in the quest for understanding the neurobiology of schizophrenia as well as other psychiatric disorders. Parallel studies in non-psychotic siblings provide a unique opportunity to understand both risk and resilience in schizophrenia. PMID:25819937

Neuroimaging findings from childhood onset schizophrenia patients and their non-psychotic siblings.

PubMed

Ordóñez, Anna E; Luscher, Zoe I; Gogtay, Nitin

2016-06-01

Childhood onset schizophrenia (COS), with onset of psychosis before age 13, is a rare form of schizophrenia that represents a more severe and chronic form of the adult onset illness. In this review we examine structural and functional magnetic resonance imaging (MRI) studies of COS and non-psychotic siblings of COS patients in the context of studies of schizophrenia as a whole. Studies of COS to date reveal progressive loss of gray matter volume and cortical thinning, ventricular enlargement, progressive decline in cerebellar volume and a significant but fixed deficit in hippocampal volume. COS is also associated with a slower rate of white matter growth and disrupted local connectivity strength. Sibling studies indicate that non-psychotic siblings of COS patients share many of these brain abnormalities, including decreased cortical thickness and disrupted white matter growth, yet these abnormalities normalize with age. Cross-sectional and longitudinal neuroimaging studies remain some of the few methods for assessing human brain function and play a pivotal role in the quest for understanding the neurobiology of schizophrenia as well as other psychiatric disorders. Parallel studies in non-psychotic siblings provide a unique opportunity to understand both risk and resilience in schizophrenia. Published by Elsevier B.V.

Neuroimaging in psychiatric pharmacogenetics research: the promise and pitfalls.

PubMed

Falcone, Mary; Smith, Ryan M; Chenoweth, Meghan J; Bhattacharjee, Abesh Kumar; Kelsoe, John R; Tyndale, Rachel F; Lerman, Caryn

2013-11-01

The integration of research on neuroimaging and pharmacogenetics holds promise for improving treatment for neuropsychiatric conditions. Neuroimaging may provide a more sensitive early measure of treatment response in genetically defined patient groups, and could facilitate development of novel therapies based on an improved understanding of pathogenic mechanisms underlying pharmacogenetic associations. This review summarizes progress in efforts to incorporate neuroimaging into genetics and treatment research on major psychiatric disorders, such as schizophrenia, major depressive disorder, bipolar disorder, attention-deficit/hyperactivity disorder, and addiction. Methodological challenges include: performing genetic analyses in small study populations used in imaging studies; inclusion of patients with psychiatric comorbidities; and the extensive variability across studies in neuroimaging protocols, neurobehavioral task probes, and analytic strategies. Moreover, few studies use pharmacogenetic designs that permit testing of genotype × drug effects. As a result of these limitations, few findings have been fully replicated. Future studies that pre-screen participants for genetic variants selected a priori based on drug metabolism and targets have the greatest potential to advance the science and practice of psychiatric treatment.

25 years of neuroimaging in amyotrophic lateral sclerosis.

PubMed

Foerster, Bradley R; Welsh, Robert C; Feldman, Eva L

2013-09-01

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques--such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy--allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development.

Neuroimaging with functional near infrared spectroscopy: From formation to interpretation

NASA Astrophysics Data System (ADS)

Herrera-Vega, Javier; Treviño-Palacios, Carlos G.; Orihuela-Espina, Felipe

2017-09-01

Functional Near Infrared Spectroscopy (fNIRS) is gaining momentum as a functional neuroimaging modality to investigate the cerebral hemodynamics subsequent to neural metabolism. As other neuroimaging modalities, it is neuroscience's tool to understand brain systems functions at behaviour and cognitive levels. To extract useful knowledge from functional neuroimages it is critical to understand the series of transformations applied during the process of the information retrieval and how they bound the interpretation. This process starts with the irradiation of the head tissues with infrared light to obtain the raw neuroimage and proceeds with computational and statistical analysis revealing hidden associations between pixels intensities and neural activity encoded to end up with the explanation of some particular aspect regarding brain function.To comprehend the overall process involved in fNIRS there is extensive literature addressing each individual step separately. This paper overviews the complete transformation sequence through image formation, reconstruction and analysis to provide an insight of the final functional interpretation.

25 years of neuroimaging in amyotrophic lateral sclerosis

PubMed Central

Foerster, Bradley R.; Welsh, Robert C.; Feldman, Eva L.

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques—such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy—allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development. PMID:23917850

Bayesian spatial transformation models with applications in neuroimaging data

PubMed Central

Miranda, Michelle F.; Zhu, Hongtu; Ibrahim, Joseph G.

2013-01-01

Summary The aim of this paper is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. Our STMs include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov Random Field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. PMID:24128143

Three-dimensional numerical simulations of local scouring around bridge piers

USDA-ARS?s Scientific Manuscript database

This paper presents a novel numerical method for simulating local scouring around bridge piers using a three-dimensional free-surface RANS turbulent flow model. Strong turbulent fluctuations and the down-flows around the bridge pier are considered important factors in scouring the bed. The turbulent...

The coordinate-based meta-analysis of neuroimaging data.

PubMed

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E; Johnson, Timothy D

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research.

The coordinate-based meta-analysis of neuroimaging data

PubMed Central

Samartsidis, Pantelis; Montagna, Silvia; Nichols, Thomas E.; Johnson, Timothy D.

2017-01-01

Neuroimaging meta-analysis is an area of growing interest in statistics. The special characteristics of neuroimaging data render classical meta-analysis methods inapplicable and therefore new methods have been developed. We review existing methodologies, explaining the benefits and drawbacks of each. A demonstration on a real dataset of emotion studies is included. We discuss some still-open problems in the field to highlight the need for future research. PMID:29545671

Functional neuroimaging in psychiatry.

PubMed Central

Fu, C H; McGuire, P K

1999-01-01

Functional neuroimaging is one of the most powerful means available for investigating the pathophysiology of psychiatric disorders. In this review, we shall focus on the different ways that it can be employed to this end, describing the major findings in the field in the context of different methodological approaches. We will also discuss practical issues that are particular to studying psychiatric disorders and the potential contribution of functional neuroimaging to future psychiatric research. PMID:10466156

Reading the Freudian theory of sexual drives from a functional neuroimaging perspective

PubMed Central

Stoléru, Serge

2014-01-01

One of the essential tasks of neuropsychoanalysis is to investigate the neural correlates of sexual drives. Here, we consider the four defining characteristics of sexual drives as delineated by Freud: their pressure, aim, object, and source. We systematically examine the relations between these characteristics and the four-component neurophenomenological model that we have proposed based on functional neuroimaging studies, which comprises a cognitive, a motivational, an emotional and an autonomic/neuroendocrine component. Functional neuroimaging studies of sexual arousal (SA) have thrown a new light on the four fundamental characteristics of sexual drives by identifying their potential neural correlates. While these studies are essentially consistent with the Freudian model of drives, the main difference emerging between the functional neuroimaging perspective on sexual drives and the Freudian theory relates to the source of drives. From a functional neuroimaging perspective, sources of sexual drives, conceived by psychoanalysis as processes of excitation occurring in a peripheral organ, do not seem, at least in adult subjects, to be an essential part of the determinants of SA. It is rather the central processing of visual or genital stimuli that gives to these stimuli their sexually arousing and sexually pleasurable character. Finally, based on functional neuroimaging results, some possible improvements to the psychoanalytic theory of sexual drives are suggested. PMID:24672467

Neurologic outcome of urea cycle disorder liver transplant recipients may be predicted by pretransplant neurological imaging.

PubMed

Bolton, Scott M; Campbell, Kathleen M; Kukreja, Marcia; Kohli, Rohit

2015-08-01

Liver transplantation treats the hepatic affectation of UCDs; however, irreversible neurologic damage pretransplant is difficult to assess providing transplant teams with ethical dilemmas for liver transplantation. The purpose of our study was to determine whether pretransplant neuroimaging can predict developmental outcomes post-liver-transplant in children with UCDs. Patients undergoing liver transplantation for UCDs at Cincinnati Children's Hospital Medical Center between 2002 and 2012 were identified. Neurologic assessments prior to and after transplantation were categorized into mild, moderate, or severe disability. Neuroimaging data were categorized into mild, moderate, or severe by a single pediatric neuroradiologist. Fifteen patients were identified of whom eight had neuroimaging prior to transplantation. Of the eight patients that had neuroimaging, four were categorized as severe, one moderate, and three no-to-mild delay. All four patients whose imaging was severe were found to have moderate-to-severe neurologic delay. Of the three patients with no-to-mild changes on neuroimaging two of three were found to have no-to-mild delay on developmental assessments after transplantation. Neuroimaging may be a helpful tool in determining developmental prognosis and outcomes post-liver-transplantation for UCDs. Further studies maybe needed to validate our preliminary findings. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Co-evolution of Neuroimaging and Psychiatric Neurosurgery.

PubMed

Dyster, Timothy G; Mikell, Charles B; Sheth, Sameer A

2016-01-01

The role of neuroimaging in psychiatric neurosurgery has evolved significantly throughout the field's history. Psychiatric neurosurgery initially developed without the benefit of information provided by modern imaging modalities, and thus lesion targets were selected based on contemporary theories of frontal lobe dysfunction in psychiatric disease. However, by the end of the 20th century, the availability of structural and functional magnetic resonance imaging (fMRI) allowed for the development of mechanistic theories attempting to explain the anatamofunctional basis of these disorders, as well as the efficacy of stereotactic neuromodulatory treatments. Neuroimaging now plays a central and ever-expanding role in the neurosurgical management of psychiatric disorders, by influencing the determination of surgical candidates, allowing individualized surgical targeting and planning, and identifying network-level changes in the brain following surgery. In this review, we aim to describe the coevolution of psychiatric neurosurgery and neuroimaging, including ways in which neuroimaging has proved useful in elucidating the therapeutic mechanisms of neuromodulatory procedures. We focus on ablative over stimulation-based procedures given their historical precedence and the greater opportunity they afford for post-operative re-imaging, but also discuss important contributions from the deep brain stimulation (DBS) literature. We conclude with a discussion of how neuroimaging will transition the field of psychiatric neurosurgery into the era of precision medicine.

Understanding Youth Antisocial Behavior Using Neuroscience through a Developmental Psychopathology Lens: Review, Integration, and Directions for Research

PubMed Central

Hyde, Luke W.; Shaw, Daniel S.; Hariri, Ahmad R.

2013-01-01

Youth antisocial behavior (AB) is an important public health concern impacting perpetrators, victims, and society. Functional neuroimaging is becoming a more common and useful modality for understanding neural correlates of youth AB. Although there has been a recent increase in neuroimaging studies of youth AB and corresponding theoretical articles on the neurobiology of AB, there has been little work critically examining the strengths and weaknesses of individual studies and using this knowledge to inform the design of future studies. Additionally, research on neuroimaging and youth AB has not been integrated within the broader framework of developmental psychopathology. Thus, this paper provides an in-depth review of the youth AB functional neuroimaging literature with the following goals: 1. to evaluate how this literature has informed our understanding of youth AB, 2. to evaluate current neuroimaging studies of youth AB from a developmental psychopathology perspective with a focus on integrating research from neuroscience and developmental psychopathology, as well as placing this research in the context of other related areas (e.g., psychopathy, molecular genetics), and 3. to examine strengths and weaknesses of neuroimaging and behavioral studies of youth AB to suggest how future studies can develop a more informed and integrated understanding of youth AB. PMID:24273368

Ostwald ripening of faceted Si particles in an Al-Si-Cu melt

DOE PAGES

Shahani, A. J.; Xiao, X.; Skinner, K.; ...

2016-07-04

The microstructural evolution of an Al-Si-Cu alloy during Ostwald ripening is imaged via synchrotron-based, four-dimensional (i.e., space and time resolved) X-ray tomography. Samples of composition Al-32 wt%Si-15 wt%Cu were annealed isothermally at 650 °C, in the two-phase solid-liquid regime, while tomographic projections were collected in situ over the course of five hours. Advances in experimental methods and computational approaches enable us to characterize the local interfacial curvatures and velocities during ripening. The sequence of three-dimensional reconstructions and interfacial shape distributions shows highly faceted Si particles in a copper-enriched liquid, that become increasingly isotropic or rounded over time. In addition, wemore » find that the coarsening rate constant is approximately the same in the binary and ternary systems. By coupling these experimental measurements with CALPHAD modeling and ab initio molecular dynamics simulation, we assess the influence of Cu on the coarsening process. Lastly, we find the unusual “pinning” of microstructure at the junction between rough and smooth interfaces and suggest a mechanism for this behavior.« less

Three-Dimensional Localized-Delocalized Anderson Transition in the Time Domain

NASA Astrophysics Data System (ADS)

Delande, Dominique; Morales-Molina, Luis; Sacha, Krzysztof

2017-12-01

Systems which can spontaneously reveal periodic evolution are dubbed time crystals. This is in analogy with space crystals that display periodic behavior in configuration space. While space crystals are modeled with the help of space periodic potentials, crystalline phenomena in time can be modeled by periodically driven systems. Disorder in the periodic driving can lead to Anderson localization in time: the probability for detecting a system at a fixed point of configuration space becomes exponentially localized around a certain moment in time. We here show that a three-dimensional system exposed to a properly disordered pseudoperiodic driving may display a localized-delocalized Anderson transition in the time domain, in strong analogy with the usual three-dimensional Anderson transition in disordered systems. Such a transition could be experimentally observed with ultracold atomic gases.

Entanglement entropy in a one-dimensional disordered interacting system: the role of localization.

PubMed

Berkovits, Richard

2012-04-27

The properties of the entanglement entropy (EE) in one-dimensional disordered interacting systems are studied. Anderson localization leaves a clear signature on the average EE, as it saturates on the length scale exceeding the localization length. This is verified by numerically calculating the EE for an ensemble of disordered realizations using the density matrix renormalization group method. A heuristic expression describing the dependence of the EE on the localization length, which takes into account finite-size effects, is proposed. This is used to extract the localization length as a function of the interaction strength. The localization length dependence on the interaction fits nicely with the expectations.

Distinct Regions within Medial Prefrontal Cortex Process Pain and Cognition

PubMed Central

Jahn, Andrew; Nee, Derek Evan; Alexander, William H.

2016-01-01

Neuroimaging studies of the medial prefrontal cortex (mPFC) suggest that the dorsal anterior cingulate cortex (dACC) region is responsive to a wide variety of stimuli and psychological states, such as pain, cognitive control, and prediction error (PE). In contrast, a recent meta-analysis argues that the dACC is selective for pain, whereas the supplementary motor area (SMA) and pre-SMA are specifically associated with higher-level cognitive processes (Lieberman and Eisenberger, 2015). To empirically test this claim, we manipulated effects of pain, conflict, and PE in a single experiment using human subjects. We observed a robust dorsal-ventral dissociation within the mPFC with cognitive effects of PE and conflict overlapping dorsally and pain localized more ventrally. Classification of subjects based on the presence or absence of a paracingulate sulcus showed that PE effects extended across the dorsal area of the dACC and into the pre-SMA. These results begin to resolve recent controversies by showing the following: (1) the mPFC includes dissociable regions for pain and cognitive processing; and (2) meta-analyses are correct in localizing cognitive effects to the dACC, although these effects extend to the pre-SMA as well. These results both provide evidence distinguishing between different theories of mPFC function and highlight the importance of taking individual anatomical variability into account when conducting empirical studies of the mPFC. SIGNIFICANCE STATEMENT Decades of neuroimaging research have shown the mPFC to represent a wide variety of stimulus processing and cognitive states. However, recently it has been argued whether distinct regions of the mPFC separately process pain and cognitive phenomena. To address this controversy, this study directly compared pain and cognitive processes within subjects. We found a double dissociation within the mPFC with pain localized ventral to the cingulate sulcus and cognitive effects localized more dorsally within the dACC and spreading into the pre-supplementary motor area. This provides empirical evidence to help resolve the current debate about the functional architecture of the mPFC. PMID:27807031

Grand unified brane world scenario

NASA Astrophysics Data System (ADS)

Arai, Masato; Blaschke, Filip; Eto, Minoru; Sakai, Norisuke

2017-12-01

We present a field theoretical model unifying grand unified theory (GUT) and brane world scenario. As a concrete example, we consider S U (5 ) GUT in 4 +1 dimensions where our 3 +1 dimensional spacetime spontaneously arises on five domain walls. A field-dependent gauge kinetic term is used to localize massless non-Abelian gauge fields on the domain walls and to assure the charge universality of matter fields. We find the domain walls with the symmetry breaking S U (5 )→S U (3 )×S U (2 )×U (1 ) as a global minimum and all the undesirable moduli are stabilized with the mass scale of MGUT. Profiles of massless standard model particles are determined as a consequence of wall dynamics. The proton decay can be exponentially suppressed.

Dynamic Analysis of the Melanoma Model: From Cancer Persistence to Its Eradication

NASA Astrophysics Data System (ADS)

Starkov, Konstantin E.; Jimenez Beristain, Laura

In this paper, we study the global dynamics of the five-dimensional melanoma model developed by Kronik et al. This model describes interactions of tumor cells with cytotoxic T cells and respective cytokines under cellular immunotherapy. We get the ultimate upper and lower bounds for variables of this model, provide formulas for equilibrium points and present local asymptotic stability/hyperbolic instability conditions. Next, we prove the existence of the attracting set. Based on these results we come to global asymptotic melanoma eradication conditions via global stability analysis. Finally, we provide bounds for a locus of the melanoma persistence equilibrium point, study the case of melanoma persistence and describe conditions under which we observe global attractivity to the unique melanoma persistence equilibrium point.

Locoregional and Microvascular Free Tissue Reconstruction of the Lateral Skull Base.

PubMed

Arnaoutakis, Demetri; Kadakia, Sameep; Abraham, Manoj; Lee, Thomas; Ducic, Yadranko

2017-11-01

The goals of reconstruction following any oncologic extirpation are preservation of function, restoration of cosmesis, and avoidance of morbidity. Anatomically, the lateral skull base is complex and conceptually intricate due to its three-dimensional morphology. The temporal bone articulates with five other cranial bones and forms many sutures and foramina through which pass critical neural and vascular structures. Remnant defects following resection of lateral skull base tumors are often not amenable to primary closure. As such, numerous techniques have been described for reconstruction including local rotational muscle flaps, pedicled flaps with skin paddle, or free tissue transfer. In this review, the advantages and disadvantages of each reconstructive method will be discussed as well as their potential complications.

Turbulent transport model of wind shear in thunderstorm gust fronts and warm fronts

NASA Technical Reports Server (NTRS)

Lewellen, W. S.; Teske, M. E.; Segur, H. C. O.

1978-01-01

A model of turbulent flow in the atmospheric boundary layer was used to simulate the low-level wind and turbulence profiles associated with both local thunderstorm gust fronts and synoptic-scale warm fronts. Dimensional analyses of both type fronts provided the physical scaling necessary to permit normalized simulations to represent fronts for any temperature jump. The sensitivity of the thunderstorm gust front to five different dimensionless parameters as well as a change from axisymmetric to planar geometry was examined. The sensitivity of the warm front to variations in the Rossby number was examined. Results of the simulations are discussed in terms of the conditions which lead to wind shears which are likely to be most hazardous for aircraft operations.

Theory of carbon nanocones: mechanical chiral inversion of a micron-scale three-dimensional object.

PubMed

Jordan, Stephen P; Crespi, Vincent H

2004-12-17

Graphene cones have two degenerate configurations: their original shape and its inverse. When the apex is depressed by an external probe, the simulated mechanical response is highly nonlinear, with a broad constant-force mode appearing after a short initial Hooke's law regime. For chiral cones, the final state is an atomically exact chiral invert of the original system. If the local reflection symmetry of the graphene sheet is broken by the chemisorption of just five hydrogen atoms to the apex, then the maximal yield strength of the cone increases by approximately 40%. The high symmetry of the conical geometry can concentrate micron-scale mechanical work with atomic precision, providing a way to activate specific chemical bonds.

Automated Geo/Co-Registration of Multi-Temporal Very-High-Resolution Imagery.

PubMed

Han, Youkyung; Oh, Jaehong

2018-05-17

For time-series analysis using very-high-resolution (VHR) multi-temporal satellite images, both accurate georegistration to the map coordinates and subpixel-level co-registration among the images should be conducted. However, applying well-known matching methods, such as scale-invariant feature transform and speeded up robust features for VHR multi-temporal images, has limitations. First, they cannot be used for matching an optical image to heterogeneous non-optical data for georegistration. Second, they produce a local misalignment induced by differences in acquisition conditions, such as acquisition platform stability, the sensor's off-nadir angle, and relief displacement of the considered scene. Therefore, this study addresses the problem by proposing an automated geo/co-registration framework for full-scene multi-temporal images acquired from a VHR optical satellite sensor. The proposed method comprises two primary steps: (1) a global georegistration process, followed by (2) a fine co-registration process. During the first step, two-dimensional multi-temporal satellite images are matched to three-dimensional topographic maps to assign the map coordinates. During the second step, a local analysis of registration noise pixels extracted between the multi-temporal images that have been mapped to the map coordinates is conducted to extract a large number of well-distributed corresponding points (CPs). The CPs are finally used to construct a non-rigid transformation function that enables minimization of the local misalignment existing among the images. Experiments conducted on five Kompsat-3 full scenes confirmed the effectiveness of the proposed framework, showing that the georegistration performance resulted in an approximately pixel-level accuracy for most of the scenes, and the co-registration performance further improved the results among all combinations of the georegistered Kompsat-3 image pairs by increasing the calculated cross-correlation values.

MRI quantification of pancreas motion as a function of patient setup for particle therapy —a preliminary study

PubMed Central

Riboldi, Marco; Gianoli, Chiara; Chirvase, Cezarina I.; Villa, Gaetano; Paganelli, Chiara; Summers, Paul E.; Tagaste, Barbara; Pella, Andrea; Fossati, Piero; Ciocca, Mario; Baroni, Guido; Valvo, Francesca; Orecchia, Roberto

2016-01-01

Particle therapy (PT) has shown positive therapeutic results in local control of locally advanced pancreatic lesions. PT effectiveness is highly influenced by target localization accuracy both in space, since the pancreas is located in proximity to radiosensitive vital organs, and in time as it is subject to substantial breathing‐related motion. The purpose of this preliminary study was to quantify pancreas range of motion under typical PT treatment conditions. Three common immobilization devices (vacuum cushion, thermoplastic mask, and compressor belt) were evaluated on five male patients in prone and supine positions. Retrospective four‐dimensional magnetic resonance imaging data were reconstructed for each condition and the pancreas was manually segmented on each of six breathing phases. A k‐means algorithm was then applied on the manually segmented map in order to obtain clusters representative of the three pancreas segments: head, body, and tail. Centers of mass (COM) for the pancreas and its segments were computed, as well as their displacements with respect to a reference breathing phase (beginning exhalation). The median three‐dimensional COM displacements were in the range of 3 mm. Latero–lateral and superior–inferior directions had a higher range of motion than the anterior–posterior direction. Motion analysis of the pancreas segments showed slightly lower COM displacements for the head cluster compared to the tail cluster, especially in prone position. Statistically significant differences were found within patients among the investigated setups. Hence a patient‐specific approach, rather than a general strategy, is suggested to define the optimal treatment setup in the frame of a millimeter positioning accuracy. PACS number(s): 87.55.‐x, 87.57.nm, 87.61 PMID:27685119

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.

The effect of compliant walls on three-dimensional primary and secondary instabilities in boundary layer transition

NASA Astrophysics Data System (ADS)

Joslin, R. D.

1991-04-01

The use of passive devices to obtain drag and noise reduction or transition delays in boundary layers is highly desirable. One such device that shows promise for hydrodynamic applications is the compliant coating. The present study extends the mechanical model to allow for three-dimensional waves. This study also looks at the effect of compliant walls on three-dimensional secondary instabilities. For the primary and secondary instability analysis, spectral and shooting approximations are used to obtain solutions of the governing equations and boundary conditions. The spectral approximation consists of local and global methods of solution while the shooting approach is local. The global method is used to determine the discrete spectrum of eigenvalue without any initial guess. The local method requires a sufficiently accurate initial guess to converge to the eigenvalue. Eigenvectors may be obtained with either local approach. For the initial stage of this analysis, two and three dimensional primary instabilities propagate over compliant coatings. Results over the compliant walls are compared with the rigid wall case. Three-dimensional instabilities are found to dominate transition over the compliant walls considered. However, transition delays are still obtained and compared with transition delay predictions for rigid walls. The angles of wave propagation are plotted with Reynolds number and frequency. Low frequency waves are found to be highly three-dimensional.

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

NASA Astrophysics Data System (ADS)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.

A Neuroimaging Web Services Interface as a Cyber Physical System for Medical Imaging and Data Management in Brain Research: Design Study.

PubMed

Lizarraga, Gabriel; Li, Chunfei; Cabrerizo, Mercedes; Barker, Warren; Loewenstein, David A; Duara, Ranjan; Adjouadi, Malek

2018-04-26

Structural and functional brain images are essential imaging modalities for medical experts to study brain anatomy. These images are typically visually inspected by experts. To analyze images without any bias, they must be first converted to numeric values. Many software packages are available to process the images, but they are complex and difficult to use. The software packages are also hardware intensive. The results obtained after processing vary depending on the native operating system used and its associated software libraries; data processed in one system cannot typically be combined with data on another system. The aim of this study was to fulfill the neuroimaging community’s need for a common platform to store, process, explore, and visualize their neuroimaging data and results using Neuroimaging Web Services Interface: a series of processing pipelines designed as a cyber physical system for neuroimaging and clinical data in brain research. Neuroimaging Web Services Interface accepts magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and functional magnetic resonance imaging. These images are processed using existing and custom software packages. The output is then stored as image files, tabulated files, and MySQL tables. The system, made up of a series of interconnected servers, is password-protected and is securely accessible through a Web interface and allows (1) visualization of results and (2) downloading of tabulated data. All results were obtained using our processing servers in order to maintain data validity and consistency. The design is responsive and scalable. The processing pipeline started from a FreeSurfer reconstruction of Structural magnetic resonance imaging images. The FreeSurfer and regional standardized uptake value ratio calculations were validated using Alzheimer’s Disease Neuroimaging Initiative input images, and the results were posted at the Laboratory of Neuro Imaging data archive. Notable leading researchers in the field of Alzheimer’s Disease and epilepsy have used the interface to access and process the data and visualize the results. Tabulated results with unique visualization mechanisms help guide more informed diagnosis and expert rating, providing a truly unique multimodal imaging platform that combines magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and resting state functional magnetic resonance imaging. A quality control component was reinforced through expert visual rating involving at least 2 experts. To our knowledge, there is no validated Web-based system offering all the services that Neuroimaging Web Services Interface offers. The intent of Neuroimaging Web Services Interface is to create a tool for clinicians and researchers with keen interest on multimodal neuroimaging. More importantly, Neuroimaging Web Services Interface significantly augments the Alzheimer’s Disease Neuroimaging Initiative data, especially since our data contain a large cohort of Hispanic normal controls and Alzheimer’s Disease patients. The obtained results could be scrutinized visually or through the tabulated forms, informing researchers on subtle changes that characterize the different stages of the disease. ©Gabriel Lizarraga, Chunfei Li, Mercedes Cabrerizo, Warren Barker, David A Loewenstein, Ranjan Duara, Malek Adjouadi. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 26.04.2018.

A Standardized Generalized Dimensionality Discrepancy Measure and a Standardized Model-Based Covariance for Dimensionality Assessment for Multidimensional Models

ERIC Educational Resources Information Center

Levy, Roy; Xu, Yuning; Yel, Nedim; Svetina, Dubravka

2015-01-01

The standardized generalized dimensionality discrepancy measure and the standardized model-based covariance are introduced as tools to critique dimensionality assumptions in multidimensional item response models. These tools are grounded in a covariance theory perspective and associated connections between dimensionality and local independence.…

Relevant Feature Set Estimation with a Knock-out Strategy and Random Forests

PubMed Central

Ganz, Melanie; Greve, Douglas N.; Fischl, Bruce; Konukoglu, Ender

2015-01-01

Group analysis of neuroimaging data is a vital tool for identifying anatomical and functional variations related to diseases as well as normal biological processes. The analyses are often performed on a large number of highly correlated measurements using a relatively smaller number of samples. Despite the correlation structure, the most widely used approach is to analyze the data using univariate methods followed by post-hoc corrections that try to account for the data’s multivariate nature. Although widely used, this approach may fail to recover from the adverse effects of the initial analysis when local effects are not strong. Multivariate pattern analysis (MVPA) is a powerful alternative to the univariate approach for identifying relevant variations. Jointly analyzing all the measures, MVPA techniques can detect global effects even when individual local effects are too weak to detect with univariate analysis. Current approaches are successful in identifying variations that yield highly predictive and compact models. However, they suffer from lessened sensitivity and instabilities in identification of relevant variations. Furthermore, current methods’ user-defined parameters are often unintuitive and difficult to determine. In this article, we propose a novel MVPA method for group analysis of high-dimensional data that overcomes the drawbacks of the current techniques. Our approach explicitly aims to identify all relevant variations using a “knock-out” strategy and the Random Forest algorithm. In evaluations with synthetic datasets the proposed method achieved substantially higher sensitivity and accuracy than the state-of-the-art MVPA methods, and outperformed the univariate approach when the effect size is low. In experiments with real datasets the proposed method identified regions beyond the univariate approach, while other MVPA methods failed to replicate the univariate results. More importantly, in a reproducibility study with the well-known ADNI dataset the proposed method yielded higher stability and power than the univariate approach. PMID:26272728

Visualization of anisotropic-isotropic phase transformation dynamics in battery electrode particles

DOE PAGES

Wang, Jiajun; Karen Chen-Wiegart, Yu-chen; Eng, Christopher; ...

2016-08-12

Anisotropy, or alternatively, isotropy of phase transformations extensively exist in a number of solid-state materials, with performance depending on the three-dimensional transformation features. Fundamental insights into internal chemical phase evolution allow manipulating materials with desired functionalities, and can be developed via real-time multi-dimensional imaging methods. In this paper, we report a five-dimensional imaging method to track phase transformation as a function of charging time in individual lithium iron phosphate battery cathode particles during delithiation. The electrochemically driven phase transformation is initially anisotropic with a preferred boundary migration direction, but becomes isotropic as delithiation proceeds further. We also observe the expectedmore » two-phase coexistence throughout the entire charging process. Finally, we expect this five-dimensional imaging method to be broadly applicable to problems in energy, materials, environmental and life sciences.« less

ON THE GEOMETRY OF MEASURABLE SETS IN N-DIMENSIONAL SPACE ON WHICH GENERALIZED LOCALIZATION HOLDS FOR MULTIPLE FOURIER SERIES OF FUNCTIONS IN L_p, p>1

NASA Astrophysics Data System (ADS)

Bloshanskiĭ, I. L.

1984-02-01

The precise geometry is found of measurable sets in N-dimensional Euclidean space on which generalized localization almost everywhere holds for multiple Fourier series which are rectangularly summable.Bibliography: 14 titles.

The role of cerebral spinal fluid in light propagation through the mouse head: improving fluorescence tomography with Monte Carlo modeling

NASA Astrophysics Data System (ADS)

Ancora, Daniele; Zacharopoulos, Athanasios; Ripoll, Jorge; Zacharakis, Giannis

2016-03-01

Optical Neuroimaging is a highly dynamical field of research owing to the combination of many advanced imaging techniques and computational tools that uncovered unexplored paths through the functioning of the brain. Light propagation modelling through such complicated structures has always played a crucial role as the basis for a high resolution and quantitative imaging where even the slightest improvement could lead to significant results. Fluorescence Diffuse Optical Tomography (fDOT), a widely used technique for three dimensional imaging of small animals and tissues, has been proved to be inaccurate for neuroimaging the mouse head without the knowledge of a-priori anatomical information of the subject. Commonly a normalized Born approximation model is used in fDOT reconstruction based on forward photon propagation using Diffusive Equation (DE) which has strong limitations in the optically clear regime. The presence of the Cerebral Spinal Fluid (CSF) instead, a thin optically clear layer surrounding the brain, can be more accurately taken into account using Monte Carlo approaches which nowadays is becoming more usable thanks to parallelized GPU algorithms. In this work we discuss the results of a synthetic experimental comparison, resulting to the increase of the accuracy for the Born approximation by introducing the CSF layer in a realistic mouse head structure with respect to the current model. We point out the importance of such clear layer for complex geometrical models, while for simple slab phantoms neglecting it does not introduce a significant error.

Association between brain structure and phenotypic characteristics in pedophilia.

PubMed

Poeppl, Timm B; Nitschke, Joachim; Santtila, Pekka; Schecklmann, Martin; Langguth, Berthold; Greenlee, Mark W; Osterheider, Michael; Mokros, Andreas

2013-05-01

Studies applying structural neuroimaging to pedophiles are scarce and have shown conflicting results. Although first findings suggested reduced volume of the amygdala, pronounced gray matter decreases in frontal regions were observed in another group of pedophilic offenders. When compared to non-sexual offenders instead of community controls, pedophiles revealed deficiencies in white matter only. The present study sought to test the hypotheses of structurally compromised prefrontal and limbic networks and whether structural brain abnormalities are related to phenotypic characteristics in pedophiles. We compared gray matter volume of male pedophilic offenders and non-sexual offenders from high-security forensic hospitals using voxel-based morphometry in cross-sectional and correlational whole-brain analyses. The significance threshold was set to p < .05, corrected for multiple comparisons. Compared to controls, pedophiles exhibited a volume reduction of the right amygdala (small volume corrected). Within the pedophilic group, pedosexual interest and sexual recidivism were correlated with gray matter decrease in the left dorsolateral prefrontal cortex (r = -.64) and insular cortex (r = -.45). Lower age of victims was strongly associated with gray matter reductions in the orbitofrontal cortex (r = .98) and angular gyri bilaterally (r = .70 and r = .93). Our findings of specifically impaired neural networks being related to certain phenotypic characteristics might account for the heterogeneous results in previous neuroimaging studies of pedophilia. The neuroanatomical abnormalities in pedophilia seem to be of a dimensional rather than a categorical nature, supporting the notion of a multifaceted disorder. Copyright © 2013 Elsevier Ltd. All rights reserved.

The occipital place area represents the local elements of scenes

PubMed Central

Kamps, Frederik S.; Julian, Joshua B.; Kubilius, Jonas; Kanwisher, Nancy; Dilks, Daniel D.

2016-01-01

Neuroimaging studies have identified three scene-selective regions in human cortex: parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA). However, precisely what scene information each region represents in not clear, especially for the least studied, more posterior OPA. Here we hypothesized that OPA represents local elements of scenes within two independent, yet complementary scene descriptors: spatial boundary (i.e., the layout of external surfaces) and scene content (e.g., internal objects). If OPA processes the local elements of spatial boundary information, then it should respond to these local elements (e.g., walls) themselves, regardless of their spatial arrangement. Indeed, we found OPA, but not PPA or RSC, responded similarly to images of intact rooms and these same rooms in which the surfaces were fractured and rearranged, disrupting the spatial boundary. Next, if OPA represents the local elements of scene content information, then it should respond more when more such local elements (e.g., furniture) are present. Indeed, we found that OPA, but not PPA or RSC, responded more to multiple than single pieces of furniture. Taken together, these findings reveal that OPA analyzes local scene elements – both in spatial boundary and scene content representation – while PPA and RSC represent global scene properties. PMID:26931815

The occipital place area represents the local elements of scenes.

PubMed

Kamps, Frederik S; Julian, Joshua B; Kubilius, Jonas; Kanwisher, Nancy; Dilks, Daniel D

2016-05-15

Neuroimaging studies have identified three scene-selective regions in human cortex: parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA). However, precisely what scene information each region represents is not clear, especially for the least studied, more posterior OPA. Here we hypothesized that OPA represents local elements of scenes within two independent, yet complementary scene descriptors: spatial boundary (i.e., the layout of external surfaces) and scene content (e.g., internal objects). If OPA processes the local elements of spatial boundary information, then it should respond to these local elements (e.g., walls) themselves, regardless of their spatial arrangement. Indeed, we found that OPA, but not PPA or RSC, responded similarly to images of intact rooms and these same rooms in which the surfaces were fractured and rearranged, disrupting the spatial boundary. Next, if OPA represents the local elements of scene content information, then it should respond more when more such local elements (e.g., furniture) are present. Indeed, we found that OPA, but not PPA or RSC, responded more to multiple than single pieces of furniture. Taken together, these findings reveal that OPA analyzes local scene elements - both in spatial boundary and scene content representation - while PPA and RSC represent global scene properties. Copyright © 2016 Elsevier Inc. All rights reserved.

Legal liability and research ethics boards: the case of neuroimaging and incidental findings.

PubMed

Zarzeczny, Amy; Caulfield, Timothy

2012-01-01

Neuroimaging research covers a wide range of intriguing issues from revealing brain structures to investigating what happens in our brain when we lie. The field appears to be thriving, but skepticism and alertness to the various ethical, scientific, policy and philosophical challenges associated with it also appear to be on the rise. One particularly complex issue concerns what to do with incidental findings that emerge during the course of neuroimaging research. Research ethics boards (REBs) play a central role in research oversight. In this paper, we will consider some of the potential issues associated with REB liability in negligence in the context of incidental findings in neuroimaging research. Copyright © 2011 Elsevier Ltd. All rights reserved.

Imperial College near infrared spectroscopy neuroimaging analysis framework.

PubMed

Orihuela-Espina, Felipe; Leff, Daniel R; James, David R C; Darzi, Ara W; Yang, Guang-Zhong

2018-01-01

This paper describes the Imperial College near infrared spectroscopy neuroimaging analysis (ICNNA) software tool for functional near infrared spectroscopy neuroimaging data. ICNNA is a MATLAB-based object-oriented framework encompassing an application programming interface and a graphical user interface. ICNNA incorporates reconstruction based on the modified Beer-Lambert law and basic processing and data validation capabilities. Emphasis is placed on the full experiment rather than individual neuroimages as the central element of analysis. The software offers three types of analyses including classical statistical methods based on comparison of changes in relative concentrations of hemoglobin between the task and baseline periods, graph theory-based metrics of connectivity and, distinctively, an analysis approach based on manifold embedding. This paper presents the different capabilities of ICNNA in its current version.

A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits

PubMed Central

Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

2017-01-01

Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz) and slow-2 (0.198–0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands. PMID:28680397

A Comprehensive Analysis of the Correlations between Resting-State Oscillations in Multiple-Frequency Bands and Big Five Traits.

PubMed

Ikeda, Shigeyuki; Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Miyauchi, Carlos Makoto; Sakaki, Kohei; Nozawa, Takayuki; Yokota, Susumu; Magistro, Daniele; Kawashima, Ryuta

2017-01-01

Recently, the association between human personality traits and resting-state brain activity has gained interest in neuroimaging studies. However, it remains unclear if Big Five personality traits are represented in frequency bands (~0.25 Hz) of resting-state functional magnetic resonance imaging (fMRI) activity. Based on earlier neurophysiological studies, we investigated the correlation between the five personality traits assessed by the NEO Five-Factor Inventory (NEO-FFI), and the fractional amplitude of low-frequency fluctuation (fALFF) at four distinct frequency bands (slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz)). We enrolled 835 young subjects and calculated the correlations of resting-state fMRI signals using a multiple regression analysis. We found a significant and consistent correlation between fALFF and the personality trait of extraversion at all frequency bands. Furthermore, significant correlations were detected in distinct brain regions for each frequency band. This finding supports the frequency-specific spatial representations of personality traits as previously suggested. In conclusion, our data highlight an association between human personality traits and fALFF at four distinct frequency bands.

Balancing Newtonian gravity and spin to create localized structures

NASA Astrophysics Data System (ADS)

Bush, Michael; Lindner, John

2015-03-01

Using geometry and Newtonian physics, we design localized structures that do not require electromagnetic or other forces to resist implosion or explosion. In two-dimensional Euclidean space, we find an equilibrium configuration of a rotating ring of massive dust whose inward gravity is the centripetal force that spins it. We find similar solutions in three-dimensional Euclidean and hyperbolic spaces, but only in the limit of vanishing mass. Finally, in three-dimensional Euclidean space, we generalize the two-dimensional result by finding an equilibrium configuration of a spherical shell of massive dust that supports itself against gravitational collapse by spinning isoclinically in four dimensions so its three-dimensional acceleration is everywhere inward. These Newtonian ``atoms'' illuminate classical physics and geometry.

On-line analysis of algae in water by discrete three-dimensional fluorescence spectroscopy.

PubMed

Zhao, Nanjing; Zhang, Xiaoling; Yin, Gaofang; Yang, Ruifang; Hu, Li; Chen, Shuang; Liu, Jianguo; Liu, Wenqing

2018-03-19

In view of the problem of the on-line measurement of algae classification, a method of algae classification and concentration determination based on the discrete three-dimensional fluorescence spectra was studied in this work. The discrete three-dimensional fluorescence spectra of twelve common species of algae belonging to five categories were analyzed, the discrete three-dimensional standard spectra of five categories were built, and the recognition, classification and concentration prediction of algae categories were realized by the discrete three-dimensional fluorescence spectra coupled with non-negative weighted least squares linear regression analysis. The results show that similarities between discrete three-dimensional standard spectra of different categories were reduced and the accuracies of recognition, classification and concentration prediction of the algae categories were significantly improved. By comparing with that of the chlorophyll a fluorescence excitation spectra method, the recognition accuracy rate in pure samples by discrete three-dimensional fluorescence spectra is improved 1.38%, and the recovery rate and classification accuracy in pure diatom samples 34.1% and 46.8%, respectively; the recognition accuracy rate of mixed samples by discrete-three dimensional fluorescence spectra is enhanced by 26.1%, the recovery rate of mixed samples with Chlorophyta 37.8%, and the classification accuracy of mixed samples with diatoms 54.6%.

Two-dimensional character of internal rotation of furfural and other five-member heterocyclic aromatic aldehydes

NASA Astrophysics Data System (ADS)

Bataev, Vadim A.; Pupyshev, Vladimir I.; Godunov, Igor A.

2016-05-01

The features of nuclear motion corresponding to the rotation of the formyl group (CHO) are studied for the molecules of furfural and some other five-member heterocyclic aromatic aldehydes by the use of MP2/6-311G** quantum chemical approximation. It is demonstrated that the traditional one-dimensional models of internal rotation for the molecules studied have only limited applicability. The reason is the strong kinematic interaction of the rotation of the CHO group and out-of-plane CHO deformation that is realized for the molecules under consideration. The computational procedure based on the two-dimensional approximation is considered for low lying vibrational states as more adequate to the problem.

Brain Imaging, Forward Inference, and Theories of Reasoning

PubMed Central

Heit, Evan

2015-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities. PMID:25620926

Brain imaging, forward inference, and theories of reasoning.

PubMed

Heit, Evan

2014-01-01

This review focuses on the issue of how neuroimaging studies address theoretical accounts of reasoning, through the lens of the method of forward inference (Henson, 2005, 2006). After theories of deductive and inductive reasoning are briefly presented, the method of forward inference for distinguishing between psychological theories based on brain imaging evidence is critically reviewed. Brain imaging studies of reasoning, comparing deductive and inductive arguments, comparing meaningful versus non-meaningful material, investigating hemispheric localization, and comparing conditional and relational arguments, are assessed in light of the method of forward inference. Finally, conclusions are drawn with regard to future research opportunities.

Stimulated Brillouin scattering in the field of a two-dimensionally localized pumping wave

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

Solikhov, D. K., E-mail: davlat56@mail.ru; Dvinin, S. A., E-mail: dvinin@phys.msu.ru

2016-06-15

Stimulated Brillouin scattering of electromagnetic waves in the field of a two-dimensionally localized pump wave at arbitrary scattering angles in the regime of forward scattering is analyzed. Spatial variations in the amplitudes of interacting waves are studied for different values of the pump field and different dimensions of the pump wave localization region. The intensity of scattered radiation is determined as a function of the scattering angle and the dimensions of the pump wave localization region. It is shown that the intensity increases with increasing scattering angle.

NeuroImaging Radiological Interpretation System (NIRIS) for Acute Traumatic Brain Injury (TBI).

PubMed

Wintermark, Max; Li, Ying; Ding, Victoria Y; Xu, Yingding; Jiang, Bin; Ball, Robyn L; Zeineh, Michael; Gean, Alisa; Sanelli, Pina

2018-04-18

To develop an outcome-based NeuroImaging Radiological Interpretation System (NIRIS) for acute traumatic brain injury (TBI) patients that would standardize the interpretation of non-contrast head CTs and consolidate imaging findings into ordinal severity categories that would inform specific patient management actions and that could be used as a clinical decision support tool. We retrospectively identified all patients transported to our emergency department by ambulance or helicopter, for whom a trauma alert was triggered per established criteria and who underwent a non-contrast head CT due to suspicion of TBI, between November 2015 and April 2016. Two neuroradiologists reviewed the non-contrast head CTs and assessed the TBI imaging common data elements (CDEs), as defined by the National Institutes of Health (NIH). Using descriptive statistics and receiver operating characteristic curve analyses to identify imaging characteristics and associated thresholds that best distinguished among outcomes, we classified patients into five mutually exclusive categories: 0-discharge from the emergency department; 1-follow-up brain imaging and/or admission; 2-admission to an advanced care unit; 3-neurosurgical procedure; 4-death up to 6 months after TBI. Sensitivity of NIRIS with respect to each patient's true outcome was then evaluated and compared to that of the Marshall and Rotterdam scoring systems for TBI. In our cohort of 542 TBI patients, NIRIS was developed to predict discharge (182 patients), follow-up brain imaging/admission (187 patients), need for advanced care unit (151 patients). neurosurgical procedures (10 patients) and death (12 patients). NIRIS performed similarly to the Marshall and Rotterdam scoring systems in terms of predicting mortality. We developed an interpretation system for neuroimaging using the CDEs that informs specific patient management actions and could be used as a clinical decision support tool for patients with TBI. Our NIRIS classification, with evidence-based grouping of the CDEs into actionable categories, will need to be validated in different TBI populations.

iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization.

PubMed

Blenkmann, Alejandro O; Phillips, Holly N; Princich, Juan P; Rowe, James B; Bekinschtein, Tristan A; Muravchik, Carlos H; Kochen, Silvia

2017-01-01

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2-3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.

iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization

PubMed Central

Blenkmann, Alejandro O.; Phillips, Holly N.; Princich, Juan P.; Rowe, James B.; Bekinschtein, Tristan A.; Muravchik, Carlos H.; Kochen, Silvia

2017-01-01

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions. PMID:28303098

Approximate Analysis for Interlaminar Stresses in Composite Structures with Thickness Discontinuities

NASA Technical Reports Server (NTRS)

Rose, Cheryl A.; Starnes, James H., Jr.

1996-01-01

An efficient, approximate analysis for calculating complete three-dimensional stress fields near regions of geometric discontinuities in laminated composite structures is presented. An approximate three-dimensional local analysis is used to determine the detailed local response due to far-field stresses obtained from a global two-dimensional analysis. The stress results from the global analysis are used as traction boundary conditions for the local analysis. A generalized plane deformation assumption is made in the local analysis to reduce the solution domain to two dimensions. This assumption allows out-of-plane deformation to occur. The local analysis is based on the principle of minimum complementary energy and uses statically admissible stress functions that have an assumed through-the-thickness distribution. Examples are presented to illustrate the accuracy and computational efficiency of the local analysis. Comparisons of the results of the present local analysis with the corresponding results obtained from a finite element analysis and from an elasticity solution are presented. These results indicate that the present local analysis predicts the stress field accurately. Computer execution-times are also presented. The demonstrated accuracy and computational efficiency of the analysis make it well suited for parametric and design studies.

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty.

PubMed

de Pierrefeu, Amicie; Lofstedt, Tommy; Hadj-Selem, Fouad; Dubois, Mathieu; Jardri, Renaud; Fovet, Thomas; Ciuciu, Philippe; Frouin, Vincent; Duchesnay, Edouard

2018-02-01

Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover the dominant patterns of variability within a population. Despite its ability to represent a data set in a low-dimensional space, PCA's interpretability remains limited. Indeed, the components produced by PCA are often noisy or exhibit no visually meaningful patterns. Furthermore, the fact that the components are usually non-sparse may also impede interpretation, unless arbitrary thresholding is applied. However, in neuroimaging, it is essential to uncover clinically interpretable phenotypic markers that would account for the main variability in the brain images of a population. Recently, some alternatives to the standard PCA approach, such as sparse PCA (SPCA), have been proposed, their aim being to limit the density of the components. Nonetheless, sparsity alone does not entirely solve the interpretability problem in neuroimaging, since it may yield scattered and unstable components. We hypothesized that the incorporation of prior information regarding the structure of the data may lead to improved relevance and interpretability of brain patterns. We therefore present a simple extension of the popular PCA framework that adds structured sparsity penalties on the loading vectors in order to identify the few stable regions in the brain images that capture most of the variability. Such structured sparsity can be obtained by combining, e.g., and total variation (TV) penalties, where the TV regularization encodes information on the underlying structure of the data. This paper presents the structured SPCA (denoted SPCA-TV) optimization framework and its resolution. We demonstrate SPCA-TV's effectiveness and versatility on three different data sets. It can be applied to any kind of structured data, such as, e.g., -dimensional array images or meshes of cortical surfaces. The gains of SPCA-TV over unstructured approaches (such as SPCA and ElasticNet PCA) or structured approach (such as GraphNet PCA) are significant, since SPCA-TV reveals the variability within a data set in the form of intelligible brain patterns that are easier to interpret and more stable across different samples.

Relationships between cognitive performance, neuroimaging, and vascular disease: the DHS-Mind Study

PubMed Central

Hsu, Fang-Chi; Raffield, Laura M.; Hugenschmidt, Christina E.; Cox, Amanda; Xu, Jianzhao; Carr, J. Jeffery; Freedman, Barry I.; Maldjian, Joseph A.; Williamson, Jeff D.; Bowden, Donald W.

2015-01-01

Background Type 2 diabetes mellitus increases risk for cognitive decline and dementia; elevated burdens of vascular disease are hypothesized to contribute to this risk. These relationships were examined in the Diabetes Heart Study-Mind using a battery of cognitive tests, neuroimaging measures, and subclinical cardiovascular disease (CVD) burden assessed by coronary artery calcified plaque (CAC). We hypothesized that CAC would attenuate the association between neuroimaging measures and cognition performance. Methods Associations were examined using marginal models in this family-based cohort of 572 European Americans from 263 families. All models were adjusted for age, gender, education, type 2 diabetes, and hypertension, with some neuroimaging measures additionally adjusted for intracranial volume. Results Higher total brain volume (TBV) was associated with better performance on the Digit Symbol Substitution Task (DSST) and Semantic Fluency (both p≤7.0 x 10−4). Higher gray matter volume (GMV) was associated with better performance on the Modified Mini-Mental State Examination and Semantic Fluency (both p≤9.0 x 10−4). Adjusting for CAC caused minimal changes to the results. Conclusions Relationships exist between neuroimaging measures and cognitive performance in a type 2 diabetes-enriched European American cohort. Associations were minimally attenuated after adjusting for subclinical CVD. Additional work is needed to understand how subclinical CVD burden interacts with other factors and impacts relationships between neuroimaging and cognitive testing measures. PMID:26185004

ABrIL - Advanced Brain Imaging Lab : a cloud based computation environment for cooperative neuroimaging projects.

PubMed

Neves Tafula, Sérgio M; Moreira da Silva, Nádia; Rozanski, Verena E; Silva Cunha, João Paulo

2014-01-01

Neuroscience is an increasingly multidisciplinary and highly cooperative field where neuroimaging plays an important role. Neuroimaging rapid evolution is demanding for a growing number of computing resources and skills that need to be put in place at every lab. Typically each group tries to setup their own servers and workstations to support their neuroimaging needs, having to learn from Operating System management to specific neuroscience software tools details before any results can be obtained from each setup. This setup and learning process is replicated in every lab, even if a strong collaboration among several groups is going on. In this paper we present a new cloud service model - Brain Imaging Application as a Service (BiAaaS) - and one of its implementation - Advanced Brain Imaging Lab (ABrIL) - in the form of an ubiquitous virtual desktop remote infrastructure that offers a set of neuroimaging computational services in an interactive neuroscientist-friendly graphical user interface (GUI). This remote desktop has been used for several multi-institution cooperative projects with different neuroscience objectives that already achieved important results, such as the contribution to a high impact paper published in the January issue of the Neuroimage journal. The ABrIL system has shown its applicability in several neuroscience projects with a relatively low-cost, promoting truly collaborative actions and speeding up project results and their clinical applicability.

Neuroimaging of Human Balance Control: A Systematic Review

PubMed Central

Wittenberg, Ellen; Thompson, Jessica; Nam, Chang S.; Franz, Jason R.

2017-01-01

This review examined 83 articles using neuroimaging modalities to investigate the neural correlates underlying static and dynamic human balance control, with aims to support future mobile neuroimaging research in the balance control domain. Furthermore, this review analyzed the mobility of the neuroimaging hardware and research paradigms as well as the analytical methodology to identify and remove movement artifact in the acquired brain signal. We found that the majority of static balance control tasks utilized mechanical perturbations to invoke feet-in-place responses (27 out of 38 studies), while cognitive dual-task conditions were commonly used to challenge balance in dynamic balance control tasks (20 out of 32 studies). While frequency analysis and event related potential characteristics supported enhanced brain activation during static balance control, that in dynamic balance control studies was supported by spatial and frequency analysis. Twenty-three of the 50 studies utilizing EEG utilized independent component analysis to remove movement artifacts from the acquired brain signals. Lastly, only eight studies used truly mobile neuroimaging hardware systems. This review provides evidence to support an increase in brain activation in balance control tasks, regardless of mechanical, cognitive, or sensory challenges. Furthermore, the current body of literature demonstrates the use of advanced signal processing methodologies to analyze brain activity during movement. However, the static nature of neuroimaging hardware and conventional balance control paradigms prevent full mobility and limit our knowledge of neural mechanisms underlying balance control. PMID:28443007

Dimensionality reduction based on distance preservation to local mean for symmetric positive definite matrices and its application in brain-computer interfaces

NASA Astrophysics Data System (ADS)

Davoudi, Alireza; Shiry Ghidary, Saeed; Sadatnejad, Khadijeh

2017-06-01

Objective. In this paper, we propose a nonlinear dimensionality reduction algorithm for the manifold of symmetric positive definite (SPD) matrices that considers the geometry of SPD matrices and provides a low-dimensional representation of the manifold with high class discrimination in a supervised or unsupervised manner. Approach. The proposed algorithm tries to preserve the local structure of the data by preserving distances to local means (DPLM) and also provides an implicit projection matrix. DPLM is linear in terms of the number of training samples. Main results. We performed several experiments on the multi-class dataset IIa from BCI competition IV and two other datasets from BCI competition III including datasets IIIa and IVa. The results show that our approach as dimensionality reduction technique—leads to superior results in comparison with other competitors in the related literature because of its robustness against outliers and the way it preserves the local geometry of the data. Significance. The experiments confirm that the combination of DPLM with filter geodesic minimum distance to mean as the classifier leads to superior performance compared with the state of the art on brain-computer interface competition IV dataset IIa. Also the statistical analysis shows that our dimensionality reduction method performs significantly better than its competitors.

Divergent Relationship of Depression Severity to Social Reward Responses Among Patients with Bipolar Versus Unipolar Depression

PubMed Central

Sharma, Anup; Satterthwaite, Theodore D.; Vandekar, Lillie; Katchmar, Natalie; Daldal, Aylin; Ruparel, Kosha; A.Elliott, Mark; Baldassano, Claudia; Thase, Michael E.; Gur, Raquel E.; Kable, Joseph W.; Wolf, Daniel H.

2016-01-01

Neuroimaging studies of mood disorders demonstrate abnormalities in brain regions implicated in reward processing. However, there is a paucity of research investigating how social rewards affect reward circuit activity in these disorders. Here, we evaluated the relationship of both diagnostic category and dimensional depression severity to reward system function in bipolar and unipolar depression. In total, 86 adults were included, including 24 patients with bipolar depression, 24 patients with unipolar depression, and 38 healthy comparison subjects. Participants completed a social reward task during 3T BOLD fMRI. On average, diagnostic groups did not differ in activation to social reward. However, greater depression severity significantly correlated with reduced bilateral ventral striatum activation to social reward in the bipolar depressed group, but not the unipolar depressed group. In addition, decreased left orbitofrontal cortical activation correlated with more severe symptoms in bipolar depression, but not unipolar depression. These differential dimensional effects resulted in a significant voxelwise group by depression severity interaction. Taken together, these results provide initial evidence that deficits in social reward processing are differentially related to depression severity in the two disorders. PMID:27295401

Five-dimensional collective Hamiltonian with the Gogny force: An ongoing saga

NASA Astrophysics Data System (ADS)

Libert, J.; Delaroche, J.-P.; Girod, M.

2016-07-01

We provide a sample of analyses for nuclear spectroscopic properties based on the five-dimensional collective Hamiltonian (5DCH) implemented with the Gogny force. The very first illustration is dating back to the late 70's. It is next followed by others, focusing on shape coexistence, shape isomerism, superdeformation, and systematics over the periodic table. Finally, the inclusion of Thouless-Valatin dynamical contributions to vibrational mass parameters is briefly discussed as a mean of strengthening the basis of the 5DCH theory.

Towards a model-based cognitive neuroscience of stopping - a neuroimaging perspective.

PubMed

Sebastian, Alexandra; Forstmann, Birte U; Matzke, Dora

2018-07-01

Our understanding of the neural correlates of response inhibition has greatly advanced over the last decade. Nevertheless the specific function of regions within this stopping network remains controversial. The traditional neuroimaging approach cannot capture many processes affecting stopping performance. Despite the shortcomings of the traditional neuroimaging approach and a great progress in mathematical and computational models of stopping, model-based cognitive neuroscience approaches in human neuroimaging studies are largely lacking. To foster model-based approaches to ultimately gain a deeper understanding of the neural signature of stopping, we outline the most prominent models of response inhibition and recent advances in the field. We highlight how a model-based approach in clinical samples has improved our understanding of altered cognitive functions in these disorders. Moreover, we show how linking evidence-accumulation models and neuroimaging data improves the identification of neural pathways involved in the stopping process and helps to delineate these from neural networks of related but distinct functions. In conclusion, adopting a model-based approach is indispensable to identifying the actual neural processes underlying stopping. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Brain dysfunction behind functional symptoms: neuroimaging and somatoform, conversive, and dissociative disorders.

PubMed

García-Campayo, Javier; Fayed, Nicolas; Serrano-Blanco, Antoni; Roca, Miquel

2009-03-01

Neuroimaging research in psychiatry has been increasing exponentially in recent years, yet many psychiatrists are relatively unfamiliar with this field. This article summarizes the findings of the most relevant research articles on the neuroimaging of somatoform, conversive, and dissociative disorders published from January 2007 through June 2008. Neuroimaging findings summarized here include alterations of stress regulation and coping in somatoform pain disorders, the importance of catastrophizing in somatization disorder, and the relevance of a history of physical/sexual abuse in irritable bowel syndrome. Regarding fibromyalgia, three of the most significant advances have been the impossibility of differentiating primary and concomitant fibromyalgia in the presence of quiescent underlying disease, the role of hippocampal dysfunction, and the possibility that fibromyalgia may be characterized as an aging process. In dissociative disorders, the high levels of elaborative memory encoding and the reduced size of the parietal lobe are highlighted. The most promising clinical consequence of these studies, in addition to improving knowledge about the etiology of these illnesses, is the possibility of using neuroimaging findings to identify subgroups of patients, which could allow treatments to be tailored.

Choosing Wisely: A Neurosurgical Perspective on Neuroimaging for Headaches

PubMed Central

Hawasli, Ammar H.; Chicoine, Michael R.; Dacey, Ralph G.

2016-01-01

Multiple national initiatives seek to curb spending in order to address increasing health care costs in the United States. The Choosing Wisely® initiative is one popular initiative that focuses on reducing health care spending by setting guidelines to limit tests and procedures requested by patients and ordered by physicians. To reduce spending on neuroimaging, the Choosing Wisely® initiative and other organizations have offered guidelines to limit neuroimaging for headaches. Although the intentions are laudable, these guidelines are inconsistent with the neurosurgeon’s experience with brain tumor patients. If adopted by governing or funding organizations, these guidelines threaten to negatively impact the care and outcomes of patients with brain tumors, who frequently present with minimal symptoms or isolated headaches syndromes. As we grapple with the difficult conflict between evidence-based cost-cutting guidelines and individualized patient-tailored medicine, a physician must carefully balance the costs and benefits of discretionary services such as neuroimaging for headaches. By participating in the development of validated clinical decision rules on neuroimaging for headaches, neurosurgeons can advocate for their patients and improve their patients’ outcomes. PMID:25255253

Introduction and overview of the special issue "Brain imaging and aging": The new era of neuroimaging in aging research.

PubMed

Furukawa, Katsutoshi; Ishiki, Aiko; Tomita, Naoki; Onaka, Yuta; Saito, Haruka; Nakamichi, Tomoko; Hara, Kazunari; Kusano, Yusuke; Ebara, Masamune; Arata, Yuki; Sakota, Miku; Miyazawa, Isabelle; Totsune, Tomoko; Okinaga, Shoji; Okamura, Nobuyuki; Kudo, Yukitsuka; Arai, Hiroyuki

2016-09-01

It is well known that the brain is one of the organs particularly affected by aging in terms of function, relative to the gastrointestinal tract and liver, which exhibit less functional decline. There is also a wide range of age-related neurological disorders such as stroke, Alzheimer's disease, and Parkinson's disease. Therefore, it is very important to understand the relationship between functional age-related change and neurological dysfunction. Neuroimaging techniques including magnetic resonance imaging and positron emission tomography have been significantly improved over recent years. Many physicians and researchers have investigated various mechanisms of age-related cerebral change and associated neurological disorders using neuroimaging techniques. In this special issue of Ageing Research Reviews, we focus on cerebral- and neuro-imaging, which are a range of tools used to visualize structure, functions, and pathogenic molecules in the nervous system. In addition, we summarize several review articles about the history, present values, and future perspectives of neuroimaging modalities. Copyright © 2016 Elsevier B.V. All rights reserved.

Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

PubMed Central

Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella

2015-01-01

Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468

Neuroimaging of the Periaqueductal Gray: State of the Field

PubMed Central

Linnman, Clas; Moulton, Eric A.; Barmettler, Gabi; Becerra, Lino; Borsook, David

2011-01-01

This review and meta-analysis aims at summarizing and integrating the human neuroimaging studies that report periaqueductal gray (PAG) involvement; 250 original manuscripts on human neuroimaging of the PAG were identified. A narrative review and meta-analysis using activation likelihood estimates is included. Behaviors covered include pain and pain modulation, anxiety, bladder and bowel function and autonomic regulation. Methods include structural and functional magnetic resonance imaging, functional connectivity measures, diffusion weighted imaging and positron emission tomography. Human neuroimaging studies in healthy and clinical populations largely confirm the animal literature indicating that the PAG is involved in homeostatic regulation of salient functions such as pain, anxiety and autonomic function. Methodological concerns in the current literature, including resolution constraints, imaging artifacts and imprecise neuroanatomical labeling are discussed, and future directions are proposed. A general conclusion is that PAG neuroimaging is a field with enormous potential to translate animal data onto human behaviors, but with some growing pains that can and need to be addressed in order to add to our understanding of the neurobiology of this key region. PMID:22197740

The big bang as a higher-dimensional shock wave

NASA Astrophysics Data System (ADS)

Wesson, P. S.; Liu, H.; Seahra, S. S.

2000-06-01

We give an exact solution of the five-dimensional field equations which describes a shock wave moving in time and the extra (Kaluza-Klein) coordinate. The matter in four-dimensional spacetime is a cosmology with good physical properties. The solution suggests to us that the 4D big bang was a 5D shock wave.

Dimensionality and Typology of Perfectionism: The Use of the Frost Multidimensional Perfectionism Scale with Chinese Gifted Students in Hong Kong

ERIC Educational Resources Information Center

Chan, David W.

2009-01-01

This study investigated the dimensionality and typology of perfectionism based on the Frost Multidimensional Perfectionism Scale with a sample of 380 Chinese gifted students in Hong Kong. Confirmatory factor analyses supported a five-dimensional model that includes constructs of personal standards, parental expectations, parental criticism,…

An Assessment of Five Modeling Approaches for Thermo-Mechanical Stress Analysis of Laminated Composite Panels

NASA Technical Reports Server (NTRS)

Noor, A. K.; Malik, M.

2000-01-01

A study is made of the effects of variation in the lamination and geometric parameters, and boundary conditions of multi-layered composite panels on the accuracy of the detailed response characteristics obtained by five different modeling approaches. The modeling approaches considered include four two-dimensional models, each with five parameters to characterize the deformation in the thickness direction, and a predictor-corrector approach with twelve displacement parameters. The two-dimensional models are first-order shear deformation theory, third-order theory; a theory based on trigonometric variation of the transverse shear stresses through the thickness, and a discrete layer theory. The combination of the following four key elements distinguishes the present study from previous studies reported in the literature: (1) the standard of comparison is taken to be the solutions obtained by using three-dimensional continuum models for each of the individual layers; (2) both mechanical and thermal loadings are considered; (3) boundary conditions other than simply supported edges are considered; and (4) quantities compared include detailed through-the-thickness distributions of transverse shear and transverse normal stresses. Based on the numerical studies conducted, the predictor-corrector approach appears to be the most effective technique for obtaining accurate transverse stresses, and for thermal loading, none of the two-dimensional models is adequate for calculating transverse normal stresses, even when used in conjunction with three-dimensional equilibrium equations.

A domain swapping approach to elucidate differential regiospecific hydroxylation by geraniol and linalool synthases from perilla.

PubMed

Sato-Masumoto, Naoko; Ito, Michiho

2014-06-01

Geraniol and linalool are acyclic monoterpenes found in plant essential oils that have attracted much attention for their commercial use and in pharmaceutical studies. They are synthesized from geranyl diphosphate (GDP) by geraniol and linalool synthases, respectively. Both synthases are very similar at the amino acid level and share the same substrate; however, the position of the GDP to which they introduce hydroxyl groups is different. In this study, the mechanisms underlying the regiospecific hydroxylation of geraniol and linalool synthases were investigated using a domain swapping approach and site-directed mutagenesis in perilla. Sequences of the synthases were divided into ten domains (domains I to IV-4), and each corresponding domain was exchanged between both enzymes. It was shown that different regions were important for the formation of geraniol and linalool, namely, domains IV-1 and -4 for geraniol, and domains III-b, III-d, and IV-4 for linalool. These results suggested that the conformation of carbocation intermediates and their electron localization were seemingly to be different between geraniol and linalool synthases. Further, five amino acids in domain IV-4 were apparently indispensable for the formation of geraniol and linalool. According to three-dimensional structural models of the synthases, these five residues seemed to be responsible for the different spatial arrangement of the amino acid at H524 in the case of geraniol synthase, while N526 is the corresponding residue in linalool synthase. These results suggested that the side-chains of these five amino acids, in combination with several relevant domains, localized the positive charge in the carbocation intermediate to determine the position of the introduced hydroxyl group. Copyright © 2014 Elsevier Ltd. All rights reserved.

[How to start a neuroimaging study].

PubMed

Narumoto, Jin

2012-06-01

In order to help researchers understand how to start a neuroimaging study, several tips are described in this paper. These include 1) Choice of an imaging modality, 2) Statistical method, and 3) Interpretation of the results. 1) There are several imaging modalities available in clinical research. Advantages and disadvantages of each modality are described. 2) Statistical Parametric Mapping, which is the most common statistical software for neuroimaging analysis, is described in terms of parameter setting in normalization and level of significance. 3) In the discussion section, the region which shows a significant difference between patients and normal controls should be discussed in relation to the neurophysiology of the disease, making reference to previous reports from neuroimaging studies in normal controls, lesion studies and animal studies. A typical pattern of discussion is described.

Locally Linear Embedding of Local Orthogonal Least Squares Images for Face Recognition

NASA Astrophysics Data System (ADS)

Hafizhelmi Kamaru Zaman, Fadhlan

2018-03-01

Dimensionality reduction is very important in face recognition since it ensures that high-dimensionality data can be mapped to lower dimensional space without losing salient and integral facial information. Locally Linear Embedding (LLE) has been previously used to serve this purpose, however, the process of acquiring LLE features requires high computation and resources. To overcome this limitation, we propose a locally-applied Local Orthogonal Least Squares (LOLS) model can be used as initial feature extraction before the application of LLE. By construction of least squares regression under orthogonal constraints we can preserve more discriminant information in the local subspace of facial features while reducing the overall features into a more compact form that we called LOLS images. LLE can then be applied on the LOLS images to maps its representation into a global coordinate system of much lower dimensionality. Several experiments carried out using publicly available face datasets such as AR, ORL, YaleB, and FERET under Single Sample Per Person (SSPP) constraint demonstrates that our proposed method can reduce the time required to compute LLE features while delivering better accuracy when compared to when either LLE or OLS alone is used. Comparison against several other feature extraction methods and more recent feature-learning method such as state-of-the-art Convolutional Neural Networks (CNN) also reveal the superiority of the proposed method under SSPP constraint.

Vertigo/dizziness in pediatric emergency department: Five years' experience.

PubMed

Raucci, Umberto; Vanacore, Nicola; Paolino, Maria Chiara; Silenzi, Romina; Mariani, Rosanna; Urbano, Antonella; Reale, Antonino; Villa, Maria Pia; Parisi, Pasquale

2016-05-01

Vertigo/Dizziness in childhood is not a rare cause of visits to the emergency department (ED). We analyzed a selected group with vertigo/dizziness to identify signs and symptoms that may help to guide the diagnostic approach and management. A total of 616 children admitted for vertigo to the ED over a five-year period were retrospectively reviewed. Their medical history, clinical characteristics, laboratory and neuroimaging tests, final diagnoses and management were analyzed. Migraine and syncope were the most frequent causes. Two patients were affected by life-threatening cardiac syncope, while structural life-threatening central nervous system diseases were found in 15 patients, none of whom presented with vertigo as an isolated clinical finding. Most cases of vertigo/dizziness in childhood that consist mainly of migraine and syncope are of benign origin. The prompt identification of neurological or cardiological signs or symptoms associated with vertigo in children is mandatory to rule out life-threatening conditions. © International Headache Society 2015.

One- and Two-dimensional Solitary Wave States in the Nonlinear Kramers Equation with Movement Direction as a Variable

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Ishibashi, Kazuya

2018-06-01

We study self-propelled particles by direct numerical simulation of the nonlinear Kramers equation for self-propelled particles. In our previous paper, we studied self-propelled particles with velocity variables in one dimension. In this paper, we consider another model in which each particle exhibits directional motion. The movement direction is expressed with a variable ϕ. We show that one-dimensional solitary wave states appear in direct numerical simulations of the nonlinear Kramers equation in one- and two-dimensional systems, which is a generalization of our previous result. Furthermore, we find two-dimensionally localized states in the case that each self-propelled particle exhibits rotational motion. The center of mass of the two-dimensionally localized state exhibits circular motion, which implies collective rotating motion. Finally, we consider a simple one-dimensional model equation to qualitatively understand the formation of the solitary wave state.

Edge-mode superconductivity in a two-dimensional topological insulator.

PubMed

Pribiag, Vlad S; Beukman, Arjan J A; Qu, Fanming; Cassidy, Maja C; Charpentier, Christophe; Wegscheider, Werner; Kouwenhoven, Leo P

2015-07-01

Topological superconductivity is an exotic state of matter that supports Majorana zero-modes, which have been predicted to occur in the surface states of three-dimensional systems, in the edge states of two-dimensional systems, and in one-dimensional wires. Localized Majorana zero-modes obey non-Abelian exchange statistics, making them interesting building blocks for topological quantum computing. Here, we report superconductivity induced in the edge modes of semiconducting InAs/GaSb quantum wells, a two-dimensional topological insulator. Using superconducting quantum interference we demonstrate gate-tuning between edge-dominated and bulk-dominated regimes of superconducting transport. The edge-dominated regime arises only under conditions of high-bulk resistivity, which we associate with the two-dimensional topological phase. These experiments establish InAs/GaSb as a promising platform for the confinement of Majoranas into localized states, enabling future investigations of non-Abelian statistics.

Implementation of one and three dimensional models for heat transfer coeffcient identification over the plate cooled by the circular water jets

NASA Astrophysics Data System (ADS)

Malinowski, Zbigniew; Cebo-Rudnicka, Agnieszka; Hadała, Beata; Szajding, Artur; Telejko, Tadeusz

2017-10-01

A cooling rate affects the mechanical properties of steel which strongly depend on microstructure evolution processes. The heat transfer boundary condition for the numerical simulation of steel cooling by water jets can be determined from the local one dimensional or from the three dimensional inverse solutions in space and time. In the present study the inconel plate has been heated to about 900 °C and then cooled by six circular water jets. The plate temperature has been measured by 30 thermocouples. The heat transfer coefficient and the heat flux distributions at the plate surface have been determined in time and space. The one dimensional solutions have given a local error to the heat transfer coefficient of about 35%. The three dimensional inverse solution has allowed reducing the local error to about 20%. The uncertainty test has confirmed that a better approximation of the heat transfer coefficient distribution over the cooled surface can be obtained even for limited number of thermocouples. In such a case it was necessary to constrain the inverse solution with the interpolated temperature sensors.

Classification of topological insulators and superconductors in three spatial dimensions

NASA Astrophysics Data System (ADS)

Schnyder, Andreas P.; Ryu, Shinsei; Furusaki, Akira; Ludwig, Andreas W. W.

2008-11-01

We systematically study topological phases of insulators and superconductors (or superfluids) in three spatial dimensions. We find that there exist three-dimensional (3D) topologically nontrivial insulators or superconductors in five out of ten symmetry classes introduced in seminal work by Altland and Zirnbauer within the context of random matrix theory, more than a decade ago. One of these is the recently introduced Z2 topological insulator in the symplectic (or spin-orbit) symmetry class. We show that there exist precisely four more topological insulators. For these systems, all of which are time-reversal invariant in three dimensions, the space of insulating ground states satisfying certain discrete symmetry properties is partitioned into topological sectors that are separated by quantum phase transitions. Three of the above five topologically nontrivial phases can be realized as time-reversal invariant superconductors. In these the different topological sectors are characterized by an integer winding number defined in momentum space. When such 3D topological insulators are terminated by a two-dimensional surface, they support a number (which may be an arbitrary nonvanishing even number for singlet pairing) of Dirac fermion (Majorana fermion when spin-rotation symmetry is completely broken) surface modes which remain gapless under arbitrary perturbations of the Hamiltonian that preserve the characteristic discrete symmetries, including disorder. In particular, these surface modes completely evade Anderson localization from random impurities. These topological phases can be thought of as three-dimensional analogs of well-known paired topological phases in two spatial dimensions such as the spinless chiral (px±ipy) -wave superconductor (or Moore-Read Pfaffian state). In the corresponding topologically nontrivial (analogous to “weak pairing”) and topologically trivial (analogous to “strong pairing”) 3D phases, the wave functions exhibit markedly distinct behavior. When an electromagnetic U(1) gauge field and fluctuations of the gap functions are included in the dynamics, the superconducting phases with nonvanishing winding number possess nontrivial topological ground-state degeneracies.

Neuroimaging and Recovery of Language in Aphasia

PubMed Central

Thompson, Cynthia K.; den Ouden, Dirk-Bart

2010-01-01

The use of functional neuroimaging techniques has advanced what is known about the neural mechanisms used to support language processing in aphasia resulting from brain damage. This paper highlights recent findings derived from neuroimaging studies focused on neuroplasticity of language networks, the role of the left and right hemispheres in this process, and studies examining how treatment affects the neurobiology of recovery. We point out variability across studies as well as factors related to this variability, and we emphasize challenges that remain for research. PMID:18957184

Right hemispheric dysfunction in a case of pure progressive aphemia: fusion of multimodal neuroimaging.

PubMed

Vitali, Paolo; Nobili, Flavio; Raiteri, Umberto; Canfora, Michela; Rosa, Marco; Calvini, Piero; Girtler, Nicola; Regesta, Giovanni; Rodriguez, Guido

2004-01-15

This article describes the unusual case of a 60-year-old woman suffering from pure progressive aphemia. The fusion of multimodal neuroimaging (MRI, perfusion SPECT) implicated the right frontal lobe, especially the inferior frontal gyrus. This area also showed the greatest functional MRI activation during the performance of a covert phonemic fluency task. Results are discussed in terms of bihemispheric language representation. The fusion of three sets of neuroimages has aided in the interpretation of the patient's cognitive brain dysfunction.

Neuroimaging of neurocutaneous diseases.

PubMed

Nandigam, Kaveer; Mechtler, Laszlo L; Smirniotopoulos, James G

2014-02-01

An in-depth knowledge of the imaging characteristics of the common neurocutaneous diseases (NCD) described in this article will help neurologists understand the screening imaging modalities in these patients. The future of neuroimaging is geared towards developing and refining magnetic resonance imaging (MRI) sequences. The detection of tumors in NCD has greatly improved with availability of high-field strength 3T MRI machines. Neuroimaging will remain at the heart and soul of the multidisciplinary care of such complex diagnoses to guide early detection and monitor treatment. Published by Elsevier Inc.

[Influence of autoclave sterilization on dimensional stability and detail reproduction of 5 additional silicone impression materials].

PubMed

Xu, Tong-kai; Sun, Zhi-hui; Jiang, Yong

2012-03-01

To evaluate the dimensional stability and detail reproduction of five additional silicone impression materials after autoclave sterilization. Impressions were made on the ISO 4823 standard mold containing several marking lines, in five kinds of additional silicone. All the impressions were sterilized by high temperature and pressure (135 °C, 212.8 kPa) for 25 min. Linear measurements of pre-sterilization and post-sterilization were made with a measuring microscope. Statistical analysis utilized single-factor analysis with pair-wise comparison of mean values when appropriate. Hypothesis testing was conducted at alpha = 0.05. No significant difference was found between the pre-sterilization and post-sterilization conditions for all locations, and all the absolute valuse of linear rate of change less than 8%. All the sterilization by the autoclave did not affect the surfuce detail reproduction of the 5 impression materials. The dimensional stability and detail reproduction of the five additional silicone impression materials in the study was unaffected by autoclave sterilization.

A conformal transceive array for 7 T neuroimaging.

PubMed

Gilbert, Kyle M; Belliveau, Jean-Guy; Curtis, Andrew T; Gati, Joseph S; Klassen, L Martyn; Menon, Ravi S

2012-05-01

The first 16-channel transceive surface-coil array that conforms to the human head and operates at 298 MHz (7 T) is described. Individual coil elements were decoupled using circumferential shields around each element that extended orthogonally from the former. This decoupling method allowed elements to be constructed with arbitrary shape, size, and location to create a three-dimensional array. Radiofrequency shimming achieved a transmit-field uniformity of 20% over the whole brain and 14% over a single axial slice. During radiofrequency transmission, coil elements couple tightly to the head and reduce the amount of power necessary to achieve a mean 90° flip angle (660-μs and 480-μs pulse lengths were required for a 1-kW hard pulse when shimming over the whole brain and a single axial slice, respectively). During reception, the close proximity of coil elements to the head increases the signal-to-noise ratio in the periphery of the brain, most notably at the superior aspect of the head. The sensitivity profile of each element is localized beneath the respective shield. When combined with the achieved isolation between elements, this results in the capacity for low geometry factors during both transmit and receive: 1.04/1.06 (mean) and 1.25/1.54 (maximum) for 3-by-3 acceleration in the axial/sagittal plane. High cortical signal-to-noise ratio and parallel imaging performance make the conformal coil ideal for the study of high temporal and/or spatial cortical architecture and function. Copyright © 2011 Wiley Periodicals, Inc.

Haptic fMRI: using classification to quantify task-correlated noise during goal-directed reaching motions.

PubMed

Menon, Samir; Quigley, Paul; Yu, Michelle; Khatib, Oussama

2014-01-01

Neuroimaging artifacts in haptic functional magnetic resonance imaging (Haptic fMRI) experiments have the potential to induce spurious fMRI activation where there is none, or to make neural activation measurements appear correlated across brain regions when they are actually not. Here, we demonstrate that performing three-dimensional goal-directed reaching motions while operating Haptic fMRI Interface (HFI) does not create confounding motion artifacts. To test for artifacts, we simultaneously scanned a subject's brain with a customized soft phantom placed a few centimeters away from the subject's left motor cortex. The phantom captured task-related motion and haptic noise, but did not contain associated neural activation measurements. We quantified the task-related information present in fMRI measurements taken from the brain and the phantom by using a linear max-margin classifier to predict whether raw time series data could differentiate between motion planning or reaching. fMRI measurements in the phantom were uninformative (2σ, 45-73%; chance=50%), while those in primary motor, visual, and somatosensory cortex accurately classified task-conditions (2σ, 90-96%). We also localized artifacts due to the haptic interface alone by scanning a stand-alone fBIRN phantom, while an operator performed haptic tasks outside the scanner's bore with the interface at the same location. The stand-alone phantom had lower temporal noise and had similar mean classification but a tighter distribution (bootstrap Gaussian fit) than the brain phantom. Our results suggest that any fMRI measurement artifacts for Haptic fMRI reaching experiments are dominated by actual neural responses.

Two-dimensional character of internal rotation of furfural and other five-member heterocyclic aromatic aldehydes.

PubMed

Bataev, Vadim A; Pupyshev, Vladimir I; Godunov, Igor A

2016-05-15

The features of nuclear motion corresponding to the rotation of the formyl group (CHO) are studied for the molecules of furfural and some other five-member heterocyclic aromatic aldehydes by the use of MP2/6-311G** quantum chemical approximation. It is demonstrated that the traditional one-dimensional models of internal rotation for the molecules studied have only limited applicability. The reason is the strong kinematic interaction of the rotation of the CHO group and out-of-plane CHO deformation that is realized for the molecules under consideration. The computational procedure based on the two-dimensional approximation is considered for low lying vibrational states as more adequate to the problem. Copyright © 2016 Elsevier B.V. All rights reserved.

Prefrontal oscillations during recall of conditioned and extinguished fear in humans.

PubMed

Mueller, Erik M; Panitz, Christian; Hermann, Christiane; Pizzagalli, Diego A

2014-05-21

Human neuroimaging studies indicate that the anterior midcingulate cortex (AMC) and the ventromedial prefrontal cortex (vmPFC) play important roles in the expression and extinction of fear, respectively. Electrophysiological rodent studies further indicate that oscillatory neuronal activity in homolog regions (i.e., prelimbic and infralimbic cortices) changes during fear expression and fear extinction recall. Whether similar processes occur in humans remains largely unexplored. By assessing scalp surface EEG in conjunction with LORETA source estimation of CS-related theta and gamma activity, we tested whether a priori defined ROIs in the human AMC and vmPFC similarly modulate their oscillatory activity during fear expression and extinction recall, respectively. To this end, 42 healthy individuals underwent a differential conditioning/differential extinction protocol with a Recall Test on the next day. In the Recall Test, nonextinguished versus extinguished stimuli evoked an increased differential (CS(+) vs CS(-)) response with regard to skin conductance and AMC-localized theta power. Conversely, extinguished versus nonextinguished stimuli evoked an increased differential response with regard to vmPFC-localized gamma power. Finally, individuals who failed to show a suppressed skin conductance response to the extinguished versus nonextinguished CS(+) also failed to show the otherwise observed alterations in vmPFC gamma power to extinguished CS(+). These results indicate that fear expression is associated with AMC theta activity, whereas successful fear extinction recall relates to changes in vmPFC gamma activity. The present work thereby bridges findings from prior rodent electrophysiological research and human neuroimaging studies and indicates that EEG is a valuable tool for future fear extinction research. Copyright © 2014 the authors 0270-6474/14/347059-08$15.00/0.

Real-time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG

PubMed Central

Mullen, Tim R.; Kothe, Christian A.E.; Chi, Mike; Ojeda, Alejandro; Kerth, Trevor; Makeig, Scott; Jung, Tzyy-Ping; Cauwenberghs, Gert

2015-01-01

Goal We present and evaluate a wearable high-density dry electrode EEG system and an open-source software framework for online neuroimaging and state classification. Methods The system integrates a 64-channel dry EEG form-factor with wireless data streaming for online analysis. A real-time software framework is applied, including adaptive artifact rejection, cortical source localization, multivariate effective connectivity inference, data visualization, and cognitive state classification from connectivity features using a constrained logistic regression approach (ProxConn). We evaluate the system identification methods on simulated 64-channel EEG data. Then we evaluate system performance, using ProxConn and a benchmark ERP method, in classifying response errors in 9 subjects using the dry EEG system. Results Simulations yielded high accuracy (AUC=0.97±0.021) for real-time cortical connectivity estimation. Response error classification using cortical effective connectivity (sdDTF) was significantly above chance with similar performance (AUC) for cLORETA (0.74±0.09) and LCMV (0.72±0.08) source localization. Cortical ERP-based classification was equivalent to ProxConn for cLORETA (0.74±0.16) but significantly better for LCMV (0.82±0.12). Conclusion We demonstrated the feasibility for real-time cortical connectivity analysis and cognitive state classification from high-density wearable dry EEG. Significance This paper is the first validated application of these methods to 64-channel dry EEG. The work addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting. Such advances can have broad impact in research, medicine, and brain-computer interfaces. The pipelines are made freely available in the open-source SIFT and BCILAB toolboxes. PMID:26415149

Structural and Functional Alterations in Neocortical Circuits after Mild Traumatic Brain Injury

NASA Astrophysics Data System (ADS)

Vascak, Michal

National concern over traumatic brain injury (TBI) is growing rapidly. Recent focus is on mild TBI (mTBI), which is the most prevalent injury level in both civilian and military demographics. A preeminent sequelae of mTBI is cognitive network disruption. Advanced neuroimaging of mTBI victims supports this premise, revealing alterations in activation and structure-function of excitatory and inhibitory neuronal systems, which are essential for network processing. However, clinical neuroimaging cannot resolve the cellular and molecular substrates underlying such changes. Therefore, to understand the full scope of mTBI-induced alterations it is necessary to study cortical networks on the microscopic level, where neurons form local networks that are the fundamental computational modules supporting cognition. Recently, in a well-controlled animal model of mTBI, we demonstrated in the excitatory pyramidal neuron system, isolated diffuse axonal injury (DAI), in concert with electrophysiological abnormalities in nearby intact (non-DAI) neurons. These findings were consistent with altered axon initial segment (AIS) intrinsic activity functionally associated with structural plasticity, and/or disturbances in extrinsic systems related to parvalbumin (PV)-expressing interneurons that form GABAergic synapses along the pyramidal neuron perisomatic/AIS domains. The AIS and perisomatic GABAergic synapses are domains critical for regulating neuronal activity and E-I balance. In this dissertation, we focus on the neocortical excitatory pyramidal neuron/inhibitory PV+ interneuron local network following mTBI. Our central hypothesis is that mTBI disrupts neuronal network structure and function causing imbalance of excitatory and inhibitory systems. To address this hypothesis we exploited transgenic and cre/lox mouse models of mTBI, employing approaches that couple state-of-the-art bioimaging with electrophysiology to determine the structuralfunctional alterations of excitatory and inhibitory systems in the neocortex.

Transition density of one-dimensional diffusion with discontinuous drift

NASA Technical Reports Server (NTRS)

Zhang, Weijian

1990-01-01

The transition density of a one-dimensional diffusion process with a discontinuous drift coefficient is studied. A probabilistic representation of the transition density is given, illustrating the close connections between discontinuities of the drift and Brownian local times. In addition, some explicit results are obtained based on the trivariate density of Brownian motion, its occupation, and local times.

The Dimensionality of Inference Making: Are Local and Global Inferences Distinguishable?

ERIC Educational Resources Information Center

Muijselaar, Marloes M. L.

2018-01-01

We investigated the dimensionality of inference making in samples of 4- to 9-year-olds (Ns = 416-783) to determine if local and global coherence inferences could be distinguished. In addition, we examined the validity of our experimenter-developed inference measure by comparing with three additional measures of listening comprehension. Multitrait,…

Localization of a mobile laser scanner via dimensional reduction

NASA Astrophysics Data System (ADS)

Lehtola, Ville V.; Virtanen, Juho-Pekka; Vaaja, Matti T.; Hyyppä, Hannu; Nüchter, Andreas

2016-11-01

We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.